Computational identification of mutator-derived lncRNA signatures of genome instability for improving the clinical outcome of cancers: a case study in breast cancer. (28th October 2019)
- Record Type:
- Journal Article
- Title:
- Computational identification of mutator-derived lncRNA signatures of genome instability for improving the clinical outcome of cancers: a case study in breast cancer. (28th October 2019)
- Main Title:
- Computational identification of mutator-derived lncRNA signatures of genome instability for improving the clinical outcome of cancers: a case study in breast cancer
- Authors:
- Bao, Siqi
Zhao, Hengqiang
Yuan, Jian
Fan, Dandan
Zhang, Zicheng
Su, Jianzhong
Zhou, Meng - Abstract:
- Abstract: Emerging evidence revealed the critical roles of long non-coding RNAs (lncRNAs) in maintaining genomic instability. However, identification of genome instability-associated lncRNAs and their clinical significance in cancers remain largely unexplored. Here, we developed a mutator hypothesis-derived computational frame combining lncRNA expression profiles and somatic mutation profiles in a tumor genome and identified 128 novel genomic instability-associated lncRNAs in breast cancer as a case study. We then identified a genome instability-derived two lncRNA-based gene signature (GILncSig) that stratified patients into high- and low-risk groups with significantly different outcome and was further validated in multiple independent patient cohorts. Furthermore, the GILncSig correlated with genomic mutation rate in both ovarian cancer and breast cancer, indicating its potential as a measurement of the degree of genome instability. The GILncSig was able to divide TP53 wide-type patients into two risk groups, with the low-risk group showing significantly improved outcome and the high-risk group showing no significant difference compared with those with TP53 mutation. In summary, this study provided a critical approach and resource for further studies examining the role of lncRNAs in genome instability and introduced a potential new avenue for identifying genomic instability-associated cancer biomarkers.
- Is Part Of:
- Briefings in bioinformatics. Volume 21:Number 5(2020)
- Journal:
- Briefings in bioinformatics
- Issue:
- Volume 21:Number 5(2020)
- Issue Display:
- Volume 21, Issue 5 (2020)
- Year:
- 2020
- Volume:
- 21
- Issue:
- 5
- Issue Sort Value:
- 2020-0021-0005-0000
- Page Start:
- 1742
- Page End:
- 1755
- Publication Date:
- 2019-10-28
- Subjects:
- genome instability -- mutator phenotype -- long non-coding RNAs
Genetics -- Data processing -- Periodicals
Molecular biology -- Data processing -- Periodicals
Genomes -- Data processing -- Periodicals
572.80285 - Journal URLs:
- http://bib.oxfordjournals.org ↗
http://www.oxfordjournals.org/content?genre=journal&issn=1477-4054 ↗
http://ukcatalogue.oup.com/ ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1093/bib/bbz118 ↗
- Languages:
- English
- ISSNs:
- 1467-5463
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 2283.958363
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21869.xml