Oxidative stress genes define two subtypes of triple-negative breast cancer with prognostic and therapeutic implications

Shenting Liu; He Xu; Ying Feng; Ulf D Kahlert; Renfei Du; Luz Angela Torres-de la Roche; Kai Xu; Wenjie Shi; Fanshuai Meng

doi:10.3389/fgene.2023.1230911

Oxidative stress genes define two subtypes of triple-negative breast cancer with prognostic and therapeutic implications

Front Genet. 2023 Jul 13:14:1230911. doi: 10.3389/fgene.2023.1230911. eCollection 2023.

Authors

Shenting Liu¹, He Xu², Ying Feng², Ulf D Kahlert³, Renfei Du³, Luz Angela Torres-de la Roche⁴, Kai Xu², Wenjie Shi³, Fanshuai Meng⁵

Affiliations

¹ Department of Oncology Medicine, Hainan Cancer Hospital, Haikou, Hainan, China.
² Department of Thyroid and Breast Surgery, Xuzhou Municipal Hospital Affiliated to Xuzhou Medical University, Xuzhou, China.
³ Molecular and Experimental Surgery, University Clinic for General- Visceral- Vascular- and Trans-Plantation Surgery, Medical Faculty University Hospital Magdeburg, Otto-von Guericke University Magdeburg, Germany.
⁴ University Hospital for Gynecology, Pius-Hospital, University Medicine Oldenburg, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.
⁵ Translational and Trauma Surgery Laboratory, University of Ulm, Ulm, Germany.

Abstract

Introduction: Oxidative stress (OS)-related genes have been confirmed to be closely related to the prognosis of triple-negative breast cancer (TNBC) patients; despite this fact, there is still a lack of TNBC subtype strategies based on this gene guidance. Here, we aimed to explore OS-related subtypes and their prognostic value in TNBC. Methods: Data from The Cancer Genome Atlas (TCGA)-TNBC and Sequence Read Archive (SRA) (SRR8518252) databases were collected, removing batch effects using a combat method before analysis. Consensus clustering analysis identified two OS subtypes (clusters A and B), with cluster A showing a better prognosis. Immune infiltration characteristics were analyzed using ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) algorithms, revealing higher ImmuneScore and ESTIMATEscore in cluster A. Tumor-suppressive immune cells, human leukocyte antigen (HLA) genes, and three immune inhibitors were more prevalent in cluster A. Results: An eight-gene signature, derived from differentially expressed genes, was developed and validated as an independent risk factor for TNBC. A nomogram combining the risk score and clinical variables accurately predicted patient outcomes. Finally, we also validated the classification effect of subtypes using hub markers of each subtype in the test dataset. Conclusion: Our study reveals distinct molecular clusters based on OS-related genes to better clarify the reactive oxygen species (ROS)-mediated progression and the crosstalk between the ROS and tumor microenvironment (TME) in this heterogenetic disease, and construct a risk prognostic model which could provide more support for clinical treatment decisions.

Keywords: immunotherapy; molecular subtype; oxidative stress; relapse-free survival; triple-negative breast cancer; tumor microenvironment.