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Inferences of drug responses in cancer cells from cancer genomic features and compound chemical and therapeutic properties.

Abstract：

:Accurately predicting the response of a cancer patient to a therapeutic agent is a core goal of precision medicine. Existing approaches were mainly relied primarily on genomic alterations in cancer cells that have been treated with different drugs. Here we focus on predicting drug response based on integration of the heterogeneously pharmacogenomics data from both cell and drug sides. Through a systematical approach, named as PDRCC (Predict Drug Response in Cancer Cells), the cancer genomic alterations and compound chemical and therapeutic properties were incorporated to determine the chemotherapeutic response in cancer patients. Using the Cancer Cell Line Encyclopedia (CCLE) study as the benchmark dataset, all pharmacogenomics data exhibited their roles in inferring the relationships between cancer cells and drugs. When integrating both genomic resources and compound information, the prediction coverage was significantly increased. The validity of PDRCC was also supported by its effective in uncovering the unknown cell-drug associations with database and literature evidences. It set the stage for clinical testing of novel therapeutic strategies, such as the sensitive association between cancer cell 'A549_LUNG' and compound 'Topotecan'. In conclusion, PDRCC offers the possibility for faster, safer, and cheaper the development of novel anti-cancer therapeutics in the early-stage clinical trails.

journal_name

Sci Rep

journal_title

Scientific reports

authors

Wang Y,Fang J,Chen S

doi

10.1038/srep32679

subject

Has Abstract

pub_date

2016-09-20 00:00:00

pages

32679

issn

2045-2322

pii

srep32679

journal_volume

6

pub_type

杂志文章

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