Research Paper Volume 13, Issue 9 pp 12660—12690
Identification of the miRNA signature associated with survival in patients with ovarian cancer
- 1 Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI 54449, USA
- 2 Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan
- 3 Institute of Population Health Sciences, National Health Research Institutes, Miaoli, Taiwan
- 4 Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
- 5 Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
- 6 Center For Intelligent Drug Systems and Smart Bio-devices (IDS2B), National Yang Ming Chiao Tung University, Hsinchu, Taiwan
Received: October 30, 2020 Accepted: March 23, 2021 Published: April 27, 2021
https://doi.org/10.18632/aging.202940How to Cite
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.