Clinical significance and immunogenomic landscape analyses of the immune cell signature based prognostic model for patients with breast cancer

Author:

Wang Shiyuan1,Xiong Yuqiang1,Zhang Qi1,Su Dongqing1,Yu Chunlu2,Cao Yiyin2,Pan Yi1,Lu Qianzi1,Zuo Yongchun3ORCID,Yang Lei1

Affiliation:

1. College of Bioinformatics Science and Technology, Harbin Medical University

2. Public Health College, Harbin Medical University

3. State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University

Abstract

Abstract Breast cancer is one of the most common types of cancers and the leading cause of death from malignancy among women worldwide. Tumor-infiltrating lymphocytes are a source of important prognostic biomarkers for breast cancer patients. In this study, based on the tumor-infiltrating lymphocytes in the tumor immune microenvironment, a risk score prognostic model was developed in the training cohort for risk stratification and prognosis prediction in breast cancer patients. The prognostic value of this risk score prognostic model was also verified in the two testing cohorts and the TCGA pan cancer cohort. Nomograms were also established in the training and testing cohorts to validate the clinical use of this model. Relationships between the risk score, intrinsic molecular subtypes, immune checkpoints, tumor-infiltrating immune cell abundances and the response to chemotherapy and immunotherapy were also evaluated. Based on these results, we can conclude that this risk score model could serve as a robust prognostic biomarker, provide therapeutic benefits for the development of novel chemotherapy and immunotherapy, and may be helpful for clinical decision making in breast cancer patients.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Heilongjiang Province

Harbin Medical University Scientific Research Innovation Fund

Heilongjiang Postdoctoral Research Startup Foundation

Innovative Research Program for Graduates of Harbin Medical University

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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