A genomic and transcriptomic study toward breast cancer - Wang, Shan; Shang, Pei; Yao, Guangyu; Ye, Changsheng; Chen, Lujia; Hu, Xiaolei (Frontiers in Genetics, 2022)
Background: Breast carcinoma is well recognized as having the highest global occurrence rate among all the cancer, being the leading cause of cancer mortality in female. The aim of this study was to elucidate breast cancer at the genomic and transcriptome level in different subtypes so that we can develop more personalized treatments and precision medicine to obtain better outcomes. Method: In this study, an expression profiling dataset downloaded from the Gene Expression Omnibus database, GSE45827, was re-analyzed to compare the expression profiles of breast cancer samples in different subtype. Using GEO2R tool, different expression genes were identified. Using STRING online tool, the protein-protein interaction networks were conducted. Using Cytoscape software, we found modules, seed genes and hub genes and performed pathway enrichment analysis. Kaplan-Meier plotter was used to analyze the overall survival. MicroRNAs and transcription factors targeted different expression genes were predicted by Enrichr web server. Result: The analysis of these elements implied that the carcinogenesis and development of triple negative breast cancer was the most important and complicated one in breast carcinoma, occupying the most different expression genes, modules, seed genes, hub genes and the most complex protein-protein interaction network and signal pathway. Besides, the luminal A subtype might occur in a completely different way from other three subtypes, as the pathways enriched in luminal A subtype had no overlap with the others. We identified 16 hub genes that were related to good prognosis in triple negative breast cancer. Moreover, SRSF1 was negatively correlated with overall survival in Her2 subtype while in the Luminal A subtype it showed the opposite relationship. And in the Luminal B subtype, CCNB1 and KIF23 were associated with poor prognosis. Furthermore, new transcription factors and microRNAs were introduced to breast cancer which would throw light upon breast cancer in a new way and provide novel therapy strategy. Conclusion: We preliminarily delved the potentially comprehensive molecular mechanisms of breast cancer by creating a holistic view at the genomic and transcriptome level in different subtypes using computational tools. We also introduced new prognosis-related genes and novel therapeutic strategy, and cast new light upon breast cancer.