Comprehensive bioinformatic analysis reveals a cancer-associated fibroblast gene signature as a poor prognostic factor and potential therapeutic target in gastric cancer

Abstract

Background: Gastric cancer is one of the deadliest cancers in the world. The lack of prognostic markers and efficient molecular targets limits the success of current therapies. Therefore, we aimed to identify new prognostic markers and therapeutic targets in gastric cancer. Methods: We analyzed four GEO gene expression datasets with a network-based approach. We used The Cancer Genome Atlas (TCGA) stomach adenocarcinoma data as the validation set. Since all the hub genes indicated the cancer-associated fibroblast infiltration in gastric tumors, we performed a stepwise multivariate Cox regression analysis to identify a poor prognostic gene signature for cancer-associated fibroblast infiltration. Lastly, we searched the drug databases for drugs that target the signature genes. Results: Our network-based approach revealed the extracellular matrix components COL1A1, COL1A2, COL3A1, COL5A1, FN1, and SPARC as the central genes in gastric cancer. These genes were overexpressed and displayed poor prognostic significance in TCGA stomach adenocarcinoma samples. We demonstrated the substantial correlation between these genes and the cancer-associated fibroblast infiltration in gastric cancer. The stepwise multivariate Cox regression elucidated COL1A1 and COL5A1, together with ITGA4, Emilin1, and TSPAN9 as poor prognostic signature genes for the cancer-associated fibroblast infiltration. The search on drug databases revealed: collagenase clostridium histolyticum, ocriplasmin, and halofuginone which target collagen subunits; and natalizumab, firategrast, and BIO-1211 which target ITGA4 as the potential drugs for further investigation. Conclusions: Our study demonstrated the central role of extracellular matrix components secreted and remodeled by the cancer-associated fibroblasts in gastric cancer. The cancer-associated fibroblast gene signature we identified in this study carries a high potential as a predictive tool for poor prognosis in gastric cancer patients. Elucidating the mechanisms by which the signature genes contribute to poor patient outcomes can lead to the discovery of more potent molecular-targeted agents and; increase the therapeutic success in gastric cancer.