Hub genes associated with immune cell infiltration in breast cancer, identified through bioinformatic analyses of multiple datasets.

ABSTRACT:

Objective

The aim of this study was to identify hub genes associated with immune cell infiltration in breast cancer through bioinformatic analyses of multiple datasets.

Methods

Nonparametric (NOISeq) and robust rank aggregation-ranked parametric (EdgeR) methods were used to assess robust differentially expressed genes across multiple datasets. Protein-protein interaction network, GO, KEGG enrichment, and sub-network analyses were performed to identify immune-associated hub genes in breast cancer. Immune cell infiltration was evaluated with the CIBERSORT, XCELL, and TIMER methods. The association between the hub gene-based risk signature and survival was determined through Kaplan-Meier survival analysis, multivariate Cox analysis, and a nomogram with external verification.

SUBMITTER: Zhao H 

PROVIDER: S-EPMC9500228 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature