Identification of potential key genes and their regulatory microRNAs and transcription factors in lymph node and skin metastasis in breast cancer using in silico analysis. (Preprint)

Abstract

Breast cancer with metastasis like lymph node and skin metastasis represents a significant cause of morbidity and mortality in patients. Patients with lymph node metastasis (LNM) has poor prognosis of the disease and likewise skin metastases may impair the quality of life due to physical appearance, odour, and bleeding. So therefore, it urgent to elucidate the key genes and pathways involved in lymph node and skin metastasis of breast cancer and its prognosis.

In the present study, we aimed to identify the key genes that are involved in both lymph node and skin metastasis from the publicly available datasets and through survival analysis their role has been identified in breast cancer.

GSE29431 and GSE53752 microarray gene expression datasets were obtained from the GEO (Gene Expression Omnibus) database, which included LNM and skin metastasis samples of breast cancer. Differentially expressed genes (DEGs) were obtained between lymph node and skin metastasis through GEO2R tool. Bioinformatical methods including Gene Ontology (GO) functional annotation analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using database for annotation, visualization and integrated discovery (DAVID) with the screened DEGs. The protein-protein interaction (PPI) network of the DEGs was constructed through Search Tool for the Retrieval of Interacting Genes database (STRING) website, and visualized through Cytoscape and HUB genes were identified Molecular Complex Detection (MCODE) and cytoHubba. Hub genes expression was analyzed for overall survival (OS) through Gene Expression Profiling Interactive Analysis (GEPIA). Their targeting miRNAs and transcription factors (TFs) were identified using mirNet.

In total 156 DEGs were identified. The GO function and KEGG pathway enrichment analyses indicated that these DEGs were enriched in extracellular matrix organisation, positive regulation of cell migration, immunoglobulin receptor binding, Wnt-protein binding. PPI was established with 142 nodes, 155 edges and through MCODE and Cytohubba thirteen Hub genes were identified. Four candidate genes MS4A1, CD79A, VPREB3, FCRLA had worse overall survival (OS) in breast cancer. A total 34miRNAs and 121TFs that target the candidate genes were identified through mirNet and hsa-mir-335-5p is found to be most significant miRNA that target three out of four hub genes.

Our study suggests that the four hub genes (MS4A1, CD79A, VPREB3, FCRLA) and 34 miRNAs are associated with lymph node and skin metastasis of breast cancer which can be a potential biomarker for therapeutics.