Identifying Molecular Mechanisms Driving Ovarian Cancer
Posted: Tuesday, May 19, 2020
An integrated bioinformatics analysis published in the Journal of Ovarian Research reported on the identification of hub genes and therapeutic medications related to ovarian cancer. The study sought to understand “the molecular mechanisms underlying the tumorigenesis and prognosis” of the disease.
“The data may produce new insights regarding [ovarian cancer] pathogenesis and treatment,” concluded Yang Liu, MD, PhD, of China Medical University, and colleagues. “Hub genes and candidate drugs may improve individualized diagnosis and therapy for [ovarian cancer] in the future.”
The analysis utilized four gene-expression profiles (GSE54388, GSE69428, GSE36668, and GSE4595) sourced from the Gene Expression Omnibus. Using GEO2R and FunRich software, 171 differentially expressed genes were identified: 114 were upregulated and 57 were downregulated.
A Gene Ontology analysis revealed that the upregulated differentially expressed genes were primarily responsible for cell division, nuclear activity, and protein binding, whereas downregulated genes were involved in “negative regulation of transcription from RNA polymerase II promoter, protein complex and apicolateral plasma membrane, and glycosaminoglycan binding.” In addition, a relationship was identified between upregulated genes and “metabolic pathways, biosynthesis of antibiotics, biosynthesis of amino acids, cell cycle, and HTLV-I infection.”
A survival analysis of the 10 identified hub genes (KIF4A, CDC20, CCNB2, TOP2A, RRM2, TYMS, KIF11, BIRC5, BUB1B, and FOXM1) found that a high expression of KIF4A, CDC20, CCNB2, TYMS, KIF11, BIRC5, BUB1B, and FOXM1 in patients with ovarian cancer was associated with a worsened progression-free survival. These results were verified using the GEPIA2 database, whereas the DGIdb database was used to identify and select the potentially targeted candidate treatments for ovarian cancer.
Disclosure: The study authors reported no conflicts of interest.