Biomarkers of vincristine-induced peripheral neuropathy

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Vincristine is among the most commonly used anticancer agents; but little is known regarding vincristine's disposition and optimal dosing, which can lead to negative clinical outcomes such as serious side effects due to drug overdosing or lack of efficacy due to sub-therapeutic dosing. Vincristine is associated with highly variable cumulative dose-dependent peripheral neuropathy (PN). When severe PN occurs, the vincristine dosage must be decreased to avoid disabling PN. However, vincristine dose reductions may result in sub-therapeutic drug exposure, thereby compromising efficacy. Pediatric data from our group indicate links between CYP3A5 genotype, PN, patient age, and vincristine metabolism in children with acute lymphoblastic leukemia (ALL) with 1) young CYP3A5 expressers having the fastest vincristine metabolism and 2) fast vincristine metabolism being associated with less severe neuropathy. While our body of knowledge related to vincristine in children with ALL is growing, vincristine is used in the treatment of over 50% of pediatric cancers both in the U.S. and in developing countries; and the things we have learned about vincristine in children with ALL have not been investigated in these other pediatric populations. This project will use a series of innovative tools to build on our substantial knowledge base related to vincristine-induced PN (VIPN) toward achieving our goal of optimizing vincristine dosing for children throughout the world. Our overall hypothesis is that a focused panel of biomarkers (including targeted vinca alkaloid pathway genomics, PK, and clinical) best predicts VIPN. In this project, we will examine the association between a focused panel of germline genomic variants in the vinca alkaloid pharmacologic pathway and vincristine neuropathy and pharmacokinetics in two populations of children. We also propose to carefully evaluate the impact of age and CYP3A5 genotype on vincristine metabolism using a bank of genotyped pediatric and adult human liver microsomes. Our Biostatistics and Modeling Core will use these data along with our existing dataset from children with ALL to develop a more informed pharmacologic prediction model of vincristine neuropathy in children as a tool for making recommendations for optimized pediatric vincristine dosing.