Identification of Six N7-Methylguanosine-Related miRNA Signatures to Predict the Overall Survival and Immune Landscape of Triple-Negative Breast Cancer through In Silico Analysis

Abstract

Triple-negative breast cancer (TNBC) is a widely prevalent breast cancer, with a mortality rate of up to 25%. TNBC has a lower survival rate, and the significance of N7-methylguanosine (m7G) modification in TNBC remains unclear. Thus, this study is aimed at investigating m7G-related miRNAs in TNBC patients through in silico analysis. In our research, RNA sequencing and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. The miRNAs targeting typical m7G modification regulators Methyltransferase-like 1 (METTL1) and WD repeat domain 4 (WDR4) were predicted on the TargetScan website. A miRNA risk model was built, and its prognostic value was evaluated by R soft packages. Single-sample gene set enrichment analysis was used to assess immune infiltration, and further expression of immune checkpoints was investigated. As a result, miR-421, miR-5001-3p, miR-4326, miR-1915-3p, miR-3177-5p, and miR-4505 were identified to create the risk model. A nomogram consisting of the stage N and risk model predicted overall survival effectively among TNBC patients. Treg and TIL were shown to be strongly linked to the risk model, and the high-risk group had higher levels of four immune checkpoints expression (CD28, CTLA-4, ICOS, and TNFRSF9). A risk model consisting of m7G-related miRNAs was constructed. The findings of the current study could be used as a prognostic biomarker and can provide a novel immunotherapy insight for TNBC patients.