A core matrisome gene signature predicts cancer outcome

Abstract

Background: Accumulating evidence implicates the tumour stroma as an important determinant of cancer progression but the protein constituents relevant for this effect are unknown. Here we utilised a bioinformatics approach to identify an extracellular matrix (ECM) gene signature overexpressed in multiple cancer types and strongly predictive of adverse outcome.

Methods: Gene expression levels in cancers were determined using Oncomine. Geneset enrichment analysis was performed using the Broad Institute desktop application. Survival analysis was performed using KM plotter. Survival data were generated from publically available genesets.

Results: We analysed ECM genes significantly upregulated across a large cohort of patients with ovarian, lung, gastric and colon cancers and defined a signature of nine commonly upregulated genes. Each of these nine genes was considerably overexpressed in all the cancers studied, and cumulatively, their expression was associated with poor prognosis across all data sets. Further, the gene signature expression was associated with enrichment of genes governing processes linked to poor prognosis, such as EMT, angiogenesis, hypoxia, and inflammation.

Conclusions: Here we identify a nine-gene ECM signature, which strongly predicts outcome across multiple cancer types and can be used for prognostication after validation in prospective cancer cohorts.

Figure 1

Development of a core matrisome gene signature from multiple cancer data sets. (A) CM gene expression based on gene rank for cancer vs normal tissue in various tumour types. Red squares indicate high rank in the cancer relative to the normal tissue. Grey indicates that the gene was not measured. Genes are listed in order of median rank across the analysis of included studies for that particular cancer type. (B) Venn diagram used to identify common CM genes that are significantly overrepresented throughout all cancer types identified in A. (C) The gene signature derived from the Venn diagram in B displaying the nine common, significantly upregulated genes identified across the analyses of all cancer types from A. (D) The nine-gene CM signature showing median gene rank (red=high expression) in cancer compared with normal tissue for each included study and FDR-corrected P values for the meta-analytical comparison. (E) Fluorescence immunohistochemistry for SPP1, Col10a1, Col1a1 and Col11a1 in colon cancers and matched normal colon with quantification of the area (%) of the microarray core demonstrating positive staining (n=20 per analysis). A full colour version of this figure is available at the British Journal of Cancer journal online.

Figure 2

Expression of the core matrisome gene signature predicts survival in various cancer types. (A) Overall survival (top row) and recurrence-free survival (bottom row) for cohorts of patients whose tumours demonstrate overexpression (red) or normal expression (blue) of the nine-gene CM gene signature. Numbers represent hazard ratios (95% confidence intervals). (B) GSEA analysis of colorectal and gastric cancer TCGA data sets analysed for EMT, angiogenesis, hypoxia, inflammation, oxidative phosphorylation, apoptotic regulation and genomic instability geneset enrichment in patients with high or normal expression of the nine-gene CM signature. NES, normalised enrichment score. A full colour version of this figure is available at the British Journal of Cancer journal online.