Identification of the prognostic value of ferroptosis-related gene signature in breast cancer patients

BMC Cancer. 2021 May 31;21(1):645. doi: 10.1186/s12885-021-08341-2.

Abstract

Background: Breast cancer (BRCA) is a malignant tumor with high morbidity and mortality, which is a threat to women's health worldwide. Ferroptosis is closely related to the occurrence and development of breast cancer. Here, we aimed to establish a ferroptosis-related prognostic gene signature for predicting patients' survival.

Methods: Gene expression profile and corresponding clinical information of patients from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database. The Least absolute shrinkage and selection operator (LASSO)-penalized Cox regression analysis model was utilized to construct a multigene signature. The Kaplan-Meier (K-M) and Receiver Operating Characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes, Genomes (KEGG) pathway and single-sample gene set enrichment analysis (ssGSEA) were performed for patients between the high-risk and low-risk groups divided by the median value of risk score.

Results: We constructed a prognostic signature consisted of nine ferroptosis-related genes (ALOX15, CISD1, CS, GCLC, GPX4, SLC7A11, EMC2, G6PD and ACSF2). The Kaplan-Meier curves validated the fine predictive accuracy of the prognostic signature (p < 0.001). The area under the curve (AUC) of the ROC curves manifested that the ferroptosis-related signature had moderate predictive power. GO and KEGG functional analysis revealed that immune-related responses were largely enriched, and immune cells, including activated dendritic cells (aDCs), dendritic cells (DCs), T-helper 1 (Th1), were higher in high-risk groups (p < 0.001). Oppositely, type I IFN response and type II IFN response were lower in high-risk groups (p < 0.001).

Conclusion: Our study indicated that the ferroptosis-related prognostic signature gene could serve as a novel biomarker for predicting breast cancer patients' prognosis. Furthermore, we found that immunotherapy might play a vital role in therapeutic schedule based on the level and difference of immune-related cells and pathways in different risk groups for breast cancer patients.

Keywords: Breast cancer; Ferroptosis; Immune status; Prognostic signature.

Publication types

  • Validation Study

MeSH terms

  • Antineoplastic Agents, Immunological / pharmacology
  • Antineoplastic Agents, Immunological / therapeutic use*
  • Biomarkers, Tumor / antagonists & inhibitors
  • Biomarkers, Tumor / genetics*
  • Breast / immunology
  • Breast / pathology
  • Breast Neoplasms / genetics
  • Breast Neoplasms / immunology
  • Breast Neoplasms / mortality*
  • Breast Neoplasms / therapy
  • Datasets as Topic
  • Female
  • Ferroptosis / drug effects
  • Ferroptosis / genetics*
  • Ferroptosis / immunology
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic / drug effects
  • Gene Expression Regulation, Neoplastic / immunology
  • Humans
  • Kaplan-Meier Estimate
  • Middle Aged
  • Predictive Value of Tests
  • Prognosis
  • Protein Interaction Maps / drug effects
  • Protein Interaction Maps / genetics
  • ROC Curve
  • Risk Assessment / methods

Substances

  • Antineoplastic Agents, Immunological
  • Biomarkers, Tumor