PLoS One. 2022 Jul 22;17(7):e0271539. doi: 10.1371/journal.pone.0271539. eCollection 2022.
ABSTRACT
Considering the vast biological diversity and high mortality rate in high-grade ovarian cancers, identification of novel biomarkers, enabling precise diagnosis and effective, less aggravating treatment, is of paramount importance. Based on scientific literature data, we selected 80 cancer-related genes and evaluated their mRNA expression in 70 high-grade serous ovarian cancer (HGSOC) samples by Real-Time qPCR. The results were validated in an independent Northern American cohort of 85 HGSOC patients with publicly available NGS RNA-seq data. Detailed statistical analyses of our cohort with multivariate Cox and logistic regression models considering clinico-pathological data and different TP53 mutation statuses, revealed an altered expression of 49 genes to affect the prognosis and/or treatment response. Next, these genes were investigated in the validation cohort, to confirm the clinical significance of their expression alterations, and to identify genetic variants with an expected high or moderate impact on their products. The expression changes of five genes, PROM1, CXCL8, RUNX1, NAV1, TP73, were found to predict prognosis or response to treatment in both cohorts, depending on the TP53 mutation status. In addition, we revealed novel and confirmed known SNPs in these genes, and showed that SNPs in the PROM1 gene correlated with its elevated expression.
PMID:35867729 | DOI:10.1371/journal.pone.0271539
