Identification of hub genes and upstream regulatory factors based on cell adhesion in triple-negative breast cancer by integrated bioinformatical analysis

Abstract

Background/aim: Triple-negative breast cancer (TNBC) is characterized by metastasis and invasion, as well as poor prognosis, with chemotherapy being the main treatment option. Cell adhesion regulates tumorigenesis and new blood vessel formation. Thus, accurately identifying effective targets for TNBC and cell adhesion is challenging. Herein, we screened for differentially expressed genes between TNBC and normal cancer-free tissues to identify genes contributing to TNBC. Materials and methods: Microarray data were obtained using a comprehensive gene-expression database. We used Database for Annotation, Visualization and Integrated Discovery, Kyoto Encyclopedia of Genes and Genomes and Functional Enrichment (FunRich) to perform Gene Ontology functional enrichment and predict signal pathways. The protein interaction network was predicted using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape v. 3.8.2. for visualization of results. TargetScan, miRanda, miRDB, miRWalk and RNA22 were used to predict miRNAs regulating key genes, and long non-coding RNAs (lncRNAs) regulating miRNAs were predicted using StarBase V2.0 from a comprehensive gene-expression database. Results: Differentially expressed genes were mainly concentrated in the biological process of cell-cell adhesion. The protein-protein interaction network identified eight hub genes: Fibronectin 1 (FN1), Rac family small GTPase 1 (RAC1), heat-shock protein 90 alpha family class B member 1 (HSP90AB1), tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein zeta (YWHAZ), heat-shock protein family A member 8 (HSPA8), IQ motif containing GTPase-activating protein 1 (IQGAP1), CD44 molecule (CD44), and catenin beta 1 (CTNNB1). miRNAs related to TNBC occurrence and development were hsa-miR-142-5p, hsa-miR-144, hsa-miR-28-5p, hsa-miR-548d-3p, hsa-miR-587, hsa-miR-641, and hsa-miR-708. StarBase v2.0 predicted 12 lncRNAs, namely NEAT1, XIST, OIP5-AS1, MALAT1, AL035425.3, NORAD, AL391069.4, AC118758.3, AC026362.1, AC009065.4, AC016876.2, and AC093010.3, as upstream molecules that regulate miRNAs and which may regulate TNBC. Conclusion: Overall, mRNA-miRNA-lncRNA interactions appear to play a role in TNBC development.