An Epithelial-Mesenchymal Transition-Related LncRNA Signature Predicts Prognosis in Triple-Negative Breast Cancer

Abstract

Objective: This study aimed to identify a prognostic epithelial-mesenchymal transition (EMT)-correlated long noncoding RNA (lncRNA) signature in triple-negative breast cancer (TNBC). Methods: Gene expression data of TNBC were obtained from TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus) databases. EMT-related genes were searched using MSigDB. Differentially expressed (DE) EMT-related mRNAs and DE-lncRNAs were selected between tumor and normal samples, followed by correlation analysis to analyze EMT-correlated lncRNAs. Based on the EMT-correlated lncRNAs obtained, a risk score (RS) model was established, and the samples were divided into low- and high-risk groups based on the RS value. The prognosis, tumor microenvironment, and pathways were compared between the two groups. Four EMT-correlated lncRNAs (MIR22HG, HOXB-AS1, LINC00511, and AC097713.3) were screened to construct an RS model after multistep bioinformatics analyses. The samples in both datasets were divided into low- and high-risk groups. The overall survival of the samples in the low-risk group was significantly better than that in the high-risk group. Immune infiltration levels, expression of immune checkpoint genes, major histocompatibility complex (MHC), and costimulatory and coinhibitory molecule genes significantly differed between the two groups. Finally, a nomogram model significantly associated with the prognosis of patients with TNBC was constructed. Conclusions: Our study developed an EMT-related four-lncRNA signature that can predict the prognosis of TNBC and may serve as a treatment target for TNBC.