ANALYSIS OF CD9 AS A CANDIDATE STEM CELL MARKER IN CHILDHOOD
ACUTE LYMPHOBLASTIC LEUKEMIA AND SPECIFIC TARGETING OF
CANCER CELLS
Elaina Kenney
B.A., University of California, Berkeley, 2006
PROJECT
Submitted in partial satisfaction of
the requirements for the degree of
MASTER OF ARTS
in
BIOLOGICAL SCIENCES
(Stem Cell)
at
CALIFORNIA STATE UNIVERSITY, SACRAMENTO
SPRING
2011
2
ANALYSIS OF CD9 AS A CANDIDATE STEM CELL MARKER IN CHILDHOOD
ACUTE LYMPHOBLASTIC LEUKEMIA AND SPECIFIC TARGETING OF
CANCER CELLS
A Project
by
Elaina Kenney
Approved by:
__________________________________, Committee Chair
Thomas R. Peavy, Ph.D.
__________________________________, Second Reader
Thomas Landerholm Ph. D.
__________________________________, Third Reader
Jan Nolta, Ph. D.
____________________________
Date
ii
Student: Elaina Kenney
I certify that this student has met the requirements for format contained in the University
format manual, and that this project is suitable for shelving in the Library and credit is to
be awarded for the project.
__________________________, Graduate Coordinator
Susanne Lindgren, Ph.D.
Department of Biological Sciences
iii
________________
Date
Abstract
of
ANALYSIS OF CD9 AS A CANDIDATE STEM CELL MARKER IN CHILDHOOD
ACUTE LYMPHOBLASTIC LEUKEMIA AND SPECIFIC TARGETING OF
CANCER CELLS
by
Elaina Kenney
Acute lymphoblastic leukemia is the most common malignancy diagnosed in
children. High-risk leukemia patients have poor outcomes despite advancements in
chemotherapy treatments. Due to current therapy dose limitations, toxicities to normal
cells, long term side effects and leukemia cells developing resistance to chemotherapy,
there is great need for the development of innovative therapies. Leukemia stem cells
(LSCs) are thought to be the precursors to leukemia cells and are suspected to be the
cause of leukemia proliferation, metastasis, and relapse. Therefore, it is critical to develop
novel therapies to target LSCs specifically. However, due to the lack of ability to identify
LSCs, no LSC targeted therapies have been developed. The goal of this project is to
identify LSCs in childhood precursor B acute lymphoblastic leukemia (ALL), in order to
target these LSCs and spare normal cells, by using a combination of flow cytometry,
Raman spectroscopy, and peptide screening.
iv
Since recent reports have correlated CD9 with LSCs in acute lymphoblastic
leukemia cell lines, primary human ALL cells obtained from the University of California,
Davis Medical Center were sorted by flow cytometry based on expression levels of the
cell surface marker CD9. Sorted populations were engrafted into immunodeficient mice
to analyze their ability to re-initiate leukemia. Sorted candidates subsequently were
characterized using the laser-based technique, Raman spectroscopy, in order to determine
whether the intrinsic biochemical signatures obtained by Raman spectroscopy could
further identify LSCs. Lastly, LSCs and primary ALL samples were screened through
one-bead one-compound (OBOC) combinatorial libraries to investigate peptides that will
specifically target cell surface marker of LSCs. The OBOC peptides identified will be
used to selectively target LSCs using drug loaded nanoparticles.
After establishing a mouse model that could successfully engraft human ALL,
three primary ALL samples were chosen for our study. When injected with sorted cells,
25%of the CD9 positive injected mice and 14% of the CD9 negative injected mice,
developed leukemia. Furthermore, the Raman analysis of these sorted cells showed CD9
positive and CD9 negative cells have very similar intracellular signatures. Together this
indicates that CD9 is not a good marker for LSCs in childhood ALL. As for OBOC
screening, unsorted primary ALL samples were screened against OBOC peptide libraries
and 33 leukemia-specific ligand sequences were identified. Eleven of the most common
sequences were synthesized into biotinylated ligands to test for their binding affinity to
leukemia cells.
v
Although the LSC population was not identified by CD9 sorting or Raman
signatures of ALL patient samples, OBOC screening of the unsorted cancer cells did
result in the identification of leukemia-specific ligands which have the potential to be
used to coat drug loaded nanoparticles. These nanoparticles could then be used for direct
targeting of leukemia cells which should have minimal toxicity to all other normal cells
since the ligands are specific to leukemia. Furthermore, this OBOC technique could be
applied to other childhood malignancies and lead to new cancer therapies.
______________________________, Committee Chair
Thomas R. Peavy, Ph. D.
____________________________
Date
vi
TABLE OF CONTENTS
Page
List of Tables ............................................................................................................ viii
List of Figures ............................................................................................................. ix
INTRODUCTION ........................................................................................................1
MATERIALS AND METHODS ............................................................................... 13
RESULTS
............................................................................................................ 19
DISCUSSION ............................................................................................................ 42
Literature Cited .......................................................................................................... 49
vii
LIST OF TABLES
Page
Table 1. Leukemia injected NSG mice and outcomes ......................................................25
Table 2. Amino acid sequences of identified peptides .....................................................32
Table 3. Structure and formula of synthesized peptides ...................................................38
viii
LIST OF FIGURES
Page
Figure 1. Leukemia specific nanoparticle ...........................................................................9
Figure 2. Diagram of LLP2A synthesis ............................................................................16
Figure 3. NSG symptoms of leukemia prior to necropsy .................................................20
Figure 4. CD9 sorting of preB ALL..................................................................................22
Figure 5. Raman signatures of CD9 sorted cells...............................................................23
Figure 6. Evidence of preB ALL engraftment in NSG mouse .........................................27
Figure 7. Leukemia cells harvested from NSG mouse .....................................................28
Figure 8. Bead screening of leukemia cells ......................................................................31
Figure 9. Schematic of biotinylated ligand .......................................................................34
Figure 10. HPLC of biotinylated ligand LLS14 ................................................................36
Figure 11. Identification of pure ligand in HPLC fraction by MALDI MS ......................37
ix
1
INTRODUCTION
Leukemia is a detrimental disease that affects over 250,000 individuals per year.
Many of these affected adults and children will die from Leukemia. Although there are
many types of leukemia, the most prevalent in children is acute lymphoblastic leukemia
(ALL). Annually, 2,500-3,500 children are diagnosed with ALL (2). The peak prevalence
occurs in children two to five years of age, with another peak in adults. With recent
improvements in diagnosis and treatment, overall cure rates for children with acute
lymphoblastic leukemia now approaches 80% (adults is roughly 50%) (1). However,
some patients have a high risk of relapse or the disease spreading and the four-year eventfree survival rate for these high-risk patients is only near 65%. It is poorly understood as
to why these high-risk individuals relapse (1). Furthermore, many patients who do relapse
often die. Therefore, more effective therapies need to be developed in order to improve
cure rates for patients at high risk, while limiting the toxicity of therapies for patients
with a low risk of relapse.
Leukemia is a type of cancer affecting cells of the bone marrow or blood and is
characterized by abnormally high amounts of white blood cells. There are two broad
categories of leukemia, acute and chronic. Acute leukemia is characterized by excessive
amounts of immature blood cells, progenitor cells that will go on to form other types of
blood cells. Whereas chronic leukemia is comprised of relatively mature malignant white
blood cells and progresses much more slowly than acute forms. Acute leukemia is the
2
most common malignancy to affect children, representing nearly one third of all pediatric
cancers (1).
These two divisions are subdivided further depending on the types of cells
affected. The two subcategories are myelogenous and lymphoblastic leukemia.
Myelogenous leukemia is distinguished by cancer of myeloid cells, progenitor cells in the
bone marrow that go on to form red blood cells, platelets, and some white blood cells
(neutrophils, eosinophils or basophils). Whereas, lymphoblastic leukemia is cancer of
lymphoblasts, progenitor cells in the marrow that give rise to white blood cells (B-cells
and T-cells) called lymphocytes. Lymphocytes make up the immune cells that fight off
infection. Lymphoblastic leukemia can also be further classified depending if precursor
B-cells or T-cells are affected.
This makes a total of four major types of leukemia: acute lymphoblastic
leukemia, acute myelogenous leukemia, chronic lymphocytic leukemia, and chronic
myelogenous leukemia. As previously stated, acute lymphoblastic leukemia (ALL) is the
most common type and is characterized by excessive lymphoblasts and is the focus of our
study (1, 2). In acute lymphoblastic leukemia, a lymphoid progenitor cell undergoes
genetic mutations and subsequently undergoes dysregulated proliferation, survival, and
clonal expansion (2).
Acute lymphoblastic leukemia causes damage by overcrowding normal cells in
the bone marrow and metastasizing to other tissues (3). This overcrowding in the bone
marrow prevents the production of healthy blood cells. The lack of normal, healthy cells
circulating in the body causes many essential systems to malfunction, including the
3
kidney and liver. Patients also develop aberrantly functioning red blood cells, platelets
and leukocytes (3). Due to these consequences of the disease and to its rapid progression,
acute lymphoblastic leukemia requires immediate treatment. If left untreated, ALL can be
fatal in as little as a few weeks. Although a small percentage of cases are associated with
inherited genetic syndromes, the cause of acute lymphoblastic leukemia remains largely
unknown (2).
Treatment for acute lymphoblastic leukemia can include chemotherapy, steroids,
radiation therapy, bone marrow transplantation or an intensive combination of treatments
(2). The initial and most common treatment is chemotherapy with cytotoxic antileukemic drugs. However, this cytotoxicity is not limited to leukemia cells, but will affect
and target cells that are proliferating and dividing, including all normal cells in the body
as well as cancerous ones. This usually causes limitations on the dose of these antileukemic drugs that can be given to patients and how long individuals can be on them.
Furthermore, leukemia cells can eventually develop resistance to chemotherapy drugs,
leaving only the normal and healthy cells to be affected. This problem decreases the
current therapy’s effectiveness and increases the need for more specific and targeted
chemotherapeutics.
In addition to the limitations of current treatments, issues relating to long-term
morbidity and mortality associated with this toxicity and side effects to other organ
systems are of great concern. Because of the young age of these cancer survivors, the
delayed toxic effects of treatment might not show up for many years, and can have a
significant impact on their lives (3). Reported long-term consequences include impaired
4
intellectual and psychomotor functioning, neuroendocrine abnormalities, impaired
reproductive capacity, cardiotoxicity, and second malignant tumors (3). All together, this
signifies a great need for novel strategies to combat this type of childhood malignancy.
What's more, any research breakthroughs could potentially lead to novel therapies that
might also be applied to other types of leukemia as well as other types of neoplasia.
Recently, a popular cancer stem cell model of tumor biology has rapidly emerged.
This model suggests there is a small, rare population of cells, cancer stem cells, which
possess the ability to self-renew and is responsible for tumor progression and metastasis.
These cancer stem cells are usually rare and have properties that are distinct from most
other tumor cells (4). These unique cells can, like other stem cells, divide and
differentiate into the cells that comprise the whole tumor, as well as expand their own
population.
Malignant stem cells have recently been described as the source of several types
of human cancer (4). There are two proposed mechanisms for the origin of these cancer
stem cells. The first being organ stem cells, which naturally have the ability to selfrenew, undergo genetic and epigenetic changes and become tumorigenic. The second
mechanism is proliferative progenitor cells that somehow acquire genetic changes or
mutations and develop self-renewal properties. Whatever the mode of origin, these cells
could potentially be like other stem cells and infrequently enter the cell cycle. If this is
true, these rare cancer stem cells would be resistant to current cancer treatments that
target rapidly dividing cells and would be left to reconstitute the tumor.
5
Early studies of the 1960’s suggest cancers of the blood have immature cell
populations that are able to generate a population of cancer cells and points to the
existence of leukemia stem cells (5). Later studies in the late 1990’s indicated that there
were cancer stem cells in acute myelogenous leukemia (AML). This study found all
AML cells (no matter the maturation) displayed a specific cell surface marker that was
similar to normal hematopoietic primitive cells (5). This suggested that primitive cells
were the leukemic initiating cell, and not progenitor cells. This study also indicates that
AML is organized in a hierarchical manner and these leukemia-initiating cells were found
to possess the ability to initiate human AML when transplanted into a mouse (5). Several
other studies indicate that leukemic stem cells (LSCs) are present in certain types of acute
lymphoblastic leukemia (ALL) and are thought to be the precursors to all leukemia cells
(4, 6). Additionally, LSCs are proposed to be responsible for tumorigenesis, proliferation,
metastasis, and relapse.
Unfortunately, the use of cytotoxic agents in current cancer treatments and
therapies targets both the leukemia and normal stem cell populations. Therefore, new
strategies are required that specifically and preferentially target the malignant stem cells,
while sparing normal stem cells, thus decreasing systemic toxicity and long term side
effects. In order to develop new therapies that will target LSCs directly, LSCs in different
populations of ALL must first be identified and characterized. Due to the inability to
accurately identify LSCs, currently no such treatment has been achieved (7). Therefore,
treatments continue to target all cancer cells as well as normal tissues and cells. However,
6
if these rare cancer stem cells can be specifically targeted and eliminated, then treatment
can be more effective and will prevent metastasis and lead to tumor regression.
Previous studies have reported human B cell acute lymphoblastic leukemia cell
lines to have a high expression level of the surface glycoprotein CD9, although it is not
solely specific to leukemia cells (8). CD9 is a transmembrane surface protein that plays a
role in different signal transduction pathways including cell development, activation,
growth and motility. Although not specific, CD9 may be able to be used to isolate LSCs
(11). Dr. Noriko Satake has previously tested primary human ALL samples for CD9
expression and discovered they in fact express this marker, although at differing levels. It
remains to be determined as to which population of CD9 expressing cells corresponds to
LSCs.
Unfortunately, no single unique cell surface marker has been identified for LSCs
in ALL, and cells sharing the same markers cannot be easily separated using a separation
technique such as flow cytometry. However, expression differences can be utilized to
separate different populations when their levels are significantly different. In order to
efficiently separate LSCs, unique markers or properties need to be identified.
Unfortunately, to screen even just one cell surface marker and evaluate its candidacy as a
cancer stem cell marker is extremely time consuming and can take years to demonstrate
the cancer initiating properties of these cells over multiple generations, which involves
serial transplantation in model organisms. Since prior studies have demonstrated high
levels of CD9 expression in potential LSCs, this study will attempt to separate putative
7
LSCs based on this criteria and compare them to cell populations with low or no
expression levels.
In addition to analyzing surface markers, intrinsic cellular markers can be used to
categorize different cell types. Raman Spectroscopy is a laser-based technique to
determine the intrinsic molecular signatures by analyzing internal rotational and
vibrational changes of molecules within the cell resulting in a unique Raman signature.
Raman spectroscopy studies by James Chan and colleagues at the Center for
Biophotonics Science and Technology (CBST) have shown that different cell types have
unique Raman molecular signatures (12, 13). Using these signatures, blood cells,
hematopoietic stem cells and human embryonic stem cells can be distinguished from one
another. Previously, primary ALL samples have been analyzed and compared to CD34
positive hematopoietic stem cells, and determined they too have distinctive Raman
signatures (12, 13). The different profiles can potentially be evaluated to add another
selection criteria to identify and characterize these different cell populations.
Once a specific marker for LSCs can be identified, it will be possible to target
only that cell population, sparing normal tissues and cells. In order to target cell surface
markers, the one-bead one-compound (OBOC) combinatorial library method developed
by Dr. Kit Lam’s research group can be utilized. This technique uses a bead covered with
a synthesized peptide that was randomly generated so as to create a library of different
beads that can be used as a probe to target specific cellular markers. Therefore, target
cells that do bind to particular peptide covered beads can be separated and the peptides
identified by sequencing.
8
Dr. Kit Lam and colleagues have also developed nanocarriers made of
polyethylene glycol (PEG), lysine and oligocholic acid polymers (together called
telodendrimers) that can self-assemble under aqueous conditions to form core-shell
structures that can carry drugs in their hydrophobic core (Figure1) (9). In addition, it has
been demonstrated that drug- loaded nanoparticles (NPs) can be taken up by solid tumor
xenografts (9). Recently, Lam and colleagues have developed a disulfide-based selfassembling cross-linker system so that the NP can be further stabilized to avoid
premature release of the loaded drugs during circulation (9). This will ensure that a toxic
drug or other biomolecules will be released inside or in close proximity to the target cell.
This direct targeting can only be achieved once a specific ligand is identified. This
specific ligand can then be used to target leukemia stem cells as well as all tumor cells
since they will share the same surface marker. For example, Dr. Lam has shown that a
short amino acid sequence, called LLP2A, is a ligand against activated α4β1 integrin.
This has been shown to bind to T-cell and B-cell lymphoma with high specificity in a
xenograft model (9). Preliminary data indicated 7 out of 7 ALL samples from children
express activated α4β1 integrin, although at different levels. This integrin may be used
for targeting leukemia cells but would not be considered a good marker for leukemia
stem cells as it is not specific to acute lymphoblastic leukemia.
These seven previously tested primary ALL patient samples also showed strong
binding to LLP2A. Therefore, LLP2A or related analogues can be tested to determine if
they can be used as a vehicle to deliver chemotherapeutic-loaded nanoparticles to
leukemia cells and possibly the LSCs. To achieve this, nanoformulations of the most
9
Figure 1. Leukemia specific nanoparticle. Schematic of telodendrimer nanoparticle
used in targeted delivery therapies, consisting of a drug loaded hydrophobic core
(reproduced with permission from Peng L, Liu R, Andrei M, Xiao W, Lam KS. In
vivo optical imaging of human lymphoma xenograft using a library-derived
peptidomimetic against alpha4beta1 integrin. Molecular Cancer Therapy. 2008; 7 (2):
432-37).
10
commonly used chemotherapy drugs for childhood ALL (DAUN, VCR and VP6) will
first be developed at higher doses than clinically used. Then NPs can be decorated with
LLP2A or related analogues for targeting leukemia cells. This specific targeting has the
potential to reduce toxicities to non-leukemic cells and tissues, while exclusively killing
leukemia cells including leukemia stem cells.
Although LLP2A also binds to hematopoietic stem cells, preliminary data shows
it has a much weaker affinity than binding to potential LSCs. Moreover, to test for
greater specificity of binding to LSCs, LLP2A related OBOC combinatorial libraries will
be screened with LSCs candidates isolated from ALL samples in order to optimize
exclusive targeting. This drug-loaded LLP2A vehicle targeted to LSCs will be tested
using an immunodeficient mouse animal model.
In the past, researchers have used leukemia cell lines since primary human
leukemia cells have not been successfully cultured in vitro. However, a more useful
experimental model is an animal model that can be used for primary leukemia
engraftment and serial transplantations, as well as testing targeted nanoparticle therapies.
An excellent model is the non-obese diabetic/severe combined
immunodeficiency/Interleukin 2 receptor gamma chain knockout mice
(NOD/SCID/IL2Rγ null). To date the NOD/SCID/IL2R γ null (NSG) mouse model is
one of the most immunodeficient strains, lacking mature T cells, B cells, and natural
killer (NK) cells (14).
11
Due to the combined immunodeficiencies of all three strains, NSG mice are able
to efficiently engraft human cells, including human primary leukemia samples.
Successful engraftment and serial transplantation of primary leukemia cells has been
achieved with a traditional NOD/SCID mouse model. However, it has been shown that
the use of the more sensitive new mouse strain, NOD/SCID/IL2R γ null (NSG), and the
intra-bone marrow injection of cells result in a greater efficiency of leukemia cell
engraftment (14).
With the use of this mouse model and intra bone marrow injections, we will test
LSC candidates to determine their leukemia initiating potential. As previously stated,
high expression levels of CD9 are thought to correspond to leukemia stem cells.
Therefore, it is our goal to determine if this will be a good cell surface marker to identify
LSCs in childhood ALL. In order to achieve this goal, primary patient samples will be
collected and sorted based on the level of CD9 expression. These cell populations will
then be transplanted into our NSG immunodeficient mouse model to determine their
leukemia initiating capabilities. These sorted cells will also be analyzed by Raman
spectroscopy for further characterization, to determine if cells expressing high levels of
CD9 have distinguishable Raman signatures compared to cells with low CD9 expression.
Next, we aim to identify a leukemia specific ligand by screening LLP2A-related OBOC
libraries. Ligands identified by bead screening will be synthesized for future testing of
nanoparticle drug delivery to leukemia cells. This direct targeting of leukemia cells,
including leukemia stem cells, via peptide-covered nanoparticles should provide an
12
excellent starting point for the development of novel cancer therapies that will decrease
cytotoxic effects and increase survival rates in these young patients.
13
MATERIALS AND METHODS
Precursor B Cell Lines
The REH and JM1 leukemia cell lines, which were initially derived from children with
precursor-B ALL, were purchased from the American Tissue Culture Collection
(Manassas, VA, USA). The REH line was cultured in RPMI 1640 medium containing
with 10% fetal bovine serum. The media was changed every two to three days. The
freezing media used was 95% FBS and 5% DMSO. The JM1 line was cultured in
Iscove's Modified Dulbecco's Medium containing 0.05 mM β-mercaptoethanol and 10%
FBS. Media was replaced two to three times per week. The freeze media used was 95%
culture medium and 5% DMSO.
Flow Cytometry/Cell Sorting & Transplantation/Engraftment
Mononuclear blood cells were previously sorted based on their expression of cell surface
markers using flow cytometry (by Astra Chang and Noriko Satake). Leukemia stem cell
candidates were sorted based on their positive CD9 expression, then analyzed by Raman
spectroscopy (by James Chan at CBST). Both CD9+ and CD9- cells were sorted and
transplanted into NSG mice six to eight weeks of age via intratibial bone marrow
injection. Normal hematopoietic stem cells were isolated using a CD34 microbead kit
from Miltenyi Biotec and used as a control for further experiments.
14
Monitoring Mice for Development of Leukemia
Injected mice were monitored on a daily basis and their degree of disease progression
was evaluated based on their physical signs. Rough fur, arched spine, crouching, white
ears and tail were all sign of sickness and the development of leukemia. Mice displaying
any of these signs were closely monitored until their state worsened. Mice showing signs
of disease were also shaved on their left side and splenomegaly was observed through the
skin.
Harvesting Murine Cells
Upon development of the disease, the cells were harvested from the spleen and bone
marrow (and any other tumors that may have developed). Mice were euthanized using
CO2, followed by cervical dislocation. All dissections and cell harvests took place inside
a biosafety cabinet. Spleens were mechanically minced and mouse red blood cell lysis
buffer was used to only collect the white blood cells. Single cell suspensions were
obtained using a 70 μm nylon mesh cell strainer, then washed and resuspended in PBS.
White blood cells from the tibia and femur were flushed out using a 27 ½ gauge syringe
and suspended in PBS. Any tumors collected were mechanically minced in PBS and the
free cells were collected. All cells were counted and frozen in 90% FBS and 10% DMSO
(if not used immediately).
Primary patient samples
Primary ALL samples were obtained from the University of California, Davis Medical
15
Center. Patient samples were washed in PBS and the mononuclear blood cells were
collected by ficol separation using 2500 rpm for 30 minutes. Mononuclear blood cells
were washed in PBS, cells were counted and then re-suspended for freezing (if not used
immediately) in 90% FBS and 10% DMSO.
Solid phase synthesis of random libraries and biotinylated peptides
Random libraries and LLP2A-related libraries used for LSC bead screening were
created following the same basic method of making biotinylated peptides. However,
instead of coupling one amino acid at a time, a mixture of amino acids were used during
each coupling for random libraries. For LLP2A-related libraries, amino acids that had
similar qualities to those used for LLP2A were used at random. Using a mixture of amino
acids ensures random coupling and provides many combinations in one library. Figure 2
shows a diagram of LLP2A synthesis.
To make each peptide Rink amide MBHA resin (0.5 g, 0.325 mmol, loading 0.65
mmol/g, GL Biochem, Shanghai, China) was swollen in DMF for 3 h before Fmocdeprotection with 20% 4-methylpiperidine in DMF twice (5 min, 15 min). The beads
were washed with DMF (310 mL), MeOH (310 mL) and DMF (310 mL). A Kaiser
test was performed to determine if free amine groups were present (dark blue color).
Fmoc-Lys(Biotin) ( 0.580 g, 0.975 mmol) was dissolved in a solution of HOBt (0.149 g,
0.975 mmol) and DIC (152 L, 0.975 mmol) in NMP (8 mL), and was then added into
the beads. The coupling was carried out at room temperature overnight. Kaiser test were
subsequently performed to determine that no free amine groups were present (yellow
16
1) 20% Piperidine
2) Fmoc-Lys(Biotin), HOBt, DIC
3) 20% Piperidine
H2 N
FmocNH
Rink amide resin
1) Fmoc-Linker, HOBt, DIC
2) 20% Piperidine
3) Fmoc-Linker, HOBt, DIC
O
4) 20% Piperidine
H
Linker
N
H2 N
NH
Linker
H
S
NH
HN
H N O
H
O
COOtBu
O
NH
HN
O
COOtBu
O
H
N
H2 N
N
H
O
H
N
Linker
O
O
Couple Fmoc-Lys(Dde)
NH
Linker
H
NH
S
HN
H N
H
O
1) 20% Piperidine
O
O
O
O
H
N
N
H
N
H
O
O
H
N
Linker
NH
2) Couple
HO
H N
H
O
H
N
H
N
O
N
H
O
H
N
O
O
H
N
Linker
Linker
N
H
O
H
NH
S
H N
H
O
H2 N
O
NH2
O
HN
O
O
NH
N
N
H
NH
S
HN
DdeNH
O
O
1) 2% NH2NH2
O
Linker
H
NH
H N
H
O
H
N
O
S
HN
OH
H
N
NH
Linker
COOH
Cleave and purify
O
H
N
Linker
N
H
O
COOtBu
O
H
N
H N
H
O
2) Couple
H
N
H
N
N
H
H
NH
S
O
DdeNH
H
N
H
N
Fmoc-NH
1) Couple Fmoc-Ach
2) Couple Fmoc-Aad(tBu)
O
H
N
Biotinylated 2A
O
COOH
Linker
O
Figure 2. Diagram of LLP2A synthesis. Chemical steps in the synthesis of biotinylated
LLP2A ligand. The Rink amide resin is coupled with Lys-biotin, then two linkers,
followed by Ach, Ada, Lys and a small molecule. After coupling the bead resin is cleaved
and the biotinylated ligand is purified. For other ligand synthesis other amino acids are
coupled in the same fashion.
17
color), indicating complete coupling. After filtration, the beads were washed with DMF
(310 mL), MeOH (310 mL) and DMF (310 mL), respectively, three times each. After
removal of Fmoc, the beads were then subjected to two cycles of coupling and
deprotection of Fmoc-PEG linker. Following the Kaiser test and Fmoc deprotection, the
first amino acid, Fmoc-X1-OH (0.365 g, 0.975 mmol) was dissolved in a solution of
HOBt (0.149 g, 0.975 mmol) and DIC (152 L, 0.975 mmol) in DMF, and was then
added to the beads. The coupling was carried out at room temperature for 2 h. After
filtration, the beads were washed with DMF (310 mL), MeOH (310 mL), and DMF
(310 mL), respectively, three times each. The Fmoc deprotection group was removed
with 20% 4-methylpiperidine twice (5 min, 15 min). After washing with DMF, MeOH,
and DMF respectively, the beads were then subjected to additional coupling and
deprotection cycles stepwise with Fmoc-X2 and Fmoc-X3 in the same manner as
described above. After removal of Fmoc, a solution of 4-[(N’-2-methylphenyl)
ureido]phenylacetic acid (0.923 g, 3.25 mmol), HOBt (0.498 g, 3.25 mmol) and DIC (509
L, 3.25 mmol) in DMF was added to the beads. The reaction was conducted at room
temperature overnight. The beads were washed with DMF (310 mL), methanol (310
mL), and DMF (310 mL). Kaiser tests were subsequently performed to confirm the
absence of amine groups. The beads were then washed with DMF (5 x 5 mL), MeOH (3
x 5 mL) and DCM (3 x 5 mL). Afterwards, the beads were dried under a vacuum for 1 h
before adding a cleavage mixture of 95% TFA: 2.5% water: 2.5% TIS. The peptide was
then cleaved from the bead at room temperature for 2 h. The liquid was collected and
18
concentrated by evaporation of TFA solution. The crude product was precipitated with
diethyl ether and purified using preparative RP-HPLC. The fractions collected were then
analyzed by MALDI-TOF mass spectroscopy (preformed by Eddie Sanchez from Dr.
Lam’s laboratory).
Peptide Bead Screening
Patient primary leukemia samples and cells harvested from leukemic mouse bone marrow
were screened against 4 LLP2A related random libraries (WHO4, WHO5, LDO1A and
LDO2A) , and LLP2A as a control. One million cells were added to each well of a 6 well
plate in a total volume of 1ml of RPMI 1640 phenol-red free. Each bead library was
suspended in 1mL 70% ethanol. The ethanol was filtered out and the bead libraries were
washed with water (3x1 mL), PBS (3x1 mL), and then resuspended in 500uL PBS.
100uL of the bead mixture was added to one well. PBS was filtered and the beads were
stored in 1mL 70% ethanol. The cells were place in a shaking incubator for 10 minutes.
Beads with over 70% binding (or those showing the most) were picked and subsequently
washed in water (1 minute), guanidine (20 minutes), water (2x1 minute), and PBS (2x1
minute). Approximately 10-15 beads were selected for each sample. These selected beads
were then screened against normal cells and beads with no binding were selected and
washed. The peptides on these beads were then sequenced by Edman degradation.
19
RESULTS
Primary pediatric acute lymphoblastic leukemia samples were received from the
University of California, Davis Medical Center for this study. A total of 62 samples were
collected and named in the order which they were acquired, 1 through 62. Each sample
was ficoll separated in order to collect the mononuclear blood cells (MNBCs), which
contain all of the leukemia cells including leukemia stem cells (LSCs). This separated
layer containing the MNBCs was collected, washed and the total number of cells was
counted for each sample. Each sample gave a total cell count ranging from 107 to 1010
cells. Most of these were frozen and stored in liquid nitrogen for future use. However,
some fresh cells were kept for immediate analysis. Also, several healthy bone marrow
samples and normal blood cells were obtained from the medical center for their use as
controls. These bone marrow samples were ficoll separated to collect the MNBCs. This
layer of MNBCs contains hematopoietic stem cells, which were isolated using a CD34+
microbead kit.
Each primary leukemia sample received was injected into NOD/SCID/IL2R γ null
(NSG) mice via intra-tibial injections, to determine which samples successfully engraft
into our mouse model. Monitoring of these mice was conducted on a daily basis in order
to determine if leukemia symptoms developed. Figure 3 shows symptomatic mice just
prior to necropsy. Symptoms indicating disease include: slowed movement, hunched
posture, shaking, white tail and ears, and enlarged spleen that is visible through the skin.
From the samples that had successful leukemia engraftment, three pre-B acute
20
Figure 3. NSG symptoms of leukemia prior to necropsy. NSG mice injected with
leukemia sample 44 showed signs of illness prior to necropsy. Arched spine indicates
discomfort and white ears and a pale tail indicates increased levels of circulating white
blood cells.
21
lymphoblastic leukemia samples were selected for further evaluation of leukemia stem
cells. These samples, 13, 41, and 46, were chosen based on repeated successful
transplantation and engraftment.
After sample 13, 41, and 46 were elected for further analysis, the expression of
CD9 was examined to assess whether it would be a good cell surface marker for LSCs.
Each sample was sorted by flow cytometry based on their level of CD9 expression. Flow
cytometry data in Figure 4 shows that pre-B leukemia cells have varying levels of CD9
expression. Therefore, differences in expression levels were used to separate cells into
two populations. Cells with high expression levels of CD9 were considered the CD9
positive group and our LSC candidate, and cells with no or extremely low levels of CD9
were the CD9 negative group.
The CD9 positive and negative cells from each sample was then analyzed by
Raman spectroscopy to determine if they had distinguishable intracellular properties that
could be used to improve characterization of LSCs. It was previously established that
CD9 sorted cells showed a different pattern of peaks and vibrational changes from
normal hematopoietic stem cells (data not shown). Therefore, Raman signatures for each
group were obtained and analyzed by James Chan at CBST, to examine how unique these
signatures were, as shown in Figure 5. The Raman signatures of CD9 positive and
negative cells were very similar, however there were some small difference in peaks
between the two groups.
22
Figure 4. CD9 sorting of preB ALL. The pre-B ALL cells were sorted by flow cytometry
based on the level of CD9 expression. High expression levels were selected as CD9
positive cells (LSC candidate) and low expression levels were selected for CD9 negative
cells.
23
Figure 5. Raman signatures of CD9 sorted cells. CD9 positive (blue) and CD9 negative
(green) cells were analyzed by Raman Spectroscopy. Differences in intracellular
properties are detected by vibrational changes. Raman signature are composed of Raman
shifts (x-axis) and their intensity (y-axis).
24
After the intracellular properties were examined, sorted cells were then analyzed
by transplantation into our mouse model in order to determine whether the CD9 positive
cells (candidate LSCs) could initiate leukemia. To achieve this, CD9 positive and CD9
negative cell populations from the three samples were injected into six week old NSG
mice via intra-tibial bone marrow injections, and their physical conditions were closely
examined for signs of leukemia. Each sample was injected into different numbers of
mice due to limitations on the quantity of the primary samples we had to work with, as
we wanted to make sure there was enough of the identical sample for future studies. To
begin with, five groups of mice (each group had four to five mice) were injected with
either CD9 positive or CD9 negative sorted sample thirteen at different times (Table 1).
In total, there were eleven CD9 positive mice and ten CD9 negative mice for sample 13.
Next, positive and negative sorted cells of sample 41 were injected into three groups of
NSG mice, with a total of seven CD9 positive and five CD9 negative mice. And lastly,
one group of NSG mice was injected with CD9 positive and negative sorted ALL cells
from sample 46, three positive and one negative.
After monitoring the health status of the injected mice daily, mice began to
display the symptoms of leukemia (signs of physical illness or discomfort as described
previously) as early as one month after injection. Necropsies were preformed on the
mice with symptoms to look for spleen enlargement and excessive amounts of
lymphoblasts. Those that did not display symptoms of illness were kept for up to ten
months until necropsies were preformed. Table 1 shows one mouse injected with CD9
25
Table 1. Leukemia injected NSG mice and outcomes. Multiple groups of mice were
injected with CD9+ sorted and CD9- cells from three different primary patient samples
(sample number 13, 41, and 46).
SAMPLE
GROUP
Group 1
Group 2
Group 3
13
NUMBER OF
MICE
INJECTED CELL
NUMBER (x106)
3 positive
2 negative
2 positive
2 negative
2 positive
2 negative
0.3
0.3
1.5
1.0
0.6
0.6
2 positive
>0.2
2 negative
>0.2
2 positive
2 negative
>0.2
>0.2
3 positive
0.7
1 negative
0.7
2 positive
2 negative
2 positive
2 negative
1.7
1.7
5.0
5.0
1 leukemic, 1 not,
1 dead at 1 month
Died upon
injection
All alive at 9
months
All alive at 8
months
3 positive
1 negative
1.9
1.5
All leukemic at
2.5 months
Group 4
Group 5
Group 1
41
Group 2
Group 3
46
Group 4
OUTCOME
All alive at 10
months
All alive at 4
months
All alive at 7
months
1 leukemic, 1 not
at 6 months
1 leukemic, 1
found dead at 6
months
All alive at 8
months
26
negative sample 41 died upon injection, and one CD 9 negative sample 13 and one CD9
positive sample 46 mouse were found dead at six months and one month respectively.
These three mice were discarded from any further data analysis, as it was not possible to
determine if they developed leukemia. All remaining mice were monitored for the
development of leukemic symptoms.
When examining the outcome of all the mice injected with CD9 positive cells, a
total of five out of twenty mice (25%) were determined to have leukemia upon necropsy.
Figure 5 shows the first visible evidence of leukemia development in these mice. A
spleen taken from a leukemic NSG mouse compared to a normal mouse spleen shows
that the diseased spleen is pale and enlarged due to excessive amounts of white blood
cells (Figure 6a). Leukemia was further confirmed by white bone marrow and blood
smears showing excessive lymphoblasts that had the same morphology as the initial
human leukemia bone marrow cells (Figure 6b and Figure 7). Continuing with the
outcome of the remaining mice, after displaying signs of discomfort, two of the CD9
positive injected mice were determined to not have leukemia. And lastly, the remaining
13 out of 20 mice from the CD9 positive group were still alive at the last day of
inspection, which was many months after the normal time period when leukemia
develops. Therefore, these 13 mice were concluded to not be leukemic.
The results from the CD9 negative groups were similar to the outcomes of the
CD9 positive group. Two out of fourteen (14%) CD9 negative injected mice were
confirmed to have leukemia upon necropsy which is similar to that found for the CD9
27
Figure 6. Evidence of preB ALL engraftment in NSG mouse. (A) The top spleen is from
a leukemic mouse and shows splenomegaly, measuring 3 cm in length. The bottom
spleen is from a healthy mouse and is 1 cm in length. (B) Top is a tibia from a leukemic
NSG mouse showing white bone marrow compared to the normal pink bone marrow
below.
28
Figure 7. Leukemia cells harvested from NSG mouse. Engraftment of Sample 13 Pre B
ALL in NSG mouse bone marrow smear using Wright-Giemsa staining (1000x
magnification), shows the same morphology as the primary human samples (data not
shown).
29
positive group (5 out of 20; 25%). The remaining twelve mice from the CD9 negative
group were still alive at the last day of inspection and deduced to not be leukemic. There
was no significant difference in outcomes between the CD9 positive and CD9 negative
groups, as calculated using a contingency table and statistical significance test using a p
value of 0.5. Table 1 summarizes the results.
Leukemia cells from the mice that developed ALL in both the CD9 positive and
CD9 negative groups were collected for further analysis. Single cell suspensions were
made from the harvested spleens and bone marrow. The majority of these cells were
frozen for future use and/or serial transplantations to determine if they maintained the
ability to initiate leukemia with the same morphology.
Also, fresh cells from leukemic mouse bone marrow cells were kept and screened
against four LLP2A related peptide bead libraries. Bone marrow cells were used since
they have a higher fraction of white blood cells as compared to harvested spleens. In
addition to murine leukemia cells, all human primary patient samples were screened
against the same libraries at the time they were received. For peptide screening, one
million cells were incubated separately with 200 µl of the WHO4 and WHO5 peptide
libraries (roughly 1000 beads) for ten minutes. After incubation, the beads were inspected
to examine the amount of cells bound. If no significant binding occurred within this
time frame, the cells were placed in a shaking incubator for an additional ten minutes to
promote cell-bead interaction. Once binding was observed, ten to fifteen beads from each
leukemia sample were selected that had greater than 75% coverage with cells bound and
30
then washed to remove these cells (Figure 8). These beads were then incubated with
normal human bone marrow and CD34+ hematopoietic stem cells to determine if they are
were specific to leukemic cells. Beads that had no binding to normal healthy cells were
then selected and washed to strip off the remaining cells. The peptides covering these
chosen beads were cleaved off and then sequenced by Edman degradation. From the
hundreds of beads picked that were screened with the primary leukemia samples, 33
different peptide sequences were identified. Out of the 33 sequences, 11 of the most
common were chosen for peptide synthesis and continued experimentation for possible
use in targeted nanoparticle therapies (Table 2).
Initially, four sequences were individually synthesized into biotinylated ligands
that could be used for future assays and leukemia sample screenings to test their binding
affinity by flow cytometry. Figure 9 shows the general structure of these ligands, starting
with lysine-biotin attached to two PEG linkers, then followed by the amino acid
sequences and a small molecule. These first four peptides that were synthesized were:
LLS12, LLS14, LLS14m, and LLS 33 (from Table 2). After chemical synthesis, these
four ligands were HPLC purified into separate fractions. Each peak in the HPLC
chromatogram signifies individual peptides-PEG-biotin conjugate with different
molecular structure. These peaks were collected and individually analyzed by MALDI
mass spectroscopy. Analysis of the MS data showed that these four peptides were not
pure or synthesized correctly due to incomplete coupling, as the weights did not match
the theoretical weights of the full peptide (data not shown).
31
Figure 8. Bead screening of leukemia cells. Primary ALL cells and leukemia cells
harvested from NSG mice were separately incubated with two LLP2A-focused libraries.
The beads with the arrow pointing to it has greater than 75% of its surface area bound by
cells demonstrating a positive reaction (100x magnification).
32
Table 2. Amino acid sequences of identified peptides. Beads with more than 75% binding
were processed and sequenced. From these beads we have identified 33 analogues of
LLP2A using three fresh preB ALL samples from screening two LLP2A-focused
libraries. Eleven of the most common sequences were chosen for peptide synthesis.
Amino acid sequence is shown, with X1 being the first amino acid to be coupled and X3
being the last.
Peptide
Amino Acid Position
X2
E
Ana
X3
Cpa
LLS5
COOH
H2N
H2N
COOH
H2N
X1
COOH
COOH
HoCit
LLS6
H 2N
Bmc
H2N
COOH
NHCONH2
S
HoCit
LLS8
H 2N
H2N
COOH
LLS12
H2N
H2N
COOH
I
OH
COOH
E
COOH
COOH
Tyr(di-I)
COOH
S
Nle
H2N
COOH
Bmc
NHCONH2
H2N
D-Phe
COOH
I
Nle
COOH
H2N
COOH
COOH
LLS13
HoCit
Bmc
H 2N
H2N
COOH
NHCONH2
LLS14
S
HoCit
Bmc
H 2N
H2N
COOH
NHCONH2
LLS14m
Bmc
H2N
H2N
COOH
LLS16
HN
COOH
COOH
Cl
Ach
H2N
COOH
COOH
Ach
COOH
H2N
COOH
N
S
O
N-Me-Leu
H2N
COOH
COOH
S
Lys(A38)
H
N
Phe(3-Cl)
COOH
COOH
E
H2N
D-Ala
COOH
COOH
H 2N
COOH
33
Table 2. Continued
No.
LLS30
X3
N-Me Leu
HN
COOH
Amino Acid Position
X2
Bmc
Acpc
H2N
COOH
S
Aoc
LLS33
NH2
H2N
COOH
COOH
D
COOH
H2N
X1
Nle
H2N
COOH
COOH
COOH
HoLeu
LLS35
H2N
COOH
Bmc
H2N
D-Leu
COOH
S
COOH
H2N
COOH
34
H
N
O
N
H
O
N
H
O
O
X3 X2X1
N
H
O
O
O
HN
O
O
O
O
O
Ligand
N
H
O
O
O
NH2
N
H
S
H
H
HN
NH
O
Linker-linker-Lys(Biotin)
Figure 9. Schematic of biotinylated ligand. This diagram is of the general chemical
structure of all the biotinylated ligands that were synthesized. Biotin is attached to
Lysine, which is linked to two PEG linkers to aid in the hydrophobicity of the peptide.
Next, X1, X2, and X3 of each ligand are specified in Table 2, were coupled to the linkers,
followed by a small molecule.
35
However, a second round of peptide synthesis was conducted using new resin
beads that were already linked to lysine-biotin. All 11 peptides plus LLP2A for a control
were synthesized simultaneously. Once synthesis was complete, each peptide sample was
fractionated by HPLC. Figure 10 shows a representative HPLC chromatogram displaying
the different peaks that were separated and collected. Each fraction was analyzed for their
purity using MALDI mass spectroscopy. Figure 11 is MALDI mass spectroscopy data
from the same peptide synthesis in Figure 10 (the remaining peptide data is not shown).
A total of 12 biotinylated ligands were chemically synthesized and purified. The
chemical structure and formulas are listed in Figure 12. These peptides will be used in
future studies that can take advantage of the biotin label attached to these leukemia
specific ligands, to test each ligands specificity and binding affinity to the original
leukemia samples through flow cytometry.
Since primary patient samples and NSG harvested cells are precious and hard to
come by, leukemia cells lines were pursued for initial experimentation using the
synthesized peptide conjugates. Therefore, two lymphoblast cell lines (JM1 and Reh)
were purchased from ATCC and expanded for future in vitro experiments. These
suspension cell lines were propagated and then divided into multiple cyrovials for liquid
nitrogen preservation. The cell line Reh was extremely proliferative resulting in a large
expansion of cells. Although JM1 was not as fast growing, expansion was also achieved.
Further studies with these cell lines will need to be continued since time ran out for the
internship project.
36
Figure 10. HPLC of biotinylated ligand LLS14. HPLC purification of synthesized peptide
LLS14 shows two major peaks, starting after 25 minutes of running the HPLC. These two
peaks were separately collected.
37
Figure 11. Identification of pure ligand in HPLC fractions by MALDI MS. MALDI mass
spectroscopy was preformed on all HPLC fractions collected for each synthesized
biotinylated ligand. The third fraction (F3) of synthesized peptide LLS14, has two major
peaks at a mass of 1646 and 1662 m/z containing the pure ligand.
38
Table 3. Structure and formula of synthesized peptides. The chemical formulas, mass and
molecular weight of each ligand-linker-biotin conjugate that was chemically synthesized
is provided. Structures were drawn using ChemBioDraw Ultra 11.0 software.
LLS5-dPEG-Biotin
LLS6-dPEG-Biotin
COOH
H
N
O
N
H
N
H
S
O
H
N
N
H
O
O
N
H
O
H
N
O
O
O
O
HN
O
O
O
O
O
NH2
N
H
O
O
O
O
NH2
S
N
H
H
H
HN
Chemical Formula: C75H114N14O21S2
Exact Mass: 1610.7724
Molecular Weight: 1611.9189
NH
O
LLS8-dPEG-Biotin
COOH
H
N
O
N
H
N
H
O
S
O
H
N
N
H
O
H
N
O
O
N
H
O
O
NH2
OH
I
O
O
I
HN
O
O
O
O
N
H
O
O
O
O
NH2
N
H
S
H
H
HN
Chemical Formula: C75H112I 2N14O22S2
Exact Mass: 1878.5606
Molecular Weight: 1879.7113
NH
O
39
Table 3. Continued.
LLS12-dPEG-Biotin
LLS13-dPEG-Biotin
COOH
H
N
O
N
H
N
H
S
O
H
N
N
H
O
N
H
O
H
N
O
O
O
O
O
O
Cl
HN
O
O
O
O
NH2
N
H
O
O
O
O
NH2
S
N
H
H
H
HN
Chemical Formula: C75H113ClN14O21S2
Exact Mass: 1644.7335
Molecular Weight: 1646.3639
NH
O
LLS14-dPEg-Biotin
COOH
H
N
O
N
H
N
H
O
S
O
H
N
N
H
O
H
N
O
O
O
N
H
O
O
O
HN
O
N
H
O
O
O
NH2
O
O
NH2
N
H
S
H
H
HN
Chemical Formula: C73H116N14O21S2
Exact Mass: 1588.7881
Molecular Weight: 1589.9133
O
O
NH
O
40
Table 3. Continued.
LLS14m-dPEG-Biotin
COOH
H
N
O
N
H
N
H
S
O
N
H
O
N
H
O
H
N
O
O
H
N
O
O
O
O
N
H
O
O
HN
O
O
O
O
O
O
NH2
S
N
H
H
H
HN
N
NH
O
Chemical Formula: C80H120N 14O21S2
Exact Mass: 1676.8194
Molecular Weight: 1678.0200
LLS16-dPEG-Biotin
LLS30-dPEG-Biotin
COOH
S
O
N
O
N
H
N
H
O
N
H
H
N
O
O
O
N
H
O
O
O
HN
O
O
O
O
N
H
O
O
O
O
NH2
N
H
S
H
H
HN
Chemical Formula: C70H110N12O20S2
Exact Mass: 1502.7401
Molecular Weight: 1503.8208
NH
O
41
Table 3. Continued.
LLS33-dPEG-Biotin
LLS35-dPEG-Biotin
H
N
O
N
H
N
H
COOH
O
H
N
O
N
H
O
O
O
N
H
O
O
O
HN
O
O
O
O
N
H
O
O
O
O
NH2
S
N
H
H
H
HN
Chemical Formula: C71H114N12O 20S
Exact Mass: 1486.7993
Molecular Weight: 1487.7983
NH
O
LLP2A-dPEG-Biotin
COOH
H
N
O
N
H
N
H
O
O
N
H
N
H
O
H
N
O
O
H
N
O
O
O
HN
O
O
O
O
O
N
H
O
O
O
O
NH2
N
Chemical Formula: C81H122N14O 21S
Exact Mass: 1658.8630
Molecular Weight: 1659.9816
N
H
S
H
H
HN
NH
O
42
DISCUSSION
Precursor B acute lymphoblastic leukemia (ALL) is the most common form of
childhood cancer (1). Recently, there has been a large effort in identifying cancer stem
cells for many different neoplasias, however the leukemia stem cell for ALL has not been
identified or characterized. Once leukemia stem cells characteristics and properties are
known, direct targeting of these rare cell populations can be achieved using novel cellular
therapies. In order to study leukemia, the first step is establishing a model organism that
will allow for the engraftment of human leukemia cells.
Previous studies have shown that primary leukemia samples are not successfully
grown in vitro, resulting in prompt apoptosis (15, 16). For this reason, leukemia research
is primarily conducted using immunodeficient mouse models. It has been shown that
intravenous injection of human leukemia cells into the classic NOD/SCID mouse results
in successful engraftment, as well as, cell survival, proliferation, and invasion of the bone
marrow and spleen (15, 16). However, other studies, as well as from our research, have
shown that the NOD/SCID/IL2R γ null (NSG) mouse strain allows for greater cell
engraftment and a shorter time to leukemia development, without radiation. The NSG
strain proves to be a more immunodeficient mouse model due to an absolute lack of
natural killer cells, where as the classic NOD/SCID mouse still has low levels. In
addition to this more sensitive mouse model, we have shown that injection directly in to
the bone marrow (intratibial) of NSG mice provides enhanced human leukemia
engraftment. This is possibly due to the LSCs not having to home to their proper niche.
43
Many of the primary ALL samples that did engraft into NSG mice produced
terminal leukemia, in which human lymphoblasts invaded and took over mouse bone
marrow, blood, spleen, and other organs. The leukemia engraftment and proliferation was
shown to be similar to human leukemia, and the lymphoblast morphology retrieved from
the NSG mice were shown to have the same immunophenotype as the original primary
samples. Serial transplants of samples into this mouse model also generated leukemia that
was similar to the initial transplants as well as the original leukemia sample. This implies
great stability of the lymphoblasts and their capacity to initiate leukemia without having
to acquire additional mutations.
Because of the overall successful engraftment, proliferation and infiltration of
human leukemia cells, this highly immunodeficient mouse model has proven to be an
excellent in vivo model organism for leukemia research. This model provides a reliable
assay in order to study the basic biology of leukemia, new chemotherapeutic agents, drug
delivery and novel treatments. In addition to these areas of research, NSG mice can also
be utilized in order to study rare leukemia stem cells.
In hopes to identify a LSC for childhood pre-B ALL, we examined CD9 as a
possible cell surface marker to these rare cells. A previous study correlated CD9+ cells
with potential leukemia stem cells using B-ALL cell lines (8). Therefore, CD9 was
analyzed in three primary pre-B ALL samples to determine if this surface marker would
be a good identifier of LSCs. The three primary pre-B ALL samples were sorted based on
their level of CD9 expression by flow cytometry. Because cells showed varying levels of
expression, it was our hypothesis that only those populations of cells expressing CD9 at
44
high levels would be characteristic of LSC due to it’s involvement in cell development,
activation, growth and motility. Following intratibial injection of these sorted cells in
NSG mice, engraftment of human lymphoblast cells did occur and resulted in the
development of leukemia. However, there was no significant difference in the
development of leukemia from the CD9 positive and CD9 negative group. Furthermore,
the morphology of harvested leukemia cells from these diseased mice was shown to be
similar to the original sample. Although preliminary studies may have suggested that
CD9 was a potential marker for cancer stem cells in human B acute leukemia, it appears
as though CD9 is not a good marker in primary preB ALL samples from pediatric
patients.
The data from injected mice indicated that many of the groups did not develop
leukemia. This could possibly be due to improper engraftment of human leukemia cells,
or leukemia stem cells. It is possible that most of the cells within the sorted population
were not leukemia stem cells, or the lymphoblast cells could have lacked a necessary
recognition factor needed by the mouse immune system needed in order to engraft.
Failure to generate leukemia could also be due to a need for a specific human
microenvironments for these LSCs to grow. However, the specific dynamics affecting
human leukemia engraftment and proliferation were not the focus of this study. This
would require a larger number of mice and many more types of ALL to assess
engraftment questions. Our goal was to examine CD9 as a potential LSC marker in pre-B
ALL. The collected data indicates CD9 alone was not sufficient enough to identify LSCs
as determined by successful engraftments. Conceivably, additional markers may need to
45
first be identified, and then the possible combination of the two markers would enable the
sorting of an enriched LSC population for further study.
In addition to analyzing CD9 as a marker to distinguish ALL LSCs from other
cancerous cells, the intracellular properties of the CD9 sorted cells were analyzed by
Raman spectroscopy in hopes of finding unique characteristics of these sorted
populations. Raman analysis showed variable signatures for CD9 negative and positive
leukemia cells compared to CD34 positive cells from normal bone marrow. This suggests
that as cells differentiate through a more mature lineage, their intracellular signatures will
also change according to the differences in their molecule makeup. Therefore, progenitor
cells and leukemia stem cells should theoretically have different Raman spectroscopy
signatures compared to their progeny. Although, there may be different Raman signatures
between CD9 positive and negative cells in some of the preB ALL samples, there was no
single pattern of Raman signatures in preB ALL or the preB ALL CD9 positive sorted
cells. This suggests that childhood preB ALL is a heterogeneous group of cell types
leading to their disease phenotypes, and could possibly have many different LSCs in a
single population.
Because of the heterogeneity of ALL, it is possible that acute lymphoblastic
leukemia is not a hierarchical disease like acute mylogenous leukemia (where the cancer
stem cell has been identified). The hierarchical cancer stem cell model suggests that only
rare cancer stem cells have the ability for self-renewal and give rise to all other cells in
the cancer population. This model organizes the structure of human cancers in the same
fashion as the normal hematopoietic hierarchical lineage. In contrast to this model, our
46
data suggests it is possible that most or all of pre-B ALL cells can function as LSCs,
possessing the ability to cause tumorigenesis, proliferation, metastasis, and relapse. If this
is the case, human precursor B ALL would follow more of a stochastic cancer model, in
which all cancer cells have the capacity for self-renewal and can individually generate
cancer heterogeneity.
Unfortunately, if no LSCs can be identified for ALL, specific targeting will not be
possible. However, if all ALL cells function as LSCs and contribute to the progression of
the disease, treatment would have to target leukemia cells in general and not just a rare
subpopulation. Thus, it may be to one's advantage to adopt a more general approach to
target all leukemia cells include cancer stem cells.
As it turns out, the research performed in this study using the one-bead onecompound screening for ligands that bind to leukemia cells was a more general approach.
All of samples used in the screening process (primary leukemia patients and NSG
harvested leukemia cells) contained all the different cell types and were used to identify
ligands derived from a LLP2A-focused peptide libraries on beads that bound tightly to
leukemia cells. LLP2A is known to be a ligand against activated α4β1 integrin which
appears to be a good marker for leukemia cells. Thirty-three peptides from this library
were discovered and selected based on their high binding to unsorted leukemia cells and
low binding to normal blood cells and hematopoietic stem cells. Of these 33 peptide
sequences, eleven of the most common ligands were selected for synthesis, as well as
LLP2A as a control. All 12 peptides were chemically synthesized and linked to biotin
with the hopes of using them in further rounds of leukemia cell binding assays and
47
nanoparticle delivery treatments, however, the internship project time frame came to an
end.
Future studies are expected to focus on the use of these 12 synthesized peptides to
target acute lymphoblastic leukemia cells instead of the originally desired LSCs. These
synthesized biotinylated ligands will likely be initially tested in our propagated leukemia
cell lines, JM1 and Reh, and then in the primary patient leukemia samples to determine
whether they have a high affinity to childhood ALL. Cells can be analyzed by flow
cytometry to determine whether they bound the biotinylated peptides using streptavidin
conjugated to the fluorophore PE. . The ligands that show high affinity in vitro could also
be injected into NSG mice bearing leukemia cells. The relative affinity of the ligands to
the cells could also be tested by flow cytometry after leukemia cells were harvested from
ligand-injected NSG mice. Furthermore, because LLP2A has been shown to promote
endocytosis in lymphoma cells, these ligands could also be tested for their endocytotic
properties upon binding to leukemia cells.
After these ligands are tested, ones with high leukemia specificity and affinity to
preB ALL would be used to deliver chemotherapeutic drugs directly to leukemia cells.
Nanoparticles developed by Dr. Lam and colleagues, can carry nanoformulations of antileukemic drugs and can be decorated with these tested ligands for targeted drug delivery.
Not only can these nanoparticles be used for drug vehicles, they can also be loaded with
siRNA to knock-down gene overexpression in preB ALL cells. These nanotherapeutics
could be tested in the same NSG mouse model used in this initial study.
48
In summary, although CD9 did not prove to be a good marker for LSCs, the
ultimate goal was to develop nanoparticle-targeted therapies for ALL. This study
provides the platform for future analyses of leukemia-specific ligands that can potentially
be utilized in novel leukemia-targeted treatments. If successful, this targeted therapy has
the potential to overcome the dose limitations that current treatments have since it should
not be toxic to all other healthy cells.
49
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