The predictive effect of immune therapy and chemotherapy under T cell-related gene prognostic index for Gastric cancer

Jingyao Chen; Xing Li; Tsz Kin Mak; Xiaoqun Wang; Hui Ren; Kang Wang; Zi Chong Kuo; Wenhui Wu; Mingzhe Li; Tengfei Hao; Changhua Zhang; Yulong He

doi:10.3389/fcell.2023.1161778

The predictive effect of immune therapy and chemotherapy under T cell-related gene prognostic index for Gastric cancer

Front Cell Dev Biol. 2023 May 18:11:1161778. doi: 10.3389/fcell.2023.1161778. eCollection 2023.

Authors

Jingyao Chen¹, Xing Li¹, Tsz Kin Mak¹, Xiaoqun Wang¹, Hui Ren¹, Kang Wang¹, Zi Chong Kuo¹, Wenhui Wu¹, Mingzhe Li¹, Tengfei Hao¹, Changhua Zhang^{1

2}, Yulong He^{1

2

3}

Affiliations

¹ Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
² Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong, China.
³ Department of Gastrointestinal Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.

Abstract

Background: Gastric cancer (GC) is one of the most common malignancies in the human digestive tract. CD4+T cells can eliminate tumor cells directly through the mechanism of cytolysis, they can also indirectly attack tumor cells by regulating the tumor TME. A prognostic model of CD4+T cells is urgently needed to improve treatment strategies and explore the specifics of this interaction between CD4+T cells and gastric cancer cells. Methods: The detailed data of GC samples were downloaded from the Cancer Genome Atlas (TCGA), GSE66229, and GSE84437 datasets. CD4⁺ T cell-related genes were identified to construct a risk-score model by using the Cox regression method and validated with the Gene Expression Omnibus (GEO) dataset. In addition, postoperative pathological tissues of 139 gastric cancer patients were randomly selected for immunohistochemical staining, and their prognostic information were collected for external verification. Immune and molecular characteristics of these samples and their predictive efficacy in immunotherapy and chemotherapy were analysed. Results: The training set and validation set had consistent results, with GC patients of high PROC and SERPINE1 expression having poorer prognosis. In order to improve their clinical application value, we constructed a risk scoring model and established a high-precision nomogram. Low-risk patients had a better overall survival (OS) than high-risk patients, consistent with the results from the GEO cohort. Furthermore, the risk-score model can predict infiltration of immune cells in the tumor microenvironment of GC, as well as the response of immunotherapy. Correlations between the abundance of immune cells with PROC and SERPINE1 genes were shown in the prognostic model according to the training cohort. Finally, sensitive drugs were identified for patients in different risk subgroup. Conclusion: The risk model not only provides a basis for better prognosis in GC patients, but also is a potential prognostic indicator to distinguish the molecular and immune characteristics of the tumor, and its response to immune checkpoint inhibitor (ICI) therapy and chemotherapy.

Keywords: T Cell related gene; T-cell score; gastric cancer; immune microenvironment infiltration; immune therapy.

Grants and funding

This study was supported by the Guangdong Provincial Key Laboratory of Digestive Cancer Research (No. 2021B1212040006), Shenzhen Sustainable Project (KCXFZ202002011010593), National Natural Science Foundation of China (82073148), Sanming Project of Medicine in Shenzhen (No. SZSM201911010), Shenzhen Key Medical Discipline Construction Fund (No. SZXK016), Guangdong–Hong Kong–Macau University Joint Laboratory of Digestive Cancer Research (2021LSYS003) and Shenzhen Fundamental Research Program (JCYJ20190809142807444).