Construction and Validation of a Ferroptosis-Related Prognostic Model for Gastric Cancer.

Xiaotao Jiang,Zhihua Zheng,Kunhai Zhuang,Xingrui Yan,Peng Liu,Kechao Nie,Yuancheng Huang,Fengbin Liu,Qiaofeng Yan,Peiwu Li,Linling Xie,Jinglin Pan,Yi Wen,Jiahua Huang,Yanhua Yan,Kailin Jiang,Yushan Zou,Xuan Chen,Junhui Zheng,Shiyun Tang ,Shiqi Xu

doi:10.1155/2021/6635526

Abstract

Background Gastric cancer (GC), an extremely aggressive tumor with a very different prognosis, is the third leading cause of cancer-related mortality. We aimed to construct a ferroptosis-related prognostic model that can be distinguished prognostically. Methods The gene expression and the clinical data of GC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO). The ferroptosis-related genes were obtained from the FerrDb. Using the “limma” R package and univariate Cox analysis, ferroptosis-related genes with differential expression and prognostic value were identified in the TCGA cohort. Last absolute shrinkage and selection operator (LASSO) Cox regression was applied to shrink ferroptosis-related predictors and construct a prognostic model. Functional enrichment, ESTIMATE algorithm, and single-sample gene set enrichment analysis (ssGSEA) were applied for exploring the potential mechanism. GC patients from the GEO cohort were used for validation. Results An 8-gene prognostic model was constructed and stratified GC patients from TCGA and meta-GEO cohort into high-risk groups or low-risk groups. GC patients in high-risk groups have significantly poorer OS compared with those in low-risk groups. The risk score was identified as an independent predictor for OS. Functional analysis revealed that the risk score was mainly associated with the biological function of extracellular matrix (ECM) organization and tumor immunity. Conclusion In conclusion, the ferroptosis-related model can be utilized for the clinical prognostic prediction in GC.

Highlights

According to the latest global cancer statistics, gastric cancer (GC) ranks fifth in the incidence of cancers and is the third leading cause of cancer-related mortality [1]. e overall survival of patients with Gastric cancer (GC) varies widely in different regions of the world
26% in Europe [1]. e conditions mentioned above indicated that GC is a disease with high heterogeneity [2]. e conventional system for prognosis prediction, such as histological grade and tumor stage, is becoming increasingly difficult to cover the clinical diversity of GC [3]. erefore, developing a novel prognostic model is urgent
A total of 80 DEGs were identified related to ferroptosis in GC, and 10 of them were correlated with overall survival (OS) (Figure 2(a))

Summary

Introduction

According to the latest global cancer statistics, gastric cancer (GC) ranks fifth in the incidence of cancers and is the third leading cause of cancer-related mortality [1]. e overall survival of patients with GC varies widely in different regions of the world. CDO1 [9] and ALOX15 [10] can promote ferroptosis in human GC cell while SCD1 [11], PLIN2 [12] and GDF15 [13] are opposite. Whether these ferroptosis-related genes are correlated with the prognosis of GC patients still remains to be explored. An 8-gene prognostic model was constructed and stratified GC patients from TCGA and meta-GEO cohort into high-risk groups or low-risk groups. The ferroptosis-related model can be utilized for the clinical prognostic prediction in GC

Objectives

Results

Conclusion