Retrospective Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Mar 24, 2024; 15(3): 391-410
Published online Mar 24, 2024. doi: 10.5306/wjco.v15.i3.391
Ferroptosis biomarkers predict tumor mutation burden's impact on prognosis in HER2-positive breast cancer
Jin-Yu Shi, Xin Che, Rui Wen, Si-Jia Hou, Yu-Jia Xi, Yi-Qian Feng, Ling-Xiao Wang, Shi-Jia Liu, Wen-Hao Lv, Ya-Fen Zhang
Jin-Yu Shi, Shi-Jia Liu, Wen-Hao Lv, Ya-Fen Zhang, Department of Breast Surgery, The Fifth Hospital of Shanxi Medical University, Taiyuan 030000, Shanxi Province, China
Jin-Yu Shi, Xin Che, Ling-Xiao Wang, Shi-Jia Liu, Wen-Hao Lv, The Fifth Clinical Medical College, Shanxi Medical University, Taiyuan 030000, Shanxi Province, China
Xin Che, Ling-Xiao Wang, Department of Colorectal Surgery, The Fifth Hospital of Shanxi Medical University, Taiyuan 030000, Shanxi Province, China
Rui Wen, College of Pharmacy, Shanxi Medical University, Taiyuan 030000, Shanxi Province, China
Si-Jia Hou, Department of Neurology, The First Hospital of Shanxi Medical University, Taiyuan 030000, Shanxi Province, China
Yu-Jia Xi, Department of Urology, The Second Hospital of Shanxi Medical University, Taiyuan 030000, Shanxi Province, China
Yi-Qian Feng, Department of Breast Surgery, The First Hospital of Shanxi Medical University, Taiyuan 030000, Shanxi Province, China
Author contributions: All authors participated in the conception and design of the study; conceptualization: Shi JY, Zhang YF, Wang LX; Methodology: Wen R, Shi JY, Formal analysis and investigation: Wen R, Hou SJ, Shi JY, and Che X; Writing - original draft preparation: Feng YQ and Xi YJ; Writing - review and editing: Liu SJ and Lv WH; Funding acquisition: Zhang YF; Resources: Zhang YF; Supervision: Zhang YF and Wang LX; All authors read and approved the paper.
Supported by The Science and Technology Commission of Shanxi province, No. 201901D111428.
Institutional review board statement: The study was reviewed and approved by the Shanxi Provincial People's Hospital Institutional Review Board, Approval No. 2022-240.
Informed consent statement: All study participants or their legal guardians provided informed written consent before enrollment.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: The public datasets to support the results can be obtained from TCGA (https://portal.gdc.cancer.gov/), METABRIC (www.cbioportal.org/), GTEx (https://gtexportal.org/home/datasets), FerrDb (http://www.zhounan.org/ferrdb/current/), GDSC (https://www.cancerrxgene.org/celllines) and GEO database (https://www.ncbi.nlm.nih.gov/geo/).
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Ya-Fen Zhang, MD, Chief Doctor, Department of Breast Surgery, The Fifth Hospital of Shanxi Medical University, Shuangta West Street, Yingze District, Taiyuan 030000, Shanxi Province, China. cocoren2005@163.com
Received: October 17, 2023
Peer-review started: October 17, 2023
First decision: December 31, 2023
Revised: January 14, 2024
Accepted: February 3, 2024
Article in press: February 3, 2024
Published online: March 24, 2024
Processing time: 156 Days and 20 Hours
ARTICLE HIGHLIGHTS
Research background

Our study identified a 4-gene model that, when combined with the tumor mutation burden (TMB) score, may have critical implications for clinical medical decisions and personalized treatment of patients with HER2-positive breast cancer.

Research motivation

This study aimed to identify and evaluate fresh ferroptosis-related biomarkers for HER2+ breast cancer (BC).

Research objectives

Identifying reliable prognostic biomarkers can direct clinical practice and help develop a more individualized clinical follow-up approach.

Research methods

The prediction model was constructed using data from the TCGA and METABRIC databases. Subsequently, patients were categorized into high-risk and low-risk groups according to their median risk scores, independent predictors for overall survival (OS). We investigated immune infiltration, mutations, and drug sensitivity across risk groups. Moreover, we integrated tumor mutational burden (TMB) with risk scores to assess patient prognosis. Finally, we analyzed vital gene expression through single-cell RNA sequencing (scRNA-seq) in cancerous and normal epithelial cells.

Research results

Our model helps guide the prognosis of HER2+ breast cancer patients, and its combination with the TMB can aid in more accurate assessment of patient prognosis and provide new ideas for further diagnosis and treatment.

Research conclusions

By analyzing the RNA expression data of HER2-positive breast cancer patients, we constructed a risk score model (PROM2, SLC7A11, FANCD2, and FH) for ferroptosis and evaluated the relationship between the high-risk score and patient prognosis. We verified that the high-risk group was associated with poorer immune infiltration and a greater tumor mutation load. By combining the risk score with the TMB, we found that patients with a high TMB-score had the worst prognosis, while patients with a low TMB-score had the best prognosis.

Research perspectives

The prediction model was constructed using data from the TCGA and METABRIC cohorts. Patients were subsequently categorized into high-risk and low-risk groups according to their median risk score, an independent predictor of overall survival. We investigated immune infiltration, mutations, and drug sensitivity across risk groups. Moreover, we integrated the TMB with risk scores to assess patient prognosis. Finally, we analyzed vital gene expression through single-cell RNA sequencing in cancerous and normal epithelial cells.