A Novel Ferroptosis-Related Gene Risk Signature for Predicting Prognosis and Immunotherapy Response in Gastric Cancer | Zendy

Shijin Liu | Zendy; Yabing Yang | Zendy; Jiaxin Zhou | Zendy; Yujian Lin | Zendy; Yun-long Pan | Zendy; Jinghua Pan | Zendy

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A Novel Ferroptosis-Related Gene Risk Signature for Predicting Prognosis and Immunotherapy Response in Gastric Cancer

Author(s) -

Shijin Liu,

Yabing Yang,

Jiaxin Zhou,

Yujian Lin,

Yun-long Pan,

Jinghua Pan

Publication year - 2021

Publication title -

disease markers

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.912

H-Index - 66

eISSN - 1875-8630

pISSN - 0278-0240

DOI - 10.1155/2021/2385406

Subject(s) - immunotherapy , cancer , gene signature , medicine , cancer research , signature (topology) , gene , oncology , immunology , biology , gene expression , genetics , geometry , mathematics

Background Gastric cancer (GC) is the third leading cause of cancer death worldwide with complicated molecular and cellular heterogeneity. Iron metabolism and ferroptosis play crucial roles in the pathogenesis of GC. However, the prognostic role and immunotherapy biomarker potential of ferroptosis-related genes (FRGs) in GC still remains to be clarified.Methods We comprehensively analyzed the prognosis of different expression FRGs, based on gastric carcinoma patients in the TCGA cohort. The functional enrichment and immune microenvironment associated with these genes in gastric cancer were investigated. The prognostic model was constructed to clarify the relation between FRGs and the prognosis of GC. Meanwhile, the ceRNA network of FRGs in the prognostic model was performed to explore the regulatory mechanisms.Results Gastric carcinoma patients were classified into the A, B, and C FRGClusters with different features based on 19 prognostic ferroptosis-related differentially expressed genes in the TCGA database. To quantify the FRG characteristics of individual patients, FRGScore was constructed. And the research shows the GC patients with higher FRGScore had worse survival outcome. Moreover, thirteen prognostic ferroptosis-related differentially expressed genes (DEGs) were selected to construct a prognostic model for GC survival outcome with a superior accuracy in this research. And we also found that FRG RiskScore can be an independent biomarker for the prognosis of GC patients. Interestingly, GC patients with lower RiskScore had less immune dysfunction and were more likely to respond to immunotherapy according to TIDE value analysis. Finally, a ceRNA network based on FRGs in the prognostic model was analyzed to show the concrete regulation mechanisms.Conclusions The ferroptosis-related gene risk signature has a superior potent in predicting GC prognosis and acts as the biomarkers for immunotherapy, which may provide a reference in clinic.

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