Literature DB >> 33049494

Comprehensive analysis of a 14 immune-related gene pair signature to predict the prognosis and immune features of gastric cancer.

Chuan Liu1, Bo Chen2, Zhangheng Huang3, Chuan Hu4, Liqing Jiang1, Chengliang Zhao5.   

Abstract

BACKGROUND: As a new method for predicting tumor prognosis, the predictive effect of immune-related gene pairs (IRGPs) has been confirmed in several cancers, but there is no comprehensive analysis of the clinical significance of IRGPs in gastric cancer (GC).
METHOD: Clinical and gene expression profile data of GC patients were obtained from the GEO database. Based on the ImmPort database, differentially expressed immune-related gene (DEIRG) events were determined by a comparison of GC samples and adjacent normal samples. Cox proportional regression was used to construct an IRGP signature, and its availability was validated using three external validation datasets. In addition, we explored the association between clinical data and immune features and established a nomogram to predict outcomes in GC patients. RESULT: A total of 88 DEIRGs were identified in GC from the training set, which formed 3828 IRGPs. Fourteen overall survival (OS)-related IRGPs were used to construct the prognostic signature. As a result, patients in the high-risk group exhibited poorer OS compared to those in the low-risk group. In addition, the fraction of CD8+ T cells, plasma cells, CD4 memory activated T cells, and M1 macrophages was higher in the high-risk group. Expression of two immune checkpoints, CD276 and VTCN1, was significantly higher in the high-risk group as well. Based on the independent prognostic factors, a nomogram was established and showed excellent performance.
CONCLUSION: The 14 OS-related IRGP signature was associated with OS, immune cells, and immune checkpoints in GC patients, and it could provide the basis for related immunotherapy.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Gastric cancer; Immune cells; Immune-related gene pairs; Nomogram; Prognosis

Mesh:

Substances:

Year:  2020        PMID: 33049494     DOI: 10.1016/j.intimp.2020.107074

Source DB:  PubMed          Journal:  Int Immunopharmacol        ISSN: 1567-5769            Impact factor:   4.932


  6 in total

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  6 in total

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