Immune signature profiling identified prognostic factors for gastric cancer

• Published in: Chinese journal of cancer research Vol. 31; no. 3; pp. 463 - 470
• Main Authors: Yang, Wenhui, Lai, Zhiyong, Li, Yuan, Mu, Jianbing, Yang, Mudan, Xie, Jun, Xu, Jun
• Format: Journal Article
• Language: English
• Published: China Shanxi Academy of Medical Sciences, Shanxi Dayi Hospital, Taiyuan 030032, China 01.06.2019; Department of Biochemistry and Molecular Biology, Shanxi Medical University, Taiyuan 030001, China%Shanxi Academy of Medical Sciences, Shanxi Dayi Hospital, Taiyuan 030032, China%Department of Oncology, Renmin Hospital of Wuhan University, Wuhan 430060, China%Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville 20852,USA%Shanxi Provincial Cancer Hospital, Affiliated Cancer Hospital of Shanxi Medical University, Taiyuan 030013, China%Department of Biochemistry and Molecular Biology, Shanxi Medical University, Taiyuan 030001, China; AME Publishing Company
• Subjects: Original; overall survival; immune; stomach adenocarcinoma; Gastric cancer; prognosis
• ISSN: 1000-9604; 1993-0631
• DOI: 10.21147/j.issn.1000-9604.2019.03.08

Tumor microenvironment, especially the host immune system, plays a pivotal role in tumor initiation and progression. Profiling of immune signature within tumor might uncover biomarkers for targeted therapies and clinical outcomes. However, systematic analysis of immune-related genes in gastric cancer (GC) has not been reported. Expressions of a total of 718 immune-related genes were generated in 372 stomach adenocarcinoma (STAD) patients from The Cancer Genome Atlas (TCGA) database using RNA-sequencing data. Integrated bioinformatics analyses were performed to identify prognostic factors as well. Survival analyses revealed 73 genes, which were significantly associated with patient's overall survival (OS). Taken together with clinicopathological parameters, we established a predictive model, containing 10 immune-related genes, which were , , , , , , , , and , with powerful efficiency in distinguishing satisfactory or poor survival of STAD patients. Moreover, the top 3 ranked prognostic genes, , and , were also significantly associated with patient's OS by an independent validation achieved from Kaplan-Meier plotter database. We profiled prognostic immune signature and established prognostic predictive model for GC, which could reflect immune disorders within tumor microenvironment, and also may provide novel predictive and therapeutic targets for GC patients in the near future.