Background and Aims: Gastric adenocarcinoma (gastric cancer, GC) is a major cause of global cancer mortality. Identifying molecular programs contributing to GC patient survival may improve our understanding of GC pathogenesis, highlight new prognostic factors, and reveal novel therapeutic targets. We aimed to produce a comprehensive inventory of gene expression programs expressed in primary GCs, and to identify those expression programs significantly associated with patient survival. Methods: Using a network modeling approach, we performed a large scale meta-analysis of GC transcriptome data integrating 940 gastric transcriptomes from multiple independent patient cohorts. We analyzed a training set of 428 GCs and 163 non neoplastic gastric mucosa (‘non-malignants’), and a validation set of 288 GCs and 61 non-malignants. Results: We identified 178 gene expression programs (modules) expressed in primary GCs, which were associated with distinct biological processes, chromosomal location patterns, cis-regulatory motifs, and clinicopathological parameters. Amongst these modules, expression of a TGF-B-signaling associated “super-module” of stroma-related genes consistently predicted patient survival in multiple GC validation cohorts. Analysis of histopathological tissue sections from gastrectomy specimens revealed that expression of this stromal module was associated with the proportion of intra-tumoral stroma (ITS). Further supporting the stromal module expression/ITS association, we found that the ITS proportion, measured directly from tissue sections, also predicted GC patient survival. Conclusion: Stromal gene expression predicts GC patient survival in multiple independent cohorts and may be closely related to the ITS proportion, a specific morphological GC phenotype. These findings suggest that therapeutic approaches targeting pathways associated with the GC stroma may merit evaluation.
Overall design
Profiling of 86 gastric samples (83 tumors and 3 non-malignants) on Affymetrix GeneChip U133A Array. All samples were collected with approvals from National Cancer Centre of Singapore. Profiling of 34 gastric tumors on Custom cDNA Microarray(30K). All samples were collected with approvals from VU University Medical Centre, Amsterdam, The Netherlands. Profiling of 65 gastric samples (29 tumors and 36 non-malignants) on Affymetrix GeneChip Human Genome U133 set Array. All samples were collected with approvals from Leeds Institute for Molecular Medicine, St James’s University Hospital, Leeds, United Kingdom.
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