AUTHOR=Hu Shaojun , Qu Xiusheng , Jiao Yu , Hu Jiahui , Wang Bo 

TITLE=Immune Classification and Immune Landscape Analysis of Triple-Negative Breast Cancer

JOURNAL=Frontiers in Genetics

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2021.710534

DOI=10.3389/fgene.2021.710534

ISSN=1664-8021

ABSTRACT=Objective: To classify the immunotyping of triple-negative breast cancer (TNBC) using the TCGA database, analyze the differences between subtypes in terms of clinical characteristics and explore the role and clinical significance of immune subtypes in TNBC immunotherapy.
Methods: The collected clinical information data and gene expression data from TNBC patients were downloaded from the cBioPortal and GEO databases. The immune genes were grouped by consensus clustering to obtain immune gene modules and annotate their biological functions. Log-rank tests and univariate and multivariate Cox regression were used to evaluate the prognosis of immune subtypes. Analysis of variance was used to evaluate the correlation between immune subtypes and various immune-related molecular and cellular characteristics. Drug sensitivity analysis was also performed for the differences among immune subtypes in immunotherapy and chemotherapy. In addition, dimension reduction analysis based on graph learning was utilized to reveal the internal structure of the immune system and visualize the distribution of patients.
Results: A total of three immune subtypes (IS1, IS2 and IS3) were identified by typing 299 TNBC samples based on 1702 immune-associated cell genes. Significant differences in prognosis were observed between subtypes, with the best in IS3 and the worst in IS1. Moreover, immune-related genes were divided into 7 functional modules. The distribution of immune subtypes in functional modules was significantly different. Interestingly, the immune subtypes and gene modules were highly reproducible in independent datasets. Analysis of variance indicated that the molecular and cytological characteristics of the immune subtypes were inconsistent, with the highest content of immune cells in IS3. The sensitivity of different immune subtypes to immunotherapy and chemotherapy was found to be different. The better the prognosis was, the higher the sensitivity. In addition, the analysis of the immune landscape suggested intraclass heterogeneity among immune subtypes.
Conclusion: The three identified immune subtypes of TNBC were significantly different in terms of prognosis, gene mutation, immune infiltration, drug sensitivity and heterogeneity. We validated the independent role of immune subtypes in tumor progression and immunotherapy for TNBC. This study provides a new perspective for personalized immunotherapy and the prognosis evaluation of TNBC patients in the future.