| Literature DB >> 23061376 |
Jason C Wong1, Guozhi Tang, Xihan Wu, Chungen Liang, Zhenshan Zhang, Lei Guo, Zhenghong Peng, Weixing Zhang, Xianfeng Lin, Zhanguo Wang, Jianghua Mei, Junli Chen, Song Pan, Nan Zhang, Yongfu Liu, Mingwei Zhou, Lichun Feng, Weili Zhao, Shijie Li, Chao Zhang, Meifang Zhang, Yiping Rong, Tai-Guang Jin, Xiongwen Zhang, Shuang Ren, Ying Ji, Rong Zhao, Jin She, Yi Ren, Chunping Xu, Dawei Chen, Jie Cai, Song Shan, Desi Pan, Zhiqiang Ning, Xianping Lu, Taiping Chen, Yun He, Li Chen.
Abstract
Herein, we describe the pharmacokinetic optimization of a series of class-selective histone deacetylase (HDAC) inhibitors and the subsequent identification of candidate predictive biomarkers of hepatocellular carcinoma (HCC) tumor response for our clinical lead using patient-derived HCC tumor xenograft models. Through a combination of conformational constraint and scaffold hopping, we lowered the in vivo clearance (CL) and significantly improved the bioavailability (F) and exposure (AUC) of our HDAC inhibitors while maintaining selectivity toward the class I HDAC family with particular potency against HDAC1, resulting in clinical lead 5 (HDAC1 IC₅₀ = 60 nM, mouse CL = 39 mL/min/kg, mouse F = 100%, mouse AUC after single oral dose at 10 mg/kg = 6316 h·ng/mL). We then evaluated 5 in a biomarker discovery pilot study using patient-derived tumor xenograft models, wherein two out of the three models responded to treatment. By comparing tumor response status to compound tumor exposure, induction of acetylated histone H3, candidate gene expression changes, and promoter DNA methylation status from all three models at various time points, we identified preliminary candidate response prediction biomarkers that warrant further validation in a larger cohort of patient-derived tumor models and through confirmatory functional studies.Entities:
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Year: 2012 PMID: 23061376 DOI: 10.1021/jm3011838
Source DB: PubMed Journal: J Med Chem ISSN: 0022-2623 Impact factor: 7.446