Development and Validation of a Three-Gene Prognostic Signature Based on Tumor Microenvironment for Gastric Cancer

Frontiers in Genetics

Qingfei Kong¹  Ying Jiang²  Yalan He³  Jiayue Qiu³  Junwei Han³  Xiangmei Li³  Jiashuo Wu³  Yahui Wang³  Qian Wang³  Ji Li³ 

[1] College of Basic Medical Science, Harbin Medical University, Harbin, China;College of Basic Medical Science, Heilongjiang University of Chinese Medicine, Harbin, China;College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China;

关键词: gastric cancer;    prognostic signature;    tumor microenvironment;    survival analysis;    three-gene prognostic signature;   

DOI  :  10.3389/fgene.2021.801240

来源: DOAJ

【 摘 要 】

Gastric cancer (GC), which has high morbidity and low survival rate, is one of the most common malignant tumors in the world. The increasing evidences show that the tumor microenvironment (TME) is related to the occurrence and progression of tumors and the prognosis of patients. In this study, we aimed to develop a TME-based prognostic signature for GC. We first identified the differentially expressed genes (DEGs) related to the TME using the Wilcoxon rank-sum test in a training set of GC. Univariate Cox regression analysis was used to identify prognostic-related DEGs. To decrease the overfitting, we performed the least absolute shrinkage and selection operator (LASSO) regression to reduce the number of signature genes and obtained three genes (LPPR4, ADAM12, NOX4). Next, the multivariate Cox regression was performed to construct the risk score model, and a three-gene prognostic signature was developed. According to the signature, patients were classified into high-risk and low-risk groups with significantly different survival. The signature was then applied to three independent validated sets and obtained the same results. We conducted the time-dependent Receiver Operating Characteristic (ROC) curve analysis to evaluate our signature. We further evaluated the differential immune characters between high-risk and low-risk patients to reveal the potential immune mechanism of the impact on the prognosis of the model. Overall, we identified a three-gene prognostic signature based on TME to predict the prognosis of patients with GC and facilitate the development of a precise treatment strategy.

【 授权许可】

Unknown