AUTHOR=Xu Ming , Li Yu , Li Wenhui , Zhao Qiuyang , Zhang Qiulei , Le Kehao , Huang Ziwei , Yi Pengfei 

TITLE=Immune and Stroma Related Genes in Breast Cancer: A Comprehensive Analysis of Tumor Microenvironment Based on the Cancer Genome Atlas (TCGA) Database

JOURNAL=Frontiers in Medicine

VOLUME=Volume 7 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2020.00064

DOI=10.3389/fmed.2020.00064

ISSN=2296-858X

ABSTRACT=Background: Tumor microenvironment is essential for breast cancer progression and metastasis. Our study sets out to examine the stromal and immune infiltration in breast cancer progression, prognosis and treatment.
Materials and Methods: This work provides an approach for quantifying stromal and immune scores by using the ESTIMATE algorithm based on the gene expression matrix of breast cancer patients in the TCGA database. We found differentially expressed genes (DEGs) through the limma R package. Functional enrichments were accessed through Gene Ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Besides, we constructed a protein-protein network, identified several hub genes in Cytoscape and discovered functionally similar genes in GeneMANIA. Hub genes were validated with prognostic data by Kaplan-Meier analysis both in The Cancer Genome Atlas (TCGA) database and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database. Furthermore, their relationship with infiltrating immune cells was evaluated by Tumor IMmune Estimation Resource(TIMER) web tool. Cox regression was utilized for overall survival (OS) and recurrence-free survival (RFS) assessment in order to evaluate the impact of stromal and immune scores on patients prognosis
Results: 1085 breast patients were investigated and 480 differentiated expressed genes(DEGs) were found based on the analysis of mRNA expression profiles. Functional analysis of DEGs revealed their potential functions in immune response and extracellular interaction. The protein-protein interaction network gave evidence of 10 hub genes. Some of the hub genes could be used as predictive markers for patients' prognosis. In this study, we found that tumor purity and specific immune cells infiltration varied in response to hub genes expression. The multivariate Cox regression highlighted the fact that immune score plays a detrimental role in overall survival (HR=0.45, 95%CI: 0.27-0.74, p=0.002) and recurrence-free survival (HR=0.41, 95%CI: 0.22-0.77, p=0.006).
Conclusions: Our findings promote a better understanding of the mechanisms behind the regulation of tumor microenvironment and cell infiltration. Immune score should be considered as a prognostic factor for patients’ survival and prognosis.