The prognostic significance of a novel ferroptosis-related gene model in breast cancer

Yu-Jie Lu; Yang Gong; Wen-Jing Li; Chen-Yi Zhao; Feng Guo

doi:10.21037/atm-22-479

The prognostic significance of a novel ferroptosis-related gene model in breast cancer

Ann Transl Med. 2022 Feb;10(4):184. doi: 10.21037/atm-22-479.

Authors

Yu-Jie Lu^#¹, Yang Gong^#¹, Wen-Jing Li², Chen-Yi Zhao¹, Feng Guo¹

Affiliations

¹ Department of Oncology, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China.
² Department of Clinical Laboratory, Suzhou Municipal Hospital, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China.

^# Contributed equally.

Abstract

Background: Breast cancer (BRCA) is the most common malignancy with high heterogeneity in women, and the prognostic prediction for BRCA has remained poor. Ferroptosis, a recently identified iron-dependent form of programmed cell death, plays a significant role in BRCA treatment. Some BRCA cell lines are proven to be sensitive to ferroptosis, and some ferroptosis-related genes have been identified as divers or suppressors in the progress of BRCA. This study aimed to explore the prognostic value of ferroptosis-related genes in BRCA.

Methods: A ferroptosis-related gene list, messenger RNA (mRNA) gene expression of BRCA patients, and corresponding clinicopathological data were collected from public databases. The patients of the Cancer Genome Atlas (TCGA) were identified as the training cohort, and the ones of the Gene Expression Omnibus (GEO) were looked as the validation cohort. Univariate Cox regression analysis was utilized to identify prognostic ferroptosis-related genes, and subsequent multivariate analysis further screened out important genes to establish a prognostic model. Receiver operating characteristic (ROC) curves were used to validate the model in both internal and external cohorts. Functional analysis was generated to evaluate the potential correlation between tumor immunity and ferroptosis-related genes in BRCA.

Results: A ferroptosis-related gene signature stratifying patients into 2 risk score groups was established based on the TCGA cohort, and validated in the GEO cohort. Patients with lower risk scores had better overall survival (OS) compared to those with higher risk scores (P<0.001, TCGA cohort; P<0.05, GEO cohort). The risk score was independently associated with the OS of BRCA patients (P<0.001, TCGA cohort; P<0.05, GEO cohort). The area under the curves (AUCs) of the model in the training and validation cohorts were all around 0.7. Immune-related biological pathways and immune status were significantly different between the 2 divided risk groups.

Conclusions: The novel prognostic model composed of 9 ferroptosis-related genes accurately predicts the survival of BRCA patients. It might provide a new sight for ferroptosis-related BRCA therapy.

Keywords: Breast cancer (BRCA); ferroptosis; immunity; prognosis.