Identification of a novel immune prognostic model in gastric cancer
- PDF / 8,049,887 Bytes
- 10 Pages / 595.276 x 790.866 pts Page_size
- 37 Downloads / 211 Views
RESEARCH ARTICLE
Identification of a novel immune prognostic model in gastric cancer Y. Li1 · X. He1 · L. Fan1 · X. Zhang1 · Y. Xu1 · X. Xu1 Received: 28 April 2020 / Accepted: 10 August 2020 © Federación de Sociedades Españolas de Oncología (FESEO) 2020
Abstract Purpose The tumor immune microenvironment (TIME) is now considered as an important factor during gastric cancer (GC) development. This study identified a novel immune-related risk model for predicting prognosis and assessing the immune status of GC patients. Methods Transcriptomic data were obtained from the TCGA database. The differential expressed immune-related genes (IRGs) were identified through the ImmPort portal. Enrichment analysis was performed to explore the potential molecular mechanism of these IRGs. By the Cox regression analysis, we constructed the immune prognostic model. Then, the association between the model and the immune microenvironment was estimated. The model was validated in the GSE84433 dataset. Results Totally, we identified 222 differentially expressed IRGs. These IRGs were closely correlated with immune response and immune signaling pathways. Through the Cox regression analysis, we developed the immune prognostic model based on the expression of seven IRGs (CXCL3, NOX4, PROC, FAM19A4, RNASE2, IGHD2-15, CGB5). Patients were stratified into two groups according to immune-related risk scores. Survival analysis indicated that the prognosis of high-risk patients was poorer than low-risk patients. Moreover, the immune-related risk score was an independent prognostic biomarker. More importantly, we found that the infiltration level of immunosuppressive cells and the expression of inhibitory immune checkpoints were higher in high-risk patients. The immune microenvironment tended to be a suppressive status in patients with high-risk scores. Conclusion This study demonstrated that our model had predictive value for prognosis and the TIME in GC. It might be a robust tool to improve personalized patient management. Keywords Gastric cancer · Immune-related gene · Model · Prognosis · Tumor immune microenvironment
Introduction According to the latest global cancer statistics, gastric cancer (GC) with high morbidity and mortality has become a major disease threatening human health [1]. Currently, surgery remains the only curative treatment for early-stage patients. However, the recurrence rate after surgical resection is very high, at around 40–60% [2]. For patients with advanced GC, palliative chemotherapy and molecular-targeted therapy have not significantly improved the prognosis and clinical Electronic supplementary material The online version of this article (https://doi.org/10.1007/s12094-020-02478-5) contains supplementary material, which is available to authorized users. * X. Xu [email protected] 1
Cancer Center, Renmin Hospital of Wuhan University, 238 Jiefang Road, Wuhan 430060, China
outcomes. The five-year survival rate among advanced GC is less than 20% [3]. In the past few years, immunotherapy has made great
Data Loading...
