Literature DB >> 20980974

Predicting idiopathic toxicity of cisplatin by a pharmacometabonomic approach.

Hyuk Nam Kwon1, Mina Kim, He Wen, Sunmi Kang, Hye-Ji Yang, Myung-Joo Choi, Hee Seung Lee, DalWoong Choi, In Suh Park, Young Ju Suh, Soon-Sun Hong, Sunghyouk Park.   

Abstract

Cisplatin has been one of the most widely used anticancer agents, but its nephrotoxicity remains a dose-limiting complication. Here, we evaluated the idiopathic nature and the predose prediction of cisplatin-induced nephrotoxicity using a nuclear magnetic resonance (NMR)-based pharmacometabonomic approach. Cisplatin produced serious toxic responses in some animals (toxic group), but had little effect in others (nontoxic group), as judged by hematological and histological results. The individual metabolic profiles, assessed by urine NMR spectra, showed large differences between the post-administration profiles of the two groups, indicating the relevance of the NMR approach. Importantly, multivariate analysis of the NMR data showed that the toxic and nontoxic groups can be differentiated based on the pretreatment metabolite profiles. Leave-one-out analysis, performed to evaluate the practical performance of our approach, gave a 66% accuracy rate in predicting toxic responses based on the pretreatment metabolite profiles. Hence, we provide a working model that can explain the idiopathic toxicity mechanism based on marker metabolites found by NMR analysis consistent with tissue NADH measurements. Thus, a pharmacometabonomic approach using pretreatment metabolite profiles may help expedite personalized chemotherapy of anticancer drugs.

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Year:  2010        PMID: 20980974     DOI: 10.1038/ki.2010.440

Source DB:  PubMed          Journal:  Kidney Int        ISSN: 0085-2538            Impact factor:   10.612


  12 in total

1.  Enhanced phase II detoxification contributes to beneficial effects of dietary restriction as revealed by multi-platform metabolomics studies.

Authors:  He Wen; Hye-Ji Yang; Yong Jin An; Joon Mee Kim; Dae Hyun Lee; Xing Jin; Sung-Woo Park; Kyung-Jin Min; Sunghyouk Park
Journal:  Mol Cell Proteomics       Date:  2012-12-09       Impact factor: 5.911

2.  Pharmacometabolomics reveals a role for histidine, phenylalanine, and threonine in the development of paclitaxel-induced peripheral neuropathy.

Authors:  Yihan Sun; Jae Hyun Kim; Kiran Vangipuram; Daniel F Hayes; Ellen M L Smith; Larisa Yeomans; N Lynn Henry; Kathleen A Stringer; Daniel L Hertz
Journal:  Breast Cancer Res Treat       Date:  2018-06-26       Impact factor: 4.872

3.  Lipid imaging for visualizing cilastatin amelioration of cisplatin-induced nephrotoxicity.

Authors:  Estefanía Moreno-Gordaliza; Diego Esteban-Fernández; Alberto Lázaro; Sarah Aboulmagd; Blanca Humanes; Alberto Tejedor; Michael W Linscheid; M Milagros Gómez-Gómez
Journal:  J Lipid Res       Date:  2018-07-26       Impact factor: 5.922

4.  An HR-MAS MR metabolomics study on breast tissues obtained with core needle biopsy.

Authors:  MuLan Li; Yonghyun Song; Nariya Cho; Jung Min Chang; Hye Ryoung Koo; Ann Yi; Hyeonjin Kim; Sunghyouk Park; Woo Kyung Moon
Journal:  PLoS One       Date:  2011-10-18       Impact factor: 3.240

5.  Pharmacometabolomics identifies dodecanamide and leukotriene B4 dimethylamide as a predictor of chemosensitivity for patients with acute myeloid leukemia treated with cytarabine and anthracycline.

Authors:  Guangguo Tan; Bingbing Zhao; Yanqing Li; Xi Liu; Zhilan Zou; Jun Wan; Ye Yao; Hong Xiong; Yanyu Wang
Journal:  Oncotarget       Date:  2017-09-08

6.  Urinary metabolomics reveals the therapeutic effect of HuangQi Injections in cisplatin-induced nephrotoxic rats.

Authors:  Chang-Yin Li; Hui-Ting Song; Xiao-Xiao Wang; Yao-Yao Wan; Xuan-Sheng Ding; Shi-Jia Liu; Guo-Liang Dai; Yue-Heng Liu; Wen-Zheng Ju
Journal:  Sci Rep       Date:  2017-06-15       Impact factor: 4.379

7.  Renal Medulla is More Sensitive to Cisplatin than Cortex Revealed by Untargeted Mass Spectrometry-Based Metabolomics in Rats.

Authors:  Pei Zhang; Jia-Qing Chen; Wan-Qiu Huang; Wei Li; Yin Huang; Zun-Jian Zhang; Feng-Guo Xu
Journal:  Sci Rep       Date:  2017-03-16       Impact factor: 4.379

8.  Pharmacometabolomic approach to predict QT prolongation in guinea pigs.

Authors:  Jeonghyeon Park; Keumhan Noh; Hae Won Lee; Mi-sun Lim; Sook Jin Seong; Jeong Ju Seo; Eun-Jung Kim; Wonku Kang; Young-Ran Yoon
Journal:  PLoS One       Date:  2013-04-04       Impact factor: 3.240

Review 9.  From Metabonomics to Pharmacometabonomics: The Role of Metabolic Profiling in Personalized Medicine.

Authors:  Jeremy R Everett
Journal:  Front Pharmacol       Date:  2016-09-08       Impact factor: 5.810

Review 10.  Pharmacometabolomics in Early-Phase Clinical Development.

Authors:  T Burt; S Nandal
Journal:  Clin Transl Sci       Date:  2016-04-29       Impact factor: 4.689

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