Computer Science
Computational identification of key pathways and differentially-expressed gene signatures in ovarian cancer stem cells
Renata Fu
Computer Science
Renata Fu
Cancer stem cells (CSCs) are a tumor cell type capable of self-renewal and differentiation and believed to be responsible for metastasis, therapy resistance, and tumor relapse. Therefore, targeting CSCs could be a promising therapy strategy to improve the outcome of cancer patients, and this requires identification of therapeutic targets genes and pathways for CSCs. In the present study, I sought to identify commonly enriched pathways and differentially-expressed genes in ovarian CSCs. Using three publicly available datasets from the Gene Expression Omnibus (GEO), I identified 6 common, potentially regulatory pathways and differentially-expressed genes that could be used to target ovarian CSCs. Several established signaling pathways, such as the MAPK pathway and the Wnt pathway, were found to be enriched in ovarian CSCs. In addition, I found that the Arrhythmogenic right ventricular cardiomyopathy pathway is enriched in ovarian CSCs, suggesting a novel regulatory mechanism for this cell population. I identified four genes, ITGB1, TUBB2B, CXCL2, and SORBS2, that are differentially expressed in ovarian CSCs across all three GEO datasets, indicating that this gene expression signature might be used to target CSCs in epithelial ovarian cancers.