Predictive Biomarkers and Personalized Medicine Pharmacometabonomic Profiling as a Predictor of Toxicity in Patients with Inoperable Colorectal Cancer Treated with Capecitabine Alexandra Backshall 1 , Rohini Sharma 2 , Stephen J. Clarke 3 , and Hector C. Keun 1 Abstract Purpose: Endogenous metabolic profiles have been shown to predict the fate and toxicity of drugs such as acetaminophen in healthy individuals. However, the clinical utility of metabonomics in oncology remains to be defined. We aimed to evaluate the effect of pretreatment serum metabolic profiles generated by 1 H NMR spectroscopy on toxicity in patients with inoperable colorectal cancer receiving single agent capecitabine. Experimental Design: Serum was collected from 54 patients with a diagnosis of locally advanced or metastatic colorectal cancer prior to treatment with single agent capecitabine. 1 H NMR spectroscopy was used to generate metabolic profile data for each patient. Toxicities were graded according to National Cancer Institute Common Toxicity Criteria version 2.0. Results: Higher levels of low-density lipoprotein–derived lipids, including polyunsaturated fatty acids and choline phospholipids predicted for higher grade toxicity over the treatment period. Statistical analyses revealed a "pharmacometabonomic" lipid profile that correlated with severity of toxicity. Conclusions: This study suggests that metabolic profiles can delineate subpopulations susceptible to adverse events and have a potential role in the assessment of treatment viability for cancer patients prior to commencing chemotherapy. Clin Cancer Res; 17(9); 1–10. Ó2011 AACR. Introduction Metabolic profiling (metabonomics/metabolomics) is a flexible approach that can be used to investigate in a systematic manner the metabolic composition of cells, tissues, and biofluids (1–4). It has recently been shown that pretreatment biofluid metabolic profiles can be used to predict the metabolic fate and toxicity of drugs in vivo, specifically for acetaminophen exposure in rodents (5), an observation subsequently shown to translate to man (6, 7). This strategy, termed "pharmacometabonomics," poten- tially offers phenotypic information not captured by genetic profiling that can be used to predict pharmacology. In the study by Winnike and colleagues (7) a combination of both the early drug metabolite profile and observed changes in common urinary endogenous metabolites were able to identify a subpopulation of individuals who experi- enced alanine aminotransferase (ALT) elevation in response to 4 g/d acetaminophen, several days before the phenotype was apparent by conventional clinical chemistry. Although this experiment shows in principle how phar- macometabonomics could help to reduce adverse events in susceptible individuals, the trial was conducted in other- wise healthy volunteers with no clinical requirement for treatment. In patients undergoing chemotherapy, systemic toxicity remains the major limitation to adequate dosing. The ability to predict adverse events prior to drug admin- istration, and to provide individualized treatment, is likely to have a significant impact on clinical outcomes and quality of life, particularly in the palliative setting. Although extensively used to characterize the tumor meta- bolome (8–10) and for the discovery of diagnostic bio- markers in body fluids (11, 12), there are relatively few examples of metabolic profiling being used to derive prog- nostic or predictive biofluid biomarkers in oncology (13). In a previous study, we used a nuclear magnetic resonance (NMR)-based approach to define a serum metabolic sig- nature predictive of weight gain secondary to chemother- apy in patients with breast cancer, showing that this platform can potentially identify phenotypes related to poorer outcomes (14). However, the utility of an NMR- based approach as a prognostic or predictive marker of clinical outcome remains to be evaluated. Capecitabine is an oral prodrug of 5-fluorouracil (5-FU) which was designed to minimize gastrointestinal toxicity Authors' Affiliations: 1 Biomolecular Medicine, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London South Kensington Campus; 2 Division of Investigative Sciences, Imperial College London Hammersmith Campus, London, United Kingdom; and 3 Department of Medical Oncology, University of Sydney Concord Hospital, Concord, Sydney, Australia Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clinicalcancerres.aacrjournals.org/). A. Backshall and R. Sharma are joint first authors. Corresponding Author: Hector Keun, Biomolecular Medicine, Depart- ment of Surgery & Cancer, Faculty of Medicine, Imperial College London South Kensington Campus, Exhibition Rd, London SW7 2AZ, United Kingdom. Phone: 44-20-7594 3161; Fax: 44-20-7594-3226; E-mail: h.keun@imperial.ac.uk doi: 10.1158/1078-0432.CCR-10-2474 Ó2011 American Association for Cancer Research. Clinical Cancer Research www.aacrjournals.org OF1 Research. on April 15, 2017. © 2011 American Association for Cancer clincancerres.aacrjournals.org Downloaded from Published OnlineFirst March 17, 2011; DOI: 10.1158/1078-0432.CCR-10-2474