Introduction: Axillary nodal metastasis is related to poor prognosis in breast cancer (BC). The metastatic progression in BC is related to molecular signatures. The currently popular methods to evaluate nodal status may give false negatives or give rise to secondary complications. In this study, key candidate genes in BC lymph node metastasis have been identified from publicly available microarray datasets and their roles in BC have been explored through survival analysis and target prediction.
Methods: Gene Expression Omnibus datasets have been analyzed for differentially expressed genes (DEGs) in lymph node-positive BC patients compared to nodal-negative and healthy tissues. The functional enrichment analysis was done in the database for annotation, visualization, and integrated discovery (DAVID). The protein-protein interaction (PPI) network was constructed in the Search Tool for the Retrieval of Interacting Genes and proteins (STRING) and visualized on Cytoscape. The candidate hub genes were identified and their expression analyzed for overall survival (OS) in Gene Expression Profiling Interactive Analysis (GEPIA). The target miRNA and transcription factors were analyzed through miRNet.
Results: A total of 102 overlapping DEGs were found. Gene Ontology revealed eleven, seventeen, and three significant terms for cellular component, biological process, and molecular function respectively. Six candidate genes, DSC3, KRT5, KRT6B, KRT17, KRT81, and SERPINB5 were significantly associated with nodal metastasis and OS in BC patients. A total of 83 targeting miRNA were identified through miRNet and hsa-miR-155-5p was found to be the most significant miRNA which was targeting five out of six hub genes.
Conclusion: In-silico survival and expression analyses revealed six candidate genes and 83 miRNAs, which may be potential diagnostic markers and therapeutic targets in BC patients and miR-155-5p shows promise as it targeted five important hub genes related to lymph-node metastasis.