Identification of Potential Key Genes Associated With the Pathogenesis, Metastasis, and Prognosis of Triple-Negative Breast Cancer on the Basis of Integrated Bioinformatics Analysis

Objective: Breast cancer is the most common solid tumor affecting women and the second leading cause of cancer-related death worldwide, and triple-negative breast cancer (TNBC) is the most lethal subtype of breast cancer. We aimed to identify potential TNBC-specific therapeutic targets by performing an integrative analysis on previously published TNBC transcriptome microarray data. Methods: Differentially expressed genes (DEGs) between TNBC and normal breast tissues were screened using six Gene Expression Omnibus (GEO) datasets, and DEGs between metastatic TNBC and non-metastatic TNBC were screened using one GEO dataset. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed on the overlapping DEGs. The Cancer Genome Atlas (TCGA) TNBC data were used to identify candidate genes that were strongly associated with survival. Expression of the candidate genes in TNBC cell lines was blocked or augmented using a lentivirus system, and transwell assays were used to determine their effect on TNBC migration. Results: Eight upregulated genes and nine downregulated genes were found to be differentially expressed both between TNBC and normal breast tissues and between metastatic TNBC and non-metastatic TNBC. Among them, S100P and SDC1 were identified as poor prognostic genes. Furthermore, compared with control cells, SDC1-overexpressing TNBC cells showed enhanced migration ability, whereas SDC1 knockdown markedly reduced the migration of TNBC cells. Conclusion: Our study determined that S100P and SDC1 may be potential treatment targets as well as prognostic biomarkers of TNBC.