Role of E-cadherin in Tumor Metastasis and Discovery
of Compounds Targeting Metastatic Cancer Cells
by
Tamer T. Onder
B.A. Biology
B.A. History
Cornell University, 2002
SUBMITTED TO THE DEPARTMENT OF BIOLOGY IN PARTIAL FULFILLMENT OF
THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOHPY IN BIOLOGY
AT THE
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
JUNE 2008
© 2008 Massachusetts Institute of Technology. All rights reserved
Signature of Author:
Department of Biology
Certified by: -
j
N,
Robert A. Weinberg
Professor of Biology
Thesis Supervisor
Accepted by:
I
S
MASSACHU
OF TEGHNot.OGy
Stephen P. Bell
Professor of Biology
Chairperson, Graduate Committee
MAY 2 9 2008
LIBRARIES 1
IARCHIVS
Role of E-cadherin in Tumor Metastasis and Discovery
of Compounds Targeting Metastatic Cancer Cells
by
Tamer T. Onder
Submitted to the Department of Biology on May 23, 2008
in Partial Fulfillment of the Requirements for the
Degree of Doctor of Philosophy
Abstract
The epithelial cell adhesion molecule E-cadherin is often downregulated during
carcinoma progression and metastatic spread of tumors. However, the precise mechanism and
molecular basis of metastasis promotion by E-cadherin loss is not completely understood. To
investigate its role in metastasis, I utilized two distinct methods of E-cadherin inhibition that
distinguish between E-cadherin's cell-cell adhesion and intracellular signaling functions. While
the disruption of cell-cell contacts alone does not enable metastasis in vivo, the loss of E-cadherin
protein does, through induction of an epithelial-to-mesenchymal transition (EMT), invasiveness
and anoikis-resistance. E-cadherin binding partner f3-catenin is necessary but not sufficient for
these phenotypes. In addition, gene expression analysis shows that E-cadherin loss results in the
induction of multiple transcription factors, at least one of which, Twist, is necessary for Ecadherin loss-induced metastasis. These findings indicate that E-cadherin loss in tumors
contributes to metastatic dissemination by inducing wide-ranging transcriptional and functional
changes.
In addition to promoting metastasis, loss of E-cadherin and the accompanying EMT
renders cells resistant to conventional chemotherapeutic drugs. As the cells that have undergone
an EMT represent the pool of cancer cells most competent to metastasize and lead to tumor
recurrence, it is of vital importance to find therapies that effectively target such cells. Paired cell
lines that differ in their differentiation state were utilized to discover compounds with selective
toxicity against cells that have undergone an EMT. High-throughput screening of small molecule
libraries resulted in a number of compounds that specifically affect the viability of cells that have
undergone an EMT while having minimal cytotoxic effects on control epithelial cells. These
studies establish a proof-of-principle for discovering compounds that target highly metastatic and
otherwise chemotherapy resistant cancer cells.
Thesis Advisor: Robert A. Weinberg
Title: Professor of Biology, MIT; Member, Whitehead Institute for Biomedical Research
Biographical note
TAMER ONDER
Whitehead Institute for Biomedical Research
9 Cambridge Center, Room 311
Cambridge, MA 02142
(617) 258-5176
onder@mit.edu
Education
Cambridge, MA
Massachusetts Institute of Technology
Ph.D. Candidate in Department of Biology. Degree expected June 2008.
Cornell University
Ithaca, NY
Bachelor of Arts, Biology, Magna Cum Laude, May 2002.
Bachelor of Arts, History
Robert College of Istanbul
Research
Experience
Istanbul, Turkey
Massachusetts Institute of Technology
Cambridge, MA
Ph.D. thesis, Laboratory of Dr. Robert A. Weinberg
"Role of E-cadherin in Tumor Metastasis and Discovery of Compounds
Targeting Metastatic Cancer Cells" (2002-2008)
Cornell University
Ithaca, NY
Senior Honors Thesis, Laboratory of Dr.Volker Vogt
"Cleavage of Rous Sarcoma Virus Gag-Pol Protein" (2001- 2002)
Cornell University
Ithaca, NY
Undergraduate Research Assistant, Laboratory of Dr. Ross MacIntyre (2000)
Publications
Tamer T. Onder, Piyush B. Gupta, Sendurai A. Mani, Jing Yang, Eric
S. Lander and Robert A. Weinberg. (2008) Loss of E-cadherin
promotes metastasis via multiple downstream transcriptional pathways.
CancerResearch 68(10):3645-54.
Christina Scheel, Tamer T. Onder, Antoine Karnoub and Robert A.
Weinberg. (2007) Adaptation versus Selection: The Origins of
Metastatic Behavior. CancerResearch 67(24):11476-9.
Tamer T. Onder, Piyush B. Gupta, Eric S. Lander and Robert A.
Weinberg. (2008) Identification of small molecules exhibiting specific
toxicity for E-cadherin-deficient metastatic cancer cells. In preparation.
Priyamvada Rai, Tamer T. Onder, Jennifer J. Young, Bo Pang, Jose
McFaline, Peter C. Dedon and Robert A. Weinberg. (2008):
Elimination of oxidized nucleotides is necessary to prevent onset of
cellular senescence. Nature Cell Biology. In Review.
Akira Orimo, Elinor Ng Eaton, Christina Scheel, Ittai Ben-Porath,
Tamer T. Onder, Zhigang Wang, Andrea Richardson, and Robert A.
Weinberg. (2008) SDF-1-CXCR4 autocrine signaling maintains
tumor-promoting myofibroblasts in the stroma of human breast
carcinomas. Submitted.
Awards
Department of Defense Breast Cancer Research Pre-doctoral
Traineeship Award (2004-2007)
Hughes Scholars Fellowship for Summer Research (2001)
Teaching
Experience
Massachusetts Institute of Technology
Cambridge, MA
7.16 Experimental Molecular Biology: Biotechnology II. Teaching
Assistant (Spring 2006)
7.013 Introductory Biology. Teaching Assistant. (Fall 2004)
Invited Talks
International Congress of Molecular Medicine, Istanbul, March 2007
Conference
Presentations
Gordon Research Conference on Signaling by Adhesion Receptors,
(poster) 2006, South Hadley, MA
Acknowledgements
I would like to begin by thanking my thesis advisor Dr. Robert A. Weinberg. Without his
support and guidance, none of this would have been possible. I also want to thank him
for giving me a great deal of freedom in the lab and launching me on the path to
becoming an independent scientist. Last but not least, I am grateful for his mentorship
and caring. I will never forget the day he came to my apartment with baskets of chicken
soup as I was trying to recover from a bout of mononucleosis!
I would like to thank my thesis committee members, Drs. David Sabatini and Richard
Hynes for their time and advice on both scientific and career questions. I am particularly
grateful to Dr. Sabatini for his help and advice during my search for a post-doctoral
position.
I am also grateful to Drs. David Housman and Karen Cichowski for giving the time and
effort to be on my thesis defense committee.
I thank members of the Weinberg Lab for providing me with a vibrant scientific
environment. I thoroughly enjoyed our daily meetings and discussions. Many lab
members, both current and former, have given me invaluable scientific and technical help
and advice. Thank you especially to Sheila Stewart for introducing me to the Weinberg
lab during my rotation, and to Jing Yang and Sendurai Mani for reagents and discussions.
Ferenc Reinhardt assisted with many animal experiments and I am grateful for all his
help. I am also grateful to Christine Hickey and Sumiko Williams for all the support they
have given me, especially during the final stretch.
I owe special gratitude to Piyush Gupta, my former baymate and fellow graduate student,
with whom I had many fruitful collaborations throughout this thesis. I benefited
immensely from his optimism in the face of experimental adversity. I also want to thank
him for introducing me to the world of the "high throughput" way of doing science.
On my first day at Whitehead orientation, I met with a fellow newcomer to the Weinberg
lab and she has been one of my best friends over the years. Priya, I thank you for
everything from hours spent at coffee breaks to the "thoughtful" discussions we had. You
have been like a big sister to me and I consider it my luck to have known you.
Although graduate school is a transforming experience, the real life-changing event for
me has been meeting my fiancee Tugba Bagci. A fellow biologist and graduate student,
she has been there for me throughout my years in Boston. I cannot thank her enough for
her support and the meaning she gave to my life.
Finally I thank my parents, Umit and Turkan Onder, for their never-ending support and
caring. I can only imagine how difficult it must have been for them to live away from
their only son for the past 10 years. I hope it was all worth it and I make you proud at the
end.
Table of Contents
Abstract ...................................................
B iographical note ..........................................................................................................
Acknow ledgem ents......................................................................................................
T able of C ontents .........................................................................................................
2
3
5
6
8
Chapterl : Introduction ................................................................................................
Metastasis is the primary cause of cancer-related mortality ..................................... 9
Invasion-metastasis cascade....................................................................................
9
Multi-step nature of the invasion-metastasis cascade...............................
...... 10
........ 14
Epithelial-to-mesenchymal transition (EMT) .......................................
EMT is a normal physiological process................................... .................................. 14
Evidence for the EMT in carcinoma progression .......................................... ...... 15
EMT in the invasion/metastasis cascade............................................
17
E-cadherin is an important epithelial cell adhesion molecule ...................................... 22
Structure of E-cadherin ................................................................................................. 23
3-catenin and the Wnt pathway ..........................................................................
24
Mechanisms of E-cadherin loss in human tumors ...................................... .... . 25
Main Questions Addressed ..................................................................................... 28
Figures........................................... ........................................................................ 30
References ..................................................................................................................... 32
Chapter 2: Loss of E-cadherin promotes metastasis via multiple downstream
transcriptional pathw ays ................................................................................................... 42
Introduction ................................................................................................................... 43
Results ...................................................
46
Characterization of in vitro phenotypes resulting from expression of E-cadherin
shRNA and dominant-negative E-cadherin .......................................
..... 46
Primary tumor formation and metastasis of E-cadherin-inhibited cells ................. 48
Functional differences in cell motility, invasion, and anoikis-resistance .................. 50
Tumor initiating capacity of E-cadherin inhibited cells ..................................... 51
Molecular mechanism of E-cadherin-loss induced EMT .....................................
52
The role of 03-catenin in EMT and metastasis induced by E-cadherin loss ............ 53
Gene expression profiling identifies global changes resulting from E-cadherin
loss
............................................................................................
55
Expression of multiple transcriptional regulators are induced upon E-cadherin
loss but not cell-cell disaggregation......................................................................57
Upregulation of Twist upon loss of E-cadherin and its functional role .................. 58
Materials and Methods..................................................................................................
62
Figures................................................................................................................................. 68
Acknowledgements.......................................................................................................
83
R eferences ..............................
...................................
. . ............................................ 84
Chapter 3: Chemoresistance and selective inhibition of cancer cells that have undergone
an epithelial-to-mesenchymal transition .................................................. 99
Introduction ................................................................................................................. 100
Results........................................... ....................................................................... 106
106
Chemoresistance in E-cadherin-loss induced EMT ........................................
108
Chemical compound screen .....................................
Validation of screen hits ........................................................... 111
113
Effects of salinomycin on cancer stem cells .....................................
118
Figures ..............................................
References ................................................................................................................... 125
Chapter 4: Conclusions and Future Directions .....................................
E-cadherin and Metastasis .....................................
Loss of E-cadherin as an inducer of EMT .....................................
Mechanism of EMT induction upon E-cadherin loss ....................
....................
EMT and Chemoresistance .....................................
Chemical screen identifies compounds targeting cells in the mesenchymal state......
Potential mechanisms of action and limitations of salinomycin.............. ...............
Final perspective ........................................
References ...................................................................................................................
A ppendix 1................................... ................................................................ ...........
A ppendix 2...................................................
A ppendix 3...................................................
129
130
132
133
137
140
142
143
145
161
172
177
Chapter 1
Introduction
Metastasis is the primary cause of cancer-related mortality
Metastasis is the spread of cancer cells from a primary tumor to secondary sites
throughout the body. While patients with primary tumors, if they are detected early, can
be cured with surgical removal and chemo/radiotherapy, those that present with
metastases have a much poorer prognosis. In fact, 90% of cancer-related deaths arise
from metastatic growths of cancers that become resistant to therapy. Therefore, it is of
vital importance to understand the molecular mechanisms that allow cancer cells to
metastasize with the hope that such an understanding will enable the development of
novel therapeutic approaches against metastatic and therapy-resistant cancers.
Invasion-metastasis cascade
The majority of cancers originate in epithelial tissues, resulting in carcinomas.
During the initial steps of tumorigenesis, normal epithelial cells acquire genetic and
epigenetic alterations that confer multiple traits necessary for primary tumor formation,
including self-sufficiency in growth signals, extended replicative potential, and a capacity
for inducing angiogenesis (Hanahan and Weinberg, 2000). However, the process of
dissemination presents multiple additional challenges for the carcinoma cells residing in
the confines of an epithelium. The multiple physical steps that the carcinoma cells have
to complete in order to form distant metastases are referred to as the "invasion-metastasis
cascade" (Weinberg, 2007).
Multi-step nature of the invasion-metastasis cascade
Local invasion and intravasation
Within a normal epithelium, individual epithelial cells are held in place by strong
cell-cell and cell-matrix adhesions and are separated from adjacent stromal cells by a
dense network of glycoproteins and proteoglycans known as the basement membrane.
Breaching this barrier is the first step toward malignancy for the incipient transformed
cells. In fact, those tumors that have not yet done so are classified as benign or in situ and
their prognosis is significantly better (Weinberg, 2007).
Local invasion is a coupled process involving both extracellular matrix (ECM)
degradation and cellular motility. Proteolytic degradation of the basement membrane
happens mainly through the actions of matrix metalloproteases (MMPs). MMP-mediated
cleavage of the ECM may also lead to the release of sequestered growth factors and
chemokines that increase proliferation and motility of tumor cells (Egeblad and Werb,
2002). With local invasion cancer cells gain more direct access to blood vessels, which
provide enhanced nutrients and oxygen to the growing tumor. Except in a few types of
cancers, such as lobular breast carcinomas, where single cells can be observed to invade
into the stroma, local invasion of most carcinomas occurs primarily through collective
(en masse) invasion into nearby stroma (Friedl and Wolf, 2003).
Dissemination of cancer cells throughout the body occurs mainly via the
bloodstream. Lymphatic spread is also widely observed in some carcinomas, and this
form of metastasis is thought to be an early prognostic indicator of tumor invasiveness
(Wong and Hynes, 2006). How the individual or clusters of carcinoma cells enter the
lumina of blood or lymphatic vessels is not completely understood. One molecular
determinant of the intravasation process was discovered by Yang et al. from our
laboratory. In that study, the transcription factor Twist was found to be essential for the
intravasation and eventual lung metastasis of murine mammary carcinoma cells
implanted subcutaneously (Yang et al., 2004). As will be discussed below, expression of
Twist in carcinoma cells leads to an epithelial-to-mesenchymal transition (EMT) with a
highly motile and invasive phenotype.
Survival in transit
As tumor cells enter the bloodstream they lose their adhesion to the ECM and are
deprived of survival signals that originate from such interactions. Therefore, if they are to
survive, tumor cells must become resistant to apoptosis that is triggered by loss of
anchorage; this form of programmed cell death is called anoikis. Although the actual time
that the tumor cells spend in transit may be on the order of minutes, successful
establishment of anchorage at the secondary site may take far longer. In experimental
systems, genes that confer resistance to anoikis, such as TrkB, XIAP and ILK, have been
shown to also facilitate formation of metastases, suggesting that anoikis resistance may
be a rate-limiting step in the invasion-metastasis cascade (Attwell et al., 2000;
Berezovskaya et al., 2005; Douma et al., 2004; Yawata et al., 1998).
Extravasation
Tumor cells come to arrest in distant capillaries by a variety of means. These
include physical entrapment due to the large diameter of tumor cells, specific attachment
to endothelial cells via integrins and other adhesion receptors, and retention in certain
tissues by chemokine receptor-ligand interactions (Gupta and Massague, 2006). At first,
tumor cells may proliferate inside the lumina of the capillaries, but they eventually break
out and invade into the surrounding tissue in a process called extravasation (Chambers et
al., 2002). Intra-vital microscopy of experimental metastasis models indicate that many
tumors can extravasate quite efficiently; in one model system 83% of intravenously
injected tumor cells were found to have extravasated after 3 days (Luzzi et al., 1998).
This finding suggests that this step of the invasion-metastasis cascade may not require the
acquisition of other traits beyond those involved in cell motility and local invasion.
Colonization and secondary tumor initiation
It has been clinically and experimentally recognized that a majority of
disseminated tumor cells persist in a dormant state in their new microenvironment
without ever growing to form secondary tumors (Chambers et al., 2002; Naumov et al.,
2002). For example, among breast cancer patients that present with only primary tumors,
30-40% were found to have cytokeratin positive- tumor cells in their bone marrow
(Braun et al., 2000). However, a majority of such patients never developed clinically
detectable metastases within four years. Therefore, growth at secondary sites, also known
as colonization, seems to be the least efficient step in the metastatic cascade. As with
primary tumor formation, successful colonization depends on both tumor-cell-intrinsic
and secondary site-specific factors.
Early work from Fidler and colleagues showed that a given primary tumor may
harbor rare subclones with high colonizing ability when injected intravenously (Fidler
and Kripke, 1977). More recent studies have suggested that only a subpopulation of cells
within solid tumors, termed cancer stem cells (CSCs), have the ability to seed the
formation of new tumors upon transplantation (Al-Hajj et al., 2003; Wicha, 2006). The
implication of these findings is that certain tumor cells, due either to their mutational
status and/or their differentiation state, are more likely to generate secondary tumors. The
functional differences that allow such subpopulations of cells to be more adept at
colonization are not well understood. However, the ability to elicit angiogenesis, to
recruit appropriate stroma, and respond to site-specific growth factors are likely to be
important factors in governing colonizing ability (Chambers et al., 2002).
Resistance to therapy
Although it is not considered to be a distinct biological step in the invasionmetastasis cascade, resistance to chemotherapy is intimately linked to the progression of
metastatic disease. In fact, eviidence from model experimental systems indicates that
migratory cells isolated from primary tumors express anti-apoptotic genes and are able to
survive chemotherapy to a greater extent (Goswami et al., 2004). Most patients whose
primary tumors are surgically removed also undergo a regimen of radiation and/or
chemotherapy. Therefore, secondary tumors thatlater arise in such patients must have
survived these initial cytotoxic treatments. When metastases become clinically apparent,
patients generally undergo a second round of extensive therapy. However, these later
treatments are rarely curative, meaning that metastatic tumors almost invariably become
resistant to subsequent rounds of therapy.
Epithelial-to-mesenchymal transition (EMT)
Due to its multi-step nature, the successful completion of the metastatic process
requires the acquisition of multiple traits by tumor cells. An important conceptual
question in the field of metastasis research has been how a transformed epithelial cell
manages to accumulate such a multitude of malignancy-associated traits. When this thesis
work was started, a transdifferentiation program that naturally occurs during development
termed epithelial-to-mesenchymal transition (EMT) was put forth as a possible
mechanism to the simultaneous acquisition of such traits (Thiery, 2002).
EMT is a normal physiological process
One aspect of an EMT is the loss of epithelial-cell attributes, such as cell polarity,
cell-cell adhesion, and cytokeratins, which are epithelium-specific intermediate filaments.
Concomitantly, cells undergoing an EMT acquire mesenchymal phenotypes, such as
spindle-shape morphology, increased motility, expression of vimentin, a mesenchymespecific intermediate filament, and N-cadherin, a cell adhesion molecule normally
expressed in neurons, muscle cells and fibroblasts (Figure 1).
EMT is a physiological process that occurs during various stages in embryonic
development. It is used mainly to create new tissues from existing cell layers, for
example during the formation of mesoderm in gastrulation and migration of the neural
crest cells from the neural plate (Savagner, 2001). Later in development, EMTs can be
observed during tubulogenesis and branching in the mammary gland and in wound
healing, where it is necessary for the re-epithelization of the wound by adjacent
keratinocytes (Grunert et al., 2003). For example, skin from knock-out mice lacking Slug,
an EMT-inducing transcription factor, shows impaired wound healing and keratinocyte
migration (Savagner et al., 2005).
Evidence for the EMT in carcinoma progression
A role for the EMT in carcinoma cell invasion was first described by Thiery and
colleagues almost 20 years ago (Boyer et al., 1989a; Boyer et al., 1989b). Since then,
direct demonstration of an EMT in human tumor samples has been difficult for two main
reasons. First, EMTs are
observed to occur in response to extracellular signals
originating from the tumor stroma; therefore they are thought to happen in a minority of
cells at the invasion fronts of carcinomas (Brabletz et al., 2001; Weinberg, 2007). Second,
histological staining of human tumors with conventional markers cannot distinguish the
mesenchymal cells that are formed during an EMT from the fibroblasts present in the
tumor stroma. For these reasons, studies on EMT and carcinoma progression initially
utilized in vitro cell lines, mouse models and eventually gene expression analyses of
clinical samples.
One of the first systems used to study the EMT was the Madin-Darby canine
kidney (MDCK) epithelial cell line. The scattering behavior of these cells in response to a
fibroblast-derived factor led to the identification of the hepatocyte growth factor (HGF),
the ligand for the c-Met receptor tyrosine kinase (Stoker and Perryman, 1985). c-Met is
known to be overexpressed or activated in certain carcinomas and can drive tumour
progression in vivo (Thiery, 2002). Another cell line frequently used in EMT studies is
the Eph4 mouse mammary carcinoma cell line. Studies by Beug and colleagues showed
that activation of the transforming growth factor-beta (TGF-3) signaling in Ras-
transformed Eph4 cells suffices to induce an EMT in vitro and metastasis in vivo (Oft et
al., 1996).
Subsequent to these studies that employ soluble proteins, specific transcription
factors that can program the EMT were identified (see below). Since then, many studies
have shown that cultured epithelial cell lines of various sources can be induced into a
mesenchymal phenotype by overexpressing
one of these factors (Batlle et al., 2000;
Bolos et al., 2003; Cano et al., 2000; Comijn et al., 2001; Perez-Moreno et al., 2001; Wu
et al., 2006; Yang et al., 2004). In addition, the expression levels of these transcription
factors were evaluated in human tumors. Histological studies showed that increased
expression of individual EMT-inducing transcription factors (EMT-TFs) is associated
with metastatic progression, poor prognosis, and tumor dedifferentiation (Aigner et al.,
2007a; Blanco et al., 2002; Elloul et al., 2005; Martin et al., 2005). For example, in breast
cancers, expression of the EMT-TFs Slug and Twist is detected preferentially in primary
tumors of patients who later develop metastatic disease (Martin et al., 2005).
More recently, transgenic mouse models have been employed to study the EMT
in carcinoma progression. For example, expression of one of the EMT-TFs, Snail, has
also been linked directly to tumor recurrence in a doxycycline-inducible MMTV-Her2
mouse mammary tumor model (Moody et al., 2005). In addition, passage though an EMT
has been shown to be required for metastasis of polyoma virus middle T antigen (PyVMT)-driven mouse mammary tumors (Xue et al., 2003). This was accomplished by
placing the thymidine kinase gene under the control of an EMT-specific promoter
(S100A4).
Administration of gancyclovir to transgenic MMTV-PyV-MT animals
inhibited lung metastases of mammary tumors, indicating that cells responsible for the
metastases undergo an EMT at one point in tumor progression (Xue et al., 2003).
Since several distinct transcription factors can lead to the same well-defined cell
biological phenotypes associated with a mesenchymal state, the EMT is thought to have a
core transcriptional program. In fact, gene expression profiling of cell lines expressing
different EMT-inducers have revealed a set of genes that are co-regulated during the
EMT (Jechlinger et al., 2003; Moreno-Bueno et al., 2006). Recent studies have taken
advantage of the presence of a core EMT signature to look for evidence of an EMT in
human tumor samples. Genes associated with an EMT were found to be upregulated in
high-risk head-and-neck squamous cell carcinomas, metaplastic carcinomas of the breast,
invasive thyroid carcinomas, and metastatic melanomas (Alonso et al., 2007; Chung et al.,
2006; Lien et al., 2007; Vasko et al., 2007). In addition, gene expression of profiling of
disseminated tumor cells obtained from bone marrow aspirates of breast cancer patients
indicated that these micrometastatic cells express high levels of Twist (Watson et al.,
2007). Interestingly, in this study the patients had already received multiple rounds of
chemotherapy, suggesting that the Twist-expressing disseminated cells survived such
treatment (Watson et al., 2007). Further studies utilizing laser capture microdissection to
isolate tumor cells at the tumor-stroma interface are likely to yield additional evidence for
an EMT in solid tumors.
EMT in the invasion/metastasis cascade
One of the hallmarks of the EMT is loss of epithelial cell-cell adhesion by
repression of the classical adhesion molecule E-cadherin. Loss of cell-cell adhesion is
thought to be a necessary step in the invasion-metastasis cascade, as it allows detachment
of carcinoma cells from one another. In fact, inhibition of disaggregation by E-cadherin
overexpression diminishes invasiveness of aggressive cell lines in vitro and prevents
progression from adenoma to carcinoma in vivo (Frixen et al., 1991; Perl et al., 1998).
The role of E-cadherin in metastasis and how its expression is regulated is discussed in
more detail below.
Loss of cell-cell adhesion during an EMT is associated with a concomitant
increase in carcinoma cell motility and invasiveness. Motile behavior induced by an EMT
is due in part to the activation of small GTPases, such as Rho (Bhowmick et al., 2001).
Importantly, expression of RhoC has been shown to be necessary and sufficient for
metastasis of in model systems (Clark et al., 2000). The EMT also leads to increased
expression of certain MMPs, such as MMP-2 and MMP-9 (Jorda et al., 2005; Tester et al.,
2000). Therefore, an EMT may allow cancer cells to invade locally and migrate through
the endothelium of capillary walls to intravasate into the bloodstream.
Recent studies have revealed that the induction of an EMT, in addition to
promoting the early steps of the invasion-metastasis cascade, may allow cancer cells to
complete the subsequent steps as well. For example, the transcription factor Snail, a
potent inducer of EMT, has been shown to confer resistance to apoptosis induced by
withdrawal of growth factors (Vega et al., 2004). There is also a growing body of
literature indicating that the EMT can confer resistance to genotoxic stress, such as that
induced by chemotherapeutic agents (Robson et al., 2006; Wang et al., 2004; Zhang et al.,
2007). Therefore, cancer cells that have undergone an EMT may be better equipped to
survive in the circulation. In addition, those who have already disseminated and formed
micrometastases at the time of therapy may be able to withstand such treatments,
eventually leading to recurrence.
Colonization of distant tissues may ultimately be tied to the ability of
disseminated tumor cells to self-renew or exist in a cancer stem cell (CSC)-like state. At
least in breast carcinomas, the CSCs have the following important cellular properties: (1)
CSCs can be enriched by sorting cells for CD44high/CD24 low antigenic profile (Al-Hajj et
al., 2003); (2) CSCs can form spherical colonies in specialized suspension cultures; these
colonies are termed mammospheres (Dontu et al., 2003; Dontu and Wicha, 2005); (3)
CSCs can form tumors at limiting dilution with as little as 1000 cells (Al-Hajj et al.,
2003; Ince et al., 2007). Recent work from our laboratory has shown that induction of an
EMT in transformed mammary epithelial cells results in the acquisition of all of these
CSC properties (Mani et al., 2008). In addition, induction of EMT in other model systems
and clinical tumors has been linked to dedifferentiation, tumor recurrence, and decrease
in relapse-free survival in patients with breast cancer (Aigner et al., 2007a; Moody et al.,
2005).
The hallmarks of the EMT enumerated above suggest that this transition can
potentially allow the carcinoma cells to execute many of the rate-limiting steps in the
invasion-metastasis cascade. Therefore, there has been great interest to identify the
mechanisms that can trigger an EMT in carcinoma cells.
Regulation of the EMT
Extracellular signals that induce the EMT
During development, EMTs are induced by a combination of extracellular
morphogenic proteins, such as fibroblast growth factor (FGF), platelet-derived growth
factor (PDGF), epidermal growth factor (EGF), transforming growth factor beta (TGF-P),
bone morphogenetic protein (BMP) and Wnt family members (Peinado et al., 2007). In
addition, carcinoma cells can be induced in vitro to undergo an EMT by HGF, IGF
(insulin-like growth factor), TNF-a (tumor necrosis alpha), PDGF, EGF, TGF-P, Notch
and Hedgehog signals (Huber et al., 2005). In tumors, these EMT-inducing signals are
thought to originate mainly from the nearby activated stroma, although in some cases
tumor cells themselves may have autocrine expression of these factors (Vincent-Salomon
and Thiery, 2003). It should be noted that there is quite a bit of cell type specificity in
EMT induction by these various signaling pathways. In addition, the underlying genetic
makeup of carcinoma cells can collaborate with certain extracellular signals to induce the
EMT, as in the case of Ras mutations and TGF-P signals (Oft et al., 1996).
Transcriptional control of the EMT
In addition to extracellular proteins, a number of transcription factors are
necessary and/or sufficient to induce the EMT both in physiological and pathological
contexts. These have originally been identified as important developmental regulators.
For example, Snail belongs to a family of zinc finger-containing transcriptional
repressors and plays an important role in the control of gastrulation (Barrallo-Gimeno and
Nieto, 2005). Slug is a related family member that functions during neural crest migration
(Nieto et al., 1994; Savagner et al., 1997). Twist is a basic-helix-loop-helix (bHLH)
transcription factor necessary for mesoderm specification (Furlong et al., 2001). Among
other such developmentally important EMT-inducing transcription factors (EMT-TFs)
are Sipl, Goosecoid, and FoxC2 (Comijn et al., 2001; Hartwell et al., 2006; Mani et al.,
2007). In addition, there are EMT-TFs that were identified based on their ability to cause
repression of E-cadherin expression, which is a hallmark of the EMT. These are the zinc
finger protein Zebl (also known as BEF1 and TCF8) and the bHLH proteins E47 and
E2A (Eger et al., 2005; Perez-Moreno et al., 2001) (Figure 1).
In the context of both physiological and pathological EMTs, the expression of
EMT-TFs is regulated by various upstream signals. During development, Snail and Twist
are under the control of FGF and NF-ic3 signaling pathways, a finding that is
recapitulated in carcinoma cell lines (Jiang et al., 1991; Julien et al., 2007). On the other
hand, Slug is regulated by the P-catenin/Wnt pathway through direct transcriptional
induction in both Xenopus development and colon cancer cell lines (Conacci-Sorrell et al.,
2003; Vallin et al., 2001). Recently, high-mobility group protein HMGA2 has been
shown to be essential for the TGF-0 induced expression of Snail, Slug and Twist
(Thuault et al., 2006). Twist is also a target of EGF-receptor signaling, where EGFR
activation results in the direct binding of signal transducer and activator of transcription-3
(STAT3) to the twist promoter (Lo et al., 2007). IL-6 or Src-induced activation of STAT3
can also lead to increased Twist expression (Cheng et al., 2008). The regulation of other
bHLH and ZEB factors during an EMT is almost completely unknown.
While the upstream signals that induce these factors are diverse, all of the EMTTFs share a common downstream target, the classical epithelial cell adhesion molecule E-
cadherin. These factors regulate E-cadherin expression either by binding directly to its
promoter or through indirect mechanisms (Peinado et al., 2007). As this thesis focuses on
how E-cadherin expression affects metastatic progression, the following sections will be
devoted to this protein.
E-cadherin is an important epithelial cell adhesion molecule
E-cadherin (originally termed Uvomorulin) was first identified as the target of an
antibody capable of preventing calcium-dependent compaction of mouse embryos and
embryonal carcinoma cells (Hyafil et al., 1981; Peyrieras et al., 1983; Yoshida and
Takeichi, 1982). Expression cloning using such antibodies allowed the isolation and
characterization of the murine E-cadherin cDNA, which was then shown to be sufficient
to cause cell-cell adhesion (Nagafuchi et al., 1987; Schuh et al., 1986). In addition, earlier
experiments using E-cadherin antibodies demonstrated an essential role for this molecule
in maintaining epithelial cell adhesion (Behrens et al., 1985; Gumbiner et al., 1988;
Vestweber and Kemler, 1985). E-cadherin is the principal component of the adherens
junctions between epithelial cells.
E-cadherin is expressed in all epithelial tissues (Shimoyama et al., 1989). The Ecadherin knock-out phenotype is early embryonic lethal due to decompaction of the
preimplantation embryo (Larue et al., 1994; Riethmacher et al., 1995) Conditional
deletion of E-cadherin in adult tissues leads to disruption of adherens junctions and loss
of epithelial integrity. Moreover, loss of E-cadherin results in altered epithelial cell
differentiation, as evidenced by tissue- specific knock-outs in the skin and the mammary
gland (Boussadia et al., 2002; Tinkle et al., 2004; Young et al., 2003). In addition to
mediating cell-cell adhesion, E-cadherin also serves to establish apico-basal polarity, a
hallmark of epithelial cells (McNeill et al., 1990). Therefore, E-cadherin has been viewed
as a gatekeeper of epithelial cell identity (Berx and Van Roy, 2001).
Structure of E-cadherin
Classical cadherin molecules (E- and N-cadherin) have five extracellular cadherin
repeats, a transmembrane, and a cytoplasmic intracellular domain. Cell adhesion is
accomplished through homophilic interactions between cadherin molecules expressed on
adjacent cells. The most amino-terminal cadherin repeat is essential for this process and
contains a histidine-alanine-valine domain and tryptophan residues that mediate transcadherin binding (Blaschuk et al., 1990; Cavallaro and Christofori, 2004; Halbleib and
Nelson, 2006). Classical cadherins preferentially form homophilic interactions (E-E or NN), although heterophilic binding has been observed in certain experimental settings
(Prakasam et al., 2006).
Early work demonstrated that the cytoplasmic domain of E-cadherin is essential
for cell adhesion even though the actual physical binding between two epithelial cells
occurs in the extracellular space (Ozawa et al., 1990). In its cytoplasmic domain, Ecadherin associates with a number of catenin proteins (3, y, p120 and indirectly oacatenin), all of which regulate the association of adherens junction to the underlying actin
cytoskeleton (Halbleib and Nelson, 2006). In addition to having structural roles in
maintaining the adherens junctions, catenins also take part in diverse signaling pathways.
For example, loss of a-catenin leads to hyperactivation of the MAPK signaling, whereas
p120 catenin has been shown to regulate Rho and Nf-1•p pathways (Perez-Moreno et al.,
2006; Vasioukhin et al., 2001; Wildenberg et al., 2006). Among the catenins, the best
studied is p-catenin, whose function as an essential component of the Wnt pathway is
discussed below.
D1-catenin and the Wnt pathway
p-catenin initially binds E-cadherin in the endoplasmic reticulum, and this
interaction is necessary for the proper post-posttranslational delivery of the latter to the
plasma membrane (Chen et al., 1999). In the absence of canonical Wnt signaling,
cytoplasmic p-catenin that is unbound to E-cadherin is targeted for degradation by the
proteasome through its phosphorylation by casein kinase I and glycogen synthase kinase3 beta (GSK-3p) (Nelson and Nusse, 2004). The phosphorylation of p-catenin occurs on
a scaffolding complex containing the axin and the adenomatous polyposis coli (APC)
proteins. Activation of Wnt signaling leads to inhibition of GSK-3p, resulting in
cytoplasmic accumulation and nuclear translocation of f3-catenin, which binds to its
transcription cofactors, T-cell factor/lymphoid enhancer factor (TCF/LEF). TCF/LEF
then activates transcription of Wnt target genes, such as ephrin receptors, CD44, cyclin
D1, fibronectin and c-myc (Clevers, 2006).
An unanswered question in the field has been whether a single pool of p-catenin
can participate in both cell adhesion and Wnt signaling. Since E-cadherin, TCF and APC
all bind to approximately the same binding groove on 3-catenin in mutually exclusive
ways, the level of E-cadherin expression is likely to have an impact on the amount of
3-catenin that is available for TCF/LEF association (Huber and Weis, 2001). Some
studies provide evidence for this notion; for example overexpression of E-cadherin or its
cytoplasmic tail is able to sequester 3-catenin away from the nucleus and decrease Pcatenin-dependent transcription (Conacci-Sorrell et al., 2003; Gottardi et al., 2001;
Kuphal and Behrens, 2006; Orsulic et al., 1999; Stockinger et al., 2001). However, other
studies suggest that there are two distinct molecular forms of 3-catenin that participate
either in Wnt signaling or cell adhesion (Gottardi and Gumbiner, 2004). In addition,
tyrosine phosphorylation of p-catenin in response to growth factor signaling seems to
play an important role in determining which of these functions it can carry out (Brembeck
et al., 2004). While there is growing evidence that E-cadherin-mediated sequestration of
3-catenin can compete with Wnt signaling, it has not been clear whether loss of Ecadherin and the concomitant increase in free cytosolic P-catenin may lower the threshold
of activation of the Wnt signaling pathway.
Mechanisms of E-cadherin loss in human tumors
In a variety of human tumors, histological examination combined with patient
outcome data has revealed that reduced or absent expression of E-cadherin is associated
with poor prognosis, tumor dedifferentiation, and occurrence of metastases (Schipper et
al., 1991; Siitonen et al., 1996; Sulzer et al., 1998; Umbas et al., 1994). A number of
genetic, epigenetic, transcriptional, and post-translational mechanisms may lead to
reduced E-cadherin expression and/or activity. In this section I will briefly discuss these.
Somatic alterations, such as point mutations, in-frame and frame-shift deletions,
and insertions in the E-cadherin gene, have been observed mainly in lobular breast
carcinomas and diffuse-type gastric carcinomas (Becker et al., 1994; Berx et al., 1995;
Berx et al., 1996; Kanai et al., 1994). Importantly, these two tumor types that have E-
cadherin gene mutations also exhibit loss of the wild-type E-cadherin allele, suggesting
that E-cadherin loss in such tumors results from a two-hit mechanism, as seen in the
classical tumor suppressor genes. In addition, germline mutations in E-cadherin are found
in familial gastric cancers, and the tumor cells arising in such families sustain secondary
somatic mutations in the wildtype E-cadherin allele (Guilford et al., 1998). E-cadherin
mutations in other types of cancers are rarely detected, although chromosome 16q22.1,
where the E-cadherin locus resides, is frequently deleted in advanced hepatocellular,
prostate and breast carcinomas (Hirohashi, 1998; Sato et al., 1990; Tsuda et al., 1990).
In contrast to somatic mutations, which happen predominantly in the two types of
cancers mentioned above, many other tumor types exhibit reduced E-cadherin expression
due to hypermethylation of the CpG islands in its promoter (Strathdee, 2002). In a
number of human cell lines, E-cadherin can be re-expressed by treatment with 5azacytidine, an inhibitor of DNA methyltransferases (Graff et al., 1995; Yoshiura et al.,
1995). Moreover, methylation of the E-cadherin promoter has been closely correlated
with malignant progression of breast cancer (Nass et al., 2000).
Another type of transcriptional repression of the E-cadherin promoter occurs via
the action of specific transcription factors involved in the EMT program. This type of Ecadherin repression can also be observed during developmental EMTs, for example, at
the primitive streak in the mouse embryo (Thiery, 2003). Zinc finger proteins, such Snail
and Slug, accomplish E-cadherin repression by recruiting specific chromatin-remodeling
complexes to the E-cadherin locus. These complexes contain the C-terminal binding
protein 1 (CtBP-1), Sin3a and histone deacetylases HDAC1 and 2 (Peinado et al., 2007).
The mechanism by which other EMT-TFs, such as the bHLH protein Twist, repress E-
cadherin transcription remains unknown. However, the E-box sequences in the Ecadherin promoter seem to be essential for Twist-mediated repression (Yang et al., 2004).
E-cadherin expression can also be modulated by post-translational mechanisms.
While the extracellular domains of E-cadherin can be cleaved by proteases such as
MMP7 and ADAM10, its cytoplasmic domain can be a target for proteolytic cleavage by
the 7-secretase activity of Presenilin-1 (Marambaud et al., 2002; Maretzky et al., 2005;
McGuire et al., 2003). All of these proteolytic cleavages result in loss of cell adhesion. Ecadherin
turnover can also be modulated by endocytosis,
internalization
and
ubiquitylation by the E3 ubiquitin ligase Hakai, or phosphorylation by receptor tyrosine
kinases (Avizienyte et al., 2002; Bryant and Stow, 2004; Fujita et al., 2002; Kamei et al.,
1999; Lu et al., 2003).
In addition, expression of certain glycoproteins, such as MUC1
and dysadherin, has been reported to inhibit E-cadherin's adhesive functions (Ino et al.,
2002; Makiguchi et al., 1996).
Main Questions Addressed
The mechanisms by which E-cadherin is inactivated in human tumors can be
placed into two general categories: (1) those that abrogate its adhesion function while
preserving its intracellular domain; and (2) those that lead to E-cadherin's substantial
repression or complete absence. At the time this thesis work was initiated, there was a
large body of work examining E-cadherin expression and mutational status as a
prognostic indicator. However, the contribution of different types of E-cadherin loss to
tumor progression and metastasis was largely undefined.
Since several structural proteins associated with adherens junctions can also have
intracellular signaling functions, I hypothesized that the two types of E-cadherin
inactivation may have qualitatively different outcomes in terms of cancer cell invasion
and metastasis. In the first scenario, loss of E-cadherin's adhesive function may enable
the first step of the metastatic cascade-the disaggregation of cancer cells from one
another. On the other hand, total absence of E-cadherin might lead to activation
downstream signaling pathways that support the successful completion of additional steps
of the invasion-metastasis cascade (Figure 2).
As mentioned above, passage through an EMT has the potential to endow
carcinoma cells with the ability to execute many, if not all, the steps of this cascade.
Importantly, all EMT-inducing transcription factors work, at least in part, by repressing
E-cadherin. Therefore, another question I addressed was whether loss of E-cadherin itself
could be sufficient for the induction of the EMT. In other words, given the known
correlation between loss of E-cadherin expression and the upregulation of these
transcription factors in human tumors, I was interested in learning whether the loss of E-
cadherin is just one manifestation of the multi-component EMT program that is activated
in tumors or whether, alternatively, E-cadherin itself acts as a pleiotropic regulator of cell
phenotype, enabling it to function as a master regulator of epithelial cell behavior.
Figures
EMT-TFs
Snail
Slug
Twist
Zebl
Goosecoid
EMT
Epithelial cells
Mesenchymal cells
E-cadherin
Vimentin
N-cadherin
Fibronectin
Cytokeratins
Figure 1. Schematic representation of the epithelial-to-mesenchymal transition (EMT)
A subset of EMT-inducing transcription factors (EMT-TFs) and the changes they elicit in
epithelial cells are listed.
Wild-type
DominantNegative
Loss of E-cadherin
p12 0
!
ao-catenin
Actin
Actin
Signaling
Signaling
Figure 2. Schematic representation of the structures of wild-type and dominant-negative
E-cadherin molecules. Also shown are cytoplasmic catenins that serve to link E-cadherin
to the underlying cytoskeleton. Note that while the dominant-negative E-cadherin still
binds and sequesters these catenins, the complete absence of E-cadherin leads to their
liberation and potential involvement in downstream signaling pathways.
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Chapter 2
Loss of E-cadherin promotes metastasis via
multiple downstream transcriptional pathways
Tamer T. Onder,"l Piyush B. Gupta,2'3 Sendurai A. Mani,' Jing Yang, 4 Eric S.
Lander,"2 ', and Robert A. Weinberg 1
(1) Whitehead Institute for Biomedical Research, Cambridge, MA 02142
(2) Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139
(3) Broad Institute of MIT and Harvard, Cambridge, MA 02142
(4) Department of Pharmacology and Pediatrics, University of California, San Diego,
School of Medicine, La Jolla, CA 92093-0636
(5) Department of Systems Biology, Harvard Medical School, Boston, MA 02115
An abridged from of this work has been published in:
Onder TT, Gupta PB, Mani SA, Yang J, Lander ES, Weinberg RA. Loss of E-cadherin
promotes metastasis via multiple downstream transcriptional pathways. CancerResearch.
2008. May 15; 68(10):3645-54.
Gene expression profiling was carried out in collaboration with Piyush Gupta in Eric
Lander's laboratory at the Broad Institute and Sendurai Mani in our laboratory.
Experiments involving Twist were completed in collaboration with Jing Yang. Ferenc
Reinhardt provided technical help in animal experiments. All other experimentation was
carried out by the thesis author, Tamer Onder.
Introduction
As discussed in the first chapter, upon progression to high grade neoplasia, cancer
cells acquire qualities that enable them to invade neighboring tissues and, ultimately, to
metastasize. The steps involved in metastatic dissemination include loss of cell-cell
adhesion, increased motility and invasiveness, entry into and survival in the circulation,
dispersion to distant anatomical sites, extravasation, and colonization of some of those
sites (Gupta and Massague, 2006). While significant progress has been made in
identifying molecular alterations responsible for primary tumor growth, the signaling
pathways that regulate metastatic progression are less clear.
One protein prominently associated with tumor invasiveness, metastatic
dissemination, and poor patient prognosis is the epithelial cell adhesion molecule Ecadherin. For example, according to one early study more than 70% of advanced in breast
tumors with either lymph node or distant metastases exhibited reduced E-cadherin
expression (Oka et al., 1993). Similar observations were subsequently made in prostate,
lung and squamous cell carcinomas (Schipper et al., 1991; Sulzer et al., 1998; Umbas et
al., 1994). Based on the function of E-cadherin as a cell-cell adhesion molecule, it was
hypothesized that loss of homotypic epithelial cell adhesion is an important contributor to
carcinoma progression.
Initial in vitro experiments involving forced expression of E-cadherin in invasive
cancer cells showed that E-cadherin acts as a suppressor of invasiveness (Frixen et al.,
1991; Vleminckx et al., 1991). Subsequently, Christofori and colleagues have shown that
loss of E-cadherin can be causally involved in progression from adenoma to carcinoma in
an in vivo mouse model (Perl et al., 1998). In the Rip-Tag model of P-islet cell
tumorigenesis, transgenic expression of E-cadherin prevented malignant progression.
Moreover, expression of a truncated E-cadherin allele that acts as a dominant-negative
accelerated tumor cell invasion (Perl et al., 1998). Recently, the Jonkers group also
showed that combined loss of p53 and E-cadherin in the mouse mammary gland results in
metastatic tumors resembling human lobular breast cancers (Derksen et al., 2006).
In human tumors, loss or reduction of E-cadherin expression can be caused by
somatic mutations, chromosomal deletions, proteolytic cleavage, and silencing of the
CDH1 promoter (Berx et al., 1998; Hirohashi, 1998; Maretzky et al., 2005; Strathdee,
2002). While some of these events, such as point mutations, lead to loss of the adhesive
function of E-cadherin, they may preserve the expression of the intracellular domain of
E-cadherin. Alternatively, other mechanisms of E-cadherin loss, such as promoter
hypermethylation, lead to a complete shut down of E-cadherin synthesis. Therefore, I
first wished to ascertain whether there is a qualitative difference in cell phenotype
following two different types of E-cadherin inactivation.
In light of its well-established function in maintaining adherens junctions, Ecadherin loss ostensibly promotes metastasis by enabling the first step of the metastatic
cascade-the disaggregation of cancer cells from one another. However, it has been
unclear whether E-cadherin loss also supports the successful completion of additional
steps of the invasion-metastasis cascade. Previous work has revealed that several
structural proteins associated with adherens junctions can also mediate intracellular
signaling functions (see chapter 1) (Nelson and Nusse, 2004; Perez-Moreno et al., 2006;
Vasioukhin et al., 2001; Wildenberg et al., 2006). Accordingly, E-cadherin loss may
result in the activation of specific downstream signal transduction pathways that, in turn,
confer traits upon cancer cells facilitating completion of the later steps of metastasis.
In the first part of this work, I examined whether loss of cell-cell contacts is the
sole contribution to metastasis provided by E-cadherin loss. I observed that experimental
inhibition of cell-adhesion alone does not lead to metastasis. On the other hand, inhibition
of E-cadherin protein expression led to the activation of multiple transcriptional pathways
associated with the induction of an epithelial-to-mesenchymal transition and facilitated
robust metastasis. I demonstrated that at least two of these downstream pathways
contribute to the later steps of metastatic dissemination. Thus, these findings reveal a
complex transcriptional network that is controlled by the E-cadherin molecule.
Results
Characterization of in vitro phenotypes resulting from expression of E-cadherin
shRNA and dominant-negative E-cadherin
In the following set of experiments I took advantage of a series of human
mammary epithelial cell lines to express or inhibit genes of interest. These cells were
initially derived in our laboratory from primary human mammary epithelial cells
(HMECs) by the sequential introduction of the genes encoding the SV40 early region and
the telomerase catalytic subunit, yielding immortalized but untransformed human
mammary epithelial cells (HMLE) (Elenbaas et al., 2001). I subsequently infected HMLE
cells with a retrovirus carrying an oncogenic H-ras allele to create the transformed
HMLER cell line. In addition, I infected the cells with a viral vector expressing the green
fluorescent protein (GFP). Figure 1 depicts the scheme used in creating these and
subsequent cell lines.
To resolve E-cadherin's role in cell-cell adhesion from its intracellular signaling
functions, I utilized two distinct methods of inhibiting E-cadherin function: (1) shRNAmediated knockdown of E-cadherin, which resulted in >90% reduction of E-cadherin
protein levels (shEcad) and (2) expression of a truncated form of E-cadherin (DN-Ecad)
lacking the ectodomain of the wildtype protein (Figure 2A, B). This truncation product,
which retains the cytoplasmic domain, has previously been shown to act as a dominantnegative by binding and titrating cytoplasmic proteins associated with the adherens
junctions, thereby abstracting them from wild-type E-cadherin molecules (Dahl et al.,
1996). Importantly, the DN-Ecad construct utilized here mimics many of the in-framedeleted and point-mutated E-cadherin alleles isolated from human tumors. These E-
cadherin alleles have also been shown to be deficient in cell-cell adhesion and to act in a
trans-dominant manner in cell-based assays (Handschuh et al., 1999).
HMLER cells expressing control shRNA (shCntrl) grew in monolayer culture as
epithelial clusters with a typical cobblestone morphology, while knockdown of Ecadherin and expression of the dominant-negative protein both resulted in loss of cellcell contacts and cell scattering (Figure 2A). Similar phenotypes were observed with the
immortalized HMLE cells as well (Figure 3A).
While the cell populations expressing shEcad and DN-Ecad both lost cell-cell
adhesion, the individual cells expressing shEcad displayed, in addition, an elongated,
fibroblastic morphology (Figure 2A, 3A). To confirm that this phenotype was a specific
consequence of E-cadherin ablation, I re-expressed a wild-type E-cadherin in HMLEshEcad cells. Expression of an shRNA-resistant wild-type murine E-cadherin gene
reversed the observed phenotypes, causing the shE-cad cells to revert to an epithelial
morphology and to regenerate a cobblestone growth pattern in monolayer culture (Figure
4A,B).
The acquisition of a fibroblastic morphology by the cells expressing shEcad
suggested that these cells had undergone an epithelial-to-mesenchymal transition (EMT).
To determine whether, in addition to the observed morphological changes, the molecular
alterations associated with an EMT occurred upon loss of E-cadherin, I assessed the
status of EMT markers in control, shEcad- and DN-Ecad- expressing cells. Upon shRNAmediated loss of E-cadherin, expression of mesenchymal proteins, such as N-cadherin
and vimentin, was markedly upregulated (Figure 2B, C, 3B). In contrast, none of the
mesenchymal proteins was upregulated in the HMLER-DN-Ecad cells (Figure 2B).
While the expression of adherens junction-associated catenins was largely maintained in
the absence of E-cadherin, epithelial cytokeratins were downregulated (Figure 2B). These
observations indicate that complete loss of E-cadherin protein results in an EMT, whereas
inhibition of E-cadherin-mediated cell-cell adhesion causes cell scattering without the
additional changes in differentiation state associated with passage through the EMT
program.
Primary tumor formation and metastasis of E-cadherin-inhibited cells
To determine whether E-cadherin perturbation affects primary tumor growth, I
injected the control HMLER cells and the two E-cadherin-inhibited derivative lines
subcutaneously into immunocompromised mice. While all three cell lines generated
primary tumors with comparable latencies, tumor growth rates differed slightly among
the shCntrl, DN-Ecad and shEcad HMLER cells, with the latter growing most rapidly
(Figure 5A). I confirmed that E-cadherin suppression and expression of the dominantnegative construct were maintained during the course of tumor growth (Figure 6A).
Immunohistochemical staining of tumors with anti-E-cadherin antibodies also supported
this conclusion (Figure 6B).
I next determined whether metastatic dissemination to the lungs occurred when
these various transformed cells were implanted in an orthotopic tissue site-the
mammary fat pad. To facilitate detection of micro- and macroscopic metastases, I
engineered the various introduced HMLER cells to express the green fluorescent protein
(GFP). I controlled for differences in primary tumor growth rates by sacrificing animals
when their tumor burden reached a pre-established threshold. Accordingly, the mean
primary tumor weights at the end of the experiment were comparable across the shCntrl,
shEcad and DN-Ecad cohorts (Figure 6B).
In consonance with previous findings (Elenbaas et al., 2001), control HMLER
cells did not form any macroscopic nodules in the lungs, and only a few GFP-positive
cells could be detected as micrometastases in the lungs of animals bearing these tumors
(Figure 5D). In contrast, animals bearing HMLER-shEcad tumors harbored numerous
micro- and macroscopic metastases in their lungs (Figure 5D).
In fact, the lung
metastatic burden in animals bearing HMLER-shEcad tumors covered a substantial
portion of the total lung surface after an 8 week incubation period. (Figure 5C, D). While
I did find small numbers of cells in the lungs of mice bearing HMLER-DN-Ecad tumors,
macroscopic nodules were never observed. These results indicate that the two modes of
E-cadherin inhibition yield cancer cells with qualitatively different metastatic powers.
Since the HMLER-DN-Ecad cells were incapable of forming macroscopic
metastases from primary tumors growing at orthotopic sites, I also subjected these cells to
a less stringent test of metastatic competence - the "experimental metastasis" model,
which involves tail vein injection of tumor cells. Using this assay, HMLER-shCntrl cells
rarely formed macroscopic nodules in the lungs after an 8-week incubation period (2
nodules in 1/5 mice) (Figure 5C, D).
In contrast, HMLER-shEcad cells established
numerous lung macrometastases, some of which invaded the rib cage. However, the DNEcad cells did not form either micro- or macroscopic lung nodules in any of the mice,
thereby echoing the previous results (Figure 5D).
Taken together, these observations indicated that while the loss of cell-cell
contacts does not suffice to impart metastatic competence to cancer cells, the concomitant
liberation of adherens junction proteins and other associated proteins from the
cytoplasmic tail of E-cadherin indeed suffices to do so. Hence, in addition to promoting
dissemination from primary tumor sites via the disruption of cell-cell contacts, Ecadherin loss facilitates the successful completion of one or more subsequent ratelimiting steps of the invasion-metastasis cascade.
Functional differences in cell motility, invasion, and anoikis-resistance
To determine the functional changes in cell behavior that occurred following Ecadherin loss, I employed several in vitro assays to characterize the control and Ecadherin-perturbed HMLER cells. More specifically, I utilized Boyden chamber assays
to gauge the migratory and invasive abilities of these various cells. While control cells
were minimally motile and invasive, E-cadherin loss resulted in a significant increase in
both motility and invasiveness (Figure 7A, B). However, the DN-Ecad cells, while more
motile than controls (albeit less so than the shEcad cells), failed to invade through
Matrigel-coated membranes.
Disseminating tumor cells that enter into the bloodstream lose their attachment to
the extracellular matrix, resulting in induction of the form of apoptosis termed anoikis
(Gupta and Massague, 2006). Moreover, expression of anti-apoptotic molecules that
confer resistance to anoikis has been shown to promote metastasis (Douma et al., 2004;
Martin et al., 2004). I therefore set out to evaluate the anoikis-sensitivity of the DN-Ecad,
shEcad and control HMLER cells. When placed into suspension cultures, the viability of
both control and DN-Ecad cells declined dramatically over a 2-day period (Figure 7C); in
contrast, shEcad cultures exhibited only a minor decrease in cell number during the same
time period (Figure 7C). To confirm that loss of viability was indeed a consequence of
increased apoptosis, I stained cells from these cultures with annexin V. While the control
and DN-Ecad suspension cultures exhibited a significant fraction of cells undergoing
apoptosis, minimal annexin V-positivity was observed in the shEcad cultures (Figure 7D).
Taken together, these results indicated that EMT induction upon E-cadherin loss
promotes cancer cell invasiveness and enables survival in the absence of substrate
attachment.
Tumor initiating capacity of E-cadherin inhibited cells
Colonization or establishment of distant macro-metastases, by definition, requires
that the disseminated cells be capable of tumor initiation at the secondary sites. The
recent discovery that tumor formation and growth are driven by a minor subpopulation of
cancer cells within tumors termed cancer stem cells (CSCs), led to the hypothesis that
metastatic ability of a given primary tumor may depend on the prevalence of tumorinitiating cells within that tumor (Gupta and Massague, 2006). Importantly, during the
course of this thesis, research from our laboratory indicated that breast carcinoma cells
that have undergone an EMT display many features of CSCs, such as tumor seeding at
limiting dilutions, formation of mammospheres and high CD44, low CD24 expression
(Mani et al., 2008).
Since I observed that E-cadherin-inhibited HMLER cells were highly metastatic, I
wished to determine whether loss of E-cadherin and the resulting EMT led to the
acquisition of CSC-like properties. Limiting dilution assays indicated that the HMLERshEcad line seeded tumors with as few as 1000 cells in vivo, which was approximately
two orders of magnitude less than the minimum number of cells required by the HMLERshCntrl line to seed tumors (Figure 8A). Additionally, when grown in suspension,
HMLER-shEcad cells showed a -100-fold increase in mammosphere formation relative
to control cells (15 spheres vs. -0.15 spheres per 100 cells; Figure 8B).
These functional assays indicated that the HMLERshEcad line harbored
significantly greater numbers of cells with CSC-like properties relative to the HMLERshCntrl cells. This notion was further supported by FACS analyses using antibodies
against markers that are reported to enrich for breast CSC populations (Figure 8C) (AlHajj et al., 2003). Thus, the HMLER-shEcad line exhibited a -10-fold increase in the
percentage of CD44high/CD24low cells compared to the control HMLERshCntrl line
(Figure 8C). Taken together, these results demonstrated that loss of E-cadherin and the
resulting EMT led to the acquisition of CSC-like properties. Moreover, these findings
lend credence to the idea that the number of metastases generated from a primary tumor
depends on the proportion of cells that have a CSC-like phenotype within that primary
tumor
Molecular mechanism of E-cadherin-loss induced EMT
Collectively, the above experiments indicate that induction of the EMT upon loss
of E-cadherin is sufficient to endow cells with essentially all the traits needed to complete
the invasion-metastasis cascade. Importantly, the acquisition of these traits was not a
direct consequence of the disruption of cell-cell adhesion per se, suggesting that
activation of specific signaling pathways following loss of E-cadherin is important for the
observed phenotypes.
The role of P-catenin in EMT and metastasis induced by E-cadherin loss
A critical intracellular protein associated with the E-cadherin cytoplasmic tail is
3-catenin, which has previously been implicated in the induction of EMTs in various
contexts (Conacci-Sorrell et al., 2003; Eger et al., 2004; Kim et al., 2002; Liebner et al.,
2004; Morali et al., 2001; Yang et al., 2006b). I therefore examined whether E-cadherin
loss influenced [-catenin status and whether such change in [-catenin contributed, in turn,
to the subsequent induction of EMT. While in control cells [-catenin localization was
predominantly associated with cell-cell junctions, shEcad cells exhibited a diffuse
cytoplasmic and nuclear localization pattern (Figure 9A).
Examination of the
phosphorylation status of P-catenin in shEcad cells indicated that it was largely
unphosphorylated and therefore present in an active state (Figure 9A) (Nelson and Nusse,
2004). In contrast, a significant amount of [-catenin protein in control cells was
phosphorylated and thus targeted for ubiquitylation and degradation (Figure 9A).
It is known that the main kinase responsible for phoshorylating and thereby
labeling [-catenin for subsequent ubiquitylation is GSK3-P (Clevers, 2006). In
accordance, treatment of cells with a GSK3-1
inhibitor reduced the amount of
phosphorylated p-catenin in whole cell lysates, suggesting that this pathway is also
functional in the human mammary epithelial cell system (Figure 9A). I next determined
whether the observed levels of p-catenin phosphorylation in control and shEcad cells was
correlated with the activateion state of GSK-30. Indeed, I found that GSK-30 was
largely in a phosphorylated and therefore inactive state in the shEcad cells, in contrast to
its unphosphorylated state in control cells (Figure 9A) (Cross et al., 1995). Hence, loss of
E-cadherin was sufficient to liberate P-catenin from its site of sequestration adjacent to
the plasma membrane and to permit its survival in an unphosphorylated, stabilized state.
To determine whether P-catenin was functionally active following E-cadherin loss,
I inhibited 3-catenin expression in HMLER-shEcad cells using a lentiviral shRNA vector
(shEcad+shBcat; Figure 9B). Downregulation of P-catenin resulted in a slightly reduced
growth rate in vitro (Figure 9C). Importantly, 3-catenin knockdown in shEcad cells
significantly diminished expression of the mesenchymal proteins N-cadherin, vimentin
and fibronectin (Figure 9B). In contrast, the expression of epithelial cytokeratins in the
shEcad cells did not change upon P-catenin knockdown (Figure 8B).
I next assessed whether P-catenin affected cell-biological phenotypes associated
with metastasis. P-catenin inhibition in shEcad cells decreased cancer cell invasiveness
(Figure 9D). In addition, knockdown of 0-catenin sensitized shEcad cells to apoptosis
when the cells were placed in suspension culture (Figure 9D). To assess the contribution,
if any, of 3-catenin to the metastatic behavior of shEcad cells, I introduced the control
shEcad and double knockdown (shEcad+shpcat) cells via the tail-vein directly into the
circulation. I observed that the HMLER+shEcad+shpcat cells were significantly impaired
(approxiametly 10-fold) in their ability to form lung metastases compared to the
HMLER+shEcad cells (Figure 9E).
Since P-catenin was necessary for various aspects of the EMT occurring
following E-cadherin loss, I examined whether P-catenin activation would, on its own,
suffice to induce EMT. To accomplish this I made use of an N-terminal truncation
mutant of P-catenin that is refractory to GSK-30 mediated phosphorylation and
subsequent degradation (Kolligs et al., 1999). Overexpression of this constitutively active
p-catenin in HMLE cells failed to induce an EMT (Figure 9F). Although significant
overexpression was achieved, I did not detect any increase in the expression of
mesenchymal markers and no change in cell morphology (Figure 9F). Taken together,
these data indicate that while p-catenin is required for changes in the expression of
certain biochemical markers associated with the EMT as well as for acquisition of traits
facilitating metastasis, it does not suffice on its own to induce these phenotypes.
Gene expression profiling identifies global changes resulting from E-cadherin loss
To obtain an unbiased view of the molecular changes resulting from the liberation
of intracellular adherens junction proteins from the cytoplasmic domain of E-cadherin,
we compared the gene expression profiles of the shEcad, DN-Ecad, and control cells. In
order to avoid the influence of specific oncogenic lesions, we utilized the immortalized,
non-transformed mammary epithelial (HMLE) cells for this analysis. Furthermore, we
reasoned that a comparison between the shEcad- and the DN-Ecad- expressing cells
would make it possible to identify those changes in gene expression that were not
consequences of the loss of cell-cell adhesion. In addition, we incorporated into this
analysis the expression profile of cells in which both E-cadherin and p-catenin were
inhibited; this would allow us to evaluate the contribution of p-catenin to the gene
expression changes observed following inhibition of E-cadherin.
The global expression profiles revealed that the shEcad cells exhibited
significantly greater overall differential gene expression relative to the control cells than
did the DN-Ecad cells (Figure 10A, B; see Appendix 1 and 2 for complete lists).
Nonetheless, there was an overlap between the genes that were differentially expressed in
both the shEcad and DN-Ecad cells relative to the control cells (18 induced and 59
repressed; Appendix 3). This indicated that the loss of cell-cell contacts, on its own,
suffices to alter expression of this subset of cellular genes.
Among the genes significantly induced in the shEcad cells relative to controls
were a number of mesenchymal markers known to be associated with passage through an
EMT, including N-cadherin, vimentin, fibronectin, and 7 distinct collagens. In addition
to these induced mesenchymal
markers,
11 distinct cytokeratin genes
were
downregulated in the shEcad cells relative to the controls (Appendix 1). While none of
the above-mentioned mesenchymal genes was induced in cells expressing DN-Ecad, we
did observe downregulation of 4 of the 11 cytokeratin genes in the DN-Ecad-expressing
cells.
We further analyzed these changes by testing for their association with the
biological processes arrayed in the Gene Ontology (GO) database (Dennis et al., 2003).
Genes most significantly downregulated in the shEcad and DN-Ecad cells were, in both
cases, strongly associated with cell differentiation (Figure 10C). While the genes induced
in the shEcad cells were strongly associated with matrix adhesion and skeletal
development, the genes induced in the DN-Ecad cells were not significantly associated
with any specific biological processes listed in the GO database (Figure 10C). This
indicated that downregulation of certain epithelial genes results directly from the
dissolution of cell-cell contacts, and that the induction of mesenchymal characteristics
required, in addition, the loss of the cytoplasmic domain of E-cadherin.
To directly assess the extent to which of these various cell lines had entered into a
mesenchymal state, we performed hierarchical clustering on the expression data using a
global metric computed on the basis of a 225-gene set capable of discriminating between
mammary epithelial cells that have or have not been induced to undergo EMT by a
variety of means, including the expression of the Snail and Twist transcription factors
(manuscript in preparation).
This analysis revealed that the expression profiles of the
control and DN-Ecad cell lines were essentially indistinguishable with respect to these
EMT-associated genes and were both indicative of cells that have not undergone an EMT
(Figure 10A). In contrast, the expression profile of the shEcad cells indicated that they
had in fact passed through an EMT (Figure 10A). These findings reinforced our earlier
conclusion that the shEcad cells, but not the DN-Ecad cells, have indeed adopted a
mesenchymal cell state.
Expression of multiple transcriptional regulators are induced upon E-cadherin loss
but not cell-cell disaggregation
To evaluate the contribution of P-catenin to the gene expression changes observed
upon E-cadherin loss, we compared the expression profile of the doubly altered cells
(HMLE shEcad + sh3cat) with the profile of the shEcad cells. We observed that -14% of
the genes (84 genes out of 617) that were differentially expressed in shEcad cells relative
to the control cells were dependent upon p-catenin for their regulation. The p-catenindependence of a number of representative genes induced or repressed by E-cadherin loss
is depicted in Figure 10D. Among these p-catenin dependent genes were a subset of
known Wnt target genes such as ephrin B2 receptor, cadherinl 1 and fibronectin (Batlle et
al., 2002; De Langhe et al., 2005; Hadeball et al., 1998).
Since 84% of the gene expression changes that occurred upon E-cadherin loss
were not dependent on p-catenin function, it was likely that other transcriptional
regulators were mediating the transcriptional changes following E-cadherin loss. In fact,
there were 19 transcription regulators that were upregulated more than 3-fold in shEcad
cells relative to control cells (Figure 10E). Of these factors, only two were upregulated in
the DN-Ecad cells, indicating that induction of the remaining 17 required the loss of the
cytoplasmic tail of E-cadherin. In light of the observation that p-catenin is responsible
for a minority of gene expression changes that occurred upon E-cadherin loss, these
findings further implicated one or more of these 17 factors as potential contributors to the
EMT observed following E-cadherin loss.
Upregulation of Twist upon loss of E-cadherin and its functional role
The presence of the transcription factors Twist and TCF8 (ZEB-1) among the set
of genes highly upregulated upon E-cadherin loss was surprising (Figure 10D). Twist
had previously been shown to be essential for the metastasis of mouse mammary tumor
cells and to be expressed in a high proportion of human lobular breast cancers in
correlation with E-cadherin downregulation (Yang et al., 2004). Twist is functionally
related to a set of transcription factors, including Snail, Slug, SIP1, ZEB-1, that are
known to repress E-cadherin expression and are sufficient in various cellular contexts to
induce EMTs.
Based on extensive previous work, these factors are thought to act
upstream of E-cadherin, and several are known to directly repress transcription of the
CDH1 gene itself (Bolos et al., 2003; Cano et al., 2000; Comijn et al., 2001; Eger et al.,
2005; Grooteclaes and Frisch, 2000).
The identification of Twist and ZEB1 in our gene expression data suggested the
opposite possibility-namely that the expression of EMT-inducing transcription factors
may, under certain circumstances, be controlled by the levels of E-cadherin. We pursued
this hypothesis by examining the functional consequences of Twist induction following
E-cadherin loss. Analyses of Twist mRNA levels using real-time RT-PCR validated the
expression array data, indicating that Twist was specifically upregulated in HMLERshEcad but not in control or the DNE-cad cells (Figure 11A).
To determine whether Twist expression played a functionally important role in
the EMT induced upon E-cadherin loss, we super-infected shEcad cells with a lentiviral
shRNA vector targeting Twist.
Introduction of this shRNA vector resulted in an
approximately 5-fold decrease in Twist levels, reducing it below the basal levels present
in the parental HMLER line; Figure 11B).
While Twist inhibition led to a -50%
reduction of N-cadherin levels, the expression of vimentin remained largely unaffected
(Figure 11B).
To further evaluate the functional consequences of Twist upregulation to
metastasis-associated traits, we characterized the contribution of Twist to the induction of
invasion and anoikis resistance following E-cadherin loss. Twist inhibition resulted in a
significant reduction in the invasive behavior of shEcad cells (Figure 11C). In addition,
sensitivity to induction of anoikis was partially restored upon Twist inhibition (Figure
11C).
These findings indicated that Twist is an important mediator of signaling in
response to E-cadherin loss and operates upstream of certain cellular functions that
contribute to metastatic competence. The observed effects on motility, invasiveness and
anoikis-resistance following Twist knock-down were similar to those observed upon 3catenin knock-down. Since the induction of Twist was not P-catenin-dependent, we
concluded that these two factors may be acting in parallel to program the cellular changes
observed following E-cadherin loss.
To determine if Twist was also mediating the acquisition of metastatic powers
following E-cadherin downregulation, we evaluated the metastatic ability of Twistinhibited cells using the experimental metastasis assay. While control shEcad cells were
able to efficiently colonize the lung, as before, cells doubly inhibited for E-cadherin and
Twist exhibited a marked decrease in the ability to do so (Figure 11D). Collectively,
these results indicate that Twist is a crucial downstream effector of cellular functions in
response to E-cadherin loss and is necessary for the metastasis of E-cadherin-deficient
cells.
Taken together, the experiments described in this chapter indicate that while loss
of cell-cell adhesion may be a requisite step in the invasion-metastasis cascade, it on its
own does not enable formation of metastases. On the other hand, loss of E-cadherin
expression is sufficient to endow cells with metastatic powers and it does so through
induction of an epithelial-to-mesenchymal transition (EMT), invasiveness and anoikisresistance. Moreover, wide-ranging transcriptional changes are observed upon E-cadherin
loss, some of which depend on E-cadherin binding partner P-catenin. E-cadherin also
regulates the expression levels of several additional transcription factors, one of which,
Twist, is functionally important for metastasis following loss of E-cadherin.
These
observations indicate that E-cadherin acts a master regulator of epithelial cell identity and
of carcinoma cell dissemination.
Materials and Methods
Cell culture. Immortalized human breast epithelial cells (HMLE) generated through the
introduction of the SV40 large T (LT) antigen, and hTERT were maintained as described
(Elenbaas et al. 2001). To generate tumorigenic and GFP-expressing derivatives, we
infected HMLE cells with a pBabe H-ras and PRRL-GFP vector (Elenbaas et al., 2001).
To measure cell growth rates, 2500 cells were seeded onto 96 well plates in triplicate.
Cell viability was measured using Cell-titer-Glo (Promega) according to manufacturer's
instructions. Treatment with the GSK inhibitor BIO (Calbiochem) was done for 6 hours
at 1gM concentration.
Plasmids. Sequences targeting the E-cadherin and 3-catenin shRNAs were taken from
the website of the RNAi consortium at the Broad Institute and cloned into the PLKOpuro and -hygro vectors 1 (Stewart et al., 2003). E-cadherin and p-catenin targeting
sequences were GCAGAAATTATTGGGCTCTTT and GCTTGGAATGAGACTGCT
GAT, respectively.
Control shRNAs were either targeted against GFP or a non-
functional E-cadherin shRNA. Twist shRNA expression vector was described previously
(Yang et al. 2004). Wildtype and dominant-negative mutant E-cadherin cDNAs (gifts of
Dr. Gerhard Christofori) were expressed from the pWZL-Blasticidin vector. pBp-AN90pcatenin vector was used as described (Hartwell et al., 2006).
1(http://www.broad.mit.edu/genome bio/trc/
Viral Production and Infection of target cells. Viral production and infection of target
cells were described previously (Stewart et al., 2003). Infected cells were selected with
2ug/ml puromycin, 200ug/ml Hygromycin, and 10ug/ml Blasticidin.
Antibodies, Immunoblotting, Immunofluorescence and Histology. Antibodies utilized
were E-cadherin, ax-catenin, 0-catenin, y-catenin, N-cadherin (BD Transduction),
phospho-p-catenin,
phospho-GSK3p,
GSK3P
(Cell
Signaling),
Vimentin
V9
(NeoMarkers), Actin, Tubulin (Abcam), H-Ras (Santa Cruz), Fibronectin (Sigma),
Cytokeratin 8 (Troma-1, Developmental Studies Hybridoma Bank, University of Iowa).
Twist monoclonal antibody was used as previously described (Yang et al., 2004). For
immunohistochemical staining anti-large T antigen (Santa Cruz) and anti-E-cadherin
(Cell Signaling) antibodies were used as described (Elenbaas et al. 2001).
FACS. The anti-CD44 (clone G44-26) antibody conjugated to Allophycocyanin (APC)
and the anti-CD24 antibody (clone ML5) conjugated to Phycoerythrin (PE) used for
FACS analysis were obtained from BD Bioscience and used according to the
manufacturer's instructions. Propidium Iodide (5ug/ml) was included in the staining
protocol to distinguish live cells.
Anoikis assays. 75,000 cells were seeded onto 6-well ultra-low attachment plates
(Coming). After 24 or 48 hours, cells were harvested and incubated at 370 C with 0.25%
trypsin for 5 min to prevent cell aggregation. Viable cells were counted using trypan blue.
For FACS analysis, we used the ApoAlert Annexin V-FITC Apoptosis Kit (Takara-Bio)
according to manufacturer's instructions and used a FACSCalibur flow cytometer
(Becton Dickinson)
Motility and Invasion assays. 5 x 105 cells were resuspended in 1:1 mixture of
DME:F12 and placed into uncoated or Matrigel- coated Transwell inserts containing 8pm filter (BD Falcon) in triplicate. The bottom wells contained DME:F12 media with
growth factors, insulin (10 pg/mL), epidermal growth factor (10 ng/mL), and
hydrocortisone (1 pg/mL). After 12 or 16 hours the cells on the upper surface of the
filters were removed with a cotton swab. The filters were fixed and stained using a DiffQuick staining kit (Dade Behring) and photographed. The migrated cells were then
counted.
Mammosphere Assays. Mammosphere culture was performed as described (Dontu et al.,
2003), except that the culture medium contained 0.9 % methyl cellulose (Stem cell
technologies) to prevent cell aggregation. 102 or 103 cells were plated per well in ultralow attachment 96-well plates (Coming). The mammospheres were cultured for 7-10
days and then photographed and counted.
In vivo tumorigenesis and metastasis assays. NOD-SCID mice (propagated on site) and
nude mice (NCR nude; Taconic, Hudson, NY) were used in these studies, and all
protocols were approved by the Massachusetts Institute of Technology Committee on
Animal Care. Nude mice received 400 rad of 7-radiation using a dual 137Cesium source 1
day before tumor cell injection. Mice were anesthetized with either avertin or isoflurane.
For orthotopic injections, 1 million cells in 20 pl of Matrigel (Becton Dickinson) diluted
1:2 in DME were injected into each of two mammary glands per female NOD-SCID
mouse. For subcutaneous injections, lx 106 cells in 100 pl of Matrigel diluted 1:2 in
DME were injected at each of two sites per nude mouse. Tumor diameters were measured
biweekly using precision calipers. Primary tumor bearing animals were sacrificed when
the tumors reached a diameter of 2 cm. For tail vein injections, 5 x 105 cells in 200 pl
PBS were injected per NOD/SCID mouse and the mice were sacrificed 8 weeks post
injections. For limiting dilution assays 106, 105 104 , and 103 of HMLER-shCntrl or
HMLER-shEcad cells in 100 pl of Matrigel diluted 1:2 in DME were injected
subcutaneously into NOD-SCID mice. The tumor incidence was monitored for 60 days
following injection.
Visualization and Quantification of GFP-Labeled Lung Metastases. Upon necropsy,
lungs of injected mice were removed and examined under a Leica MZ 12 fluorescence
dissection microscope. Images of lung lobes were captured at identical settings. The
amount of metastatic burden was quantified using ImageJ 2 and expressed as a percentage
of the total lung area captured (Rasband, 1997-2006).
Microarray Hybridization, Data Collection, and Analysis. Total RNA was extracted
from 3 independent culture plates for each cell type using an RNeasy Mini kit (Qiagen).
Synthesis of cRNA and hybridization/scanning of microarrays were performed with
Affymetrix GeneChip products as described in the GeneChip manual. Normalization of
the raw gene expression data, quality-control checks and subsequent analyses were
2 http://rsb.info.nih.gov/ii/
performed using the open-source R-project statistical software (http://www.r-project.org/)
(Team, 2007) in conjunction with Bioconductor packages. Raw data files (.CEL) were
converted into probe-set values using RMA normalization. Hierarchical clustering with
complete linkage was performed on the probe-set data using the Euclidean metric. The
probes used for hierarchical clustering and heatmap generation were identified on the
basis of their consistent up-regulation and down-regulation across a set of isogenic lines
(HMLE) that were induced into EMT using a variety of inducers: Twist-, TGF-P3-, Snailor Goosecoid- overexpression.
The identified probes constitute an EMT expression
signature whose targets are >3-fold up-regulated or down-regulated in each of the cell
lines induced into EMT relative to vector control cells that were not induced into EMT.
The microarray data have been deposited in NCBIs Gene Expression Omnibus and are
accessible through GEO Series accession number GSE9691.
SYBR-Green Real-Time RT-PCR. RT-PCR analysis of Twist were carried out as
described
(Yang
et
al.,
2004).
Twist
GGAGTCCGCAGTCTTACGAG,
and
its
TCTGGAGGACCTGGTAGAGG.
GAPDH
GACCCCTTCATTGACCTCAAC,
and
RT-PCR
RT-PCR
RT-PCR
its
RT-PCR
forward
primer
is
reverse
primer
is
forward
primer
is
reverse
primer
is
CTTCTCCATGGTGGTGAAGA. Total RNA extracted as described above was reverse
transcribed with Hexanucleotide Mix (Roche). The resulting cDNAs were used for PCR
using SYBR-Green Master PCR mix (Applied Biosystem) in triplicates. PCR and data
collection were performed on iCycler (BioRad). All quantitations were normalized to an
endogenous control GAPDH. The relative quantitation value for each target gene
compared to the calibrator for that target is expressed as 2 -(Ct"c) (Ct and Cc are the mean
threshold cycle differences after normalizing to GAPDH).
Figures
Primary Human Mammary Epithelial Cells (HMEC)
+ Telomerase - hTert
HME
+ Large T, small T antigen
HMLE
+GFP
+ oncogenic H-Ras
HMLER
Jc-q-----.
4'
shCntrl
shE-cad
DN-Ecad
Figure 1. Schematic representation of the generation of HMLER-shCntrl, shEcad, and
DN-Ecad cell lines. HMLE cell line was created by Elenbaas et al. (Elenbaas et al., 2001).
All subsequent genetic manipulations were performed during the course of this thesis
work as described.
Figure 2. Characterization of in vitro phenotypes resulting from expression of E-cadherin
shRNA and dominant-negative E-cadherin
HMLE R
shCntri
*o
shEcad
po
W-DN-Ecad
0
DU
ap
a
Uj
U
I
N-cadherin
E-cadherin
-
Vimentin
-catenin
-
-
~&catenin
-
a-catenin
DN-Ecad -
CK-8 A
C
E-cadherin
Vimentin
.e-
N-cadherin
shCntrl
shEcad
Figure 2. Characterization of in vitro phenotypes resulting from expression of Ecadherin shRNA and dominant-negative E-cadherin.
(A) The morphology of HMLER-shCntrl, shEcad, and DN-Ecad cell lines as grown
under regular tissue culture conditions.
(B) Expression levels of the endogenous and dominant-negative mutant E-cadherin
(Arrowhead), p-catenin, '-catenin, a catenin, Cytokeratin-8 and mesenchymal proteins
N-cadherin and vimentin in HMLER-shCntrl, shEcad, and DN-Ecad cells examined by
immunoblotting. 3-actin is used as a loading control.
(C) Immunofluorescence staining of E-cadherin (green), vimentin (red) and N-cadherin
(Green) in the HMLER cells expressing either shCntrl or shEcad. The blue signal
represents the nuclear DNA staining by DAPI.
Figure 3. Morphology of shCntrl, shEcad and DN-Ecad expressing HMLE cells
A
B
HMLE
shCntrl shEcad
LUULJ
H-Ras
I
0-catenin
N-cadheri n ~
N-cadheri n
Vimentin
DN-Ecad
_jJ
".W
E-cadherin
shEcad
ijiliJ
-.J
2
shCntrl
Actin
~
~
";~
-~9-~s~A·
I
-WO
Figure 3. Morphology of immortalized HMLE cells expressing shCntrl, shEcad, and
DN-Ecad.
(A) The morphology of HMLE-shCntrl, shEcad, and DN-Ecad cell lines as grown under
regular tissue culture conditions.
(B) Expression levels of H-ras, E-cadherin, P-catenin, N-cadherin and vimentin in
shCntrl- or shEcad- expressing immortalized (HMLE) and transformed (HMLER) breast
epithelial cells examined by immunoblotting. p-actin is used as a loading control.
A
B
shEcad
LL
shEcad
pWB-GFP
E-cadherin
II
N-caanenrn
pWB-Ecad
shEcad
*iN.
Vimentin
Actin
wo
Figure 4. Re-expression of E-cadherin restores the epithelial phenotype in shEcad
cells.
(A) Morphology of immortalized HMLE-shEcad cells expressing control vector (pWB)
or murine E-cadherin expression vector (pWB-Ecad).
(B) Expression levels of E-cadherin, N-cadherin and vimentin in HMLE-shCntrl or
HMLE-shEcad cells expressing control vector (pWB) or murine E-cadherin expression
vector (pWB-Ecad). p-actin is used as a loading control.
disaggregation
Figure 5. Loss of E-cadherin is sufficient for metastasis whereas cellular
isnot
C
B
A
25
-4- MO-*w
- s•Ead
25
15
_
;5 10
9
16
l
0 10 20 30 40 50
ii
Days
Tail-vein
Orthotopic
GFP
LargeT
1·. LargeT
GFP
shCrtrl
S
:·'
T~-,·
I:
shEcad
-;i-_
I-
-.
- - ------
DN-Ecad
**
;;:;:,·
;··
Figure 5. Loss of E-cadherin is sufficient for metastasis whereas cellular
disaggregation is not.
(A) Growth patterns of primary subcutaneous tumors formed by the HMLER-shCntrl,
shEcad and DN-Ecad cells. Each data point represents the mean ± s.d. (standard
deviation) of 8 primary tumors.
(B) Final primary tumor weights of HMLER-shCntrl, shEcad, and DN-Ecad tumors
grown subcutaneously. Each bar represents the mean ± s.d. of 8 primary tumors.
(C) Quantification of total lung metastasis burden in mice bearing either orthotopic
(implanted in mammary gland) primary tumors of HMLER-shCntrl, shEcad, and DNEcad cells or 8-weeks after tail-vein injection of these lines. Each bar represents the mean
± s.d. of 5 mice analyzed per group (* p<0.001).
(D) Representative fluorescence images of mouse lung lobes bearing either orthotopic
primary tumors of HMLER-shCntrl, shEcad, and DN-Ecad cells or 8-weeks after tailvein injection of these lines. GFP signal denotes the presence of tumor cells (Left Panels).
Arrows point to occasional tumor cells detected in the lungs of control and DN-Ecad
tumor bearing animals. Representative immunohistochemical staining of sections with
anti-Large T antibody from the same set of lungs. Brown nuclear staining denotes the
tumor cells. N, lung tissue; M, metastatic nodule (Right Panels).
Figure 6. Maintenance of E-cadherin knock-down and DN-Ecad expression in primary
tumors and tumor-derived cell lines
A
shEcad
shCntrl
.E
Qa
EE E
E
H-H
DN-Ecad
0--
EE
O.H
E-cadherin
Tubulin
DN-Ecad -
shCntrl
shEcad
Large T
E-cadherin
Figure 6. Maintenance of E-cadherin knock-down and DN-Ecad expression in
primary tumors and tumor-derived cell lines.
(A) Expression levels of E-cadherin and dominant-negative mutant E-cadherin
(Arrowhead) in parental and tumor derived HMLER-shCntrl, shEcad, and DN-Ecad cells.
Tubulin is used as loading controls.
(B)Representative serial tumor sections stained for E-cadherin and Large T antigen to
mark the tumor cells (T). Arrowhead in lower left panel points to membranous Ecadherin staining in shCntrl tumors whereas no such staining is observed in shEcad
tumors. Note that the staining in the mouse skin adjacent to the shEcad tumor serves as a
positive control.
Figure 7.Loss of E-cadherin leads to increased invasiveness and resistance to anoikis
A
B
shCntrl
Motilitv
AInvasion
DN-Ecad
shEcad
I t
I i
C
r
r,
LIATM
CD
UA)
U,
w
CO
E
0i
-----
StIW
-·--
LJt1*Cad
M
--
·
I
i `- -ii
5Gc
O
E
g
r
WJ~
j
C)
bP
OOM
I N&Sd OEM
~
I
f Vnnexi
V -
Sh V CN&
Figure 7. Loss of E-cadherin leads to increased invasiveness and resistance to
anoikis.
(A) HMLER-shCntrl, shEcad, and DN-Ecad cells were induced to move or invade
through uncoated or Matrigel-coated transwell membranes. After 12 (uncoated) or 16
(Matrigel-coated) hours the migrated cells were fixed, stained, photographed.
Representative photographs of Transwell membranes showing stained migrated cells
from either motility or invasion experiments.
(B) Quantification of motility and invasion experiments (A) performed by counting the
number of migrated cells. Assays were done in triplicate, and the mean ± s.d. are shown
(* p<0.01 compared to shCntrl).
(C) HMLER-shCntrl, shEcad, and DN-Ecad cells were put in suspension and cultured on
ultra-low attachment plates in triplicate. After the indicated times, viable cells were
counted using trypan blue. Each bar represents the mean + s.d of the remaining viable
cells expressed as a percentage of the initial seeding.
(D) Representative FACS histograms indicating the percentage of apoptotic HMLERshCntrl, shEcad, and DN-Ecad cells in suspension as determined by binding of FITCconjugated Annexin-V. The FACS analyses were done 24 hours after suspension culture.
Each bar on the right graph represents the mean + s.d of the Annexin V positive cells
expressed as a percentage of total cells (*p<0.001).
Figure 8. HMLER-shEcad cells have cancer stem cell-like properties
Tumorigenicity- HMLER
shCntrl
shEcad
1x10 6
8/10
10110
1x1 05
3/4
4/4
1x10 4
1/4
4/4
1x103
0/4
4/4
B
II
QlEcid,
... .....
# of
amrnospheres/ 100 cells
shEcad
shCntrl
i~~k
I )O
~ ~
·-
·1~
CD24
Figure 8. HMLER-shEcad cells have cancer stem cell-like properties
(A) Subcutaneous injections of serial dilutions of HMLER cells expressing either control
shRNA (shCntrl) or shRNA targeting E-cadherin (shEcad). The proportion of injection
sites that developed tumors within 60 days is shown.
(B) Number of mammospheres formed from an initial seeding of 100 cells per well. On
the right are representative photographs of wells showing increased numbers of
mammospheres in HMLER-shEcad seeded wells.
(C) Antigenic profile of HMLER-shCntrl and HMLER-shEcad cells as determined by
FACS analysis with APC-conjugated CD44 and PE-conjugated CD24 antibodies. Note
that CD44h" /CD24Low population is reported to enrich for breast CSCs (Al-Hajj et al.,
2003).
Figure 9. p-catenin is activated upon E-cadherin loss and is necessary for E-cadherinloss-induced EMT
A
B
shEcad
$.catenin + Dapi
#-catenin
U
DMSO GSKi
E-cadherin
shCntrl
p--0
p-
at
.
r:E}}2;
.
?)
:
,catenin
N-cadherin
I
p-GSK3-,
Fibronectin
GSK3-,
shEcad
Vimentin
CK-8
Actin
-
r-
0-.9
aC
0
1
Days
2
3
Ssnostiksa
stican
Anoikis
Invasion
cc
-
shEcad
-0
n,
LU
m
1-catenin
E-cadherin
shEcad +
N-cad herin
-
shBcat
Vimentin
Actin
...
O
Figure 9. P-catenin is activated upon E-cadherin loss and is necessary for Ecadherin induced EMT
(A) Immunofluorescence staining for p-catenin (Green) in shCntrl and shEcad cells
showing differential localization. Right panels show the nuclear DAPI (blue) staining of
the same cells. White arrows indicate the nuclear p-catenin staining observed in the
shEcad cells. Immunoblots showing phospho-P-catenin, total 3-catenin, phosho-GSK3p
and total GSK levels in either untreated shCntrl and shEcad cells or in the same set of
cells treated with DMSO or GSK inhibitor BIO (1pM) for 6 hours.
(B) Expression levels of E-cadherin, 3-catenin, E-cadherin, N-cadherin and vimentin in
HMLER-shCntrl, shEcad, and double-knock down cells (shEcad+shp-cat) cells examined
by immunoblotting. 3-actin is used as a loading control.
(C) In vitro growth rate of HMLER shEcad and shEcad + shBcat cell lines as determined
by Cell-titer-glo assay.
(D) Left graph: HMLER-shCntrl, shEcad, and shEcad + shp-cat cells were induced to
invade through Matrigel-coated transwell membranes. After 16 hours, the invaded cells
were fixed, stained, photographed and counted. Assays were done in triplicate, and the
mean ± s.d. are shown relative to shCntrl cell invasion (*p<0.01 compared to shEcad).
Right graph: The percentage of apoptotic HMLER-shCntrl, shEcad, and shEcad + shp-cat
cells in suspension were determined using binding of FITC-conjugated Annexin-V. The
FACS analyses were done 24 hours after suspension culture. Each bar represents the
mean ± s.d of the Annexin V- positive cells expressed as a percentage of total cells
(*p<0.01 compared to shEcad).
(E) Representative fluorescence images of mouse lung lobes 8-weeks after tail-vein
injection of shEcad or shEcad + shp-cat cells. GFP signal denotes the presence of tumor
cells (Left Panels). Quantification of total lung metastasis burden in the same sets of mice.
Each bar represents the mean ± s.d. of 7 mice analyzed (Right Panels) (*p<0.001).
(F) Overexpression of active B-catenin is not sufficient to cause the EMT.Expression
levels of P-catenin, E-cadherin, N-cadherin and vimentin in HMLER cells expressing
either empty vector (pbp) or truncated p-catenin cDNA (pbp AN-pcat, indicated by
arrowhead). HMLER-shEcad cell lysate was included to serve as a positive control for Ncadherin and vimentin. p-actin was used as a loading control.
Figure 10. Gene expression profiling identifies molecular changes induced upon Ecadherin loss
mill
m M
-"
u
(I
U)
LU
LO
iii 0
M
Z
u,
Figure 11. Twist is upregulated upon E-cadherin loss and plays an essential role in Ecadherin-loss-induced metastasis
B
A
shEcad
-
-
C
L·
z
EQ
'5
5,
ZJ• .
Twist
0
-
C_
(V
EU
0.1
GUL0
>
N-cadherin
--
Vimentin
0r
Actin
C
C
0
v_
"_
Acin
~C
I?
r
go" VECO 04EM~a
Invasion
D
R
,; +
r,
"t
;ap
"
Anoikis
30
shEcad
20)
-1 '
shEcad +
shTwist
Zl
0 1
A
9).1
•T0)JJ
Figure 11. Twist is upregulated upon loss of E-cadherin and plays functionally
important role in E-cadherin loss-induced EMT and metastasis
(A) The relative levels of Twist mRNA measured by real-time RT-PCR in the HMLER
shEcad and DN-Ecad cells compared to shCntrl cells. Each bar represents the mean +
SEM of the PCRs in triplicate.
(B) Expression levels of Twist, vimentin and N-cadherin in HMLER-shCntrl, shEcad,
and double-knock down cells (shEcad + shTwist). 13-actin is used as a loading control.
(C) Right graph: HMLER-shCntrl, shEcad, and shEcad + shTwist cells were induced to
invade through Matrigel-coated transwell membranes. After 16 hours, the invaded cells
were fixed, stained, photographed and counted. Assays were done in triplicate, and the
mean ± s.d. are shown relative to shCntrl cell invasion (*p<0.01 compared to shEcad).
Left graph: The percentage of apoptotic HMLER-shCntrl, shEcad, and shEcad + shTwist
cells in suspension were determined using binding of FITC-conjugated Annexin-V. The
FACS analyses were done 24 hours after suspension culture. Each bar represents the
mean ± s.d of the Annexin V- positive cells expressed as a percentage of total cells
(*p<0.01 compared to shEcad).
(D) Representative fluorescence images of mouse lung lobes 8-weeks after tail-vein
injection of shEcad or shEcad + shTwist cells. GFP signal denotes the presence of tumor
cells (Left Panels). Quantification of total lung metastasis burden in the same sets of mice
is shown on the right panels. Each bar represents the mean ± s.d. of 5 mice analyzed
(*p<0.0 1).
Figure 10. Gene expression profiling identifies molecular changes induced upon Ecadherin loss
(A) Hierarchical clustering of shEcad, DN-Ecad, shEcad+shBcat and shCntrl cells.
Distances between samples were computed using the Euclidean metric applied to a 225probe subset corresponding to genes highly induced or repressed upon EMT (71 genes
induced, 84 genes repressed).
(B) Differentially expressed genes in shEcad and DN-Ecad cells relative to control
shGFP cells. The numbers of genes either induced or repressed that surpass the indicated
threshold of differential expression (1.5x, 2x, 2.5x, 3x log 2-fold change) are depicted.
(C) Gene ontology analysis of differentially induced or repressed genes in shEcad and
DN-Ecad cells with respect to enrichment of genes with assignments to specific
biological processes. Fold enrichment and the number of genes in a particular biological
process are shown. Note that no significant enrichment of genes for any biological
process was observed in DN-Ecad induced genes (indicated by *).
(D) Dependence on 3-catenin of gene expression changes in shEcad cells. Depicted are
representative genes, either induced or repressed in shEcad cells, whose regulation is
dependent on (6 genes on the left) or independent of 3-catenin activity (6 genes on the
right). Each dot represents the value for an individual replicate expression value (colors
correspond to samples) for the gene listed on the x-axis. The dotted line indicates the 1.5
log2 fold-change threshold.
(E) Induction of multiple transcription regulators in shEcad cells. Each dot represents the
value for an individual replicate expression value (colors correspond to samples) for the
gene listed on the x-axis. The dotted line indicates the 1.5 log2 fold-change threshold.
Note that TCF8 (Zeb 1) and Twist are among the highly upregualted genes in this
category.
Figure 11. Twist is upregulated upon E-cadherin loss and plays an essential role in Ecadherin-loss-induced metastasis
A
B
C
shEcad
--
Y
z
6,
ft
W
EuWi
Twist
N-cadherin
n3*16
>bin
61.
Vimentin
*1
G
---
C
C
,
...
f ..
.
4:
"_,
Actin
St
I Ata, CNon d
Invasion
D
shEcad
Anoikis
255
C
.3
'S
shEcad +
shTwist
-4
J
:1
o
Figure 11. Twist is upregulated upon loss of E-cadherin and plays functionally
important role in E-cadherin loss-induced EMT and metastasis
(A) The relative levels of Twist mRNA measured by real-time RT-PCR in the HMLER
shEcad and DN-Ecad cells compared to shCntrl cells. Each bar represents the mean +
SEM of the PCRs in triplicate.
(B) Expression levels of Twist, vimentin and N-cadherin in HMLER-shCntrl, shEcad,
and double-knock down cells (shEcad + shTwist). p-actin is used as a loading control.
(C) Right graph: HMLER-shCntrl, shEcad, and shEcad + shTwist cells were induced to
invade through Matrigel-coated transwell membranes. After 16 hours, the invaded cells
were fixed, stained, photographed and counted. Assays were done in triplicate, and the
mean ± s.d. are shown relative to shCntrl cell invasion (*p<0.01 compared to shEcad).
Left graph: The percentage of apoptotic HMLER-shCntrl, shEcad, and shEcad + shTwist
cells in suspension were determined using binding of FITC-conjugated Annexin-V. The
FACS analyses were done 24 hours after suspension culture. Each bar represents the
mean ± s.d of the Annexin V- positive cells expressed as a percentage of total cells
(*p<0.01 compared to shEcad).
(D) Representative fluorescence images of mouse lung lobes 8-weeks after tail-vein
injection of shEcad or shEcad + shTwist cells. GFP signal denotes the presence of tumor
cells (Left Panels). Quantification of total lung metastasis burden in the same sets of mice
is shown on the right panels. Each bar represents the mean + s.d. of 5 mice analyzed
(*p<0.01).
Acknowledgements
I would like to thank Priyamvada Rai, Tugba Bagci, Richard O. Hynes, David M.
Sabatini, and members of R.A.W.'s laboratory for helpful comments and discussions
throughout the course of these experiments. I also thank Drs. Gerhard Christofori and
Kimberly Hartwell for reagents, Ahmet Acar and Ferenc Reinhart for technical help, and
Casey Gates and the gene expression platform at the Broad Institute for data collection
and helpful advice. Ludwig Center for Molecular Oncology at MIT and the W.M. Keck
Foundation Biological imaging facility at the Whitehead Institute is also acknowledged.
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Chapter 3
Chemoresistance and selective inhibition of cancer
cells that have undergone an epithelial-tomesenchymal transition
Tamer T. Onder,12•' 5 Piyush B. Gupta,2'3 ' Eric S. Lander,''1
4
and Robert A.
Weinberg 1
(1) Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA
02142
(2) Department of Biology, Massachusetts Institute of Technology, Cambridge, MA
02139
(3) Broad Institute of MIT and Harvard, Cambridge, MA 02142
(4) Department of Systems Biology, Harvard Medical School, Boston, MA 02115
(5)These authors contributed equally to this work
The high throughput screening and follow-up validation studies were performed in close
collaboration with Piyush Gupta from the Lander Lab. Initial observation and
characterization of the chemoresistance of mesenchymal cells were performed by the
thesis author.
Introduction
Cancer is the leading cause of death in the US in people under 85 years of age
(Jemal et al., 2008). More than 90% of these cancer-related deaths are due to metastatic
disease that cannot be cured or controlled with the current treatments of surgery, radiation
and chemotherapy. During the past two decades there have been only small decreases in
the death rates from cancer (decrease of 1.5% per year in males from 1992 to 2002 and
0.8% per year in females from 1994 to 2002) (Jemal et al., 2008). In fact, most of the
observed decreases are due to reduction in tobacco use with respect to lung cancers and
early detection in colorectal, breast and prostate cancers (Weinberg, 2007).
The failure to decrease cancer-related mortality is ultimately due to the
inefficiency of current chemotherapeutic drugs. Although treatment is effective in
increasing 5-year survival rates, a large percentage of patients who receive treatment still
succumb to metastastatic relapse. For example, survival rates at 10 years for women
receiving multiple chemotherapy regiments is just above 50% (Clare et al., 2000).
Although in vitro and in vivo studies show that cytotoxic chemotherapy drugs are
effective in killing cancer cells, a majority of them fail to eradicate tumor cells once they
become metastatic. The main reason for this inefficiency is that tumor cells acquire
resistance to killing by such drugs.
There are a number of alternative mechanisms by which tumors become
chemoresistant. Since tumors are often heterogeneous cell populations with genomic
instability and genetic diversity, treatment with anti-cancer agents constitutes a selective
pressure for the outgrowth of subclones with pre-existing resistance mechanisms already
in place (Chabner and Roberts, 2005). One of the mechanisms of acquired resistance is
100
the alteration of proteins targeted by the drug. For example, paclitaxel (a microtubuledestabilizing chemotherapeutic) resistance is associated with the expression of a mutant
form of beta-tubulin that binds this compound with less affinity (Giannakakou et al.,
1997). Such mechanisms have also been observed with more recently developed targeted
therapies. For example, in the case of treatment of chronic myelogenous leukemia (CML)
with imatinib (Gleevec), resistance occurs due to the expansion of clones harboring
mutated bcr-abl alleles. Importantly, cells harboring such mutant and drug resistant
alleles are present before drug treatment (Roche-Lestienne et al., 2002). A similar pattern
is also observed in non-small-cell lung cancers treated with small molecule inhibitors of
the epidermal growth factor receptor (EGFR) (Kobayashi et al., 2005).
In many cases, tumor cells that become resistant to a particular cytotoxic agent
display cross-resistance to unrelated drugs as well. This phenomenon is known as
multiple drug resistance (MDR). MDR is associated with decreased intracellular drug
accumulation and/or inactivation of downstream apoptotic machinery. The first gene
conferring MDR was cloned over 20 years ago by the Housman laboratory and codes for
a p-glycoprotein efflux pump (Gros et al., 1986). Since then a family of such proteins
have been isolated and shown to act as ATP-dependent transporters of small molecules
(Dean et al., 2005). In addition, MDR can be caused by alterations in the apoptotic
pathway, such as mutations in the tumor suppressor p53 gene and overexpression of antiapoptotic Bcl2 protein (Weinberg, 2007). Regardless of how it arises, overcoming MDR
remains one of the biggest challenges to curing or controlling metastatic cancers.
101
Cancer stem cells and chemoresistance
The discovery of cancer stem cells (CSC) has added a new level of complexity to
treatment of tumors. Recent evidence shows that within a primary tumor only a subset of
the cancer cells are able to propagate the tumor, whereas the bulk rest are unable to do so.
Although the presence of such CSCs has long been recognized in hematological
malignancies, they were only recently identified in a variety of solid tumors, such as
cancers of the breast, colon, pancreas, lung, brain and melanoma (Al-Hajj et al., 2003;
Kim et al., 2005; Lapidot et al., 1994; Li et al., 2007; Ricci-Vitiani et al., 2007; Schatton
et al., 2008; Singh et al., 2004). CSCs can be prospectively identified based on expression
of specific cell-surface markers using fluorescence-activated cell sorting (FACS). Such
experiments have shown that within primary tumors only a small percentage of cells are
CSCs. Because the standard approach to identification of candidate chemotherapeutic
compounds relies on inhibition of overall tumor cell growth in short term assays, it is
quite possible that assays of this type would fail entirely to identify potential therapies
targeting minority CSC populations.
Recent reports have indicated that CSCs are more resistant to a wide spectrum of
cancer treatments in current use. For example, CD 4 4 high CD24ol w CSCs isolated from
breast carcinoma lines are resistant to gamma-irradiation and epirubicin, a commonly
used chemotherapeutic drug (Phillips et al., 2006; Yu et al., 2007). Importantly, breast
cancers from patients who received chemotherapy were found to be substantially
enriched in CD 4 4 high CD24 low cells, suggesting that treatment may in fact lead to the
relative outgrowth of CSCs within a given tumor (Yu et al., 2007). In addition, glioma
CSCs, identified based on CD133 positivity, are reported to be
102
resistant to DNA-
damaging agents (Bao et al., 2006; Diehn and Clarke, 2006). CSCs may also be multidrug resistant due to expression of high levels of ATP- binding-cassette (ABC)
transporters implicated in conferring MDR. A recent study show that melanoma stem
cells can be identified based on ABCB5 expression, a known chemoresistance mediator
(Frank et al., 2005; Schatton et al., 2008). It is unclear at this stage whether it is possible
to identify treatments that target CSCs, or whether it might not be the case that CSCs are
inevitably resistant to all forms of therapeutic intervention as a result of an intrinsic
resistance to apoptosis.
The epithelial-to-mesenchymal transition as a determinant of chemoresistance
It has become increasingly evident that an epithelial-to-mesenchymal transition
(EMT) can render cells resistant to various forms of apoptosis. Activation of TGF-P
signaling in mouse mammary carcinoma cells leads to an EMT that is accompanied by
resistance to UV-induced cell death (Robson et al., 2006). TGF-P treatment has also been
reported to lead to resistance to cyclophosphamide and cisplatin, two commonly used
chemotherapeutic drugs (Teicher et al., 1997). Recent reports suggest that the EMT can
also confer resistance to the newer generation of targeted therapies. Gene expression
profiling of 42 non-small-cell lung cancer (NSCLC) cell lines whose erlotinib (an EGFR
inhibitor) sensitivity was predetermined, revealed that resistant cell lines displayed a
strong multi-gene signature indicative of an EMT (Yauch et al., 2005). An independent
report confirmed that NSCLC cell lines that have a mesenchymal phenotype are
insensitive to the growth inhibitory effects of EGFR inhibition in vitro and in xenografts
103
(Thomson et al., 2005). These findings have recently been extended to pancreatic and
colorectal cancer cell lines as well (Buck et al., 2007).
How passage through an EMT enables cells to withstand apoptotic stimuli is not
completely understood. However, accumulating evidence suggests that cell survival is an
intrinsic part of the program activated by the EMT-inducing transcription factors (EMTTFs).
The first connection between
EMT-TFs and
cell survival was made in
Caenorhabditiselegans where a Snail superfamily member, CES1, was shown to block
the programmed cell death of certain neurons (Metzstein and Horvitz, 1999).
Subsequently, Snail was shown to confer resistance to cell death induced by the
withdrawal of serum and by pro-apoptotic signals, such TNF-a.(Vega et al., 2004) The
related family member Slug also has an anti-apoptotic function, protecting hematopoetic
progenitor cells from radiation-induced death (Inoue et al., 2002). Furthermore,
upregulation of Slug in human leukaemias is associated with cell survival, and Slug
overexpression can confer cytokine independence to a IL-3-dependent murine pro-B cell
line to a similar extent as Bcl-2 or Bcl-xL (Inukai et al., 1999).
Other EMT-TFs also have anti-apoptotic functions. For example, Twist was
idenitifed by the Hannon laboratory in a functional screen for genes that could counteract
the proapoptotic effects of the myc oncogene (Maestro et al., 1999). The clinical
relevance of this finding was confirmed by the observation that Twist is overexpressed in
N-myc-amplified neuroblastomas and inhibits the ARF/p53 pathway involved in the
myc-dependent apoptosis (Valsesia-Wittmann et al., 2004). Furthermore, the ability of
NF-icB to block cytotoxicity induced by chemotherapeutic drugs also depends on Twist
expression (Pham et al., 2007). Twist is essential for cisplatin resistance of lung
104
carcinoma cell lines, as experimental Twist inhibition sensitizes these cells to cisplatin.
(Zhuo et al., 2008). Moreover, overexpression of Twist decreases the sensitivity of
various cancer cell lines to paclitaxel, another cytotoxic agent (Cheng et al., 2007; Wang
et al., 2004; Zhang et al., 2007).
The link between EMT and chemoresistance has important implications for
cancer progression and treatment. The EMT may be one process that couples metastatic
dissemination with the development of chemoresistance. As cells that have undergone an
EMT represent the pool of cancer cells most competent to metastasize and lead to tumor
recurrence, it is of vital importance to find therapies that effectively target such cells. In
experiments described in this chapter I establish that cell lines rendered metastatic
through E-cadherin-loss-induced EMT are indeed resistant to a wide range of
chemotherapeutic drugs. These cell lines were then utilized as a basis for a highthroughput chemical library screen to identify compounds that specifically target cells
that have undergone an EMT.
105
Results
Chemoresistance in E-cadherin-loss induced EMT
We first wished to confirm that passage through an EMT confers resistance to
conventional chemotherapeutic drugs. As described in detail in Chapter 2, inhibition of
E-cadherin results in a stable mesenchymal differentiation of the experimentally
transformed HMLER human breast cancer cell line. While control shRNA expressing
cells (HMLER-shGFP) display epithelial phenotypes, such as cobblestone growth
morphology and cytokeratin expression, cells expressing an shRNA vector against Ecadherin (HMLER-shEcad) undergo an EMT characterized by the loss of these epithelial
phenotypes and the acquisition of mesenchymal ones in their stead, such as fibroblastic
morphology and expression of vimentin. We took advantage of these experimentally
derived cell lines to address whether the EMT program results in chemoresistance.
Accordingly, we treated cultured HMLER-shGFP and HMLER-shEcad cells for a
period of 3 days with either doxorubicin or paclitaxel, doing so at various drug
concentrations. Both of these drugs are commonly used chemotherapeutic drugs. While
doxorubicin is a DNA-damaging agent, paclitaxel is a microtubule-depolymerizing
compound. Examination of the dose-response curves indicated that, in the case of both
drugs, the IC50 for the HMLER-shEcad cells was significantly higher than the IC50 for
the HMLER-shGFP cells. This IC50 measurement reflects the dose of applied drug at
which a therapeutic response, such as death of treated cells, is observed. Hence, a higher
IC50 indicates an increased resistance of cells to one or another drug. Thus, compared to
control cells, HMLER-shEcad cells were -3-fold more resistant to paclitaxel and -10fold more resistant to doxorubicin (Figure 1A).
106
Increased drug resistance could be due to differential effects of the transforming
oncogene in the two cell populations or; alternatively, it could be a more general property
of mesenchymal cells or cells that have undergone an EMT. Therefore, we studied
HMLE cells, which are immortalized but non-tumorigenic breast epithelial cells that
differ from HMLER cells in that they lack an introduced HrasV12 oncogene. Importantly,
as described in Chapter 2 and similarly to HMLER cells, loss of E-cadherin in HMLE
cells also results in mesenchymal differentiation.
We treated HMLE-shGFP and HMLE-shEcad cells for a period of three days with
a series of chemical compounds at three different concentrations . These compounds
included the established chemotherapy drugs doxorubicin, paclitaxel, actinomycin D, and
camptothecin, as well as a broad spectrum kinase inhibitor, staurosporine.
The
HMLEshEcad cells displayed an increased resistance to each of the examined drugs,
relative to the HMLE-shGFP cells (Figure 1B). While the extent of resistance depended
on the particular drug examined, the increased resistance was observed for all tested
compounds. This observation indicated that the mesenhymal HMLE-shEcad cells are
intrinsically resistant to cell death compared to their epithelial counterparts, irrespective
of the death-inducing agent used. In addition, the above results indicated that epithelial
and mesenchymal populations of cells exhibit differential sensitivities to a variety of
chemical compounds independent of neoplastic transformation. Therefore, the primary
reason for the differential sensitivity to cell death exhibited by the transformed HMLERshEcad and HMLER-shGFP cells is the divergent differentiation states of these lines.
As mentioned in Chapter 1, in the tumor context the EMT can be induced by
soluble signals originating from the tumor stroma (Brabletz et al., 2001; Weinberg, 2007).
107
In general, a minority of carcinoma cells is in close contact with the surrounding stromal
cells and is thought to have undergone an EMT. Therefore, tumors are likely to be
heterogeneous cell populations composed of a majority of cells in the epithelial
differentiation state and a minority of cells that have acquired a mesenchymal phenotype.
To determine the effect of conventional chemotherapy drugs on a mixture of
epithelial and mesenchymal cells, we co-mixed GFP-labeled HMLE-shEcad cells with
unlabeled HMLE-shGFP cells at a ratio of 1:20, and treated the resulting co-culture with
paclitaxel (Figure 2). This mixture provided an internally controlled method to evaluate
whether differential drug sensitivity was also manifest under conditions in which
mesenchymal cells co-existed with epithelial cells and constituted, at the same time, a
small minority of the overall cell population. After 3 days of paclitaxel (10nM) treatment,
FACS analysis revealed a 3-fold increase in the proportion of mesenchymal HMLEshEcad cells relative to DMSO-treated co-cultures (Figure 2). A more modest increase in
HMLE-shEcad cells was also observed with a lower dose of paclitaxel (2.5nM).
Together, these results indicated that paclitaxel treatment of heterogeneous cell
populations can result in the selective outgrowth of cells that have undergone an EMT.
Chemical compound screen
Collectively, the above observations indicated that the EMT is not only associated with
an increase in metastatic ability but it is also accompanied by an increased resistance to
chemotherapy-induced cell death. Therefore, we speculated that compounds that inhibit
the viability of mesenchymal cells arising from an EMT would preferentially target
cancer cell subpopulations capable of seeding tumors and metastasizing. We postulated
108
that the HMLE-shGFP and HMLE-shEcad cell lines could be exploited for the purpose of
discovering compounds that selectively target the cells in the mesenchymal
differentiation state.
Accordingly, we developed conditions to use an ATP-based luminescence
viability assay with 384-well plates in high throughput screening (see Materials and
Methods). In this assay, the quantity of luminescence emitted by the cells is a measure of
their viability. We screened a library collection of -15,000 compounds in this initial
proof-of-concept screen. These libraries included collections of compounds with known
bioactivity, natural extracts, agents known to affect histone deacetylases, and several
commercial libraries that encompassed a diverse array of potential therapeutic
compounds (see Materials and Methods). To enable rigorous plate-based normalization,
each compound plate carried internal control wells (-10% of total) that contained only
DMSO, the solvent in which the compounds were dissolved. Each compound plate was
pin-transferred into 2 replicates for each of the HMLE-shEcad and HMLE-shGFP cell
lines. Drug treatment was initiated one day following seeding and the cell viability was
measured 3 days following drug treatment (Figure 3A-schematic). We conducted our
screen in duplicate for each of the HMLE-shGFP and HMLE-shEcad cell lines.
Using the measurements from the plate-normalized DMSO control wells, we
constructed the distribution of luminescence intensities for each cell line in the absence of
compound, but in the presence of control solvent. Each measurement for both control
and test wells constituted an average of the two replicates for a cell line. Relative to these
baseline distributions, we calculated a Z-score that reflected the biological effect of every
compound on the cells being tested, one for each of the HMLE-shGFP and HMLE-
109
shEcad cell lines (Figure 3B). The computed Z-scores did not display a positional bias
across drug plate, column, or row number, suggesting that there were no systematic
biases in the analysis of the data normalized relative to the internal control DMSO wells
(data not shown).
Identification of inhibitory compounds using this method indicated that the vast
majority of the compounds inhibited the viability of both the HMLE-shGFP and HMLEshEcad cells. Since we were interested in compounds exhibiting preferential lethality
toward the cells that had been induced to undergo an EMT, we identified those
compounds that inhibited HMLE-shEcad cell viability but did not surpass the threshold
of significance of inhibiting HMLE-shGFP viability.
About 10% of the compounds in the screened collections inhibited the viability of
HMLE-shEcad cells, but the vast majority of these compounds (98%) also inhibited the
control cells. Only -0.2% of total library exhibited selective toxicity toward the HMLEshEcad cells. Various established drugs used for cancer chemotherapy were included in
the compound plates. Less than 1% of these chemotherapeutic agents scored as being
positive in our assay, in that they failed to affect preferentially the cells that have
undergone an EMT. This suggested that compounds targeting rapidly proliferating cells
were not selectively enriched in our assay. In fact, the HMLE-shGFP cells have a
slightly higher rate of proliferation than the HLME-shEcad cells (data not shown). Thus,
there was no enrichment of positive hits in the subset of established chemotherapy drugs
relative to the total compounds screened.
110
Validation of screen hits
Based on their ready availability, we decided to pursue eight of the identified
compounds that were selectively toxic for HMLE-shEcad cells for further study; these
compounds were salinomycin, etoposide, acridine, cetylpyridinium chloride, resorcinol,
clotrimazole, abamectin, and nigericin.
For each of these compounds, we evaluated the effects on cell viability across a
range of doses, doing so in parallel for sibling cell lines that had either been induced into
or not induced to pass through an EMT. Three compounds (etoposide, salinomycin,
abamectin) showed moderate to strong selectivity (IC50 is -10-fold lower for HMLEshEcad cells vs HMLE-shCntrl cells); one compound showed weaker selectivity
(nigericin; -7-fold) (Figure 4A). The remaining 4 compounds did not exhibit specific
effects on viability upon follow-up, and therefore failed to be validated (data not shown).
To determine if the specificity of the validated compounds for the HMLE-shEcad
cells was a consequence of the mesenchymal differentiation state rather than the
particular genetic perturbation used, we also tested the effects of these compounds on
cells induced to undergo EMT due to Twist overexpression (HMLE-Twist). In fact, the
dose-response curves of each of the tested compounds for HMLE-Twist cells were
virtually identical to those observed for the HMLE-shEcad cells (Figure 4B). This
observation strongly suggested that compounds exhibiting specific activity in this assay
were targeting distinct states of differentiation rather than the particular inducing agents
themselves.
In order to examine the effects of salinomycin and abamectin treatment on
heterogenous cell populations, we co-mixed GFP-labeled HMLE cells with unlabeled
111
HMLE-Twist cells and treated the resulting co-cultures with test compounds.
As a
positive control for this experiment, we treated co-cultures with blasticidin, which selects
for the epithelial HMLE-GFP cells harboring a blasticidin-resistance gene. We observed
that treatment with salinomycin, abamectin or blasticidin resulted in an increase in the
GFP-positive fraction relative to DMSO-treated controls, indicating that the unlabelled
mesenchymal cells were depleted from the population in response to treatment (Figure 5).
This stood in contrast to our earlier findings demonstrating that paclitaxel treatment
resulted in a selection for mesenchymal cells (Figure 2). Hence, the chemical compounds
identified through our screen, in contrast to a commonly used chemotherapeutic agent,
resulted in the selective killing of cells that have undergone an EMT.
While these compounds were identified as selective inhibitors of immortalized
human mammary epithelial cells (HMLE-shEcad) that had undergone an EMT, it was not
clear whether they would also exhibit any selective effect on the corresponding
tumorigenic cells (HMLER-shEcad). To examine this notion, we treated HMLER-shCntrl
and HMLER-shEcad cells with the three most selective compounds for three days and
generated dose response curves as before. While salinomycin continued to exhibit
selective toxicity against mesenchymal cells (-6 fold difference in IC50, 1.5PM for
shEcad vs. 9 pLM for shCntrl cells), the two other compounds, abamectin and etoposide,
inhibited the viability of both cell lines to similar extents, indicating that they were no
longer differentially targeting one or the other cell populations (Figure 6). This finding
suggests that, for a subset of the compounds, oncogenic transformation masks the
sensitivity conferred by the differentiation state of the cells.
112
Effects of salinomycin on cancer stem cells
Recent studies from our laboratory indicate that induction of an EMT by
overexpression of Twist or Snail endows breast carcinoma cells with many of the
properties of cancer stem cells, such as tumor seeding at limiting dilution, mammosphere
formation, and a
CD 4 4 high/ CD24low antigenic profile (Mani et al., 2008). We had
demonstrated that these observations also hold true for cells induced into an EMT via
inhibition of E-cadherin
(HMLERshEcad;
Chapter
2,
Figure
8).
Importantly,
HMLERshEcad cells are resistant to a variety of chemotherapeutic compounds similar to
what is observed with prospectively identified CSCs from human patients and tumor cell
lines (Yu et al., 2007). Since the above mentioned screen identified compounds that are
preferentially cytotoxic to HMLERshEcad cells that have undergone an EMT, we
speculated that these compounds will also have a cytotoxic effect on the CD 4 4 high/
CD2410l CSC populations that exist in breast carcinoma cell lines.
To test this notion, we analyzed using FACS several human breast cancer cell
lines for the expression of markers (CD44high/CD24 low) reported to enrich for cancer stem
cells:
the
MDA-MB-231
and
SUM159
cells
contained
greater
than
90%
CD44high/CD241ow cells; in contrast, the T47D cell line displayed <.1% CD44high/CD241ow
cells (Figure 7A). Interestingly, the MDA-MB-231 and SUM159 lines both have a
mesenchymal and highly metastatic phenotype, whereas the T47D line is epithelial and
poorly-metastatic. We treated these lines with salinomycin and observed that the CSCenriched cell lines SUM159 and MDA-MB-231 were more sensitive across a range of
doses relative to the CSC-poor T47D cells (Figure 7B). These data suggest that
salinomycin sensitivity of breast cancer cell lines correlates with the prevalence of CSC-
113
like cells in such lines. However, further experimentation is needed to determine whether
salinomycin treatment functionally decreases tumor-initiating ability.
Taken together, the experiments described in this chapter establish a proof-ofprinciple for discovering compounds that target highly metastatic and otherwise
chemotherapy-resistant cancer cells. Although resistant to a wide range of currently used
drugs, cells that have undergone an EMT may have unique vulnerabilities that could be
uncovered using the approach outlined above. In addition, this approach could potentially
be useful to target tumors and tumor initiating cells that have a mesenchymal phenotype.
114
Materials and Methods
Cell culture. Immortalized (HMLE) or transformed (HMLER) breast epithelial cells that
express either control shRNA (shCntrl) or shRNA targeting E-cadherin (shEcad) were
generated and maintained as described in Chapter 2. HMLE-Twist cells were also
described previously (Yang et al., 2004). To create GFP ihyphen expressing lines, we
infected the HMLE and HMLE-shEcad cells with a pWZL-GFP retrovirus carrying the
blasticidin resistance gene using standard procedures (Elenbaas et al., 2001).
Characterization of resistance to cytotoxic agents.
Doxorubicin, paclitaxel,
actinomycin D, campthotecin and staurosporine were purchased from Sigma and
dissolved in dimethyl sulfoxide (DMSO). 5000 cells in 100 ul of medium were plated per
well in 96-well plates. 24 hrs after seeding, compounds at the indicated concentration
were added to wells (5 wells per each concentration). DMSO treatment was used as
negative control. Cell viability was measured after 72 hrs using the CellTiter96 AQueous
Assay (MTT) (Promega) according to manufacturer's instructions. Dose response curves
were generated with GraphPad Prism software (GraphPad Software, Inc.). For the co-mix
experiments, unlabelled and GFP-labeled cells were mixed at the indicated ratios and
seeded onto 6-well plates. Triplicate wells were then treated with DMSO or the
compounds (paclitaxel, salinomycin, abamectin and blasticidin) for 48 hrs. The cells were
washed with PBS, trypsinized and analyzed by FACS for GFP positivity.
115
Chemical Screen
Information
about
the
general
automated
HTS
protocol
is
available
at
http://www.broad.harvard.edulchembio/index.html. The assay was initiated by plating 40
iL of medium containing 1000 cells/well into white 384-well opaque-bottom plates
(Nunc, Rochester, NY) using an automated plate filler (Bio-Tek [tFiller; Winsooki, VT)
and allowing the cells to adhere for 24 hours. 100 nL of compound stock solutions in
DMSO was transferred from stock plates into the 384-well assay plates using an
automated pin-based compound transfer robot (CyBio CyBi-Well vario; Woburn, MA).
For most compounds, the final concentration in each well was calculated to be 10uM.
The screen was performed in duplicate. For negative controls, entire DMSO-treated
control plates were employed, in addition to DMSO-only control wells that were
incorporated into each compound assay plate. The cells were assayed for luciferase
activity with the addition 20 ul of CellTiter-Glo Luminescent Cell Viability Assay
solution (Promega). The luminescent signal from each plate was detected using an
automated plate reader (Perkin-Elmer Envision 1; Wellesley, MA). The compound plate
numbers for screened plates were 2158-2167, 2099-2105, 2290-2297, 2403-2407,
Biokinl-2. The primary data were analyzed using the commercial software package
SpotFire (SpotFire, Inc., Somerville, MA).
Validation of hits
Individual compounds were purchased from Sigma and dissolved in DMSO with the
exception of nigericin, which was dissolved in 100% ethnanol. Activity of the
116
compounds were quantified by generating dose-response curves for HMLE-shCntrl,
HMLE-shEcad and HMLE-Twist under the same cell density and culture conditions
described for the initial screen, using the 384-well plate based system.
117
Figures
A
HMLER
R
shGFP
shEcad
* HMLER-shGFP
* HMLER-shEcad
* HMLER-srGFP
a
,I1"1
10-12
10~
o
HMLER-shEcad
a
1010
r
Doorubidin [l4
10
f 10'
1tm
lor?0I
ir
law"
R===t~rrt'NI
mHMLE-shGFP
E HMLE-shEcad
mW I noxr
On
Dxru~II
"so
,
Doxorubicin
iU I
St
1LO"y
DI
c
Iti
Actinomycin D
Paci
1
ID
Itx
Paclitaxel
Camm
2IrM 1132or
I IM
Campthotecin
ie i1a"
S
IStaurorosporine
Chemotherapy Drugs
Figure 1. Chemoresistance of cells that have undergone an EMT
(A) Mesenchymally transdifferentiated cancer cells (HMLER-shEcad) (red) display
increased resistance to doxorubicin and paclitaxel-induced cell death relative to control
HMLER-shCntrl cells (gray). Dose response curves were generated by treating cells with the
indicated doses (X-axis) for 3 days. Cell viability was measured using the MTT assay and
values are represented as a fraction of DMSO treated control wells whose value was
arbitrarily set at 1. Dotted line indicates 50% survival, corresponding to the IC50 for that
compound.
(B) Immortalized, non-tumorigenic breast epithelial cells (HMLE) in a mesenchymal state
(shEcad) exhibit increased resistance to a variety of drug treatments compared to control
immortalized breast epithelial cells (shGFP). Values are presented as a percentage of DMSO
treated controls, which was arbitrarily set at 100%. Data were expressed as the mean ± SD.
118
HMLE-shGFP
I
Admix 5% GFP + cells
HMLE-shEca d-pWBGFP
Day 1: Treat mix cultures
Day 4 : Facs for GFP
AL, ---TDmso
-I"
1 nM
2.5nM
Paclitaxel
Figure 2. Treatment with Paclitaxel leads to selective expansion of mesenchymal
cells.
GFP-labeled immortalized epithelial cells in the mesenchymal state (HMLE-shEcadpWBGFP) were admixed to control epithelial cells (HMLE-shGFP) at ratio of 1:20. The
resulting mixed cultures were treated with paclitaxel at the indicated concentrations.
Treatment for 3 days with (2.5nM, 10nM) paclitaxel resulted in an increase (-30%,
300%) in the fraction of mesenchymally transdifferentiated HMLE-shEcad cells relative
to dmso-treated controls.
119
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L
HMLEsh6FP
HMLEshEEcad
ChII
Lurrminescence
Cel Viabiity Assay
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Figure 3. The chemical screen
(A) Schematic of the screen design and protocol.
(B) (top left) Histogram of normalized values for the viability of each tested compound
for control epithelial HMLEshGFP cells. (bottom left) Scatter plot of normalized Zscores for the viability of each tested compound for mesenchymal HMLEshEcad. The xand y-axes represent the two independent replicates for the screen. Red dots represent
DMSO-containing wells; blue dots are compound wells (top right) The red region in the
histogram represents compounds that exhibit toxicity for control cells. Thresholding out
these compounds produces the scatter plot in (bottom right), enabling the identification
of compounds that selectivity kill mesenchymally transdifferentiated epithelial cells
(yellow dots).
120
A
Ur
> ,nB
E-Z_di
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1.2
I.5
a
ano
4
.10
10
104
104
'
10-6
Salinomycin [M]
B
Etoposide [M]
-15
115.
I
"
Abamectin [M]
I.'
1
Nigericin [M]
"
SshCr•il
ELTWAn
-"
I"
1i.
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10
,I
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f
i5DNa
10'a 104 10
Etoposide [M]
107
102
10-
10-
106
Abamectin [M]
104
Nigericin [M]
Figure 4. Validation of compounds hits
(A) Dose-response curves for HMLE-shCntrl cells (green circles) and HMLE-shEcad
cells (red triangles) treated with compounds that tested positively in the primary screen.
Dose response curves were generated by treating cells with the indicated doses (X-axis)
for 3 days. Cell viability values are represented as a fraction of DMSO treated control
wells whose value was arbitrarily set at 1. Dotted line indicates 50% survival,
corresponding to the IC50 for that compound.
(B) Chemical compounds toxicities are independent of the genetic element used to induce
the EMT. Dose-response curves of the viability of HMLE-shCntrl cells (green squares)
and mammary epithelial cells that were induced to undergo an EMT through expression
of the Twist transcription factor (HMLE-Twist) (blue triangles).
121
L
ti
i
~
g
r
""`
""
Dmso
Salinomycin 5uM
Abamectin 1.25uM
a
Blasticidin
HMLE-GFP and HMLE-Twist mix
10
0
Dmso 1.25uM 5uM
Salinomycin
O.25uM 1.25uM Blast
Abamectin
Figure 5. Treatment with hit compounds can selectively deplete mesenchymal cells
from a heterogenous cell population.
GFP-labeled immortalized mammary epithelial cells (HMLE-GFP) were mixed with with
unlabeled Twist expressing cells (HMLE-Twist) at a ratio of 1:10. The mixed cultures
were treated with either salinomycin, abamectin, blasticidin (blast) or DMSO at the
indicated concentrations for 3 days, and subsequently imaged and analyzed using FACS.
Quantification of the percent of GFP-positive cells is shown. Blasticidin treatment is a
positive control for the selection of GFP-positive cells, which harbor a blasticidin
resistance gene.
122
L Jill
I'L• •~L...•'.I
FI-MLER
P-Ecad
i4
Salinomycin [M]
SI-MLER shQrl
* I-LERshEcad
ORLB.
11 .8
1g3-
143*
10'
i0
Etoposide [M]
F-MLER CQIrl
F-MLER shEad
.4
Abamectin [M]
Figure 6. Effects of transformation on compound selectivity
Dose-response curves of control (HMLER-shCntrl, green) and mesenchymal (HMLERshEcad, red) tumorigenic mammary epithelial cells treated with salinomycin, etoposide
and abamectin.
123
Cell line
% CD44 + CD24-
Suml59
92.6 %
89.9%
MDA-MB-231
TAW
7D
I 7I L.
..
S40
1I (U
SLmrn59
T47D
IV3A-231
1.50)
5
-L
I.. ....
u,
us..
1-
106- .
1
1064
Salinomycin [M]
Figure 7. Salinomycin sensitivity correlates with the prevalence of CD44high/CD24low
cells.
(A) Suml59, MDA-MB-231 and T47D breast cancer cell lines were analyzed by FACS
using anti-CD44 and anti-CD24 antibodies.
(B) Dose response curves for Sum159 (red), MDA-MB-231 (black), and T47D (green)
cells treated with salinomycin for 72 hours.
124
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Chapter 4
Conclusions and Future Directions
129
This thesis focused on two issues. First, I addressed the role of cell-cell adhesion
and E-cadherin in the epithelial-to-mesenchymal transition (EMT) and metastatic
progression. I was able to accomplish this by creating new cell line models deficient in
cell-cell adhesion and E-cadherin expression and analyzing their phenotypes in detail. In
the second part of this thesis, I examined the link between the EMT and development of
chemoresistance. I took advantage of the cell lines created in the first part to perform a
high-throughput small molecule screen. Through this screen, I identified compounds that
selectively target cell populations that have a mesenchymal phenotype. In this chapter, I
will discuss the implications of my findings and potential future directions.
E-cadherin and Metastasis
Experiments described in Chapter 2, indicate that the loss of E-cadherin has wideranging transcriptional and functional consequences for human breast epithelial cells.
First of all, E-cadherin loss, achieved through shRNA-mediated knock-down, is sufficient
to confer metastatic ability upon breast cancer cells that are otherwise essentially nonmetastatic. However, the acquisition of metastatic ability by cancer cells following Ecadherin loss is not attributable solely to the disruption of intercellular adhesion contacts,
as demonstrated by utilizing a dominant-negative E-cadherin mutant. Instead, it is the
additional loss of E-cadherin protein that provokes an EMT, attended by increased
cellular motility, invasiveness and resistance to apoptosis. Thus, E-cadherin can act as a
central modulator of the cell-biological phenotypes and the molecular factors that govern
metastatic dissemination of carcinomas.
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The mechanisms by which E-cadherin is inactivated in human tumors can be
placed into two general categories: (1) those that result in the production of a nonfunctional protein and (2) those that lead to E-cadherin's complete absence. The present
findings suggest that point mutations in the extracellular domain, which preserve Ecadherin's cytoplasmic tail and act analogously to the dominant negative mutant, are not
likely to result in an EMT or to afford functional traits that allow completion of the later
steps of metastasis (Berx et al., 1998). In contrast, complete elimination of E-cadherin
expression, as shown by RNAi experiments, results in the activation of the malignancyassociated traits listed above. Therefore, the complete absence of E-cadherin in human
carcinomas, occurring via nonsense mutations or locus repression/loss, is likely to result
in highly metastatic tumors. Stated differently, loss of E-cadherin, in combination with
certain additional oncogenic lesions, results in the acquisition of multiple functional traits
that contribute to the completion of several rate-limiting steps in the invasion-metastasis
cascade.
The oncogenic lesions that cooperate with the loss of E-cadherin and lead to an
EMT remains to be determined. It has been shown that loss of E-cadherin in normal
murine mammary gland leads to induction of apoptosis in alveolar cells (Boussadia et al.,
2002). In other tissues such as the skin, loss of E-cadherin results in loss of tissue
integrity (Tinkle et al., 2004). Therefore, it is likely that the metastasis-promoting effects
of E-cadherin loss can only become apparent after transformation or immortalization of
cells that sustain such a loss. In fact, tumor formation and metastasis is observed in mice
lacking E-cadherin in the mammary gland only when p53 is also deleted (Derksen et al.,
2006). This is consistent with my observations that E-cadherin loss results in an EMT in
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HMLE cells that lack both functional Rb and p53 pathways. On the other hand,
preliminary experiments indicate that HMEC cells that are immortalized only through
telomerase expression undergo cell death in response to loss of E-cadherin (data not
shown). Taken together these observations suggest that dismantling of tumor suppressor
pathways are necessary to counter the apoptotic stimuli that originate from loss of
homotypic cell-cell adhesion.
Loss of E-cadherin as an inducer of EMT
Transcriptional repression of E-cadherin has generally been recognized to be one
of the last downstream events in the EMT process. In fact, a number of EMT-inducing
transcription factors (EMT-TFs) have been identified specifically because of their ability
to repress E-cadherin (Comijn et al., 2001; Perez-Moreno et al., 2001). In this study, I
show that loss of E-cadherin itself can be an EMT-inducing stimulus. This suggests that,
in certain contexts, E-cadherin functions as an upstream controller of the EMT program.
Importantly, truncation of the extracellular domain and loss of cell-cell adhesion is not
sufficient to cause an EMT. This observation is in line with recent data from established
breast cancer cell lines. Expression profiling of 27 cell lines with different mechanisms of
E-cadherin inactivation revealed that the cell lines that harbor CDH1 mutations but retain
cell-surface protein expression have an epithelial gene expression signature (Lombaerts et
al., 2006). On the other hand, cell lines that have no detectable protein expression due to
promoter hypermethylation have a mesenchymal phenotype with high expression of
EMT-TFs such as Slug, and Sipl (Lombaerts et al., 2006). These observations together
with my experimental results are consistent with the notion that constitutive loss of E-
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cadherin
expression
in
human
tumors
occurring
either
through
promoter
hypermethylation or chromosomal deletions lead to a mesenchymal phenotype.
The present findings also have implications about how EMT may be induced in
human tumors. Since EMT in development is induced by soluble morphogenic signals, it
is hypothesized that, in human carcinomas, EMT-inducing signals do not originate in the
cancer cells themselves but come from other cell types in the tumor stroma (Scheel et al.,
2007). Due to restricted exposure to the soluble factors, EMT is thought to be induced
transiently in carcinomas, enabling cells to leave the primary tumor and then revert back
to an epithelial state in distant tissues. In fact, there is evidence for this notion in human
colon carcinomas (Brabletz et al., 2001). However, my findings in this thesis indicate
that loss of E-cadherin, on its own, may lead to an EMT, and therefore, suggest that
epi/genetic alterations within the cancer cell genomes can lead to cell-autonomous
induction of an EMT. Moreover, in cases where E-cadherin is permanently lost,
transdifferentiation to a mesenchymal state would be stably maintained in secondary
tumors as well (Scheel et al., 2007).
Mechanism of EMT induction upon E-cadherin loss
In the human mammary epithelial cell system, the retention of the cytoplasmic tail
of E-cadherin prevented EMT induction. Therefore, in search for mediators of EMT
induction, I initially focused on proteins known to bind this cytoplasmic domain,
specifically 3-catenin. 3-catenin has previously been implicated in the induction of EMTs
in various contexts (Conacci-Sorrell et al., 2003; Eger et al., 2004; Kim et al., 2002;
Liebner et al., 2004; Morali et al., 2001; Yang et al., 2006b). In addition, 1-catenin has
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been identified in an in vivo functional screen as a metastasis-promoting gene
(Gumireddy et al., 2007).
I observed that loss of E-cadherin resulted in the release of P-catenin from
adherens junctions. Importantly, this pool of P-catenin was stabilized due to inactivation
of GSK3P in shEcad cells. How E-cadherin modulates GSK3P activity remains an open
question. The data presented in chapter 2 showed that GSK3P is highly phosphorylated
and therefore inactive in the E-cadherin negative cells. In addition to canonical Wnts,
several mitogenic signaling pathways are known to inactivate GSK30, mainly through
increased Akt activity. Therefore, it is possible that loss of E-cadherin leads to a greater
activation of receptor tyrosine kinases such as EGFR, which then lowers the activity of
GSK3P. In fact, some studies indicate that E-cadherin inhibits ligand-dependent
activation of receptor tyrosine kinases by decreasing receptor mobility and ligand binding
affinity (Perrais et al., 2007; Qian et al., 2004). Therefore, an important future direction
would be to gauge the activity of various mitogenic signaling pathways and their
downstream effectors such as Akt in cells that have undergone an EMT.
In most studies, activation and nuclear accumulation of P-catenin is correlated
with induction of EMT, but no causal link has been established (Eger et al., 2004; Lu et
al., 2003). I wished to directly assess the functional role of 0-catenin through loss-offunction experiments. Consequently, I inhibited p-catenin expression in E-cadherinnegative mesenchymal cells and observed that the cell biological traits associated with
metastasis, such as invasiveness and anoikis resistance, were inhibited. However, gene
expression profiling indicated loss of 3-catenin did not suffice to fully reverse the global
EMT state caused by E-cadherin loss. In fact, this analysis revealed that while some
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known p-catenin targets such as fibronectin and ephrin receptor B2 were regulated by
loss of E-cadherin, other targets such as myc and cyclinD were not (Batlle et al., 2002;
Clevers, 2006; Gradl et al., 1999; Klapholz-Brown et al., 2007). These data indicate that
liberation of P-catenin due to loss of E-cadherin may not be sufficient to induce the entire
spectrum of Wnt target genes. Moreover, these observations suggest that while p-catenin
is essential for the maintenance of EMT, it only regulates a subset of the EMT program.
Although I found 0-catenin to be necessary for several aspects of E-cadherin-lossinduced EMT, it was not sufficient to cause these phenotypes. Therefore, I concluded
that additional signals beyond those conveyed by P-catenin must be important in
transducing the downstream effects of E-cadherin loss. Others have reported that the
adherens junction-associated proteins a- and p120- catenin may also modulate
intracellular signaling pathways (Vasioukhin et al., 2001; Wildenberg et al., 2006). For
example, loss of a-catenin leads to hyperactivation of the MAPK signaling, whereas
p120 catenin has been shown to regulate Rho and Nf-icp pathways (Perez-Moreno et al.,
2006; Vasioukhin et al., 2001; Wildenberg et al., 2006). However, I have been unable to
find evidence for the activation of signaling pathways by either of these two proteins
following E-cadherin loss (data not shown).
To be able to understand the molecular pathways important for E-cadherin lossinduced EMT, I undertook to identify the spectrum of transcriptional changes resulting
from E-cadherin loss. Expression profiling revealed that 19 transcription factors were
highly induced following E-cadherin loss, all of which did not ostensibly require 0catenin for their regulation (ie. their expression levels were not changed upon P-catenin
inhibition). Interestingly, Twist and ZEB-1, both previously known to cause E-cadherin
135
repression, were among the transcription factors upregulated following E-cadherin loss
(Eger et al., 2005; Yang et al., 2004). Twist had previously been shown to be essential for
the metastasis of mouse mammary tumor cells and to be expressed in a high proportion of
human lobular breast cancers (Yang et al., 2004). More than 80% of lobular breast
cancers show loss-of-heterozygosity at the CDH1 locus, and have no detectable Ecadherin expression (Strathdee, 2002). Therefore, it is tempting to speculate that
epi/genetic loss of E-cadherin is the primary reason why lobular cancers express high
levels of Twist. Re-expression of E-cadherin in the few available lobular breast cancer
lines could address this notion.
I next determined that Twist is functionally important for metastasis induced by
loss of E-cadherin. In addition, Twist was essential for cancer cell invasiveness and
resistance to anoikis. However, Twist inhibition did not result in a complete reversion to
an epithelial phenotype. While N-cadherin levels decreased, Vimentin expression was
still maintained in the absence of Twist. This suggests that Twist, on its own, regulates a
portion of the EMT program and that there are yet other signals that are important for the
maintenance of the EMT.
Another unanswered question is how Twist expression is turned on during EMT
induction. In the mouse mammary gland, Wnt overexpression can induce Twist, and
murine twist promoter has putative TCF/LEF binding sites. However, these sites are not
conserved in the human twist promoter (Howe et al., 2003). In addition, my experiments
showed that f-catenin inhibition does not alter Twist levels in mesenchymal cells,
suggesting that Twist is not downstream of P-catenin in the EMT program in human
mammary epithelial cells. During development and in some carcinoma cell lines,
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activation of NF-,ib signaling upregulates Twist expression (Jiang et al., 1991; Pham et
al., 2007). In addition, enhanced EGF-STAT3 signaling has been shown to directly
activate Twist transcription (Lo et al., 2007). In the future, it would be important to
closely examine whether these signaling pathways are activated upon loss of E-cadherin.
I found that Zebl, another EMT-TF, was highly upregulated in E-cadherinnegative cells. Zebl expression in human breast cancers is closely linked to tumor
dedifferentiation (Aigner et al., 2007b). The contribution of Zebl to the induction of
EMT and metastasis following E-cadherin loss is currently unknown and warrants further
study. The induction of multiple EMT-TFs upon E-cadherin loss suggests that E-cadherin
represses its own repressors. In fact, reporter assays indicate that E-cadherin promoter
activity is repressed in E-cadherin inhibited cells (data not shown). Taken together, these
observations suggest that loss of E-cadherin yields a feed-forward signaling loop
whereby the EMT-induced mesenchymal state, once established, is stabilized and perhaps
maintained. Thus, E-cadherin can act as a central modulator of the cell-biological
phenotypes and the molecular factors that govern metastatic dissemination of carcinomas.
EMT and Chemoresistance
During the course of experiments described in Chapter 2, I observed that cells that
have undergone an EMT become resistant to apoptosis induced by loss of anchorage.
Subsequently, I wished to determine whether EMT conferred resistance to other forms of
apoptotic stimuli as well. Given the link between metastatic recurrence and emergence of
chemotherapy resistance in human tumors, I specifically wanted to know whether
passage through an EMT resulted in resistance to chemotherapy-induced cytotoxicity.
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I observed that human mammary carcinoma cells induced to undergo an EMT by
inhibition of E-cadherin were significantly resistant to cell death following treatment with
chemotherapeutic drugs. Importantly, the utilized drugs act via diverse mechanisms, such
as intercalation into DNA (doxorubicin) or destabilization of microtubules (paclitaxel),
suggesting that EMT confers a multi-drug-resistant (MDR)-like phenotype. The observed
resistance was also independent of transformation and seemed to be a direct consequence
of the mesenchymal differentiation state.
Although there is little information about how the mesenchymal state confers
chemoresistance, accumulating evidence suggests that the actions of EMT-TFs are
crucial to block cell death. In cases where EMT-TFs protect against genotoxic stress,
such as those elicited by gamma irradiation and drugs like doxorubicin, they are thought
counteract p53-mediated induction of pro-apoptotic genes (Inoue et al., 2002; Kajita et al.,
2004). For example, in irradiated hematopoetic cells, Slug antagonizes p53-mediated
transcription of PUMA, a pro-apoptotic BH3-only protein, through direct binding to the
puma promoter (Wu et al., 2005). In addition, cells that pass through an EMT have
slower cell cycles, potentially allowing cells to repair any sustained damage. In fact, Snail
is known to repress Cyclin D2, while other EMT-TFs such as Zeb-1 can induce
p21WAF1/CIP1, thereby leading to slower progression through the cell cycle (Liu et al.,
2008; Vega et al., 2004).
In the cell system utilized throughout this thesis, the p53 pathway is nonfunctional due to expression of the Large-T antigen in the human mammary epithelial
cells. Therefore, the observed resistance to cell death is likely to occur via p53independent mechanisms. In fact, there is some evidence that EMT-TFs can act
138
independently of p53 to block programmed cell death. For example, Twist has recently
been shown to mediate resistance to paclitaxel through activation of Akt signaling
(Cheng et al., 2007; Zhang et al., 2007). In addition, Twist can interfere with downstream
apoptotic machinery through modulation of Bcl-2 phosphorylation (Pham et al., 2007). In
the future it would be important to investigate whether such mechanisms are operative in
E-cadherin-inhibited mesenchymal cells. Since mesenchymal cells have an MDR-like
phenotype, it would also be interesting to examine whether cells that have undergone an
EMT express higher level of ABC transporters that are known mediators of MDR.
The observation that EMT confers chemoresistance has important implications for
cancer therapy. First, it provides a mechanistic link between metastatic dissemination and
the development of secondary tumors that are chemoresistant. Second, it suggests that
chemotherapy treatment may actually lead to the preferential survival and expansion of
cancer cells that have a mesenchymal and more invasive phenotype. In fact, there is
growing evidence that long term exposure of cancer cell lines to cytotoxic agents
promotes the outgrowth of variants with mesenchymal properties (Kajiyama et al., 2007;
Shah et al., 2007; Wang et al., 2004; Yang et al., 2006a). Third, it suggests that, in cases
where chemotherapy resistance is due to passage through an EMT, agents that can
interfere with the EMT program may re-sensitize tumor cells to treatment. In support of
this notion, a recent study reported that short interfering RNAs directed against Twist can
sensitize lung carcinoma cells to cisplatin (Zhuo et al., 2008).
139
Chemical screen identifies compounds targeting cells in the mesenchymal state
Cells that have undergone an EMT represent a double challenge to the prevention
and management of tumor progression. Not only are they more invasive and likely to
form secondary tumors, they are also resistant to a variety current therapeutics. Therefore,
it is of vital importance to find therapies that effectively target such cells. Since Ecadherin-loss resulted in the induction of an EMT and mimicked the chemoresistant
phenotype observed in other systems, I postulated that the stable cell lines created during
the initial part of this thesis work could be used as tools for high throughput screening of
chemical libraries. Experiments in this portion of the thesis were carried out in
collaboration with Piyush Gupta from the Lander laboratory.
The use of the abovementioned cell lines afforded two main advantages. First,
chemoresistance and EMT induction was achieved through a single manipulation (Ecadherin inhibition), thereby creating almost isogenic cell lines that differ only by virtue
of being either in the epithelial or mesenchymal differentiation state. Therefore, we could
perform the chemical library screen essentially twice using cells that have undergone an
EMT and their epithelial counterparts. This approach allowed us to identify those
compounds that exhibited specific toxicity against cells in the mesenchymal
differentiation state. Second, EMT could be induced in immortalized cells, thereby
allowing us to find EMT-specific rather than transformation-specific agents. However,
the use of transformed cells should be considered as an alternative approach in the future,
because the presence of different oncogenes in cells that have undergone an EMT may
yield additional compounds.
140
We have identified one compound, salinomycin, as being selectively toxic to
carcinoma cells that have undergone an EMT. We also observed that among established
breast cancer cell lines salinomycin sensitivity correlates with the prevalence of cells with
CD44high/CD241ow antigenic profile. These markers are reported to enrich for breast CSCs
(Al-Hajj et al., 2003). Therefore, it is critical to test whether salinomycin treatment
affects CSC properties, such as tumor formation at limiting dilution. Given our
laboratory's observations that passage through an EMT leads to a CSC-like state, it is
tempting to speculate that approaches described in this thesis may be utilized to find
compounds targeting CSC populations.
We do not know at this point by which mechanism salinomycin exerts its
cytotoxic effect.
Salinomycin is a polyether antibiotic that belongs to a class of
compounds called ionophores. Ionophores are hydrophobic molecules that selectively
bind to a given metal ion and increase its cell permeability by shielding the charge of the
ion. This enables the ions to penetrate the hydrophobic interior of the lipid bilayer.
Salinomycin specifically binds potassium ions (Mitani et al., 1975).
Early reports
indicated that salinomycin causes rapid release of K' from mitochondria, loss of
mitochondrial membrane potential, and eventual inhibition of oxidative phosphorylation
(Mitani et al., 1976). Other potassium ionophores, such as valinomycin and nigericin,
also interfere with mitochondrial function (Arslan et al., 1981; Daniele et al., 1978;
Furlong et al., 1998). It is interesting to note that nigericin, like salinomycin, exhibited
differential toxicity to HMLE-shEcad cells and was an initial hit in the screen. It would
be important to know whether other potassium-selective ionophores, such as valinomycin,
141
would also be selectively toxic (valinomycin was not in the chemical libraries we
screened).
Potential mechanisms of action and limitations of salinomycin
Given the known effects of potassium ionophores on mitochondria and oxidative
respiration, it is possible that their preferential toxicity to mesenchymal cells may due to
fundamental differences in the mode of ATP production pre- and post-EMT. For example,
if the mesenchymal cells primarily rely on oxidative phosphorylation by mitochondria for
ATP production, they would be more sensitive to salinomycin compared to epithelial
cells that mainly employ glycolysis. A prediction of this hypothesis is that mesenchymal
cells will be more sensitive to inhibition of aerobic respiration by low oxygen tension,
whereas epithelial cells would be more susceptible to inhibition of glycolysis.
Preliminary experiments did not reveal significant differences between epithelial
cells and their counterparts that have undergone an EMT with respect to cell viability
under conditions of hypoxia or inhibition of glycolysis(data not shown). However, further
examination is needed to establish whether differences in the mode of ATP production
are the basis of salinomycin selectivity. Therefore, the reason why potassium ionophores
may preferentially inhibit the viability of cells in the mesenchymal state remains to be
determined.
Another unresolved issue is the mechanism by which salinomycin inhibits cell
viability. Our preliminary experiments indicate that salinomycin treatment causes cell
death rather than cell cycle arrest. Whether the observed cell death upon salinomycin
treatment is due to the activation of the classical apoptotic machinery remains to be
142
determined. While some studies
indicate that treatment with potassium ionophores
causes caspase activation, others have found that bcl-2 overexpression or caspase
inhibitors cannot rescue ionophore-induced cell death (Furlong et al., 1997; Watanabe et
al., 1998). It is possible that interference with mitochondrial function and membrane
permeability activate multiple cell death mechanisms. In fact, recent chemical screens
identified a class of compounds that act on the mitochondria and cause cell death via a
novel iron-dependent oxidative mechanism (Yagoda et al., 2007; Yang and Stockwell,
2008). In the future it would be important to determine what cell death mechanisms are
activated upon salinomycin treatment in cells that have undergone an EMT.
Although in vitro treatment of salinomycin is effective against cancer cells that
have undergone an EMT, it is not possible to use this compound in vivo. Micromolar
concentrations would have to be achieved in order to be effective against human breast
cancer cells implanted into immunocompromised mice. At such concentrations,
salinomycin is known to be highly toxic (Lagas et al., 2008). Therefore, measuring the
efficacy of salinomycin against cells that have undergone an EMT in an in vivo xenograft
model is not feasible and remains to be a limitation of this compound.
Final perspective
All in all, this study demonstrates a practical approach to the identification of
agents exhibiting specific toxicity for cancer cells that have undergone an EMT.
Moreover, it indicates that even though passage through an EMT is associated with
resistance to cell death, it is possible to find compounds that selectively kill cells in the
mesenchymal differentiation state. In fact, a recent study demonstrated that basal-type
143
and mesenchymal breast cancer cell lines are specifically sensitive to a small molecule
inhibitor of src and abl kinases (Finn et al., 2007). These findings suggest that the
induction of EMT may bring unique vulnerabilities to carcinoma cells. These
vulnerabilities can be exploited through high throughput screening approaches such as
those described here and form the basis for future therapeutics.
144
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Appendix 1
Probes and the corresponding genes upregulated more than 1.5 log-fold in shEcad cells
Symbol
ProbelD
FBLN5
GREM1
GREM1
COL3A1
COL3A1
COL1A2
DCN
COL1A2
COL3A1
FBN1
NID1
DCN
PTX3
MAP1B
TCF8
ENPP2
CDH2
COL1A1
POSTN
ANPEP
TCF8
RGS4
RGS4
DCN
C5orf 13
C5orf13
CDH11
COL1A1
PRRX1
COL6A1
IGSF4B
GNG11
RHOBTB3
TFPI
FBN1
PRG1
NR2F1
AGTR1
BIN1
LTBP1
PDGFRL
LTBP1
SPOCK
203088_at
218468_sat
218469_at
215076 s at
201852_xat
202403_s_at
201893_xat
202404_s_at
211161_sat
202766 s at
202007_at
211813 x_at
206157_at
212233_at
212764_at
209392_at
203440_at
202310_s_at
210809_s_at
202888 s at
212758 s at
204337_at
204338_s_at
211896 s at
201309 x at
201310_s_at
207173 x at
202311 s at
205991 s at
213428_sat
213948 x at
204115_at
202975_s_at
213258_at
202765 s at
201858 s at
209505_at
205357_s_at
214439 x at
202729_sat
205226_at
202728_s_at
202363_at
shEcad vs
shCntri loqfold change
8.5255
8.3169
8.1805
7.7299
7.5006
7.4536
7.059
6.9349
6.796
6.5269
6.1547
5.9537
5.8939
5.7621
5.7218
5.6529
5.637
5.6185
5.5791
5.4274
5.3506
5.3408
5.2446
5.2339
5.1119
5.0792
5.0275
5.0017
4.9379
4.8373
4.8178
4.7323
4.6948
4.6916
4.6542
4.6237
4.5814
4.5462
4.5256
4.5083
4.4753
4.4565
4.3719
Symbol
PCDH9
LOC51334
NEBL
DLC1
TOX
MME
BIN1
BIN1
RGL1
IGFBP4
ENPP2
TFPI
KCNMA1
CLEC3B
RHOBTB3
KCNMA1
STC2
CDH2
MAR3
NID1
PTGFR
TGFBR3
PRKCA
SDC2
NEBL
COL1Al
PCOLCE
BIN1
PPP1R3C
TBL1X
TRPA1
TFPI
HRASLS3
COL6A2
FLJ20701
FLJ10094
CYFIP2
DOCK10
MLPH
PVRL3
KAL1
CDH11
MME
161
ProbelD
219737 s at
220014_at
203961 _at
210762 s at
204529 s at
203434 s at
202931 x at
210201 x at
209568_s_at
201508_at
210839 s at
210664 s at
221583 s at
205200_at
202976_s_at
221584 s at
203438_at
203441 s at
213256_at
202008_s_at
207177_at
204731 at
213093_at
212154_at
203962_sat
217430 x at
202465_at
210202 s at
204284_at
213400_s_at
217590_s_at
209676_at
209581_at
209156 s at
219093_at
219501 _at
215785 s at
219279_at
218211 s at
213325_at
205206_at
207172_s at
203435_sat
shEcad vs
shCntrl loqfold change
4.2958
4.2883
4.285
4.2619
4.2601
4.2254
4.223
4.1982
4.1962
4.1851
4.1777
4.1761
4.1568
4.1464
4.1164
4.114
4.1061
4.0338
4.0263
4.0035
3.9869
3.9797
3.9304
3.9258
3.9088
3.8942
3.8924
3.8882
3.873
3.8617
3.8253
3.7594
3.7399
3.7356
3.6949
3.6914
3.6637
3.6455
3.6164
3.5922
3.57
3.5632
3.5508
SDC2
WNT5B
FBLN1
PRG1
PSCDBP
OLFML3
ITGBL1
LRIG1
COL5A2
MMP2
MYL9
EML1
STC2
RGS4
BGN
AGTR1
NPTX2
ANXA6
COL5A2
BGN
CTGF
CYP1B1
212158_at
221029_s_at
202995_sat
201859_at
209606_at
218162_at
214927_at
211596_sat
221730_at
201069_at
201058 s at
204797 s at
203439_s_at
204339 s at
213905_x_at
208016_sat
213479_at
200982_s_at
221729_at
201261_x_at
209101 _at
202437_sat
4.3594
3.4653
3.4641
3.4613
3.4607
3.4409
3.4318
3.4263
3.4211
3.3894
3.3783
3.3636
3.3635
3.3399
3.3073
3.2925
3.2837
3.2812
3.2402
3.1998
3.1784
3.173
DPYSL3
201430 s at
3.1664
PLEKHC1
MAP1B
SEP6
ITGBL1
GRB10
TWIST1
ENPP1
PNMA2
RPS6KA2
PPAP2B
KIAA0367
PLEKHC1
ZBTB16
JAM3
ARMCX2
LIN7A
CYP1B1
SYT11
ROR1
AOX1
TCF8
209209_s_at
214577_at
212414_s_at
205422_s_at
209409 at
213943 at
205066 s at
209598 at
212912_at
212226_sat
212805_at
214212_x_at
205883_at
212813_at
203404_at
206440_at
202436_s_at
209198_s_at
205805 s at
205082 s at
210875 s at
213169_at
202435 s at
213488_at
213429_at
204620 s at
3.1654
3.1537
3.1482
3.1269
3.1258
3.1236
3.1159
3.1025
3.094
3.0796
3.0685
3.0675
3.0585
3.022
3.02
3.013
3.0027
2.9614
2.948
2.9376
2.9259
2.9256
2.9067
2.8942
2.8915
2.8839
CYPIB1
SNED1
CSPG2
PODXL
KCNJ6
CHN1
TNFAIP6
SGNE1
COL6A3
DDR2
AOX1
RHOBTB3
IGSF4B
DUSP1
MAGEH1
CSPG2
FBLN1
GADD45B
CITED2
TSC22D3
DPYSL3
PPAP2B
GADD45B
KIAA0367
ATP6VOE2
L
LOC22136
2
C5orf 13
REPS2
TSC22D3
PMP22
THY1
CITED2
TRAM2
RGS17
PPARG
NID2
GRB10
PPAP2B
ZFHX4
APXL
NNMT
TAGLN
BEXL1
SEP6
TRAM2
TNFAIP6
RPS6KA2
EPHB2
CREB3L1
CDH18
DCN
162
201578_at
210454_s_at
212624 s at
206026 s at
203889_at
201438_at
205168_at
205083_at
216048_sat
221921 s at
201041 s at
218573_at
221731_x_at
202994 s at
209304_x_at
209357_at
208763_ sat
201431 s at
212230_at
207574 s at
212806_at
213587_sat
3.5237
2.7577
2.7265
2.7238
2.7164
2.7031
2.7007
2.6934
2.6925
2.6887
2.6673
2.6508
2.6478
2.6348
2.6341
2.6283
2.5896
2.5757
2.5756
2.5547
2.5471
2.5228
213248_at
2.5213
222344_at
205645_at
207001 x at
210139_s_at
208850_s_at
207980_s_at
202368 sat
220334_at
208510_s_at
204114_at
210999_s_at
209355 s at
219779_at
204967_at
202238_sat
205547 s at
215440 s at
214298 x at
202369 s at
206025_s_at
204906_at
218380_at
209589 s at
213059_at
206280 at
209335_at
2.5179
2.5137
2.5086
2.4862
2.4787
2.4619
2.4611
2.4521
2.4455
2.443
2.4224
2.4008
2.3933
2.387
2.3753
2.365
2.3606
2.3526
2.3508
2.35
2.3453
2.3413
2.3275
2.3086
2.3072
2.3029
TAF9L
FN1
FY
MLLT3
IGFBP3
CHST2
THY1
HMOX1
AP1S2
THY1
DDAH1
FLJ10357
PCAF
SATB2
NR2F1
ITGA10
FGFR1
C14orf 132
TRBV3-1
ANKRD25
FBLN1
GLRX
NNMT
PTGER4
DNAJB4
IL17RC
RIMS1
PTD015
SIX2
DUSP1
MOXD1
SLITRK5
SEMA5A
CSPG2
UGDH
SERPINE1
CYBRD1
PTD015
C10orf56
SPARC
COL6A1
BIN1
SERPINF1
EPHB2
MYBL1
HAS2
MMP19
FLOT1
AP1S2
NAP1L3
221618 s at
214701 s at
208335 s at
204917 s at
212143 s at
203921_at
213869 x at
203665 at
203300 x at
208851 s at
209094_at
58780 s at
203845_at
213435_at
209506 s at
206766_at
211535 s at
218820_at
211796 s at
218418 s at
201787_at
209276 s at
202237_at
204897_at
203811 s at
221926 s at
216184 s at
221600 s at
206510 at
201044 x at
209708_at
214930_at
205405_at
211571 s at
203343_at
202627 s at
217889 s at
221599 at
212423 at
212667 at
212091 s at
214643 x at
202283_at
211165 x at
213906_at
206432 at
204575 s at
210142 x at
203299 s at
204749 at
2.3015
2.2525
2.2483
2.2483
2.2408
2.2324
2.2306
2.2214
2.2108
2.2091
2.2042
2.181
2.1804
2.1758
2.1707
2.1667
2.1659
2.1195
2.0973
2.0969
2.0949
2.085
2.0833
2.0798
2.0786
2.0772
2.059
2.0505
2.0482
2.048
2.0426
2.0407
2.0361
2.0221
2.0221
2.0202
2.0171
2.0043
2.0003
1.9817
1.9724
1.9536
1.9509
1.9487
1.9469
1.9418
1.936
1.9346
1.7461
1.7393
IGSF4B
C14orf45
EML1
ABLIM3
ASMTL
FAM50A
DNAJB4
LTBP2
BLMH
CCNE2
GSTA4
P8
SERPINE1
LMCD1
CDKN2C
ALS2CR3
DSCR1 L1
MICAL2
FLOT1
TPM1
GALNT10
KLF9
ADAM12
FLJ22471
GULP1
TPM1
SLC7A2
WNT5A
IGFBP3
WIP149
RHOBTB1
DOCK4
MITF
SLC22A4
ABCA8
FTL
ITGA7
MICAL2
COL5A1
ICK
WASPIP
GULP1
SYNE1
ACTA2
DAB2
BPGM
CDK5RAP2
ALS2CR3
STARD13
163
211677 x at
220173 at
204796_at
205730 s at
36553_at
203262 s at
203810_at
204682 at
202179_at
211814 s at
202967_at
209230 s at
202628 s at
218574 s at
204159_at
202125 s at
203498_at
212472_at
208749 x at
206117 at
212256 at
203542 s at
202952 s at
218175_at
204235 s at
206116 s at
207626 s at
205990 s at
210095 s at
203827 at
212651_at
205003 at
207233 s at
205896_at
204719 at
213187 x at
216331 _at
212473 s at
212488 at
204569 at
202664 at
204237_at
209447 at
200974 at
201280 s at
203502_at
218031 s at
220935 s at
202124 s at
213103 at
1.9324
1.9304
1.921
1.9203
1.9185
1.9182
1.9164
1.913
1.9106
1.9074
1.8988
1.8972
1.8898
1.8886
1.8861
1.8845
1.8783
1.8709
1.8679
1.8502
1.8495
1.8482
1.848
1.8475
1.84
1.8341
1.8309
1.8212
1.8193
1.8116
1.8102
1.8099
1.8037
1.7989
1.7957
1.7896
1.7879
1.7868
1.7856
1.7806
1.7791
1.7714
1.7709
1.7656
1.7644
1.7578
1.7491
1.7471
1.5833
1.5808
GRB10
GULP1
ARL3
MAGED2
RECK
PRAF2
ARHGAP22
PPM1H
GALNT1 0
DMN
PLOD2
LOC283537
ZNF22
ASMTL
PRKCA
UQCRB
PRR3
C14orf58
COL8A1
TCEA2
GLRB
FZD2
KDELR3
LOX
NRP1
KDELR3
CMKOR1
GK
SV2A
EPS8
IGFBP7
FLOT1
LEPR
ARID5B
GYPC
MARCKS
PCOLCE2
SRR
HOXA5
KLF4
GLRB
ZNF22
209410_s_at
215913_s_at
220999_s_at
218330 s at
202641_at
208682_s_at
205407_at
203456_at
206298_at
212686_at
207357_sat
212730_at
202619 s at
214719_at
218005_at
209394_at
215195_at
209065_at
204795_at
219316_s_at
214587_at
203919_at
205280_at
210220_at
207265 sat
215446 s at
210510_s_at
204017_at
212977_at
215977 x at
203069_at
202609_at
201162_at
208748_s_at
209894_at
212614_at
202947 s at
201668_x_at
219295 s at
219205_at
213844_at
220266 s at
205279_s_at
218006 s at
1.7384
1.7375
1.7345
1.7324
1.7192
1.7112
1.7095
1.7086
1.7063
1.7038
1.7033
1.7032
1.6983
1.6975
1.6956
1.6866
1.6862
1.6852
1.684
1.6808
1.678
1.6771
1.6725
1.6697
1.6632
1.6617
1.6592
1.6563
1.6455
1.6444
1.6432
1.6423
1.629
1.6267
1.6259
1.6213
1.6194
1.6188
1.6176
1.6172
1.6096
1.5983
1.5893
1.5887
FLJ14627
FGFR1
FLJ20323
SDC3
Cl 0orf56
DGKI
MAGED1
FLJ10357
ALDH6A1
CRIP2
SEP11
COL6A1
REPIN1
C6orf145
DAB2
HRMT1 L1
H2AFY
TBL1X
PTGER4
EDG2
FKBP5
NEBL
FAT4
RNASE4
164
221909_at
210973_sat
211724_x_at
202898_at
212419_at
206806_at
209014_at
220326_sat
221588_x_at
208978_at
214293_at
212937 s at
219041 s at
212923_s at
201279_s at
202098 s at
214500 at
201867 s at
204896 s at
204036_at
212829_at
204560_at
207279 s at
219427_at
213397 x at
1.5775
1.5773
1.5754
1.5689
1.5671
1.5665
1.5658
1.5623
1.5614
1.5575
1.549
1.5474
1.5431
1.5427
1.5419
1.5408
1.535
1.5302
1.5282
1.5264
1.5233
1.5212
1.5195
1.5102
1.5049
Probes and the corresponding genes downregulated more than 1.5 log-fold in shEcad
cells
Symbol
ProbelD
SERPINB2
KLK10
SPRR1B
SPRR1A
S100A8
SLPI
KRT6B
KLK7
SPRR1A
P13
ALDH1A3
CDH1
IL1A
KRT15
TACSTD1
FXYD3
SPRR2D
FST
FST
SERPINB13
P13
EVA1
ANXA3
TGFA
204614_at
209792_s_at
205064_at
213796at
202917_s at
203021_at
213680_at
205778_at
214549_x_at
41469_at
203180_at
201131_s_at
210118_s_at
204734_at
201839_s at
202489 s at
208539_x at
204948_s_at
207345_at
217272_s at
203691_at
203780_at
209369_at
205016_at
217767_at
222242 s at
219121 _sat
213285_at
205403_at
218186_at
214456_x at
205067_at
205014_at
204379_s at
204751 x at
209863_s at
212268_at
205916_at
206023_at
219476_at
209800_at
218677_at
202712 s at
205680_at
C3
KLK5
RBM35A
TMEM30B
IL1 R2
RAB25
SAA2
IL1 B
FGFBP1
FGFR3
DSC2
TP73L
SERPINB1
S100A7
NMU
C1orf116
KRT16
S100A14
CKMT1 B
MMP10
shEcad vs
shCntrl log-fold
change
-8.0717
-7.5327
-7.4097
-7.2153
-7.2083
-7.0663
-7.0042
-6.9354
-6.8801
-6.8045
-6.6936
-6.6337
-6.6207
-6.4087
-6.3193
-5.9706
-5.7607
-5.742
-5.6254
-5.621
-5.6163
-5.4362
-5.3846
-5.3115
-5.2584
-5.119
-5.1177
-5.0971
-5.0927
-5.0546
-5.0394
-5.0166
-5.0029
-4.9797
-4.9795
-4.9643
-4.9641
-4.956
-4.9272
-4.9244
-4.8836
-4.8681
-4.8513
-4.8207
165
Symbol
ProbelD
KLK8
IL1B
DSG3
GJB3
GJB3
DSC3
EVA1
DSC3
CDH3
SPINT1
SCNN1A
CDH1
SFRP1
TP73L
CCND2
KRT13
CA2
SERPINB1
AQP3
KRT6B
SAA2
IL1 RN
TSPAN1
DSC2
ZBED2
CCND2
COL17A1
DST
SERPINB7
RBM35B
GJB5
SEMA3A
PPL
TRIM29
IL1 R2
ARTN
ST14
EREG
TMEM16A
FLJ12684
IRF6
ARTN
INHBA
CXCL1
206125 s at
39402_at
205595_at
205490 x at
215243 s at
206033_s_at
203779_s_at
206032_at
203256_at
202826 at
203453_at
201130 s at
202037 s at
211194 s at
200951 s at
207935_sat
209301_at
213572 s at
39248_at
209126 x at
208607 s at
212657 s at
209114_at
204750_s_at
219836_at
200953 s at
204636_at
204455_at
206421 s at
219395_at
206156_at
206805_at
203407_at
202504_at
211372 s at
210237_at
202005_at
205767_at
218804_at
219987_at
202597_at
207675 x at
210511 s at
204470_at
shEcad vs
shCntrl logfold change
-4.7629
-4.7398
-4.7293
-4.7065
-4.6965
-4.6921
-4.6783
-4.6599
-4.5706
-4.5679
-4.5591
-4.514
-4.4983
-4.4762
-4.4681
-4.4411
-4.4283
-4.4214
-4.3964
-4.3788
-4.3689
-4.3471
-4.3434
-4.3339
-4.2963
-4.2958
-4.2939
-4.2654
-4.2502
-4.2357
-4.2244
-4.1803
-4.1802
-4.1737
-4.1643
-4.158
-4.1383
-4.1329
-4.1232
-4.0924
-4.085
-4.0846
-4.0806
-4.0754
TNFAIP3
CSTA
CD24
S100A9
VSNL1
LAMB3
CDS1
ST14
CD24
TNFAIP3
SPINT2
SFRP1
FLRT3
MAPK13
SERPINB13
CD24
SLAC2-B
MFAP5
SLC2A9
TACSTD2
VSNL1
KCNK1
ABLIM1
CEACAM6
TPD52L1
HS3ST2
CD24
SERPINA1
CD24
CYP27B1
CD24
GPR56
PTGS2
PCDH7
DDR1
MMP9
KCNK1
KRT8
NRCAM
TNFRSF6B
DST
JAG2
PLA2G4A
SCEL
IGSF3
ARTN
JUP
VGLL1
SDC1
KRT6A
202643_s_at
204971_at
266_s_at
203535_at
203798_sat
209270_at
205709_s_at
216905_s_at
208651_x at
202644_s_at
210715_s_at
202036_sat
219250_s_at
210058_at
211361 s at
209772_s at
214734_at
213764 s at
219991 _at
202286_s_at
203797_at
204679_at
200965_sat
211657_at
203786_sat
219697_at
216379_xat
202833_s at
209771_x_at
205676_at
208650_s at
212070_at
204748_at
205534_at
210749 x at
203936_s at
204678_s at
209008_xat
204105_s at
206467_x at
216918_sat
32137_at
210145_at
206884_s at
202421_at
216052_x_at
201015_sat
215729 s at
201286_at
209125_at
-4.0657
-4.0473
-4.037
-4.0267
-4.0208
-4.0207
-4.0154
-4.0118
-4.011
-4.0056
-3.9916
-3.9871
-3.9723
-3.9676
-3.9426
-3.9378
-3.9259
-3.9144
-3.9037
-3.8993
-3.8677
-3.8465
-3.8298
-3.7978
-3.7828
-3.7793
-3.7742
-3.7566
-3.7566
-3.7529
-3.741
-3.7311
-3.724
-3.7072
-3.6849
-3.6812
-3.6525
-3.6445
-3.6417
-3.6272
-3.6262
-3.6194
-3.6193
-3.616
-3.6127
-3.6079
-3.5903
-3.5821
-3.187
-3.1851
166
WISP3
CEACAM6
MFAP5
CLCA2
LAMA3
MAP7
ST6GALNAC2
PKP3
HS3ST1
ARHGAP8
KRT6A
MST1R
SOX15
CLCA2
SNX10
TSPAN13
KIAA0746
CTSL2
F11R
CLCA2
PRR5
CLDN7
JAG2
ARHGEF3
Cl0orf10
DDR1
MMP1
TPD52L1
FRMD4B
LAMC2
MFAP5
MTSS1
TGFA
FEZ1
KRT5
ANXA8
LCN2
FGFR2
CNTN1
ITGB6
GPRC5A
RAB38
ITGB4
DDR1
SLC6A15
PRRG4
KRT18
MAPK13
MIA
EDG7
210861 s at
203757 s at
213765_at
206165 s at
203726 s at
202890_at
204542_at
209873_s_at
205466_s_at
37117_at
214580 x at
205455_at
206122_at
217528_at
218404_at
217979_at
212314_at
210074_at
221664_sat
206166 s at
205980 s at
202790_at
209784_s_at
218501 _at
209183 s at
208779_x_at
204475_at
210372 s at
213056_at
207517_at
209758 s at
203037_s at
205015_s at
203562_at
201820_at
203074_at
212531 _at
203638 s at
211203 s at
208083 s at
203108_at
219412_at
204990 s at
207169 x at
206376_at
207291 _at
201596_x at
210059 s at
206560 s at
220816_at
-3.58
-3.5544
-3.5389
-3.5318
-3.5096
-3.5069
-3.5046
-3.4894
-3.4885
-3.4827
-3.4803
-3.4788
-3.4785
-3.4718
-3.467
-3.461
-3.4417
-3.4204
-3.4129
-3.4108
-3.4074
-3.4059
-3.3989
-3.3836
-3.3761
-3.3719
-3.3695
-3.3566
-3.3527
-3.3308
-3.3306
-3.324
-3.3226
-3.3156
-3.3148
-3.3148
-3.3045
-3.302
-3.2895
-3.2884
-3.2842
-3.2708
-3.2688
-3.2506
-3.2303
-3.2143
-3.2058
-3.1947
-2.9577
-2.9522
GRHL2
PERP
OCLN
ALOX15B
MALL
KRT17
FXYD3
FGFR2
IL8
TMEM40
PTHLH
SDC1
GPR87
MAP7
CASP1
LYPD3
PTHLH
C10orf116
LISCH7
P2RX5
MAP7
AP1 M2
ITGB4
TMPRSS11E
DSP
KRT17
KIAA0040
PTPRZ1
NDRG1
EPN3
IF130
SERPINA1
ARL7
EHF
Clorf116
COBLL1
PRSS8
CAMK2B
ITGB6
MYO1D
CYB5R2
BMP2
IL18
HOOK1
PTHLH
ARHGEF4
LAD1
SLC39A8
219388_at
217744_s_at
209925_at
206714_at
209373_at
218764_at
205157_s_at
202488_s_at
208228s_at
202859_x at
219503_s_at
211756_at
201287 s at
219936_sat
202889_x_at
211368_s at
204952_at
210355_at
203571 s at
208190 s at
210448_s at
215471 s at
218261 at
204989 s at
220431_at
200606_at
212236_x at
203143_sat
204469_at
200632_sat
220318_at
201422_at
211429_ sat
202207_at
219850_s at
219856_at
203641_s at
202525_at
209956_sat
208084_at
212338_at
220230_s_at
205290_s at
213929_at
206295_at
219976_at
206300_s at
205109_sat
216641_sat
209267_s at
-3.1843
-3.1795
-3.1688
-3.1622
-3.1618
-3.1519
-3.1434
-3.1367
-3.1343
-3.1341
-3.1329
-3.1277
-3.1196
-3.0864
-3.0855
-3.0746
-3.0696
-3.0671
-3.0648
-3.0621
-3.0565
-3.047
-3.044
-3.0392
-3.039
-3.0369
-3.0288
-3.028
-3.026
-3.0254
-3.0253
-3.0218
-3.0193
-3.0179
-3.0117
-3.0062
-3.0017
-3.0008
-2.9882
-2.9867
-2.9764
-2.9722
-2.968
-2.9656
-2.9641
-2.9637
-2.6713
-2.6695
-2.6693
-2.6649
167
IL8
CAMK2B
DDR1
LPHN2
ATP12A
ST6GALNAC5
CNTNAP2
LAD1
ICAM1
SYK
ARL7
LAMC2
CASP1
ERBB3
IFIH1
EPS8L1
CCL20
NAV3
CXCL2
SLC1A3
CLCA2
ZNF185
CCND2
ITGA2
GPM6B
COBLL1
CENTD1
BACE2
ABCA12
SFRP1
SOX9
ST6GAL1
C20orf42
CELSR1
KLF5
PCDH7
AREG
CA9
CXADR
EFNA1
FLJ21511
GPM6B
IL1 F9
MCOLN3
SNCA
AMPD3
SERPINB13
APOC1
GALNT6
FZD3
211506_s_at
210404 x at
1007 sat
206953 s at
207367_at
220979 s_at
215145_s_at
203287_at
202637 s at
207540 s at
202206_at
202267_at
209970 x at
202454 s at
219209_at
91826_at
205476_at
204823_at
209774 x at
202800_at
206164_at
203585_at
200952_s_at
205032_at
209169_at
203642 s at
213618_at
217867 x at
215465_at
202035 s at
202936 s at
201998 at
60474_at
41660_at
209211_at
205535 s at
205239_at
205199_at
203917_at
202023_at
220723 s at
209168_at
220322_at
220484_at
204466 s at
207992 s at
211362 s at
204416 x at
219956_at
219683_at
-2.9502
-2.9363
-2.9327
-2.9306
-2.9275
-2.9232
-2.922
-2.8918
-2.8913
-2.8889
-2.8886
-2.8866
-2.8825
-2.8806
-2.8781
-2.8772
-2.8663
-2.8646
-2.8508
-2.842
-2.8367
-2.8347
-2.8135
-2.8122
-2.8085
-2.7934
-2.7851
-2.783
-2.7785
-2.77
-2.7474
-2.7459
-2.7443
-2.7333
-2.7262
-2.7208
-2.7179
-2.7178
-2.7145
-2.7139
-2.7075
-2.6897
-2.6885
-2.6853
-2.6822
-2.6769
-2.3753
-2.3719
-2.3662
-2.3656
ITGA6
KIAA0746
XDH
TGFA
ARHGAP25
SOX9
LEPREL1
ARHGAP25
DUOX1
KLF5
MYO5C
SLC39A8
TINAGL1
CREG1
CDC2L2
KRT14
CA12
CTSC
MBP
TFCP2L1
SLC7A5
KIBRA
AKR1C2
CA12
CST6
IVL
UPP1
LGALS7
P2RY2
TNFSF10
PITPNC1
CASP1
KIBRA
TIMP3
ARL7
PTGES
MCTP2
SORL1
EPHA1
GRB14
CASP1
HOMER1
Clorf106
MGST2
ZNF165
ARG2
EPB41 L4B
LYN
DMD
CDCP1
215177_s_at
212311_at
210301 _at
211258_s_at
38149_at
202935_sat
218717_s_at
204882_at
219597_s_at
209212 s at
218966_at
219869 s at
219058_x_at
201200_at
210473_s_at
209351_at
204508_s_at
201487_at
210136_at
219735_s at
201195_ s _at
216074_x at
209699_x_at
203963_at
206595_at
214599_at
203234_at
206400_at
206277_at
202688_at
219155_at
211366_x_at
213085_s at
201147_s at
202208_sat
210367_s_at
220603_s at
212560_at
205977_s_at
206204_at
211367 s at
213793_s at
219010_at
204168_at
206683_at
203946_s at
220161_s at
202626 s at
203881_s at
218451_at
-2.6535
-2.6529
-2.6468
-2.6412
-2.6367
-2.6291
-2.6225
-2.6175
-2.6131
-2.6122
-2.5998
-2.599
-2.5933
-2.5842
-2.5773
-2.5688
-2.5675
-2.547
-2.5457
-2.5117
-2.4963
-2.4874
-2.4775
-2.4733
-2.4664
-2.4623
-2.457
-2.451
-2.4449
-2.4372
-2.4367
-2.4346
-2.4305
-2.4287
-2.4239
-2.4235
-2.4224
-2.409
-2.4074
-2.3965
-2.3904
-2.3838
-2.3836
-2.3758
-2.2031
-2.2023
-2.2021
-2.1997
-2.1964
-2.193
168
MOSC1
C20orf42
ADRB2
CD44
ABCG2
L1CAM
ITGA6
C6orf105
AP1G1
CA12
F3
SLC31A2
AP1 M2
SERPINB13
AKR1C1
TRIM29
SLC6A8
KIAA1815
CXCL3
RNF128
TMEM22
HES1
KCNG1
GPM6B
FAT2
MPPE1
TNFRSF21
NFE2L3
C 1orf42
GCLC
LYN
BIK
CSH2
MPPE1
GALNT14
FOS
S100A8
SLC5A1
IRX4
SPAG1
SLC6A10
AKR1C1
MOBKL2B
VDR
HBEGF
LYN
KRTHB1
FGD6
LIMK2
FLJ20273
218865_at
218796_at
206170_at
217523_at
209735_at
204584_at
201656_at
215100_at
215867_x_at
210735_s_at
204363_at
204204_at
65517_at
216258 s at
204151 _xat
211002 s at
210854_x_at
218342 s at
207850_at
219263_at
219569 s at
203394 sat
214595_at
209170_s_at
208153_s_at
214071 _at
214581 _xat
204702 s at
220620_at
202922_at
210754 s at
205780_at
212737_at
213924_at
219271 _at
209189_at
214370_at
206628_at
220225_at
210117_at
215812 s at
216594_xat
219265_at
204254 s at
38037_at
202625_at
213711_at
219901 _at
202193_at
218035 s at
-2.3647
-2.3518
-2.3515
-2.3486
-2.345
-2.3411
-2.3405
-2.3374
-2.3348
-2.3279
-2.3253
-2.3245
-2.3156
-2.3142
-2.3112
-2.3103
-2.3101
-2.3097
-2.3084
-2.2968
-2.2931
-2.285
-2.284
-2.2833
-2.2746
-2.2689
-2.2674
-2.2672
-2.2661
-2.2655
-2.2651
-2.2641
-2.2632
-2.2583
-2.2465
-2.2456
-2.2432
-2.2408
-2.2365
-2.2332
-2.2312
-2.2277
-2.2269
-2.2098
-2.0319
-2.0312
-2.0263
-2.0259
-2.0259
-2.0204
BDKRB2
CLDN4
MAP3K9
RHOD
GPM6B
HBEGF
IL RN
IL4R
STAC
SERPINA3
CD1 D
CA12
ITM2A
SLC6A8
ELMO3
PARP12
DSU
CLDN1
MAST4
KLK11
PLXNB1
GCLC
GALNT3
EDN1
NRG1
SLC7A8
S100P
SFN
PSTPIP2
AQP3
TFPI2
GNA15
IGSF4
THBD
MAOA
RLN2
CORO1A
STEAP1
CYP4F11
STAP2
PTPNS1
ANK3
EPAS1
ROBO1
DUSP6
OAS3
MYO1 B
SEMA3C
CDK5R1
205870_at
201428_at
213927_at
209885_at
209167_at
203821 _at
216243 s at
203233_at
205743_at
202376_at
205789_at
214164_x at
212444_at
202747_s at
213843_x_at
219411_at
218543_s_at
219648_at
218182_s at
40016_gat
205470_s_at
215807_s_at
202923_s_at
203397_sat
218995_s_at
206343_s_at
216604 s at
204351_at
209260_at
219938_sat
39249_at
209277_at
205349_at
209030_s_at
203887_s_at
204388_sat
214519_s_at
209083_at
205542_at
206153_at
221610_s_at
202897_at
206385 s at
200878_at
213194_at
208891_at
218400_at
212364_at
203789_s at
204995_at
-2.1912
-2.1895
-2.1833
-2.1829
-2.182
-2.1753
-2.1707
-2.1625
-2.1585
-2.1547
-2.1538
-2.1517
-2.1452
-2.1426
-2.14
-2.1339
-2.1333
-2.1314
-2.1298
-2.1282
-2.1193
-2.1157
-2.1145
-2.1083
-2.1041
-2.1037
-2.0926
-2.0883
-2.0834
-2.0818
-2.0774
-2.0706
-2.0669
-2.0663
-2.066
-2.0623
-2.0609
-2.0592
-2.0511
-2.0509
-2.046
-2.0386
-1.9012
-1.9009
-1.899
-1.8986
-1.8964
-1.8945
-1.888
-1.887
169
HPSE
KLK10
SRCAP
SH2D3A
TIMP3
ICAM1
TNFSF10
KCNJ15
DUSP6
SLCl 2A8
CCNA1
PTAFR
PAMCI
VDR
AKR1C2
POPDC3
SLC6A8
LOC254531
SORL1
MTUS1
SLC27A3
CNTNAP2
DUSP6
TIMP3
C2orf31
SLC2A3
CNTNAP2
GM2A
B3GNT3
CD83
IGSF4
LRRC1
RIMS3
PDPN
FLJ20366
BIRC3
RIPK4
CAMK2N1
TIAF1
TNFRSF21
D4S234E
SLC3A2
AQP3
PTPRE
HOXA1
CYB561
DUSP10
LY75
MARK1
SRCAP
219403_s_at
215808_at
213667_at
219513 sat
201150_
s at
202638 s at
202687 s at
210119_at
208892_s_at
219874_at
205899_at
211661 _xat
210335_at
204255_ sat
211653_x_at
219926_at
202219_at
40472_at
203509_at
212096_s_at
222217 s at
219300_s_at
208893_sat
201148 s at
221245_s_at
202499_s_at
219301 s at
35820_at
204856_at
204440_at
209031 _at
218816_at
204730_at
204879_at
218692_at
210538 s at
221215 s at
218309_at
202039_at
218856_at
209569_x_at
200924 s at
203747_at
221840_at
214639 s at
209164_s_at
221563_at
205668_at
221047_sat
38766_at
-2.0146
-2.0139
-2.0127
-2.0123
-2.0097
-2.0055
-2.0035
-2.0023
-1.9934
-1.9911
-1.9898
-1.9895
-1.9858
-1.9857
-1.9829
-1.9756
-1.9707
-1.9683
-1.9654
-1.9616
-1.9544
-1.9506
-1.9492
-1.9455
-1.9452
-1.942
-1.9389
-1.9388
-1.9381
-1.9367
-1.9341
-1.9321
-1.9288
-1.9271
-1.9268
-1.9197
-1.9156
-1.9131
-1.9119
-1.9072
-1.9066
-1.9053
-1.7673
-1.764
-1.7623
-1.7599
-1.7592
-1.7585
-1.7535
-1.7521
CELSR2
Cl0orf10
FLJ20130
TIMP3
ITGB4
NRG1
Cl9orf21
IL1 3RA2
RHOD
LGR4
IL15RA
F11R
KIAA0040
KIAA0888
FAM69A
DAPP1
ABLIM1
S100A2
MYO1E
TREM2
SLC7A8
SNCA
KIAA0247
SDC4
TBC1D4
EMR2
PIP5K2C
MAST4
HERC6
PELI1
PRKCZ
CYB5R1
SEMA3C
IER3
ARHGEF5
DHRS1
TCF7L1
DAF
PLAU
CAMK2B
SLC20A2
TFRC
PLK2
ZNF574
ALS2CL
FLNB
CELSR2
KCNN4
CSF3
IL1 RAP
36499_at
209182_s at
220520_s_at
201149_s_at
211905 s at
206237_s at
212925_at
206172_at
31846_at
218326_sat
207375_s_at
222354_at
203144_s_at
213954_at
216044_x_at
219290_x_at
210461 _s_at
204268_at
203072_at
219725_at
202752_x_at
207827_x_at
202181 _at
202071_at
203387_s at
207610_s_at
218942_at
210958_s_at
219352_at
218319_at
202178_at
202263_at
203788_s at
201631 _sat
204765_at
213279_at
221016_s_at
201925_s_at
205479_s_at
211483_x at
202744_at
207332_s at
201939_at
221844_x at
222333_at
208613_s at
204029_at
204401 _at
207442_at
210233_at
-1.8833
-1.8828
-1.8787
-1.8739
-1.8721
-1.8691
-1.8647
-1.8611
-1.8605
-1.8593
-1.8579
-1.8577
-1.8572
-1.8566
-1.8549
-1.8511
-1.8451
-1.8326
-1.8299
-1.8197
-1.8139
-1.8079
-1.8064
-1.8064
-1.8057
-1.8034
-1.8023
-1.8022
-1.8001
-1.7998
-1.7989
-1.7985
-1.7971
-1.7914
-1.79
-1.7887
-1.7815
-1.7798
-1.7782
-1.769
-1.6485
-1.6453
-1.6444
-1.6422
-1.6412
-1.6403
-1.6368
-1.6368
-1.6344
-1.6342
170
KIAA1 026
PTPRF
FLJ20035
CYB561
KIAA1 609
ANKRD15
EDG4
CBLC
QPCT
AGRN
HDAC9
EPS8L2
NCF2
CD9
C20orf 19
TNFRSF25
PLAU
FAM69A
DDX58
LTB
TAGLN3
TLR2
ISG20
TMPRSS4
PTPN3
GOS2
ATP2B4
PAK6
ATP2B4
FGFR2
ADAM8
CCNG2
CSF2
LOC254531
NRCAM
CEACAM1
ARHGDIB
IGSF4
CD82
SEMA3B
AKAP1
AJAP1
ZDHHC13
EPLIN
GNAL
BHLHB3
LRP12
RPS6KA1
FHOD3
213478_at
200637_sat
218986_sat
209163_at
221843 s at
212812_at
213005 s at
206723 s at
220638 s at
205174 s at
212285 s at
205659_at
218180 s_at
209949_at
201005 at
219961_sat
219423_xat
211668 s at
213689_ x at
218943 s at
207339 s at
204743_at
204924_at
204698_at
218960_at
203997_at
213524 s at
212135_s at
219461_at
212136_at
203639 s at
205180_s at
202770 s at
210229 s at
213078_xat
216959_x_at
209498_at
201288_at
209032_sat
203904 x at
203071 _at
201675_at
215789_s_at
219296_at
217892_sat
206355_at
221530 s at
220253_sat
203379 at
218980_at
-1.7459
-1.7458
-1.7428
-1.7424
-1.7385
-1.7362
-1.7324
-1.7306
-1.7292
-1.7281
-1.7255
-1.7235
-1.7194
-1.7187
-1.7177
-1.7148
-1.7141
-1.7136
-1.7094
-1.7079
-1.7078
-1.7064
-1.7063
-1.7003
-1.6954
-1.6947
-1.6882
-1.6857
-1.6832
-1.6752
-1.6688
-1.666
-1.6635
-1.6632
-1.66
-1.66
-1.6558
-1.653
-1.6525
-1.6524
-1.527
-1.5261
-1.5204
-1.5179
-1.5146
-1.5145
-1.5116
-1.5109
-1.5083
-1.5013
ZHX2
PTPRF
RIMS2
GM2A
AGRN
MYO1B
DSCAM
CTSH
SMPDL3B
AIM1
ZC3H12A
DSG2
TFPI2
SEMA3F
PRKCH
HLA-DOB
NBEAL2
SERPINB3
TMEM51
GM2A
RSNL2
INPP4B
HSPA5BP1
OVOL2
HES1
RAPGEF5
RAB17
SLC7A8
HOOK2
SLC39A8
TP73L
CYP1A1
CORO2A
GCH1
RHBDL6
KCNJ15
EVIl
203556 at
200635 s at
206137 at
209727 at
217419 x at
212365_at
211484 s at
202295 s at
205309 at
212543 at
218810 at
217901 at
209278 s at
35666 at
206099 at
205671 s at
212443 at
209719 x at
218815 s at
33646_g_at
219944
205376
218834
211778
203395
204681
218931
216092
218780
216504
at
at
s at
s at
s at
s at
at
s at
at
s at
211834 s at
205749 at
205538_at
204224 s at
219202_at
211806 s at
221884 at
-1.6336
-1.6258
-1.6253
-1.6248
-1.6132
-1.6123
-1.6085
-1.6042
-1.6022
-1.5998
-1.5985
-1.5952
-1.5944
-1.5894
-1.5862
-1.5844
-1.584
-1.5826
-1.5789
-1.5726
-1.5707
-1.5695
-1.5661
-1.5638
-1.5615
-1.5612
-1.561
-1.5609
-1.5608
-1.5583
-1.5549
-1.5526
-1.5522
-1.5516
-1.5419
-1.5417
-1.5407
171
B4GALT4
PTPRF
TRIM34
210540 s at
200636 s at
221044 s at
-1.5012
-1.5005
-1.5355
Appendix 2
Probes and the corresponding genes upregulated more than 1.5 log-fold in DN-Ecad
cells
Symbol
ProbelD
GDF15
TSC22D3
TSC22D3
RNASE4
ATF3
CYP4F1 1
AKR1C1
FBN2
AKR1C2
SSBP1
KDELR3
P8
PER1
AKR1C1
INPP5D
CTH
HCP5
PTGS1
LEPR
PRSS8
CTH
KDELR3
TXNIP
BLNK
AKR1C2
ANG
FTL
BHLHB3
CALML4
LGALS7
LHX6
FBXO2
C1QL1
221577_x_at
208763_s_at
207001_x_at
213397_x_at
202672_s_at
206153_at
204151_x_at
215717_s_at
209699_x_at
214060_at
204017_at
209230 sat
202861_at
216594_x_at
203332_s_at
217127_at
206082_at
205127_at
209894_at
202525_at
206085 sat
207265_sat
201010_s_at
207655_s_at
211653_x_at
205141 _at
213187_x_at
221530_sat
64408 s_at
206400_at
219884_at
219305_xat
205575_at
203919_at
205158_at
210233_at
206832 sat
219153 s at
36829 at
214790_at
207339_s_at
203438_at
TCEA2
RNASE4
IL1 RAP
SEMA3F
FLJ13710
PER1
SENP6
LTB
STC2
DN-Ecad vs
shCntrl logfold change
4.1944 EPHB3
3.9408 ZNF198
3.7186 EPHX1
3.1831 CRELD1
3.1734 TXNIP
3.0435 TXNIP
2.9432 GABARAPL3
2.8419 PER2
2.7631 MGC4504
2.6847 H1FX
2.6659 STC2
2.6504 CCNA1
2.5846 ALDH6A1
2.5782 PFAAP5
2.5519 CALML4
2.5324 DNAJB9
2.5295 GPC1
2.5056 CYP1B1
2.5029 PNRC1
2.4523 NR1D2
2.4451 BTG2
2.4338 EML2
2.3868 ALDH6A1
2.3624 FTL
2.3226 DBP
2.3182 AKR1C2
2.2974 C1 orf38
2.2631 CRIP2
2.2382 BCL6
2.2194 ABCG1
2.2014 SLC39A7
2.1947 LAPTM5
2.1872 MAGED2
2.1745 CABC1
2.1719 CELSR2
2.1675 FLJ40092
2.1453 CPT1B
2.143 ALDH6A1
2.1385 TNFSF7
2.1233 Cep152
2.1183 KLF9
2.1117 MAGED1
172
1438_at
210282_at
202017_at
203368_at
201008 sat
201009_s_at
211458_s_at
205251 _at
219270_at
204805_s_at
203439_s_at
205899_at
221589 s at
214753_at
221879_at
202843_at
202755_s_at
202437 s at
209034_at
209750_at
201236_s_at
204398 s at
221588_x_at
212788 x at
209782_s_at
217626_at
210785_s_at
208978_at
203140_at
204567 s at
202667 s at
201721_s_at
208682_s_at
218168 sat
204029_at
213605 s at
210069_at
204290_s_at
206508_at
215170_s_at
203543_s_at
209014_at
2.1061
2.0994
2.0975
2.0948
2.0851
2.0652
2.0647
2.0641
2.0597
2.0426
2.035
2.0262
2.0076
1.9902
1.9777
1.9752
1.9661
1.9619
1.9592
1.9457
1.9384
1.9042
1.9016
1.9006
1.8997
1.8986
1.8979
1.8917
1.8899
1.8889
1.8446
1.8392
1.8239
1.8219
1.8212
1.8185
1.8113
1.8091
1.7891
1.7891
1.7802
1.7789
ALOX15B
Clorf38
GOLGA4
STCH
KDELR3
KLF9
GPX3
AKR1B10
LRP5
PHGDH
CTTN
PCK2
ASNS
GOLGA2
KIAA0323
USP52
ABHD4
TP53AP1
ZNF451
NINJ1
ZNF184
CSRP2
PGM3
ZNF516
DATF1
LOC81558
LRDD
DLGAP4
FLJ22639
ZNF226
POMZP3
MAGED2
CD44
EGFR
TGFB1
PRKCA
RRAS
CYP4F3
C9orf 16
KIAA0657
SMA4
SEC24D
NR1D1
KCNMA1
EPHB3
PRSS16
GCLC
BTN3A3
CARM1
206714_at
207571_x_at
215203_at
202557_at
207264_at
203542 s at
201348_at
206561 s at
209468_at
201397_at
214073_at
202847_at
205047_s_at
204384_at
212356_at
203117 s at
218581_at
209917 s at
215012_at
203045_at
213452_at
211126_sat
221788_at
203604_at
213213_at
221249_s_at
221640 s at
202570_s_at
220399 at
219603 s at
210910_s_at
213627_at
210916 s at
201984_s_at
203085_s_at
213093_at
212647_at
206515_at
204480 s at
213946 s at
215599_at
202375_at
31637_s_at
221584 s at
204600_at
208165 s at
202922_at
38241 at
221939_at
2.1082
1.7762
1.7734
1.7591
1.7589
1.7578
1.7546
1.753
1.7498
1.7479
1.7473
1.7472
1.7427
1.74
1.7353
1.7313
1.7304
1.7236
1.72
1.7163
1.7163
1.7117
1.7105
1.7088
1.7052
1.7037
1.7006
1.6998
1.6959
1.6908
1.6887
1.6875
1.6867
1.6831
1.6765
1.6747
1.6721
1.6659
1.6656
1.6617
1.6564
1.6557
1.6482
1.6449
1.6394
1.6394
1.6346
1.6316
1.6284
173
EFS
WIP149
C1orf66
PPFIBP1
FLJ20254
PDE4DIP
LEPRE1
GABARAPL1
MDM2
EFEMP2
APOE
MMP28
IL15
YIPF2
MST1
GFPT1
PFAAP5
POMZP3
HCFC1R1
IGFBP2
LOC440996
DKFZP586A0522
ZBTB16
VDP
C17orf39
FLJ13841
DKFZP586H2123
HCFC1R1i
PDE4DIP
DAF
CXorf12
AKR1C3
HERC1
PRKAG2
CDKN1B
WIG1
IGSF4C
KLHL24
204400_at
213836_s_at
218914_at
214375_at
217899_at
213388_at
220750_s_at
208869_s at
217373_x at
206580_s_at
203381_s at
219909_at
205992 s at
219075_at
216320_x_at
202722_s at
221899_at
204148 s at
45714_at
202718_at
222380 s at
207761 s at
205883_at
222316 at
220058_at
219995_s_at
213661 _at
218537_at
212390_at
201925_s_at
204340_at
209160_at
218306 s at
215231 _at
209112_at
219628_at
215259_s_at
221985_at
1.7773
1.6116
1.6106
1.6084
1.6053
1.6019
1.6007
1.6002
1.6001
1.5989
1.5933
1.589
1.5869
1.5852
1.5833
1.5823
1.5822
1.5783
1.5757
1.5741
1.5735
1.5652
1.5627
1.5618
1.5536
1.5473
1.5465
1.545
1.5442
1.542
1.5399
1.539
1.537
1.5346
1.5296
1.5088
1.5075
1.5054
Probes and the corresponding genes down-regulated more than 1.5 log-fold in DN-Ecad
cells
Symbol
ProbelD
SPRR2D
MMP10
CXCL1
FST
IL1R2
IL8
IL8
KRT13
IL1 R2
HS3ST2
CEACAM6
CEACAM6
GPRC5A
CALM1
EIF5
CALM1
IGFBP3
SERPINB2
VGLL1
SKP2
P13
TP73L
GLIPR1
KLK7
CYB5R2
S100A7
HSPH1
CCNE2
MCM10
FST
P13
KRTHA4
IL1F9
NUP98
PHLDA1
MFAP5
PTGS2
DKK1
CXCL3
PHTF2
LCMT2
ILF3
MAP4
208539 x at
205680 at
204470 at
207345 at
205403 at
202859 x at
211506 s at
207935 s at
211372 s at
219697 at
211657 at
203757 s at
203108 at
211985 s at
208290 s at
211984 at
210095 s at
204614 at
215729 s at
203626 s at
203691 at
211194 s at
204222 s at
205778 at
220230 s at
205916 at
208744 x at
211814 s at
220651 s at
204948 s at
41469_at
206969_at
220322_at
210793 s at
217997_at
213765_at
204748_at
204602_at
207850 at
217097 s at
204012 s at
208931 s at
200835 s at
DN-Ecad vs
shCntrl loqfold chanqe
-4.3198
-4.2073
-4.0769
-4.0606
-4.0554
-3.9569
-3.921
-3.9183
-3.7659
-3.3521
-3.3036
-3.2004
-3.0806
-3.0647
-3.0519
-3.0442
-3.0149
-2.9858
-2.9829
-2.9714
-2.9026
-2.859
-2.8157
-2.8134
-2.808
-2.7237
-2.7057
-2.697
-2.6952
-2.6801
-2.664
-2.6427
-2.6016
-2.6009
-2.5848
-2.5762
-2.5541
-2.5467
-2.5315
-2.5245
-2.4783
-2.0206
-2.0137
174
CCNE2
TMEM16A
BCLAF1
B3GNT1
ENC1
SCEL
ARL7
FLJ2151 1
TMPRSS11E
C12orf4
EIF5
ENC1
EXOSC2
IL6ST
MGC14376
KRT15
SFPQ
LCN2
CDC27
DNAJA1
OSMR
CXCL2
ADAMTS1
ARHGAP25
POP1
EDN1
IL7R
G3BP
PTHLH
DSC2
DRIM
MFAP5
DHX9
MFAP5
ARHGAP25
EIF5
PTHLH
DUSP6
EPN3
EIF5
UTP14A
HNRPM
SOX9
205034_at
218804_at
201101 sat
219326 s at
201340 s at
206884 s at
202206_at
220723 s at
220431_at
218374 s at
208708 x at
201341 _at
214507 s at
204864 s at
214696_at
204734 at
201585 s at
212531 at
217878 s at
200880_at
205729_at
209774 x at
222162 s at
204882 at
213449_at
218995 s at
205798_at
201514 s at
206300 s at
204751 x at
209725_at
209758 s at
212107 s at
213764 s at
38149_at
208706 s at
210355_at
208893 s at
220318_at
208705 s at
221513 s at
200072 s at
202935 s at
-2.4477
-2.3826
-2.3719
-2.3171
-2.3116
-2.3114
-2.3046
-2.29
-2.2847
-2.2585
-2.249
-2.2372
-2.2268
-2.2199
-2.2186
-2.2046
-2.1846
-2.1846
-2.1747
-2.1725
-2.1697
-2.1596
-2.1594
-2.1571
-2.1331
-2.126
-2.1137
-2.1122
-2.0935
-2.0817
-2.0775
-2.0762
-2.0727
-2.0715
-2.0603
-2.0511
-2.0479
-2.0452
-2.038
-2.0349
-2.0307
-1.7603
-1.7505
HSPA8
UTP14A
SPAG1
NUP50
TMEM2
NAV3
SERPINB13
ST6GALNAC5
IFIT5
ATP12A
SERPINB1
SFPQ
DCBLD2
JAG1
DDX18
TMPO
CSF3
HSPA8
SERPINB13
FOSL1
CANX
PHLDA1
LGALS8
HRB2
MDSRP
Cl orf42
GLIPR1
EIF4G1
BAT2D1
B3GALT3
EML4
CSF2
PPP2R1B
PTHLH
HMGCS1
IGFBP3
FEN1
LOC51136
CDC6
UGCG
Clorf116
SERPINB8
ZNF365
BRIP1
ILl B
NCBP1
PHLDA1
MCM4
MAX
11-Sep
210338_s_at
221514_at
210117_at
218294_s_at
218113_at
204823_at
216258_s_at
220979_s_at
203595_s_at
207367_at
213572_s at
201586_s_at
213865_at
209098_s at
205763_sat
209754_s at
207442_at
208687_x at
211362_s_at
204420_at
208853 s at
218000_sat
210732_s at
214085_x at
218587_s at
220620_at
204221_x at
208624_s at
211947_s at
211812_s at
220386_s at
210229_s at
202883_s_at
211756_at
205822_s at
212143_s at
204768 s at
221194_s_at
203967_at
221765_at
219856_at
206034_at
206448_at
221703 at
39402_at
209520_sat
217999_s at
222037_at
210734 x at
201308_s at
-2.0124
-2.004
-1.9953
-1.9791
-1.9725
-1.9709
-1.9641
-1.9609
-1.9533
-1.9519
-1.948
-1.9475
-1.9457
-1.9426
-1.9341
-1.9261
-1.9234
-1.919
-1.9037
-1.8928
-1.8924
-1.8906
-1.8892
-1.8747
-1.8684
-1.8638
-1.8539
-1.8512
-1.8494
-1.8483
-1.8393
-1.83
-1.8237
-1.8203
-1.8191
-1.8186
-1.8169
-1.8152
-1.7993
-1.7962
-1.7907
-1.7817
-1.7795
-1.7702
-1.7665
-1.7664
-1.5762
-1.5701
-1.5656
-1.5637
175
G3BP2
UMPS
SFRS3
WTAP
EXOSC2
FBXO9
IVL
EHF
DHX9
METAP2
DDX1 8
SETMAR
UMPS
SMARCC1
C14orf169
SUB1
SOX9
STARD13
ETS1
LARP4
ATP13A3
KLK10
MYO5C
SP100
HCCS
KRT8
EMR2
ZMPSTE24
RRS1
CBFB
CDC6
HNRPU
Cl0orf10
FLJ20516
TOE1
ARL7
TXNDC
CASP8
MOSCi
TGFA
DDX3X
HSPH1
HIST1H4C
SLC16A1
IL6ST
LOC56902
206383 s at
215165 x at
208673 s at
210285_xat
209527_at
210638 s at
214599_at
219850_s_at
212105 s at
213899_at
208896_at
206554 x at
202706 s at
201072 s at
219526_at
221727_at
202936_s_at
213103_at
214447_at
214155 s at
219558_at
215808_at
218966_at
210218 s at
203745_at
209008_xat
207610_s_at
202939_at
209567_at
206788 s at
203968 s at
200593 s at
209183 s at
219258_at
204080_at
202208_sat
208097 s at
207686 s at
218865_at
211258 s at
201211 s at
206976 s at
205967_at
202236_sat
212196_at
203622 s at
-1.7421
-1.7319
-1.73
-1.7297
-1.7263
-1.7225
-1.7207
-1.7163
-1.712
-1.7109
-1.6964
-1.6918
-1.6917
-1.6892
-1.6877
-1.6856
-1.6813
-1.6795
-1.6752
-1.6748
-1.672
-1.6714
-1.6712
-1.6577
-1.6532
-1.6501
-1.6478
-1.6441
-1.6402
-1.6284
-1.6228
-1.6152
-1.6121
-1.6089
-1.5997
-1.5982
-1.5971
-1.596
-1.5923
-1.5902
-1.5866
-1.5863
-1.5852
-1.58
-1.5785
-1.5775
PPP2R1B
TSEN2
PHLDA1
KLK10
KLF10
CHRNA5
KLK11
ARL7
RFWD3
MEST
P2RY2
TOR1AIP1
KIF5B
SERPINB13
IMP3
SERPINB1
RBM12
SLC43A3
BRCA2
SFRS2
HSMPP8
GLT28D1
PAFAH1B1
SYNCRIP
DDX52
HBEGF
SLC43A3
SCYL2
202886 s at
219581 at
217996 at
209792 s at
202393 sat
206533 at
205470 s at
202207 at
218564_at
202016 at
206277 at
216100 s at
201992 s at
217272 s at
221688 s at
212268 at
212168 at
213113 s at
214727 at
200754 x at
221771 s at
219015 s at
211547 s at
209025 s at
210320 s at
38037_at
210692 s at
221220 s at
-1.5621
-1.5551
-1.5512
-1.5463
-1.5455
-1.5402
-1.5381
-1.535
-1.5346
-1.5323
-1.5304
-1.5299
-1.5294
-1.529
-1.5273
-1.5268
-1.5243
-1.5231
-1.52
-1.515
-1.5134
-1.5125
-1.5123
-1.5117
-1.5092
-1.5014
-1.5004
-1.5004
176
Appendix 3
Genes differentially expressed more than 1.5 log-fold in both DN-Ecad and shEcad cells
Upregulated
ALDH6A1
CRIP2
CYP1B1
FTL
KCNMA1
KDELR3
KLF9
LEPR
MAGED1
MAGED2
P8
PRKCA
RNASE4
STC2
TCEA2
TSC22D3
WIP149
ZBTB16
Downregulated
ARHGAP25
ARL7
ATP12A
C10orf10
Clorf116
C1 orf42
CEACAM6
CSF2
CSF3
CXCL1
CXCL2
CXCL3
CYB5R2
DSC2
DUSP6
EDN1
EHF
EMR2
EPN3
FLJ21511
FST
GPRC5A
HBEGF
HS3ST2
IL1B
IL1F9
IL1 R2
IL8
IVL
KLK10
KLK11
KLK7
KRT13
KRT15
KRT8
LCN2
MFAP5
MMP10
MOSC1
MYO5C
NAV3
P2RY2
P13
PTGS2
PTHLH
177
S100A7
SCEL
SERPINB1
SERPINB13
SERPINB2
SOX9
SPAG1
SPRR2D
ST6GALNAC5
TGFA
TMEM16A
TMPRSS11E
TP73L
VGLL1
178