A Predictive Signature for Oxaliplatin and 5-fluorouracil Based Chemotherapy Inlocally Advanced Gastric Cancer

Abstract

Background: Adjuvantchemotherapy(AC)plays a substantial role in the treatment of locally advanced gastric cancer (LAGC), but the response remains poor. Weaims to improve its efficacy in LAGC. Methods: We identified the expression of eight genes closely associated with platinum and fluorouracil metabolism (RRM1, RRM2, RRM2B, POLH, DUT, TYMS, TYMP, MKI67) in the discovery cohort (N=291). And we further validated the findings in TCGA (N=279) and GEO. Overall survival (OS) was used as an endpoint. Univariate and multivariate Cox models were applied. A multivariate Cox regression model was simulated to predict theOS. Results: In the discovery cohort,the univariate Coxmodelindicated that AC was beneficial to high-RRM1, high-DUT, low-RRM2, low-RRM2B, low-POLH, low-KI67, low-TYMS or low-TYMP patients, the results were validated in the TCGA cohort. The multivariate Cox model showed consistent results. Cumulative analysis indicated that patients with low C-Score respond poorly to the AC, whereas thehigh and mediumC-Score patients significantly benefit from AC. A risk model based on the above variables successfully predicted the OS in both cohorts (AUC=0.75 and 0.67, respectively). Further validation in a panel of gastric cancer cell (GC) lines (N=37) indicated that C-Score is significantly associated with IC50 value to fluorouracil. Mutation profiling showed that C-Score was associated with the number and types of mutations. Conclusion: In this study, we successfully simulated a predictive signature for the efficacy of AC in LAGC patients and further explored the potential mechanisms. Our findings could promote precision medicine and improve the prognosis of LAGC patients.