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Stromal contribution to the colorectal cancer transcriptome

A Corrigendum to this article was published on 28 September 2016

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Abstract

Recent studies identified a poor-prognosis stem/serrated/mesenchymal (SSM) transcriptional subtype of colorectal cancer (CRC). We noted that genes upregulated in this subtype are also prominently expressed by stromal cells, suggesting that SSM transcripts could derive from stromal rather than epithelial cancer cells. To test this hypothesis, we analyzed CRC expression data from patient-derived xenografts, where mouse stroma supports human cancer cells. Species-specific expression analysis showed that the mRNA levels of SSM genes were mostly due to stromal expression. Transcriptional signatures built to specifically report the abundance of cancer-associated fibroblasts (CAFs), leukocytes or endothelial cells all had significantly higher expression in human CRC samples of the SSM subtype. High expression of the CAF signature was associated with poor prognosis in untreated CRC, and joint high expression of the stromal signatures predicted resistance to radiotherapy in rectal cancer. These data show that the distinctive transcriptional and clinical features of the SSM subtype can be ascribed to its particularly abundant stromal component.

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Figure 1: The CRC SSM subgroup is consistently recognized by different classifiers and is associated with high stromal content.
Figure 2: Systematic loss of SSM gene expression upon propagation of CRC tissues in PDXs.
Figure 3: Species-specific analysis of RNA-seq data from PDX samples to distinguish stromal from cancer cell gene expression.
Figure 4: Proteins encoded by SSM genes are detected in stromal rather than epithelial CRC cells.
Figure 5: Clinical impact of stromal gene signatures.

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Change history

  • 29 August 2016

    In the version of this article initially published, an affiliation for author Zsolt Fekete was incorrectly omitted. The missing affiliation was to the Department of Oncology, University of Medicine and Pharmacy Iuliu Hatieganu, Cluj-Napoca, Romania. The error has been corrected in the HTML and PDF versions of the article.

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Acknowledgements

We thank E. Trisolini, R. Porporato, D. Cantarella, B. Martinoglio, F. Sassi and S. Destefanis for technical assistance. E.M., A.B. and L.T. are members of the EurOPDX Consortium. This work was supported by grants from Associazione Italiana per la Ricerca sul Cancro (IG12944 and IG14205; 9970-2010 Special Program Molecular Clinical Oncology 5x1000), Fondazione Piemontese per la Ricerca sul Cancro (5x1000 Ministero della Salute 2010 and 2011) and Compagnia di San Paolo/Ateneo (project ‘Rethe’).

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Authors and Affiliations

Authors

Contributions

C.I. contributed study design, data analysis, bioinformatics analyses, histochemical and morphological analyses, and manuscript writing. A.T. contributed molecular and morphological data generation and analysis. S.E.B. contributed data analysis and bioinformatics analyses. C.P. contributed molecular data generation. G.G., A. Muratore, A. Mellano, Z.F., M.D.R. and G.S. contributed sample acquisition, clinical data collection and curation. R.S., A.C., C.S. and P.C. contributed histochemical and morphological analyses, sample acquisition and clinical data collection and curation. G.I. contributed histochemical and morphological analyses. L.T. contributed sample acquisition and manuscript writing. A.B. contributed data analysis, sample acquisition and manuscript writing. E.M. contributed study design, data analysis, bioinformatics analyses, histochemical and morphological analyses, manuscript writing and project oversight.

Corresponding authors

Correspondence to Claudio Isella or Enzo Medico.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 SSM signature genes are highly expressed in residual scar tissues after preoperative radiotherapy of rectal cancer.

Scatter plots comparing expression profiles of matched pretreatment tumor biopsies (x axis) and residual scars after complete response to radiotherapy (y axis) in two patients with renal cancer (RCa0003 and RCa0016, as indicated on top). Blue dots highlight signature genes corresponding to the SSM subtype, respectively, in the CRCA classifier (a), CCS classifier (b) and CCMS classifier (c).

Supplementary Figure 2 GSEA testing of CRC classifier signatures for differential expression in stromal versus neoplastic cells.

The signature gene sets for the CCMS4, CRCA5, CCS3, CCMS2 and CRCA1 subtypes, as indicated in each panel, were tested for upregulation in stromal cell populations (FAP+, CD31+, CD45+) versus epithelial cells (EpCAM+), as indicated. NES, normalized enrichment score.

Supplementary Figure 3 Scatter plots for signal comparisons in Affymetrix HG-U133 Plus 2 arrays hybridized with human, mouse and mixed RNA.

(a) Standard probe set analysis; x axis: average signal across 27 human tumors (GSE35144); y axis, maximum signal for 3 Mouse universal RNA samples (GSE49353). (b) Single-probe analysis: x axis, average signal for 27 human tumors; y axis, maximum signal for Mouse universal RNA. The horizontal red line indicates the signal threshold above which probes are considered to cross-hybridize with mouse sequences. (c) Signals of new probe sets obtained using H-spec CDF: x axis, average signal across 27 human tumors; y axis, maximum signal for Mouse universal RNA. (d) Standard probe set analysis: x axis, average signal for 27 human tumors; y axis, average signal for the 27 matched PDX samples (GSE35144).

Supplementary Figure 4 Scatter plot comparing probe signals of Illumina human gene expression arrays upon hybridization with cRNA derived from human and mouse samples.

x axis, average probe signal of four human primary CRCs; y axis, maximum probe signal from a mouse CRC and a mouse endothelial cell sample.

Supplementary Figure 5 Human versus mouse expression of CRC subtype signature genes in PDX RNA-seq data.

Scatter plots comparing, for each gene, human ortholog (x axis) versus mouse ortholog (y axis) RPM values from PDX RNA-seq data. Colored dots identify the various subtype signatures of the three CRC classifiers.

Supplementary Figure 6 Waterfall plots of various CRC signature gene lists, ranked, from left to right, by the fraction of their expression levels contributed by the stroma.

Because of the varying size of the gene lists, the x axis reports the percentile and the y axis reports the stromal contribution to gene expression, calculated for each gene as the percentage of mouse reads over the total (mouse + human) reads. The color code for each gene list is reported at the bottom of the panel. “Up” and “Down” are relative to the differential expression as mentioned in the respective referenced works. In plots with a single gene list, the blue color indicates association with the phenotype described in the respective reference works. GSEA statistics for enrichment in the mouse or human fraction are reported in Supplementary Table 11. References for the analyzed Signatures are reported in Supplementary Note c.

Supplementary Figure 7 Stromal expression of representative SSM genes.

(a) Micrographs of IHC staining of ZEB1, MAP1B and TAGLN in rectal cancer preoperative biopsies classified as SSM. In all micrographs, specific staining of all antibodies is confined to the stromal components. ZEB1 is localized to the nuclei of fibroblasts, leukocytes and other mesenchymal cells; MAP1B preferentially stains endothelial cells and nerve structures; and TAGLN is mainly expressed by smooth muscle cells. Scale bar, 20 µm. (b) RNA in situ hybridization for ZEB1 mRNA (RNAscope 2.0 assay, Advanced Cell Diagnostics) in the CRC315 sample, classified as SSM and displaying weak cytoplasmic IHC positivity for ZEB1, as shown in Figure 4b. Scale bar, 20 µm.

Supplementary Figure 8 CRC proteomic subtype C signature expression is contributed by CAFs.

In all panels except e, blue and pink dots/lines indicate transcripts coding for proteins upregulated and downregulated in subtype C, respectively. (a) Box plots reporting, for each proteomic subgroup, tumor purity estimated by Absolute analysis on TCGA CRC samples. (b) Scatter plots comparing, for each gene ortholog pair, mouse (x axis) and human (y axis) RPM values from PDX RNA-seq data. (c) Scatter plots comparing, for each gene tested on human arrays, average signals from human CRC samples (x axis) and the corresponding PDX derivatives (y axis). Left, Affymetrix human arrays on 27 sample pairs; right, Illumina human arrays on 4 sample pairs. (d) Waterfall plots of proteomic subtype C gene lists, ranked, from left to right, by the fraction of their expression levels contributed by the stroma. Because of the varying size of the gene lists, the x axis reports the percentile and the y axis reports the stromal contribution to gene expression, calculated for each gene as the percentage of mouse reads over the total (mouse + human) reads. (e) GSEA testing for upregulation of the C type gene set in stromal cell populations (FAP+, CD31+, CD45+) versus epithelial cells (EpCAM+). NES, normalized enrichment score.

Supplementary Figure 9 Definition and characterization of three stromal signatures.

(a) Expression heat map of the three stromal signatures in sorted CRC cell subpopulations. Genes for the three stromal cell signatures (columns) distinguish the various sorted cell populations (rows): EpCAM+, epithelial cells; CD31+, endothelial cells; CD45+, leukocytes; FAP+, CAFs. (b) Dot plot reporting the 3 stromal scores (yellow, CAF; blue, leukocyte; red, endothelial; each as the percentile of its own distribution) in 450 TCGA samples, sorted by descending CAF score. (c) Venn diagrams showing the fractions of cases concordantly or discordantly falling in the top or bottom quartile of each stromal score.

Supplementary Figure 10 Reduced expression of endothelial genes after radiotherapy of rectal cancer.

(a) GSEA testing for expression of endothelial score genes comparing pretreatment biopsies of SSM cases with surgical samples classified as SSM after radiotherapy. NES, normalized enrichment score. (b) Heat map displaying the GSEA leading edge (‘core’) endothelial genes that lost expression in samples after radiotherapy.

Supplementary Figure 11 Prognosis of CRC samples stratified by the ‘Estimate’ score.

Kaplan-Meier analysis of disease-free survival on a data set of 226 CRC samples classified as having a high Estimate score (top quartile; blue line) or a low Estimate score (first to third quartiles; green line); the analysis was run on all 226 cases (a), on 138 cases that did not undergo any adjuvant therapy (b) and on 66 samples that underwent adjuvant chemotherapy after surgery (c).

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Isella, C., Terrasi, A., Bellomo, S. et al. Stromal contribution to the colorectal cancer transcriptome. Nat Genet 47, 312–319 (2015). https://doi.org/10.1038/ng.3224

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