Consort diagram describing patient tumors used in this study, including those evaluated for global mRNA abundance, the expression of molecular markers through immunohistochemistry (IHC), and chemosensitivity as patient-derived xenografts.

<p>Consort diagram describing patient tumors used in this study, including those evaluated for global mRNA abundance, the expression of molecular markers through immunohistochemistry (IHC), and chemosensitivity as patient-derived xenografts.</p

Multivariate analysis of Clinicopathological and Immunohistochemical Characteristics of Patient Tumors.

<p>The final multivariate models are shown. Factors assessed included age, gender, stage, differentiation, location, neo-adjuvant chemo-radiation, heartburn, Barrett’s esophagus and expression of p16, p53, Her-2/<i>neu</i>, EGFR and Ki-67.</p><p>*Age was modeled as a continuous variable in the logistic regression analysis; the odds ratio is reported for every increase in 10 years. For example, this is the odds ratio comparing someone aged 70 vs 60 years old; or 65 vs 55 years old.</p><p>Multivariate analysis of Clinicopathological and Immunohistochemical Characteristics of Patient Tumors.</p

Scatterplot showing mRNA abundance comparisons for each established adenocarcinoma line.

<p>Comparisons were made between P1 xenograft <i>vs</i> patient tumor (left column), P_latest<i>vs</i> P_early xenograft (middle column) and Large <i>vs</i> Small xenograft tumors (right column). Normalized expression levels for individual genes were used to plot the comparison. R² values are included for each comparison. mRNA for lines F and I could not be extracted for all comparisons since mRNA degradation in the frozen tissue had occurred. Both samples had intact mRNA for the patient tumor but Line I did not have a matching later passage xenograft while Line F did not have a matching first passage xenograft. Both lines were included in statistical comparisons where the data was present.</p

Selected molecular marker expression by immunohistochemistry (IHC).

<p>P53 in Line A and Ki-67 in Line H are examples of similar expression between patient, early passage (P1) and latest passage (P_{<i>latest</i>}) xenografts. P16 in Line H was selected to demonstrate the heterogeneity detected in the same tissue (P_<i>early</i> showing both positive and negative expression). EGFR expression in Line E exhibited an increase in intensity from patient to xenografts while Her-2/<i>neu</i> expression in Line A showed a decrease in intensity. These examples were included to demonstrate that the differences exhibited between patient tissue, early passage and latest passage xenografts were due to intrinsic heterogeneity and not to any specific patterns of expression.</p

HT-FC allows phenotypic segregation and identification of cell samples from diverse lineages.

<p>Unsupervised hierarchical clustering of percent-positive marker expression values generated on 119 samples was performed. Colours indicate emergence of biologically related samples into clusters based on surface marker profiles. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105602#pone.0105602.s002" target="_blank">Figure S2</a> for a magnified image of the dendrogram.</p

The HT-FC platform is highly reproducible.

<p>MDA-MB-231 breast cancer cells, 22RV1 prostate cancer cells, or PBMCs were each run 3 times on the HT-FC platform. When the same cell line or peripheral blood sample was analyzed 3 independent times, consistently reproducible results were obtained, with Spearman correlation coefficients between runs ranging from 0.847 to 0.973, and p<0.001 for all comparisons.</p

HT-FC allows intratumoral analysis of stromal and cancer cell subsets within primary ccRCC samples.

<p>(<b>A</b>) Heatmap showing expression of each of the 363 antibodies in four subpopulations of ccRCC samples: CD45⁺ immune cells, CD45⁻CD31⁺CD34⁺ vascular endothelial cells, CD45⁻TE7⁺ fibroblasts, and CD45⁻TE7⁻CD31⁻CD34⁻ cancer cells. Antibodies are simply arranged in alphabetical order on the vertical axis and the four populations for each sample are ordered across the top. A low resolution overview demonstrates a surprisingly reproducible “fingerprint” of tumor cell subpopulations from one sample to the next. (<b>B</b>) Supervised hierarchical clustering reveals clusters of antigens corresponding to specific cell subsets within tumors (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105602#pone.0105602.s011" target="_blank">Table S6</a> for details). (<b>C</b>) Principal components analysis of the entire data set further illustrates how effectively the cell surface profile delineates the 4 distinct cell populations within primary ccRCC samples. Red: immune cells; Green: endothelial cells; Blue: fibroblasts; Orange: cancer cells.</p

Antibodies with no staining across all cell types analyzed.

<p>Antibodies with no staining across all cell types analyzed.</p