Identification and validation of potential prognostic and predictive miRNAs of epithelial ovarian cancer

TY - JOUR

T1 - Identification and validation of potential prognostic and predictive miRNAs of epithelial ovarian cancer

AU - Prahm, Kira Philipsen

AU - Høgdall, Claus

AU - Karlsen, Mona Aarenstrup

AU - Christensen, Ib Jarle

AU - Novotny, Guy Wayne

AU - Høgdall, Estrid

PY - 2018/11

Y1 - 2018/11

N2 - 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.

AB - 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.

KW - Adult

KW - Aged

KW - Aged, 80 and over

KW - Carcinoma, Ovarian Epithelial/genetics

KW - Databases, Nucleic Acid

KW - Disease-Free Survival

KW - Female

KW - Gene Expression Profiling

KW - Humans

KW - MicroRNAs/biosynthesis

KW - Middle Aged

KW - Oligonucleotide Array Sequence Analysis

KW - Ovarian Neoplasms/genetics

KW - RNA, Neoplasm/biosynthesis

KW - Survival Rate

U2 - 10.1371/journal.pone.0207319

DO - 10.1371/journal.pone.0207319

M3 - Journal article

C2 - 30475821

SN - 1932-6203

VL - 13

JO - PLoS Computational Biology

JF - PLoS Computational Biology

IS - 11

M1 - e0207319

ER -