Breast cancer prognosis signature: linking risk stratification to disease subtypes. (3rd September 2018)
- Record Type:
- Journal Article
- Title:
- Breast cancer prognosis signature: linking risk stratification to disease subtypes. (3rd September 2018)
- Main Title:
- Breast cancer prognosis signature: linking risk stratification to disease subtypes
- Authors:
- Yu, Fulong
Quan, Fei
Xu, Jinyuan
Zhang, Yan
Xie, Yi
Zhang, Jingyu
Lan, Yujia
Yuan, Huating
Zhang, Hongyi
Cheng, Shujun
Xiao, Yun
Li, Xia - Abstract:
- Abstract: Breast cancer is a very complex and heterogeneous disease with variable molecular mechanisms of carcinogenesis and clinical behaviors. The identification of prognostic risk factors may enable effective diagnosis and treatment of breast cancer. In particular, numerous gene-expression-based prognostic signatures were developed and some of them have already been applied into clinical trials and practice. In this study, we summarized several representative gene-expression-based signatures with significant prognostic value and separately assessed their ability of prognosis prediction in their originally targeted populations of breast cancer. Notably, many of the collected signatures were originally designed to predict the outcomes of estrogen receptor positive (ER+) patients or the whole breast cancer cohort; there are no typical signatures used for the prognostic prediction in a specific population of patients with the intrinsic subtype. We thus attempted to identify subtype-specific prognostic signatures via a computational framework for analyzing multi-omics profiles and patient survival. For both the discovery and an independent data set, we confirmed that subtype-specific signature is a strong and significant independent prognostic factor in the corresponding cohort. These results indicate that the subtype-specific prognostic signature has a much higher resolution in the risk stratification, which may lead to improved therapies and precision medicine for patientsAbstract: Breast cancer is a very complex and heterogeneous disease with variable molecular mechanisms of carcinogenesis and clinical behaviors. The identification of prognostic risk factors may enable effective diagnosis and treatment of breast cancer. In particular, numerous gene-expression-based prognostic signatures were developed and some of them have already been applied into clinical trials and practice. In this study, we summarized several representative gene-expression-based signatures with significant prognostic value and separately assessed their ability of prognosis prediction in their originally targeted populations of breast cancer. Notably, many of the collected signatures were originally designed to predict the outcomes of estrogen receptor positive (ER+) patients or the whole breast cancer cohort; there are no typical signatures used for the prognostic prediction in a specific population of patients with the intrinsic subtype. We thus attempted to identify subtype-specific prognostic signatures via a computational framework for analyzing multi-omics profiles and patient survival. For both the discovery and an independent data set, we confirmed that subtype-specific signature is a strong and significant independent prognostic factor in the corresponding cohort. These results indicate that the subtype-specific prognostic signature has a much higher resolution in the risk stratification, which may lead to improved therapies and precision medicine for patients with breast cancer. … (more)
- Is Part Of:
- Briefings in bioinformatics. Volume 20:Number 6(2020)
- Journal:
- Briefings in bioinformatics
- Issue:
- Volume 20:Number 6(2020)
- Issue Display:
- Volume 20, Issue 6 (2020)
- Year:
- 2020
- Volume:
- 20
- Issue:
- 6
- Issue Sort Value:
- 2020-0020-0006-0000
- Page Start:
- 2130
- Page End:
- 2140
- Publication Date:
- 2018-09-03
- Subjects:
- breast cancer -- prognosis signature -- subtype -- integrated analysis
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/bby073 ↗
- 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:
- 12827.xml