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Supplemental Materials and Methods
Viable CEP analysis
The evaluation of viable CEP levels was previously described (1). Briefly, blood was drawn from
8-10 week old Balb/c mice (Charles River Canada) by retro-orbital sinus bleed. Cells were
immunostained with the following antibody mixture to identify viable CEPs were defined as
CD13+/VEGFR2+/CD117+/CD45-. All monoclonal antibodies were purchased from BD
Biosciences, and used in accordance with the manufacturers’ instructions. 7-aminoactinomycin
D (7-AAD) was used to distinguish between live and dead cells, as previously described (2). At
least 100,000 events were acquired using an LSR flow cytometer system followed by analysis
using the FACSDiva software (BD Biosciences).
Mass cytometry acquisition and analysis
HCI-002 tumors were excised from mice on day 11 after they were treated with capecitabine
and/or CTX. Tumors were prepared as single cell suspensions, as previously described (3,4).
Cells obtained from each tumor in the same group were pooled (n=5-6 tumors/group). Three
million cells were immunostained with a mixture of metal-tagged antibodies (Supplemental
Table 1). All antibodies were conjugated using the MAXPAR reagent (Fluidigm Inc., Vancouver,
Canada). Rhodium and Iridium intercalators were used to identify live/dead cells. Cells were
washed twice with PBS, fixed in 1.6% formaldehyde (Sigma-Aldrich), washed again in ultrapure
H2O and acquired by CyTOF mass cytometry system (DVS Sciences, Sunnyvale, CA). The analysis
of data was performed using Cyto Spanning Tree Progression of Density Normalized Events
(SPADE algorithm) on Cytobank database, as previously described (5,6). Samples were validated
by conventional flow cytometry technique. Briefly, for each marker, live cells were gated and a
threshold was set. Manual inspection of SPADE output was used to identify the closest known
gross-cell type, matching the combination clustering marker panel. The raw CyTOF data was
normalized to calibration beads and gated for live cells. We focused our analysis on CD45 + cells
and characterized the cell clusters using standard cell subset definitions: B cells
(CD45R+/CD79b+), CD8+ T cells (TCRβ+/CD8+), CD4+ T cells (TCRβ+/CD4+), CD4+ T regulatory cells
(CD4+/CD25+/Foxp3+), natural killer (NK) cells (NK1.1+/CD49b+ or NKp46+),
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granulocytes
(CD11b+, Gr1+), monocytes/macrophages (CD11b+/CD14+/F4/80+) and dendritic cells (CD11c+).
SPADE analysis was set on computing 100 clusters from the CD45+ cells. Data are presented
using SPADE Cytobank online software. For each group, CD45 expression intensity is
determined by color, and the number of events in each cluster is represented by the circle size.
Colony formation in soft agar
Colony formation assay was performed, as previously described (7), with the following
modifications. Ten microliters of RPMI medium containing MCF-7 or HT-29 cells were seeded in
96-well plates (5000 cells/well). Subsequently, 50 µl RPMI containing 0.3% Low Melt Agarose
(Bio-Rad) and 10% FCS (served as a positive control), or 5% plasma from 8-10 week old Balb/c
mice treated for one week with MTD or LDM capecitabine with or without LDM CTX, were
added to the wells to form a semi-solid layer. One week later, Hoechst 33342 nuclear dye was
added and colonies were then imaged using an IC200 (Vala Sciences) automated microscope at
10x magnification. Four fields were acquired per well and Z-stacks were obtained for each field
with 20 µm distance between slices. Between 200 and 1000 colonies were imaged for each
drug treatment. Experiments were repeated in triplicate.
High-throughput imaging analysis
Images collected from the IC200 (Vala Sciences) system were analyzed by Matlab software
followed by analysis steps illustrated in Supplemental Figure 2. The following steps were taken
in order to analyze the images as illustrated in Supplemental Figure 2. First, focus stacking was
performed on the Z-stacks to project the colonies onto a 2D image. The stacking was performed
by computing local image variance and subsequently computing the gradient for each plane.
The pixel with the maximum value of this gradient across the different planes was then used to
obtain the focus stacked image. Second, rotation invariant Gabor filters for image segmentation
of colonies was used, as previously described (8,9). The focus stacked image was convolved
with a set of rotation invariant Gabor filter bank. The pixels were then clustered using K-means
clustering to obtain foreground and background. A seeded watershed algorithm was then used
on the foreground pixels to segment individual colonies. For each colony, multiple features
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were extracted as described in Supplemental Table 3. Colonies with relatively small area
(normally between 1-3 cells) were discarded from the analysis. For assessing changes in colony
size, the area of each colony was divided by the median area of the control for each
experiment. Third, unsupervised clustering using an affinity propagation algorithm (10) was
then used to cluster colonies into 6 representative morphological phenotypes. Phenotypic
cluster profiles for the different treatment groups were generated by computing the fraction of
the treatment group in each cluster. Hellinger similarity – a statistical tool used to quantify the
similarity between two distributions - was used to measure differences between treatment
profiles. Subsequently, a 2D multi-dimensional scaling (MDS) was applied to visualize the
similarities between different treatment profiles.
Tissue immunostaining
Breast cancer derived xenograft tumors were embedded in either OCT (Sakura, Japan) or
paraffin. For TUNEL and proliferation staining, tumor OCT sections (5-8 µm thick) were fixed in
cold acetone for 15 minutes. Subsequently, tumor sections were blocked with 10% horse serum
for 20 min. For apoptosis, fixed samples were stained using TUNEL (red) (in situ cell detection
kit, Roche Diagnostic) as per the manufacturer’s instructions. For the staining of proliferation,
fixed samples were immunostained with Ki-67 (rabbit anti-Ki67, 1:150, Vector Laboratories VPK451) followed by secondary Cy-3-conjugated antibody (1:200, Jackson Immunoresearch
Laboratories, PA, USA). For staining of microvessel density (MVD), tumor sections were
immunostained with CD31 (Rat anti-mouse CD31, 1:200, BD Pharmigen) followed by Cy-3
conjugated antibody (1:200, Jackson immunoresearch Laboratories) or the Dako LSAB+ SystemHRP kit (K0690). DAPI was used to counterstain nuclei (Electron Microscopy Sciences, PA, USA).
For necrosis and cleaved caspase 3 staining, paraffin embedded sections (5 µm thick) were
prepared. For necrosis, H&E staining was performed, and the necrotic tissue autofluorescence
was detected in the fluorescein isothiocyanate (FITC) channel, as previously described (11). For
caspase 3 staining, sections were blocked with Dako Protein Block (X0909) plus 20% normal
donkey serum. Primary antibody rabbit anti-cleaved caspase-3 (1:500, Cell Signaling 5A1E) was
diluted in Dako Antibody Diluent (S3022), then the Dako LSAB+ System-HRP kit (K0690) and
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Liquid DAB+ Substrate Chromogen System (K3467) were used for detection. Tissue sections
were counterstained with hematoxylin. Images were acquired with a camera attached to an
inverted microscope (Carl Zeiss Axioplan2 microscope with 10x objective with a Carl Zeiss
AxioCam MRc camera). Quantification was performed using ImageJ (NIH).
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