title: Comprehensive analysis of lncRNA expression profiles reveals a novel lncRNA signature to discriminate nonequivalent outcomes in patients with ovarian cancer.
abstract: There is growing evidence of dysregulated long non-coding RNAs (lncRNAs) serving as potential biomarkers for cancer prognosis. However, systematic efforts of searching for an expression-based lncRNA signature for prognosis prediction in ovarian cancer (OvCa) have not been made yet. Here, we performed comprehensive analysis for lncRNA expression profiles and clinical data of 544 OvCa patients from The Cancer Genome Atlas (TCGA), and identified an eight-lncRNA signature with ability to classify patients of the training cohort into high-risk group showing poor outcome and low-risk group showing significantly improved outcome, which was further validated in the validation cohort and entire TCGA cohort. Multivariate Cox regression analysis and stratified analysis demonstrated that the prognostic value of this signature was independent of other clinicopathological factors. Associating the outcome prediction with BRCA1 and/or BRCA2 mutation revealed a superior prognosis performance both in BRCA1/2-mutated and BRCA1/2 wild-type tumors. Finally, a significantly correlation was found between the lncRNA signature and the complete response rate of chemotherapy, suggesting that this eight-lncRNA signature may be a measure to predict chemotherapy response and identify platinum-resistant patients who might benefit from other more efficacious therapies. With further prospective validation, this eight-lncRNA signature may have important implications for outcome prediction and therapy decisions.
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China.
authors.forename: Meng
authors.initials: M
authors.lastname: Zhou
authors.affiliation: Department of Microbiology, Harbin Medical University, Harbin, 150081, PR China.
authors.forename: Yanying
authors.initials: Y
authors.lastname: Sun
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China.
authors.forename: Yifan
authors.initials: Y
authors.lastname: Sun
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China.
authors.forename: Wanying
authors.initials: W
authors.lastname: Xu
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China.
authors.forename: Zhaoyue
authors.initials: Z
authors.lastname: Zhang
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China.
authors.forename: Hengqiang
authors.initials: H
authors.lastname: Zhao
authors.affiliation: Department of Microbiology, Harbin Medical University, Harbin, 150081, PR China.
authors.forename: Zhaohua
authors.initials: Z
authors.lastname: Zhong
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China.
authors.forename: Jie
authors.initials: J
authors.lastname: Sun
mesh_terms: D005260:Female; D006801:Humans; D008875:Middle Aged; D010051:Ovarian Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D011379:Prognosis; D062085:RNA, Long Noncoding / Q000096:biosynthesis* / Q000378:metabolism; D016896:Treatment Outcome
chemical_list: D062085:RNA, Long Noncoding
keywords: BRCA1/2; long non-coding RNAs; outcome; ovarian cancer