Ovarian cancer is one of the most common malignant tumors of the female reproductive system, which seriously threatens the health of patients. It is of great significance to identify biomarkers to improve the clinical status of ovarian cancer patients.
Methylation, RNA- sequencing, Copy number variation (CNV), mutation and clinical characteristics of ovarian cancer and control samples were downloaded from The Cancer Genome Atlas database (TCGA). The “iClusterPlus”. R package was used to cluster the molecular subtypes. The copy number variation of the entire lncRNA genome was analyzed using GISTIC. The prognosis-associated lncRNA related to CNV was screened as potential targets for ovarian cancer.
Six molecular subtypes were identified based on multi-omics analysis and DElncRNAs are significantly enriched in specific molecular subtypes. The deletion or amplification of lncRNA copy number affects the occurrence and development of ovarian cancer to some extent. Three prognostic-associated lncRNA including LOC101927151, LINC00861 and LEMD1-AS1 were selected. These lncRNAs can be used as biomarkers to predict survival in patients with ovarian cancer. The accuracy of results were verified using the Gene Expression Omnibus (GEO) dataset.
Based on genome-wide copy number variation, prognostic-associated lncRNAs were identified as new biomolecular markers for ovarian cancer.

Copyright © 2019. Published by Elsevier Masson SAS.