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Research Paper|Volume 12, Issue 21|pp 21597—21612

Construction and validation of an immunity-related prognostic signature for breast cancer

Tao Zhu1,2, Juyan Zheng1,2, Shuo Hu3, Wei Zhang1,2, Honghao Zhou1,2, Xi Li1,2, Zhao-Qian Liu1,2
  • 1Department of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, and National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, P.R. China
  • 2Institute of Clinical Pharmacology, Engineering Research Center for Applied Technology of Pharmacogenomics of Ministry of Education, Central South University, Changsha 410078, P.R. China
  • 3Department of Nuclear Medicine, Key Laboratory of Biological Nanotechnology of National Health Commission, Xiangya Hospital, Central South University, Changsha 410008, P.R. China
Received: June 9, 2020Accepted: August 8, 2020Published: November 7, 2020
https://doi.org/10.18632/aging.103952

Copyright: © 2020 Zhu 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 is one of the most lethal malignancies among women, and understanding the effects of host immunity on disease progression offers the potential to improve immunotherapies against it. Here, we constructed an immunity-related gene (IRG)-based prognostic signature to stratify breast cancer patients and predict their survival. We identified differentially-expressed genes by analyzing the breast cancer transcriptome data from The Cancer Genome Atlas. Univariate Cox regression revealed 179 survival-correlated IRGs, 12 of which we used to construct an immunity-based prognostic signature that stratified breast cancer patients into high- and low-risk groups. The signature was an independent predictor for survival and was validated in an independent dataset. We also investigated the correlations between our prognostic signature and immune infiltrates and found that signature-derived risk scores correlated negatively with infiltration of B cells, CD4+ T cells, CD8+ T cells, neutrophils and dendritic cells. Our results show that the proposed prognostic signature reflects the tumor immune microenvironment, which makes it a potential indicator for survival that warrants further research to assess its clinical utility.