Identification of a novel signature with prognostic value in triple-negative breast cancer through clinico-transcriptomic analysis

Chao Chen; Cai-Jin Lin; Si-Yuan Li; Xin Hu; Zhi-Ming Shao

doi:10.21037/atm-22-1931

Identification of a novel signature with prognostic value in triple-negative breast cancer through clinico-transcriptomic analysis

Ann Transl Med. 2022 Oct;10(20):1095. doi: 10.21037/atm-22-1931.

Authors

Chao Chen^#^{1

2

3}, Cai-Jin Lin^#^{1

2

3}, Si-Yuan Li^#^{1

2

3}, Xin Hu^{1

2

3}, Zhi-Ming Shao^{1

2

3}

Affiliations

¹ Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
² Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai, China.
³ Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.

^# Contributed equally.

Abstract

Background: Although perceived as a highly aggressive disease, triple-negative breast cancer (TNBC) constitutes heterogeneous features with various outcomes. In this study, we aimed to establish a prognostic signature for patients with TNBC to improve risk stratification.

Methods: Gene expression data were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) were detected pairwise between TNBC and other subtypes of samples. Then, TNBC-correlated modules were determined using coexpression network analysis. A gene signature was established based on the prognostic genes in the intersection between DEGs and selected gene modules using least absolute shrinkage and selection operator (LASSO) Cox regression. Finally, a clinico-transcriptomic signature was developed to predict overall survival (OS). Model performance was quantified, and the bootstrap resampling method was used for validation.

Results: The gene signature included 6 messenger RNAs (mRNAs) and a clinical score indicating an increased likelihood of death when used as continuous or categorical predictors. A nomogram was built by integrating the pathological stage and gene signature to predict 2-, 3-, and 5-year OS. The addition of pathological stage increased the concordance index (C-index) compared with pathological stage alone and the gene signature alone. Bootstrap resampling revealed a stable performance of the nomogram.

Conclusions: A 6-mRNA signature was established to inform prognosis for patients with TNBC. Its combination with pathological stage can contribute to improving performance and provide additional supporting evidence for clinical decision-making.

Keywords: The Cancer Genome Atlas (TCGA); Triple-negative breast cancer (TNBC); WGCNA; prognosis; transcriptome analysis.