Research Paper Volume 13, Issue 22 pp 24866—24881
A scoring model based on ferroptosis genes for prognosis and immunotherapy response prediction and tumor microenvironment evaluation in liver hepatocellular carcinoma
- 1 Department of Gastroenterology, The First Affiliated Hospital, And College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
- 2 Department of Clinical Laboratory, The First Affiliated Hospital, And College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
- 3 Department of Gastrointestinal Surgery, The First Affiliated Hospital, And College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China
Received: July 30, 2021 Accepted: October 27, 2021 Published: November 28, 2021https://doi.org/10.18632/aging.203721
How to Cite
Copyright: © 2021 Gao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Ferroptosis is a type of iron-dependent programmed cell death. Ferroptosis inducers have been shown to have a great potential for cancer therapy. We aimed to generate a risk scoring model based on ferroptosis-related genes (FRGs) and validate its predictive performances in overall survival (OS) prediction and immunotherapy efficacy evaluation in liver hepatocellular carcinoma (LIHC). Differential and Univariate Cox regression analyses were applied to analyze RNA-seq data of LIHC samples from TCGA and GEO databases to identify prognosis-related ferroptosis genes. Patients were assigned to three clusters (Ferrclusters A, B, and C) based on the cluster analysis of prognostic ferroptosis genes. The principal component analysis (PCA) was performed to build a risk scoring model based on differentially expressed FRGs. Survival analysis revealed that Ferrcluster B LIHC patients had a lower OS rate alongside more severe immune cell infiltration versus Ferrcluster A and C patients; moreover, the LIHC patients in high-ferrscore group had significantly lower survival than the low-ferrscore group. Compared to low-ferrscore patients, Programmed cell death 1 (PD-1) mRNA expression significantly increased, and either PD-1 or PD-1 plus CTLA4 (cytotoxic T-lymphocyte associated protein 4) inhibitors showed unsatisfactory efficacy in high-ferrscore patients. Our study demonstrates the implication of FRGs in prognosis prediction and evaluation of immunotherapy efficacy in LIHC patients.
CNV: Copy Number Variation; CTLA4: cytotoxic T-lymphocyte associated protein 4; FRGs: ferroptosis-related genes; ICIs: immune checkpoint inhibitors; LIHC: liver hepatocellular carcinoma; OS: overall survival; PD-1: programmed cell death 1; PCA: principal component analysis; ROS: reactive oxygen species; TCGA: The Cancer Genome Atlas; TIME: tumor immune microenvironment.