A Novel Necroptosis-Related miRNA Signature for Predicting the Prognosis of Breast Cancer Metastasis

Author:

Zheng Lin1ORCID,Wang Jie1ORCID,Jiang Hongnan2ORCID,Dong Honglin1ORCID

Affiliation:

1. Department of Vascular Surgery, The Second Hospital of Shanxi Medical University, Taiyuan, China

2. Department of Breast Surgery, The Second Hospital of Shanxi Medical University, Taiyuan, China

Abstract

Objective. Necroptosis was recently identified as a form of programmed cell death that plays an essential role in breast cancer metastasis. MicroRNAs (miRNAs) have long been recognized to affect cell death and tumor growth. In this study, we aimed to screen for necroptosis-associated miRNAs that predict breast cancer metastasis. Method. This study used The Cancer Genome Atlas (TCGA) public database to obtain miRNA expression data and associated clinical data from breast cancer patients and then retrieved miRNA data related to necrosis and apoptosis. Next, using Cox regression model analysis (univariate or multivariate) as well as a comparison analysis (differential analysis), a prognostic multi-miRNA molecular marker was established. Finally, prognosis-related miRNAs were utilized to identify target genes, and the functions of the target genes were analyzed for enrichment to investigate the probable mechanisms of the miRNAs. Results. Ten miRNAs were screened through differential analysis to build models: hsa-miR-148a-3p, hsa-miR-223-3p, hsa-miR-331-3p, has-miR-181a-5p, hsa-miR-181b-5p, hsa-miR-181c-5p, hsa-miR-181d-5p, hsa-miR-200a-5p, hsa-miR-141-3p, and hsa-miR-425-5p. The multivariate Cox regression model was an independent prognostic factor (univariate Cox regression results: HR = 3.2642 , 95 % CI = 1.5773 6.7554 , P = 0.0014 ; multivariate Cox regression results: HR = 3.1578 , 95 % CI = 1.5083 6 , P = 0.0023 ). The survival curve of the risk score also revealed that patients with a high risk score had a poor prognosis ( P = 2 e 04 ). The receiver operating characteristic (ROC) curve showed that the model has a certain prediction ability. Batch survival analysis of the miRNAs in the model was conducted and showed that hsa-miR-331-3p ( P = 0.0182 ) was strongly associated with prognosis. Twenty-three predicted target genes were obtained, and Gene Ontology (GO) enrichment analysis showed that these target genes were strongly enriched in transcriptional initiation and cell membrane trafficking. Conclusion. Our research identified a novel miRNA marker for predicting breast cancer patient prognosis and lays the groundwork for future research on necroptosis-related genes.

Publisher

Hindawi Limited

Subject

Biochemistry (medical),Clinical Biochemistry,Genetics,Molecular Biology,General Medicine

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