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Research Paper|Volume 15, Issue 16|pp 8185—8203

Construction of stemness gene score by bulk and single-cell transcriptome to characterize the prognosis of breast cancer

Jun Lin1,2,3, Deyi Feng4, Jie Liu5, Ye Yang6, Xujin Wei7, Wenqian Lin1,2,3, Qun Lin1,2,3
  • 1Department of Anesthesiology, The First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
  • 2Department of Anesthesiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China
  • 3Anesthesiology Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China
  • 4Xiamen University, Xiamen 361100, China
  • 5Department of Endoscopy, Shengli Clinical Medical College of Fujian Medical University, Fuzhou 350001, China
  • 6The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China
  • 7The Graduate School of Fujian Medical University, Fuzhou 350001, China
* Equal contribution
Received: March 15, 2023Accepted: July 17, 2023Published: August 18, 2023
https://doi.org/10.18632/aging.204963

Copyright: © 2023 Lin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Breast cancer (BC) is a heterogeneous disease characterized by significant differences in prognosis and therapy response. Numerous prognostic tools have been developed for breast cancer. Usually these tools are based on bulk RNA-sequencing (RNA-Seq) and ignore tumor heterogeneity. Consequently, the goal of this study was to construct a single-cell level tool for predicting the prognosis of BC patients. In this study, we constructed a stemness-risk gene score (SGS) model based on single-sample gene set enrichment analysis (ssGSEA). Patients were divided into two groups based on the median SGS. Patients with a high SGS scores had a significantly worse prognosis than those with a low SGS, and these groups exhibited differences in several tumor characteristics, such as immune infiltration, gene mutations, and copy number variants. Our results indicate that the SGS is a reliable tool for predicting prognosis and response to immunotherapy in BC patients.