Conference proceeding
DrugMoaMiner: A computational tool for mechanism of action discovery and personalized drug sensitivity prediction
2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), pp.368-371
02/2016
DOI: 10.1109/BHI.2016.7455911
Abstract
Heterogeneity of genomic instabilities among individual patients is believed to be a major cause of drug response heterogeneity. Cancer patients who are sensitive to anti-cancer drugs are often re-examined to understand the unknown mechanism of action (MoA) of given drugs. For example, a non-small cell lung cancer (NSCLC) patient was reported to be responsive to Dasatinib treatment and remained cancer-free four years later. Though follow-up genomic analysis showed the patient bears an inactivating BRAF [1]mutation in the tumor, the MoA remains unclear. There are two challenges in uncovering the MoA. First, Dasatinib is a kinase inhibitor, which often has many protein targets. Second, the downstream MoA signaling pathways regulated by these targets are too complicated to delineate. Currently, there is no computational tool that can effectively address both challenges. To fill this gap, we developed a computational tool DrugMoaMiner (Drug MoA Miner) that can be used to identify the comprehensive set of kinase inhibitor targets; delineate the underlying drug MoA; and predict personalized sensitivity to a given drug based on an individual's gene expression profiles. We applied the DrugMoaMiner to lung cancer cell lines to uncover the potential MoA signaling network of Dasatinib sensitivity; our result is in agreement with previous protein data analysis. Moreover, we can predict Dasatinib response of an independent set of NSCLC cell lines using the MoA signaling network uncovered.
Details
- Title: Subtitle
- DrugMoaMiner: A computational tool for mechanism of action discovery and personalized drug sensitivity prediction
- Creators
- Fuhai Li - Houston Methodist Res. Inst., Houston, TX, USALin Wang - Houston Methodist Res. Inst., Houston, TX, USARen Kong - Houston Methodist Res. Inst., Houston, TX, USAJianting Sheng - Houston Methodist Res. Inst., Houston, TX, USAHuojun Cao - Houston Methodist Res. Inst., Houston, TX, USAJames MancusoXiaofeng Xia - Houston Methodist Res. Inst., Houston, TX, USAClifford Stephan - Texas A&M Health Sci. Center, Inst. of Biosci. & Technol. Center, Houston, TX, USAStephen T. C Wong - Houston Methodist Res. Inst., Houston, TX, USA
- Resource Type
- Conference proceeding
- Publication Details
- 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), pp.368-371
- DOI
- 10.1109/BHI.2016.7455911
- eISSN
- 2168-2208
- Publisher
- IEEE
- Language
- English
- Date published
- 02/2016
- Academic Unit
- Anatomy and Cell Biology; Endodontics; Craniofacial Anomalies Research Center; Dental Research
- Record Identifier
- 9984066084402771
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