A cholesterogenic gene signature for predicting the prognosis of young breast cancer patients

Xiaoping Li; Chaorong Zhou; Chaoran Qiu; Weiwen Li; Qihe Yu; Hui Huang; Yiwen Zhang; Xin Zhang; Liangliang Ren; Xin Huang; Qinghua Zhou

doi:10.7717/peerj.13922

A cholesterogenic gene signature for predicting the prognosis of young breast cancer patients

PeerJ. 2022 Aug 18:10:e13922. doi: 10.7717/peerj.13922. eCollection 2022.

Authors

Xiaoping Li^#^{1

2}, Chaorong Zhou^#³, Chaoran Qiu², Weiwen Li², Qihe Yu⁴, Hui Huang⁵, Yiwen Zhang², Xin Zhang⁶, Liangliang Ren⁶, Xin Huang¹, Qinghua Zhou^{1

7}

Affiliations

¹ Department of Breast Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, China.
² Department of Breast, Jiangmen Central Hospital, Jiangmen, China.
³ Department of Gastrointestinal Surgery, Jiangmen Central Hospital, Jiangmen, China.
⁴ Department of Oncology, Jiangmen Central Hospital, Jiangmen, China.
⁵ Department of Breast Surgery, Jiangmen Maternity & Child Health Care Hospital, Jiangmen, China.
⁶ Clinical Experimental Center, Jiangmen Key Laboratory of Clinical Biobanks and Translational Research, Jiangmen Central Hospital, Jiangmen, China.
⁷ Department of Breast Surgery, The First Affiliated Hospital of Jinan University; The Biomedical Translational Research Institute, Faculty of Medical Science, Jinan University, Guangzhou, China.

^# Contributed equally.

Abstract

Purpose: We aimed to establish a cholesterogenic gene signature to predict the prognosis of young breast cancer (BC) patients and then verified it using cell line experiments.

Methods: In the bioinformatic section, transcriptional data and corresponding clinical data of young BC patients (age ≤ 45 years) were downloaded from The Cancer Genome Atlas (TCGA) database for training set. Differentially expressed genes (DEGs) were compared between tumour tissue (n = 183) and normal tissue (n = 30). By using univariate Cox regression and multi COX regression, a five-cholesterogenic-gene signature was established to predict prognosis. Subgroup analysis and external validations of GSE131769 from the Gene Expression Omnibus (GEO) were performed to verify the signature. Subsequently, in experiment part, cell experiments were performed to further verify the biological roles of the five cholesterogenic genes in BC.

Results: In the bioinformatic section, a total of 97 upregulated genes and 124 downregulated cholesterogenic genes were screened as DEGs in the TCGA for training the model. A risk scoring signature contained five cholesterogenic genes (risk score = -1.169 × GRAMD1C -0.992 × NFKBIA + 0.432 × INHBA + 0.261 × CD24 -0.839 × ACSS2) was established, which could differentiate the prognosis of young BC patients between high-risk and low-risk group (<0.001). The prediction value of chelesterogenic gene signature in excellent with AUC was 0.810 in TCGA dataset. Then the prediction value of the signature was verified in GSE131769 with P = 0.033. In experiment part, although the downregulation of CD24, GRAMD1C and ACSS2 did not significantly affect cell viability, NFKBIA downregulation promoted the viability, colony forming ability and invasion capability of BC cells, while INHBA downregulation had the opposite effects.

Conclusion: The five-cholesterogenic-gene signature had independent prognostic value and robust reliability in predicting the prognosis of young BC patients. The cell experiment results suggested that NFKBIA played a protective role, while INHBA played the pro-cancer role in breast cancer.

Keywords: Breast cancer; Cholesterogenic genes; Differentially expressed genes; Lipid metabolism; Prognostic model.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Breast Neoplasms* / genetics
Cell Line
Cell Survival
Female
Humans
Middle Aged
Prognosis
Reproducibility of Results

Grants and funding

This work was supported by grants from the Guangdong Medical Science Foundation Project (Funding No. B2021016) and The Elite Young Scholars Program of Jiangmen Central Hospital (Funding No. J201905 and No. J201904). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.