PMID- 20434586 OWN - NLM STAT- MEDLINE DCOM- 20100923 LR - 20211020 IS - 1532-0480 (Electronic) IS - 1532-0464 (Print) IS - 1532-0464 (Linking) VI - 43 IP - 3 DP - 2010 Jun TI - Kinase inhibition-related adverse events predicted from in vitro kinome and clinical trial data. PG - 376-84 LID - 10.1016/j.jbi.2010.04.006 [doi] AB - BACKGROUND: Kinase inhibition is an increasingly popular strategy for pharmacotherapy of human diseases. Although many of these agents have been described as "targeted therapy", they will typically inhibit multiple kinases with varying potency. Pre-clinical model testing has not predicted the numerous significant toxicities identified during clinical development. The purpose of this study was to develop a bioinformatics-based method to predict specific adverse events (AEs) in humans associated with the inhibition of particular kinase targets (KTs). METHODS: The AE frequencies of protein kinase inhibitors (PKIs) were curated from three sources (PubMed, Thompson Physician Desk Reference and PharmGKB), and affinities of 38 PKIs for 317 kinases, representing >50% of the predicted human kinome, were collected from published in vitro assay results. A novel quantitative computational method was developed to predict associations between KTs and AEs that included a whole panel of 71 AEs and 20 PKIs targeting 266 distinct kinases with K(d)<10microM. The method calculated an unbiased, kinome-wide association score via linear algebra on (i) the normalized frequencies of AEs associated with 20 PKIs and (ii) the negative log-transformed dissociation constant of kinases targeted by these PKIs. Finally, a reference standard was calculated by applying Fisher's exact test to the co-occurrence of indexed Pubmed terms (p0.05, and manually verified) for AE and associated kinase targets (AE-KT) pairs from standard literature search techniques. We also evaluated the enrichment of predictions between the quantitative method and the literature search by Fisher's exact testing. RESULTS: We identified significant associations among already empirically well established pairs of AEs (e.g. diarrhea and rash) and KTs (e.g. EGFR). The following less well recognized AE-KT pairs had similar association scores: diarrhea-(DDR1;ERBB4), rash-ERBB4, and fatigue-(CSF1R;KIT). With no filtering, the association score identified 41 prioritized associations involving 7 AEs and 19 KTs. Among them, eight associations were reported in the literature review. There were only 78 out of a total of 4522 AE-KT pairs meeting the evaluation threshold, indicating a strong association between the predicted and the text mined AE-KT pairs (p=3x10(-7)). As many of these drugs remain in development, a larger volume of more detailed data on AE-PKI associations is accessible only through non-public databases. These prediction models will be refined with these data and validated through dedicated prospective human studies. CONCLUSION AND FUTURE DIRECTIONS: Our in silico method can predict associations between kinase targets and AE frequencies in human patients. Refining this method should lead to improved clinical development of protein kinase inhibitors, a large new class of therapeutics. http://www.lussierlab.org/publication/PAS/. FAU - Yang, Xinan AU - Yang X AD - Center for Biomedical Informatics, The University of Chicago, Chicago, IL, USA. FAU - Huang, Yong AU - Huang Y FAU - Crowson, Matthew AU - Crowson M FAU - Li, Jianrong AU - Li J FAU - Maitland, Michael L AU - Maitland ML FAU - Lussier, Yves A AU - Lussier YA LA - eng GR - 1U54 RR023560-01A1/RR/NCRR NIH HHS/United States GR - K23 CA124802-04/CA/NCI NIH HHS/United States GR - UL1 RR024999/RR/NCRR NIH HHS/United States GR - UL1 RR024999-03/RR/NCRR NIH HHS/United States GR - U54 RR023560/RR/NCRR NIH HHS/United States GR - K23 CA124802-03/CA/NCI NIH HHS/United States GR - U54 CA121852/CA/NCI NIH HHS/United States GR - K23CA124802/CA/NCI NIH HHS/United States GR - K22 LM008308-05/LM/NLM NIH HHS/United States GR - 1U54CA121852/CA/NCI NIH HHS/United States GR - K23 CA124802/CA/NCI NIH HHS/United States GR - U54 CA121852-05/CA/NCI NIH HHS/United States GR - K22 LM008308/LM/NLM NIH HHS/United States GR - UL1 RR024999-04/RR/NCRR NIH HHS/United States GR - UL1 RR024999-03S5/RR/NCRR NIH HHS/United States PT - Journal Article PT - Research Support, N.I.H., Extramural PT - Research Support, Non-U.S. Gov't DEP - 20100501 PL - United States TA - J Biomed Inform JT - Journal of biomedical informatics JID - 100970413 RN - 0 (Protein Kinase Inhibitors) RN - EC 2.7.- (Protein Kinases) SB - IM MH - Clinical Trials as Topic MH - Computational Biology/*methods MH - Databases, Factual MH - Drug-Related Side Effects and Adverse Reactions/diagnosis MH - Humans MH - Protein Kinase Inhibitors/*adverse effects/therapeutic use MH - Protein Kinases/drug effects PMC - PMC2893391 MID - NIHMS202308 EDAT- 2010/05/04 06:00 MHDA- 2010/09/24 06:00 PMCR- 2011/06/01 CRDT- 2010/05/04 06:00 PHST- 2009/09/02 00:00 [received] PHST- 2010/04/14 00:00 [revised] PHST- 2010/04/23 00:00 [accepted] PHST- 2010/05/04 06:00 [entrez] PHST- 2010/05/04 06:00 [pubmed] PHST- 2010/09/24 06:00 [medline] PHST- 2011/06/01 00:00 [pmc-release] AID - S1532-0464(10)00053-5 [pii] AID - 10.1016/j.jbi.2010.04.006 [doi] PST - ppublish SO - J Biomed Inform. 2010 Jun;43(3):376-84. doi: 10.1016/j.jbi.2010.04.006. Epub 2010 May 1.