Supplementary materials and methods
Cell culture and transfections
The pEF1/Cldn2 vector was constructed by ligating the full-length murine Cldn2 cDNA
(clone ID: 4223446; Open Biosystems, Huntsville, AL, USA) into a pEF1/V5-His
expression vector (Invitrogen, Burlington, ON, Canada) using 5’ EcoR1 and 3’ Not1
restriction enzyme sites. Pooled stable 4T1 or explant populations were generated by
transfection using Lipofectamine 2000 reagent (Invitrogen). Stable cell lines were
maintained under 1mg/ml G418 antibiotic selection.
Two independent shRNAs targeting Cldn2 or CLDN2 were designed using the same
protocol: Cldn2 shRNA KD1: 5’-CTCATACAGCCTGACTGGGTAT-3’; Cldn2 ShRNA
KD2: 5’-TGC GAT ATC TAC AGT ACC CTT T-3’; CLDN2 shRNA KD1: 5’-ACC
TCC CAA AGT CAA GAG TGA G-3’; CLDN2 ShRNA KD2: 5’-ATC ACC CAG TGT
GAC ATC TAT A-3’. Pooled stable populations were maintained under 1µg/ml
puromycin antibiotic selection.
RNA amplification, labeling and hybridization to Agilent microarrays
RNA was extracted from 4T1 parental and individual in vivo selected liver metastatic
sub-populations using RNeasy Mini Kits and QIAshredder columns (Qiagen,
Mississauga, ON, Canada). Purified total RNA (40 ng) was subjected to two consecutive
rounds of T7-based amplification using Amino Allyl MessageAmp II kits (Applied
Biosystems, Streetsville, ON, Canada) and the resulting aRNA was conjugated to Cy3
and Cy5 dyes (GE Healthcare Bio-sciences, Bair d’Urfe, QC, Canada). RNA
concentration and dye incorporation was measured using a UV-VIS spectrophotometer
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(Nanodrop ND-1000, Agilent Technologies, Wilmington, DE, USA). RNA quality was
assessed using a bioanalyser (Agilent Technologies). In parallel, the same labeling
procedure was utilized to amplify and label a universal mouse reference RNA
(Stratagene, La Jolla, CA, USA). Hybridization to 44K whole mouse genome microarray
gene expression chips (Agilent Technologies) was conducted following manufacturer’s
protocol (Agilent Technologies) and dye swaps (Cy3 and Cy5) were performed for RNA
amplified from each population. Microarray chips were then washed and immediately
scanned using a DNA Microarray Scanner (Model G2565BA, Agilent Technologies).
Gene expression analysis
Microarray data were feature extracted using Feature Extraction Software (v. 9.5.3.1)
available from Agilent, using the default variables. Outlier features on the arrays were
flagged by the same software package. Data preprocessing and normalization was
automated using the BIAS system (Finak et al., 2005). Raw feature intensities were
background corrected using the RMA background correction algorithm (Irizarry et al.,
2003a; Irizarry et al., 2003b) and the resulting expression estimates were converted to log
2 ratios. Within-array normalization was done using spatial and intensity-dependent loess
(Smyth and Speed, 2003). Median absolute deviation scale normalization was used to
normalize between arrays (Yang et al., 2001). The hierarchical clustering was done using
Ward's minimum variance method with a correlation distance metric. Differential
expression was performed using Linear Models for Microarray Analysis (Smyth, 2005).
If a gene is represented by several probes, only the probe with the largest interquartile
range is used. Probes that could not be mapped to any gene were ignored. A gene is
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considered differentially expressed if it displays a fold change greater than or equal to 4
and a Holm-adjusted P-value less than or equal to 0.05 between the two categories
(Holm, 1979).
RT-qPCR
Total RNA was extracted from the indicated cell populations using RNeasy Mini Kits
and QIAshredder columns (Qiagen). According to manufacturer’s protocol, 1 μg of total
RNA was converted to DNA using a High Capacity cDNA Reverse Transcription Kit
(Applied Biosystems). Following the reverse transcription (RT) reaction, all samples
were diluted 1:50 in ddH2O and subjected to real time PCR analysis with SYBR Green
PCR Master Mix (Applied Biosystems). Ten picograms of gene specific primers
(Supplementary Table 4) were used in a total reaction volume of 15 μl. For all targets, the
cycling conditions were: 95°C for 10 minutes, followed by 40 cycles each consisting of
95°C for 15 seconds, 60°C for 30 seconds and 72°C for 45 seconds. Incorporation of
SYBR Green dye into the PCR products was monitored using a 7500 Real time PCR
system (Applied Biosystems). Serial dilutions were performed to generate a standard
curve for each gene target in order to define the efficiency of the qRT-PCR reaction. The
integrity and specificity of the amplified PCR products were confirmed by dissociation
curve analysis (SDS 2.0 software, Applied Biosystems). Pfaffl analysis method was used
to measure the relative quantity of gene expression (Pfaffl, 2001). The reference gene,
Gapdh, was selected based on its stable expression in all cell populations analyzed.
Relative mRNA levels were expressed in terms of fold induction over the parental cell
3
population (4T1p). All measurements were done in triplicate and three independent
experiments were performed for each gene target.
Motility and invasion assays
Motility and invasion assays were performed as previously described using 1x105 cells
(Rodrigues et al., 2005). In Supplementary Figure 5, the migration and invasion data is
expressed as the number of cells per field, due to the large variability in cell size and
shape exhibited by the liver-weak versus liver-aggressive explant populations. To
quantify the migration and invasion assays (Supplementary Figure 7), the average pixel
count from five independent images was first quantified using Imagescope software
(Aperio, Vista, CA, USA). We next calculated the average pixel count of one cell, using
five randomly selected individual cells within a field. The data is expressed as an
approximate number of cells per field (total pixel count/pixel count for one cell). In each
experiment, two independent inserts were quantified for each explant and the data
represents the average of 4 independent experiments.
“Scratch” wound closure assay
Cells were cultured in 6-well plates until they formed confluent monolayers, after which
a scratch wound was created using a standard 200-μl pipette tip. Wounded monolayers
were washed with PBS and digital images captured for the 0 hour timepoint with an
inverted microscope equipped with a digital camera. Digital images were again captured
6 hours post-wounding and the pictures were analyzed using image analysis software
(Imagescope, Aperio). The wound healing effect was calculated as a percentage of wound
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closure compared with the area of the initial wound. Briefly, the distance between the
wound margins was measured at 0 hours and again at 6 hours post-wounding. The
following formula was used to evaluate the wound closure: % of wound closure = 100 [(distancet=6h/distancet=0h) x 100]. The data represents the average of at least 5
independent experiments (2 wells/experiments).
Human samples
Breast cancer liver metastases were obtained from 24 patients that underwent liver
resection surgery either at the Royal-Victoria Hospital (Montréal, Canada) or the Hôpital
Paul Brousse (Villejuif, France) to remove isolated breast cancer liver metastases. The
McGill University Health Center or Assistance Publique-Hôpitaux de Paris ethics review
boards approved the protocols. Consent was obtained from all participating patients or
next of kin to gain access to the stored tissue blocks. Parameters such as hormone
receptor and ErbB-2 receptor status of each liver resection specimen (Supplementary
Table 3) were scored by a pathologist using the following antibodies: Estrogen Receptor,
Progesterone Receptor and ErbB-2 (Ventana Medical Systems, Oro Valley, AZ, USA).
Paraffin
embedded
tissues
were
sectioned
and
subjected
to
claudin-2
immunohistocytochemistry as described above.
Breast tumors were obtained from the Breast cancer Functional Genomics Group at
the McGill University. The McGill University Health Center board approved the protocol
and consent was obtained from all participating patients or next of kin to gain access to
the stored tissue blocks. Finally, matched breast tumor and liver metastasis samples were
obtained from patients with metastatic breast cancer that were enrolled into the study at
5
the Segal Cancer Centre, following a protocol approved by the Jewish General Hospital
research ethics committee. After informed consent had been obtained, the patients
underwent ultrasound-guided liver biopsy for diagnostic reasons. All biopsy and primary
breast tumor samples were assessed for conventional histopathology as well as for
estrogen receptor, progesterone receptor and ErbB-2 receptor expression by a pathologist
(Supplementary Table 3). Antigen retrieval for the assessment of estrogen and
progesterone
receptor
status
was
carried
out
by
heating,
followed
by
immunohistocytochemical staining using antibodies from Ventana Medical Systems. The
cut-off levels for hormone receptor positivity were greater than 10%. Antigen retrieval
for the assessment of ErbB-2 expression was carried out by heating representative
paraffin sections with the CB11 monoclonal antibody (Novocastra, Newcastle, UK)
followed
by
protease
digestion
using
TAB250
(Invitrogen).
Claudin-2
immunohistochemistry was performed as described above.
Statistical analysis
The significance value associated with the differences in liver metastasis formation
between claudin-2 overexpressing cells and controls (Supplementary Figure 3) was
obtained using a t-test by considering data from the three weakly aggressive cell lines
carrying the empty vector control as one group and data from the three claudin-2
overexpressing cell lines as the other group. The significance values associated with
motility and invasion differences between the weak and liver-aggressive populations
(Supplementary Figure 5) were calculated using a Wilcoxon test, performed on each
6
experimental replicate. The resulting P-values were combined in a Z-transform test
(Whitlock, 2005).
Supplementary Figure Legends
Supplementary Figure 1 In vivo selection of breast cancer cells that aggressively grow
in the liver. (a) Schematic demonstrating selection procedure. Breast cancer cells are
delivered to the liver following splenic injection and cells derived from the liver
metastases are explanted back into culture and subjected to addition rounds of injection.
(b) Surface lesions quantified over the entire liver surface from mice injected with
parental 4T1 (4T1p) cells, first (LivM1) and second (LivM2) round liver metastases
explants (n = 16 for 4T1p, n = 9 for 2270 LivM1, n = 20 for 2521 LivM2, n = 18 for
2526 LivM2, n = 8 for 2263 LivM1, n = 20 for 2568 LivM2, n = 9 for 2265 LivM1 and n
= 14 for 2557 LivM2). The average number of surface lesions is shown (*, P < 0.05;
comparisons are relative to the parental 4T1 population (4T1p)). (c) Quantification of
tumor burden (lesion area/tissue area) within the cardiac liver lobe (n = 16 for 4T1p, n =
9 for 2270 LivM1, n = 20 for 2521 LivM2, n = 18 for 2526 LivM2, n = 8 for 2263
LivM1, n = 20 for 2568 LivM2, n = 9 for 2265 LivM1 and n = 14 for 2557 LivM2). The
average percentage of total liver area that contains metastatic lesions is shown (*, P <
0.05; comparisons are relative to the parental 4T1 population (4T1p)).
Supplementary Figure 2 Liver-aggressive breast cancer populations have lost
expression of tight-junction components. Quantitative real-time PCR analysis was
performed for Cldn2, Cldn3, Cldn4, Cldn7 and Ocln in weak and liver-aggressive breast
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cancer cells normalized to total Gapdh levels. The data is depicted as fold expression
relative to 4T1p cells and is representative of 3 independent experiments performed in
triplicate.
Supplementary Figure 3 Claudin-2 overexpression in the liver-weak cell populations
promotes establishment and growth in the liver. (a) Immunoblot analysis of claudin-2
expression in cells transfected with a claudin-2 expression vector (C2) or the
corresponding empty vector (EV) as a control. Total lysate from the 2869 cells, an in vivo
selected liver-aggressive 4T1 sub-population, was used to indicate the relative claudin-2
expression levels in the transfectants. As a loading control, total cell lysates were blotted
for α-tubulin. (b) Quantification of the number of surface lesions over the entire liver. (c)
The tumor burden (tumor area/tissue area) within the cardiac liver lobe is shown. Cohort
sizes: n = 9 for 4T1p-VC, n = 8 for 4T1p-C2, n = 9 for 2648 LivM3-VC, n = 9 for 2648
LivM3-C2, n = 10 for 2801 LivM3-VC and n = 8 for 2801 LivM3-C2 (*, P < 0.05). (d)
Representative H&E images of the cardiac liver lobe are shown for mice injected with
empty vector (upper) or claudin-2 overexpressing cells (lower). Dotted lines circumscribe
the breast cancer lesions. Scale bars represent 2 mm.
Supplementary Figure 4 Reduced expression of claudin-2 has no effect on tumor
outgrowth. Tumor growth in the mammary fat pad was assessed by caliper measurement
for the liver-aggressive cell populations with claudin-2 knockdown (KD1, KD2) and their
corresponding empty vector (EV) controls. Cohort sizes: n = 10 tumors for 2776-EV,
2776-KD1, 2792-KD1, 2792-KD2 and n = 9 for 2792-EV and 2776-KD2.
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Supplementary Figure 5 Liver-aggressive 4T1 explants display enhanced motility and
invasion compared to their weak counterparts. Representative images of 4T1 explants
following migration through modified Boyden chambers with filters containing 8 m
pores (a) or invasion through a matrigel barrier (c). Quantification of motility (b) and
invasion (d) assays. Results are shown from three independent experiments performed in
triplicate.
Supplementary Figure 6 4T1-derived subpopulations that aggressively grow in the liver
are highly motile in a “wound” assay compared to their weak counterparts. Confluent
monolayer cultures were scratched with a pipette tip and images taken immediately after
the “wound” was created (0h) and again after 6 hours (6h). Representative images
illustrating that the weak populations close the wound as an adherent front of cells (a)
whereas liver-aggressive populations (b) close the wound as individual cells. (c)
Quantification of percentage wound closure at 6 hours post “wounding” for three
independent weak (grey) and three independent aggressive (black) 4T1-derived breast
cancer populations. A statistically significant increase in cell motility was observed in all
aggressive explants.
Supplementary Figure 7 Effects of elevated or diminished claudin-2 expression on
breast cancer motility and invasion. (a), Quantification of percentage wound closure at 6
hours post “wounding” in the liver-weak cell populations overexpressing claudin-2 (C2)
and their corresponding empty vector (EV). (b), Quantification of breast cancer cell
9
invasion in a modified Boyden chamber assay using the liver-weak cell populations
overexpressing claudin-2 (C2) and their corresponding empty vector (EV). (c),
Quantification of percentage wound closure at 6 hours post “wounding” in the liveraggressive cell populations with a claudin-2 knockdown (KD1, KD2) and their
corresponding empty vector (EV) and parental cell (P) controls. (d), Quantification of
breast cancer cell invasion in a modified Boyden chamber assay using liver-aggressive
cell populations with a claudin-2 knockdown (KD1, KD2) and their corresponding empty
vector (EV) and parental cell (P) controls.
Supplementary Figure 8 Claudin-2 expression enhances attachment to type IV collagen
and fibronectin. Quantification of cancer cell adhesion to collagen type IV (a) or
fibronectin–coated plates (b) using liver-weak explants populations overexpressing
claudin-2 compared to empty vector controls (EV). Statistically significant increases in
adhesion were observed in all claudin-2 overexpressing cells (*, P < 0.05).
Supplementary Figure 9 Claudin-2 knockdown (KD) in MDA-MB-231 cells has no
effect on claudin-4 expression. Expression of claudin-4 and claudin-2 was assessed by
immunoblot analysis. As a loading control, total cell lysates were blotted for α-tubulin. P,
parental MDA-MB-231; EV, empty vector control.
Supplementary Figure 10 Reduced claudin-2 expression in MDA-MB-231 cells
correlates with diminished levels of integrin α2β1 and α5β1 cell surface expression. The
signal from MDA-MB-231-EV cells was divided equally (black line in Figure 5B)
10
representing high or low surface expression of the integrin complexes. Bars show the
proportion of MDA-MB-231 KD1 and MDA-MB-231 KD2 cells that display high or low
surface expression for each integrin complex relative to MDA-MB-231 EV control. The
decrease in high surface expression of α2β1 and α5β1 in both individual knockdown (KD)
cell lines is significant compared to the empty vector (EV) control (P < 0.05).
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