# A precision medicine approach to improve prediction of severe toxicity in fluorouracil chemotherapy > **NIH NIH R01** · MAYO CLINIC ROCHESTER · 2021 · $363,713 ## Abstract PROJECT SUMMARY/ABSTRACT My long-term goal is to improve the toxicity profiles for cancer therapeutics. One-third of cancer patients treated with the commonly prescribed chemotherapeutic 5-fluorouracil (5-FU) experience severe and life- threatening toxicity to standard doses of the drug. An appreciable fraction of those patients die—not due to cancer, but because of side-effects related to treatment. Clinical studies indicate that the majority of patients who experience severe toxicity to 5-FU are deficient for an enzyme called dihydropyrimidine dehydrogenase (DPD, DPYD gene); however, only four genetic variants in DPYD have been adequately characterized to be considered predictive of 5-FU toxicity in clinical studies. My preliminary studies demonstrate that these four variants explain only a small fraction of severe 5-FU toxicities and have exceedingly limited clinical value outside of individuals with European ancestry. The primary objective of the studies proposed in this grant application is to identify additional biomarkers of 5-FU toxicity risk that can be used to individualize 5-FU dosing with the goal of improving the safety profile for the drug. My overall hypothesis is that expanded biomarker-based pre-treatment tests will more accurately identify patients with DPD deficiency, as well as the relative degree to which the DPD function is impaired, enabling more accurate dose optimization. My rationale is that improved biomarker-based approaches to dose individualization have strong potential to improve the safety profile for this commonly used therapeutic. Aim #1 will identify risk alleles for severe 5-FU–related toxicity in understudied populations. Aim #2 will characterize multi-marker haplotype contributions to 5-FU toxicity. In Aim #3, I will develop an integrated predictive model of 5-FU toxicity using deep machine learning. It is my expectation that the proposed studies, which will leverage multiple large patient and volunteer data and specimen collections to address various aspects of my primary hypothesis, will answer key questions that have vexed pharmacogenetics researchers for decades. In doing so, the proposed studies are expected to identify clinically relevant biomarkers that can be used to improve the safety profile of 5-FU through dose optimization. ## Key facts - **NIH application ID:** 10295231 - **Project number:** 1R01CA251065-01A1 - **Recipient organization:** MAYO CLINIC ROCHESTER - **Principal Investigator:** Steven Offer - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $363,713 - **Award type:** 1 - **Project period:** 2021-09-01 → 2026-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10295231 ## Citation > US National Institutes of Health, RePORTER application 10295231, A precision medicine approach to improve prediction of severe toxicity in fluorouracil chemotherapy (1R01CA251065-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10295231. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*