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

BACKGROUND

Gastric cancer is one of the deadliest cancers, currently available therapies have limited success. Cancer-associated fibroblasts (CAFs) are pivotal cells in the stroma of gastric tumors posing a great risk for progression and chemoresistance. The poor prognostic signature for CAFs is not clear in gastric cancer, and drugs that target CAFs are lacking in the clinic. In this study, we aim to identify a poor prognostic gene signature for CAFs, targeting which may increase the therapeutic success in gastric cancer.

METHODS

We analyzed four GEO datasets with a network-based approach and validated key CAF markers in The Cancer Genome Atlas (TCGA) and The Asian Cancer Research Group (ACRG) cohorts. We implemented stepwise multivariate Cox regression guided by a pan-cancer analysis in TCGA to identify a poor prognostic gene signature for CAF infiltration in gastric cancer. Lastly, we conducted a database search for drugs targeting the signature genes.

RESULTS

Our study revealed the COL1A1, COL1A2, COL3A1, COL5A1, FN1, and SPARC as the key CAF markers in gastric cancer. Analysis of the TCGA and ACRG cohorts validated their upregulation and poor prognostic significance. The stepwise multivariate Cox regression elucidated COL1A1 and COL5A1, together with ITGA4, Emilin1, and TSPAN9 as poor prognostic signature genes for CAF infiltration. The search on drug databases revealed collagenase clostridium histolyticum, ocriplasmin, halofuginone, natalizumab, firategrast, and BIO-1211 as the potential drugs for further investigation.

CONCLUSIONS

Our study demonstrated the central role of extracellular matrix components secreted and remodeled by CAFs in gastric cancer. The gene signature we identified in this study carries 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.