Abstract:
:Prognostic tests using expression profiles of several dozen genes help provide treatment choices for prostate cancer (PCa). However, these tests require improvement to meet the clinical need for resolving overtreatment, which continues to be a pervasive problem in PCa management. Genomic selection (GS) methodology, which utilizes whole-genome markers to predict agronomic traits, was adopted in this study for PCa prognosis. We leveraged The Cancer Genome Atlas (TCGA) database to evaluate the prediction performance of six GS methods and seven omics data combinations, which showed that the Best Linear Unbiased Prediction (BLUP) model outperformed the other methods regarding predictability and computational efficiency. Leveraging the BLUP-HAT method, an accelerated version of BLUP, we demonstrated that using expression data of a large number of disease-relevant genes and with an integration of other omics data (i.e. miRNAs) significantly increased outcome predictability when compared with panels consisting of a small number of genes. Finally, we developed a novel stepwise forward selection BLUP-HAT method to facilitate searching multiomics data for predictor variables with prognostic potential. The new method was applied to the TCGA data to derive mRNA and miRNA expression signatures for predicting relapse-free survival of PCa, which were validated in six independent cohorts. This is a transdisciplinary adoption of the highly efficient BLUP-HAT method and its derived algorithms to analyze multiomics data for PCa prognosis. The results demonstrated the efficacy and robustness of the new methodology in developing prognostic models in PCa, suggesting a potential utility in managing other types of cancer.
journal_name
Brief Bioinformjournal_title
Briefings in bioinformaticsauthors
Li R,Wang S,Cui Y,Qu H,Chater JM,Zhang L,Wei J,Wang M,Xu Y,Yu L,Lu J,Feng Y,Zhou R,Huang Y,Ma R,Zhu J,Zhong W,Jia Zdoi
10.1093/bib/bbaa197subject
Has Abstractpub_date
2020-09-08 00:00:00eissn
1467-5463issn
1477-4054pii
5902820pub_type
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbz109
更新日期:2020-12-01 00:00:00
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journal_title:Briefings in bioinformatics
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doi:10.1093/bib/bbaa212
更新日期:2020-10-13 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
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更新日期:2020-05-21 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
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更新日期:2017-11-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type:
doi:10.1093/bib/bbl014
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章,评审
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章,评审
doi:10.1093/bib/2.2.111
更新日期:2001-05-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章,评审
doi:10.1093/bib/bbv080
更新日期:2016-07-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
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更新日期:2020-06-26 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章,评审
doi:10.1093/bib/bbm037
更新日期:2007-09-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbaa375
更新日期:2020-12-16 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章,评审
doi:10.1093/bib/bbu016
更新日期:2015-05-01 00:00:00
abstract:MOTIVATION:With the recent advances in DNA sequencing technologies, the study of the genetic composition of living organisms has become more accessible for researchers. Several advances have been achieved because of it, especially in the health sciences. However, many challenges which emerge from the complexity of sequ...
journal_title:Briefings in bioinformatics
pub_type: 杂志文章,评审
doi:10.1093/bib/bby072
更新日期:2019-11-27 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbr034
更新日期:2011-09-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章,评审
doi:10.1093/bib/bbp016
更新日期:2009-09-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章,评审
doi:10.1093/bib/bbx055
更新日期:2018-11-27 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbz054
更新日期:2020-07-15 00:00:00
abstract::Information Integrator is an extension to IBM's relational database DB2, which uses data federation to provide benefits to molecular biology researchers through two unique capabilities: increased flexibility in combining data from disparate sources, and SQL access to non-SQL data, easing the task of automating data an...
journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/4.4.375
更新日期:2003-12-01 00:00:00
abstract:MOTIVATION:Over the past decade, the field of next-generation sequencing (NGS) has seen dramatic advances in methods and a decrease in costs. Consequently, a large expansion of data has been generated by NGS, most of which have originated from RNA-sequencing (RNA-seq) experiments. Because mitochondrial genes are expres...
journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbaa429
更新日期:2021-01-30 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbaa033
更新日期:2021-01-18 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbs062
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbv044
更新日期:2016-05-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbx011
更新日期:2018-07-20 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbaa113
更新日期:2020-07-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bby092
更新日期:2018-09-18 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbu010
更新日期:2015-03-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bby124
更新日期:2020-03-23 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bby115
更新日期:2018-11-29 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
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更新日期:2000-09-01 00:00:00