Identification of a six-lncRNA signature associated with recurrence of ovarian cancer

Ovarian cancer (OvCa) is the leading cause of death among all gynecological malignancies, and recurrent OvCa is almost always incurable. In this study, we developed a signature based on long non-coding RNAs (lncRNAs) associated with OvCa recurrence to facilitate personalized OvCa therapy. lncRNA exp...

Full description

Saved in:
Bibliographic Details
Published in:Scientific reports 2017-04, Vol.7 (1), p.752-752, Article 752
Main Authors: Yang, Kai, Hou, Yan, Li, Ang, Li, Zhenzi, Wang, Wenjie, Xie, Hongyu, Rong, Zhiwei, Lou, Ge, Li, Kang
Format: Article
Language:English
Subjects:
38/39
38/47
631/67/1517/1709
631/67/1857
631/67/69
Humanities and Social Sciences
multidisciplinary
Science
Science (multidisciplinary)
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Ovarian cancer (OvCa) is the leading cause of death among all gynecological malignancies, and recurrent OvCa is almost always incurable. In this study, we developed a signature based on long non-coding RNAs (lncRNAs) associated with OvCa recurrence to facilitate personalized OvCa therapy. lncRNA expression data were extracted from GSE9891 and GSE30161. LASSO (least absolute shrinkage and selection operator) penalized regression was used to identify an lncRNA-based signature using the GSE9891 training cohort. The signature was then validated in GSE9891 internal and GSE30161 external validation cohorts. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to explore the possible functions of identified lncRNAs. A six-lncRNA signature (RUNX1-IT1, MALAT1, H19, HOTAIRM1, LOC100190986 and AL132709.8) was identified in the training cohort and validated in internal and external validation cohorts using the LASSO method (P 
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-017-00763-y