(229ab) Pharmacometabonomics Approach for Early Prediction of Neuropathy

Vincristine (VCR) is a core chemotherapeutic drug administered to pediatric Acute Lymphoblastic Leukemia (ALL) patients during induction phase. In a subgroup of population, it leads to Vincristine Induced Peripheral Neuropathy (VIPN), which is the dose-limiting toxicity. For few patients, VIPN is severe with long-term effects. Even though VCR has been used in chemotherapy for more than 50 years now, predictors and mechanism of VIPN induction are unclear. Historically, an empirical cap of 2 mg has been kept for dosage. Due to this, a population not susceptible to VIPN receives sub-therapeutic treatment, while another population may experience severe neuropathy. It is of interest to find predictors/biomarkers which can discriminate populations based on VIPN, before the treatment starts.

Few trends in VIPN incidence have been observed. Caucasians experience VIPN more than African-Americans. CYP3A5 high expressers experience lesser VIPN, though, no clear relation between VIPN and CYP3A4/5 expression has been established. Recently, VIPN was found to be associated with a SNP in the promoter region of CEP72 gene, which encodes a centrosomal protein, involved in microtubule formation. We use pharmacometabonomics approach to find metabolites as biomarkers which can predict VIPN. In a retrospective pilot study done on 12 ALL patients, metabolites were found to be differentially expressed in high and low VIPN patients. We plan to conduct a prospective study of 77 pediatric ALL patients administered with VCR as the primary chemotherapeutic drug for treatment. Fasting serum samples are being collected at 3 times points: before induction, one week after induction and at the end of a month. An attempt will be made to find metabolites differentially expressed in pre-dose samples of low and high VIPN patients. Presently, retrospective non-fasting samples of pediatric ALL patients are used for a preliminary study. These samples were collected at three time points: day 8, day 29, +6 months. Feature selection machine learning techniques have been used to identify biomarkers in a high-dimensional data set of metabolite profiles of patients. Samples at time point +6 months are used for identification of biomarkers, primarily.

We have future plans of exploring what relevant pathways the identified metabolites lie in. We further plan to bring mechanistic modeling into the picture to provide biological insight to the problem. For this purpose, we plan to study VCR metabolism, with an assumption that liver cells have a goal while metabolizing VCR.