Dataset Information

Comprehensive Genomic Meta-analysis Identifies Intra-Tumoral Stroma as a Predictor of Gastric Cancer Patient Survival

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE37023 | GEO | 2012/07/05

SECONDARY ACCESSION(S): PRJNA157861

REPOSITORIES: GEO

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Project description:A large-scale characterization of the methylation states of candidate CpG islands (CGIs) throughout the gastric cancer methylome has not previously been conducted. Genome-wide DNA methylation profiles were compared between 4 metastatic and 4 non-metastatic gastric carcinomas (GCs) and their surgical margins (SMs). The GC genome showed significantly higher proportions of hypomethylation in the promoter and exon-1 regions, as well as increased hypermethylation of intragenic fragments when compared to SMs. Differential methylation was observed in CGIs near transcription start sites of 546 genes between GCs and SMs, and 601 genes between metastatic and non-metastatic GCs. From the list of differentially methylated CGIs, 68 candidate genes and 10 known tumor-related genes were selected for further characterization based on their known molecular function using DHPLC. Significant differential methylation was validated in the CGIs of 15 genes between GCs and SMs (Ps<0.05) and confirmed using bisulfite-sequencing. These genes include BMP3, BNIP3, CDKN2A, ECEL1, ELK1, GFRA1, HOXD10, KCNH1, PSMD10, PTPRT, SIGIRR, SRF, TBX5, TFPI2, and ZNF382. Hypomethylation of CGIs correlated with up-regulation of GFRA1 expression in GCs, while hypermethylation of other genes inactivated their transcription. Most importantly, prevalence of GFRA1, SRF, and ZNF382 methylation alterations were inversely and coordinately associated with GC metastasis and the patients’ overall survival throughout discovery and testing cohorts in China as well as independent validation cohorts in Japan and Korea. In conclusion, methylation changes in the CGIs of 15 genes correlated strongly with GC development. GFRA1 hypomethylation and SRF and ZNF382 hypermethylation are potential synergistic biomarkers for the prediction of GC metastasis. To identify differential methylation of CGIs related to GC development and metastasis, genome-wide DNA methylation changes in 8 pairs of GC and SM samples were analysed using the MCAM assay with a 99K custom-designed Agilent oligonucleotide microarray composed of 99,027 probes targeting 6,177 unique protein-coding genes containing at least two methylation-sensitive/insensitive SmaI/ XmaI restriction sites (CCC|GGG/ C|CmCGGG) as described in Shen et al, PLoS Genet 3, 2023-2036 (2007).

Dataset Information

Comprehensive Genomic Meta-analysis Identifies Intra-Tumoral Stroma as a Predictor of Gastric Cancer Patient Survival

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