Clinical and Translational Research
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Feb 6, 2024; 12(4): 700-720
Published online Feb 6, 2024. doi: 10.12998/wjcc.v12.i4.700
Identification and validation of a new prognostic signature based on cancer-associated fibroblast-driven genes in breast cancer
Zi-Zheng Wu, Yuan-Jun Wei, Tong Li, Jie Zheng, Yin-Feng Liu, Meng Han
Zi-Zheng Wu, Yuan-Jun Wei, Tong Li, Jie Zheng, Yin-Feng Liu, Meng Han, Breast Disease Diagnosis and Treatment Center, The First Hospital of Qinhuangdao, Qinhuangdao 066000, Hebei Province, China
Yuan-Jun Wei, Meng Han, Department of General Surgery, Hebei Medical University, Shijiazhuang 050000, Hebei Province, China
Yuan-Jun Wei, Meng Han, Breast Disease Diagnosis and Treatment Center, The First Hospital of Qinhuangdao, Hebei Medical University, Qinhuangdao 066000, Hebei Province, China
Tong Li, Breast Disease Diagnosis and Treatment Center, Chengde Medical College, Chengde 067000, Hebei Province, China
Co-first authors: Zi-Zheng Wu and Yuan-Jun Wei.
Author contributions: Han M conceived and designed the study and reviewed the manuscript; Wu ZZ, Wei YJ and Zheng J collected, arranged, and analyzed the data and wrote the manuscript; Li T, Liu YF designed and prepared the figures and tables; All authors reviewed and approved the final manuscript. The reasons for designating Wu ZZ and Wei YJ as co-first authors are threefold. First, the research was performed as a collaborative effort, and the designation of co corresponding authorship accurately reflects the distribution of responsibilities and burdens associated with the time and effort required to complete the study and the resultant paper. This also ensures effective communication and management of post-submission matters, ultimately enhancing the paper's quality and reliability. Second, the overall research team encompassed authors with a variety of expertise and skills from different fields, and the designation of co-first authors best reflects this diversity. This also promotes the most comprehensive and in-depth examination of the research topic, ultimately enriching readers' understanding by offering various expert perspectives. Third, Wu ZZ and Wei YJ contributed efforts of equal substance throughout the research process. The choice of these researchers as co-first authors acknowledges and respects this equal contribution, while recognizing the spirit of teamwork and collaboration of this study. In summary, we believe that designating Wu ZZ and Wei YJ as co-first authors of is fitting for our manuscript as it accurately reflects our team's collaborative spirit, equal contributions, and diversity.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of the First Hospital of Qinhuangdao.
Informed consent statement: All study participants or their legal guardians provided written informed consent before study enrollment.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: Publicly available datasets were analyzed in this study, these can be found in Xena (https://xenabrowser.net), GEO database (www.ncbi.nlm.gov/geo; GSE96058, GSE18728, and GSE21653).
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: Meng Han, MD, Director, Breast Disease Diagnosis and Treatment Center, The First Hospital of Qinhuangdao, No. 258 Wenhua Road, Haigang District, Qinhuangdao 066000, Hebei Province, China. menghan68527@163.com
Received: December 1, 2023
Peer-review started: December 1, 2023
First decision: December 7, 2023
Revised: December 14, 2023
Accepted: January 3, 2024
Article in press: January 3, 2024
Published online: February 6, 2024
Processing time: 54 Days and 18 Hours
ARTICLE HIGHLIGHTS
Research background

Breast cancer (BC), a leading malignant disease, affects women all over the world. It is still urgent to explore new biomarkers to estimate and enhance prognosis of BC patients.

Research motivation

The present study for the first time investigated the 8 cancer associated fibroblasts (CAFs)-associated genes as the potential biomarkers of the prognosis of patients using bioinformatics.

Research objectives

This study aims to establish a CAFs-associated prognostic signature to improve BC patient outcome estimation.

Research methods

We retrieved the transcript profile and clinical data of 1072 BC samples from The Cancer Genome Atlas (TCGA) databases, and 3661 BC samples from the The Gene Expression Omnibus. CAFs and immune cell infiltrations were quantified using CIBERSORT algorithm. CAF-associated gene identification was done by weighted gene co-expression network analysis. A CAF risk signature was established via univariate, LASSO regression, and multivariate Cox regression analyses. The receiver operating characteristic (ROC) and Kaplan-Meier curves were employed to evaluate the predictability of the model. Subsequently, a nomogram was developed with the risk score and patient clinical signature. Using Spearman's correlations analysis, the relationship between CAF risk score and gene set enrichment scores were examined.

Patient samples were collected to validate gene expression by quantitative real-time polymerase chain reaction (qRT-PCR).

Research results

Employing an 8-gene (IL18, MYD88, GLIPR1, TNN, BHLHE41, DNAJB5, FKBP14, and XG) signature, we attempted to estimate BC patient prognosis. Based on our analysis, high-risk patients exhibited worse outcomes than low-risk patients. Multivariate analysis revealed the risk score as an independent indicator of BC patient prognosis. ROC analysis exhibited satisfactory nomogram predictability. The AUC showed 0.805 at 3 years, and 0.801 at 5 years in the TCGA cohort. We also demonstrated that a reduced CAF risk score was strongly associated with enhanced chemotherapeutic outcomes. CAF risk score was significantly correlated with most hallmark gene sets. Finally, the prognostic signature were further validated by qRT-PCR.

Research conclusions

We introduced a newly-discovered CAFs-associated gene signature, which can be employed to estimate BC patient outcomes conveniently and accurately.

Research perspectives

The mechanisms of 8 CAFs-associated genes in BC is still unclear, which needs further confirmation through molecular biology and clinical experiments.