Identification of Hub Genes in Triple-negative Breast Cancer by Integrated Bioinformatics Analysis

Overview

Journal Gland Surg

Publisher AME Publishing Company

Specialty Endocrinology

Date 2021 Mar 12

PMID 33708561

Citations 9

Authors

Li-Min Wei

Xin-Yang Li

Zi-Ming Wang

Yu-Kun Wang

Ge Yao

Jia-Hao Fan

Xin-Shuai Wang

Affiliations

Soon will be listed here.

Abstract

Background: Triple negative breast cancer (TNBC) is usually aggressive and accompanied by a poor prognosis. The molecular biological mechanism of TNBC pathogenesis is still unclear, and requires more detailed research. The aim of this study was to screen and verify potential biomarkers of TNBC, and provide new clues for the treatment and diagnosis of TNBC.

Methods: In this work, GSE76250 was downloaded from the Gene Expression Omnibus (GEO) database and included 165 TNBC samples and 33 paired normal breast tissues. The R software and its related software package were used for data processing and analysis. Compared with normal tissues, genes with a false discovery rate (FDR) <0.01 and log fold change (logFC) ≥1 or ≤-1 were identified as differentially expressed genes (DEGs) by limma package. Survival prognoses were analyzed by Kaplan-Meier plotter database.

Results: In total, 160 up-regulated and 180 down-regulated genes were identified. The biological mechanism of enrichment analysis presented that DEGs were significantly enriched in chromosome segregation, extracellular matrix, and extracellular matrix structural constituent, among others. A total of 8 hub genes ( and ) were identified by the protein-protein interaction network (PPIN) and Cytoscape software. Survival prognosis of these hub genes showed that they were negatively correlated with overall survival.

Conclusions: The 8 hub genes and pathways that were identified might be involved in tumorigenesis and become new candidate biomarkers for TNBC treatment.

Citing Articles

Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer.

Alam M, Sultana A, Kibria M, Khanam A, Wang G, Haque Mollah M Bioinform Biol Insights. 2024; 18:11779322241272386.

PMID: 39239087 PMC: 11375675. DOI: 10.1177/11779322241272386.

Dual TTK/PLK1 inhibition has potent anticancer activity in TNBC as monotherapy and in combination.

Zanini E, Forster-Gross N, Bachmann F, Brungger A, McSheehy P, Litherland K Front Oncol. 2024; 14:1447807.

PMID: 39184047 PMC: 11341980. DOI: 10.3389/fonc.2024.1447807.

Transcriptomic analysis revealed potential regulatory biomarkers and repurposable drugs for breast cancer treatment.

Shornale Akter M, Uddin M, Rahman S, Hossain M, Ashik M, Zaman N Cancer Rep (Hoboken). 2024; 7(5):e2009.

PMID: 38717954 PMC: 11078332. DOI: 10.1002/cnr2.2009.

Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer.

Tuly K, Hossen M, Islam M, Kibria M, Alam M, Harun-Or-Roshid M Medicina (Kaunas). 2023; 59(10).

PMID: 37893423 PMC: 10608013. DOI: 10.3390/medicina59101705.

Predicting the molecular mechanism-driven progression of breast cancer through comprehensive network pharmacology and molecular docking approach.

Vyas B, Kumar S, Bhowmik R, Akhter M Sci Rep. 2023; 13(1):13729.

PMID: 37607964 PMC: 10444824. DOI: 10.1038/s41598-023-40684-7.

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