Open AccessIdentification and validation of potential prognostic and predictive miRNAs of epithelial ovarian cancer
Author(s) -
Kira Philipsen Prahm,
Claus Høgdall,
Mona Aarenstrup Karlsen,
Ib Jarle Christensen,
Guy Wayne Novotny,
Estrid Høgdall
Publication year - 2018
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0207319
Subject(s) - ovarian cancer , oncology , medicine , proportional hazards model , microrna , microarray , cancer , chemotherapy , epithelial ovarian cancer , biology , gene expression , gene , biochemistry
Background Ovarian cancer is the leading cause of death by gynecologic cancers in the Western world. The aim of the study was to identify microRNAs (miRNAs) associated with prognosis and/or resistance to chemotherapy among patients with epithelial ovarian cancer. Methods Using information from the Pelvic Mass Study we identified a cohort of women with epithelial ovarian cancer. Tumor tissues were then collected and analyzed by global miRNA microarrays. MiRNA profiling was then linked to survival and time to progression using Cox proportional-hazards regression models. Logistic regression models were used for the analysis of resistance to chemotherapy. Our results were validated using external datasets retrieved from the NCBI Gene Expression Omnibus database. Results A total of 197 patients with epithelial ovarian cancer were included for miRNA microarray analysis. In multivariate analyses we identified a number of miRNAs significantly correlated with overall survival (miR-1183 (HR: 1.42, 95% CI:1.17–1.74, p = 0.0005), miR-126-3p (HR: 1.38, 95% CI:1.11–1.71, p = 0.0036), time to progression (miR-139-3p (HR: 1.48, 95% CI: 1.13–1.94, p = 0.0047), miR-802 (HR: 0.48, 95% CI: 0.29–0.78, p = 0.0035)), progression free survival (miR-23a-5p (HR:1.32, 95% CI:1.09–1.61, p = 0.004), miR-23a-3p (HR:1.70, 95% CI:1.15–2.51, p = 0.0074), miR-802 (HR: 0.48, 95% CI: 0.29–0.80, p = 0.0048)), and resistance to chemotherapy (miR-1234 (HR: 0.26, 95% CI: 0.11–0.64, p = 0.003)). A few miRNAs identified in our training cohort, were validated in external cohorts with similar results. Conclusion Eight miRNAs were identified as significant predictors of overall survival, progression free survival, time to progression, and chemotherapy resistance. A number of these miRNAs were significantly validated using external datasets. Inter-platform and inter-laboratory variations may have influence on the ability to compare and reproduce miRNA results. The use of miRNAs as potential markers of relapse and survival in ovarian cancer warrants further investigation.