An Immune Cell Signature is Associated with Disease-Free Survival and Adjuvant Chemosensitivity of Patients with Resectable Gastric Cancer

Abstract

Background: Increasing evidence has demonstrated current TNM stage alone cannot predict prognosis and adjuvant chemotherapy benefits accurately for stage II and III gastric cancer (GC) patients after surgery. This study aimed to establish an immune signature, based on the composition of infiltrating immune cells, to improve the prediction of survival and adjuvant chemotherapy benefits of GC patients after surgery. Methods: Twenty-eight types of immune cell fraction were evaluated based on the expression profiles of GC patients from the Gene Expression Omnibus (GEO) database using single-sample gene set enrichment analysis (ssGSEA). The immunoscore was constructed using a least absolute shrinkage and selection operator (LASSO) Cox regression model. Findings: Using the LASSO model, an immunoscore (IS) classifier was established consisting of 8 immune cells. Significant difference was found between high-IS and low-IS groups in the training cohort in DFS (P<0.0001) and OS (P<0.0001). Multivariate analysis showed that the IS classifier was an independent prognostic indicator. Moreover, a combination of IS and TNM stage had better prognostic value than TNM stage alone. Further analysis demonstrated that low-IS patients had better response to adjuvant chemotherapy. Finally, we established two nomograms to screen the patients with stage II and III benefiting from adjuvant chemotherapy after surgery. Interpretation: The IS classifier, companied with TNM stage, could predict DFS and OS of GC patients effectively and precisely. The IS model represented a promising tool that could be used to identify the patients with stage II and III GC who might benefit from adjuvant chemotherapy. Funding Statement: This work was supported by the National Key Research and Development Program of China (2017YFC1308900), Technological Special Project of Liaoning Province of China (2019020176-JH1/103), Science and Technology Plan Project of Liaoning Province (NO.2013225585), The Key Research and Development Program of Liaoning Province (2018225060), The General Projects of Liaoning Province Colleges and Universities (LFWK201706), Science and Technology Plan Project of Shenyang city(19-112-4-099). Declaration of Interests: The authors declare no conflict of interests.