Patient-specific multi-omics models and the application in personalized combination therapy

被引:14
作者
John, August [1 ]
Qin, Bo [2 ,3 ,4 ]
Kalari, Krishna R. [5 ]
Wang, Liewei [2 ]
Yu, Jia [2 ]
机构
[1] Mayo Clin, Grad Sch Biomed Sci, Rochester, MN 55905 USA
[2] Mayo Clin, Dept Mol Pharmacol & Expt Therapeut, Rochester, MN 55905 USA
[3] Mayo Clin, Gastroenterol Res Unit, Rochester, MN 55905 USA
[4] Mayo Clin, Dept Oncol, Rochester, MN 55905 USA
[5] Mayo Clin, Dept Hlth Sci Res, Rochester, MN 55905 USA
关键词
data integration; high-throughput; multi-omics; personalized combination therapy; CANONICAL CORRELATION-ANALYSIS; PROTEOGENOMIC CHARACTERIZATION; PROSTATE-CANCER; GENOMIC DATA; DRUG-SENSITIVITY; RNA-SEQ; BREAST; GENES; IDENTIFICATION; INTEGRATION;
D O I
10.2217/fon-2020-0119
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
The rapid advancement of high-throughput technologies and sharp decrease in cost have opened up the possibility to generate large amount of multi-omics data on an individual basis. The development of high-throughput -omics, including genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiomics, enables the application of multi-omics technologies in the clinical settings. Combination therapy, defined as disease treatment with two or more drugs to achieve efficacy with lower doses or lower drug toxicity, is the basis for the care of diseases like cancer. Patient-specific multi-omics data integration can help the identification and development of combination therapies. In this review, we provide an overview of different -omics platforms, and discuss the methods for multi-omics, high-throughput, data integration, personalized combination therapy.
引用
收藏
页码:1737 / 1750
页数:14
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