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Research Paper|Volume 13, Issue 9|pp 12660—12690

Identification of the miRNA signature associated with survival in patients with ovarian cancer

Srinivasulu Yerukala Sathipati1,2,3, Shinn-Ying Ho2,4,5,6
  • 1Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI 54449, USA
  • 2Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan
  • 3Institute of Population Health Sciences, National Health Research Institutes, Miaoli, Taiwan
  • 4Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
  • 5Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
  • 6Center For Intelligent Drug Systems and Smart Bio-devices (IDS2B), National Yang Ming Chiao Tung University, Hsinchu, Taiwan
Received: October 30, 2020Accepted: March 23, 2021Published: April 27, 2021
https://doi.org/10.18632/aging.202940

Copyright: © 2021 Sathipati et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Ovarian cancer is a major gynaecological malignant tumor associated with a high mortality rate. Identifying survival-related variants may improve treatment and survival in patients with ovarian cancer. In this work, we proposed a support vector regression (SVR)-based method called OV-SURV, which is incorporated with an inheritable bi-objective combinatorial genetic algorithm for feature selection to identify a miRNA signature associated with survival in patients with ovarian cancer. There were 209 patients with miRNA expression profiles and survival information of ovarian cancer retrieved from The Cancer Genome Atlas database. OV-SURV achieved a mean correlation coefficient of 0.77±0.01and a mean absolute error of 0.69±0.02 years using 10-fold cross-validation. Analysis of the top ranked miRNAs revealed that the miRNAs, hsa-let-7f, hsa-miR-1237, hsa-miR-98, hsa-miR-933, and hsa-miR-889, were significantly associated with the survival in patients with ovarian cancer. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that four of these miRNAs, hsa-miR-182, hsa-miR-34a, hsa-miR-342, and hsa-miR-1304, were highly enriched in fatty acid biosynthesis, and the five miRNAs, hsa-let-7f, hsa-miR-34a, hsa-miR-342, hsa-miR-1304, and hsa-miR-24, were highly enriched in fatty acid metabolism. The prediction model with the identified miRNA signature consisting of prognostic biomarkers can benefit therapeutic decision making of ovarian cancer.