Identification and Analysis of An Epigenetically Regulated Five-lncRNA Signature Associated With Outcome and Chemotherapy Response in Ovarian Cancer

Hao Yang; Lin Gao; Meiling Zhang; Ning Ning; Yan Wang; Di Wu; Xiaomei Li

doi:10.3389/fcell.2021.644940

Identification and Analysis of An Epigenetically Regulated Five-lncRNA Signature Associated With Outcome and Chemotherapy Response in Ovarian Cancer

Front Cell Dev Biol. 2021 Feb 23:9:644940. doi: 10.3389/fcell.2021.644940. eCollection 2021.

Authors

Hao Yang¹, Lin Gao², Meiling Zhang³, Ning Ning³, Yan Wang³, Di Wu³, Xiaomei Li⁴

Affiliations

¹ Department of Radiation Oncology, Inner Mongolia Cancer Hospital and The Affiliated People's Hospital of Inner Mongolia Medical University, Hohhot, China.
² Institute for Endemic Fluorosis Control, Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, China.
³ Department of Obstetrics and Gynecology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
⁴ Department of Pathology, Harbin Medical University Cancer Hospital, Harbin, China.

Abstract

The deregulation of long non-coding RNAs (lncRNAs) by epigenetic alterations has been implicated in cancer initiation and progression. However, the epigenetically regulated lncRNAs and their association with clinical outcome and therapeutic response in ovarian cancer (OV) remain poorly investigated. This study performed an integrative analysis of DNA methylation data and transcriptome data and identified 419 lncRNAs as potential epigenetically regulated lncRNAs. Using machine-learning and multivariate Cox regression analysis methods, we identified and developed an epigenetically regulated lncRNA expression signature (EpiLncRNASig) consisting of five lncRNAs from the list of 17 epigenetically regulated lncRNAs significantly associated with outcome. The EpiLncRNASig could stratify patients into high-risk groups and low-risk groups with significantly different survival and chemotherapy response in different patient cohorts. Multivariate Cox regression analyses, after adjusted by other clinical features and treatment response, demonstrated the independence of the DEpiLncSig in predicting survival. Functional analysis for relevant protein-coding genes of the DEpiLncSig indicated enrichment of known immune-related or cancer-related biological pathways. Taken together, our study not only provides a promising prognostic biomarker for predicting outcome and chemotherapy response but also will improve our understanding of lncRNA epigenetic regulation mechanisms in OV.

Keywords: chemotherapy response; epigenetic modification; long non-coding RNAs; ovarian cancer; signature.