Search

PURPOSE Acute lymphoblastic leukemia (ALL) is the most prevalent cause of childhood cancer and requires a long course of therapy consisting of three primary phases with interval intensification blocks. Although these phases are necessary to achieve remission, the primary chemotherapeutic agents have potentially serious toxicities, which may lead to delays or discontinuations of therapy. The purpose of this study was to perform a comprehensive pharmacogenomic evaluation of common antileukemic agents and develop a polygenic toxicity risk score predictive of the most common toxicities observed during ALL treatment. METHODS This cross-sectional study included 75 patients with pediatric ALL treated between 2012 and 2020 at the University of Florida. Toxicity data were collected within 100 days of initiation of therapy using CTCAE v4.0 for toxicity grading. For pharmacogenomic evaluation, single-nucleotide polymorphisms (SNPs) and genes were selected from previous reports or PharmGKB database. 116 unique SNPs were evaluated for incidence of various toxicities. A multivariable multi-SNP modeling for up to 3-SNP combination was performed to develop a polygenic toxicity risk score of prognostic value. RESULTS We identified several SNPs predictive of toxicity phenotypes in univariate analysis. Further multivariable SNP-SNP combination analysis suggest that susceptibility to chemotherapy-induced toxicities is likely multigenic in nature. For 3-SNPscore models, patients with high scores experienced increased risk of GI ( P = 2.07E-05, 3 SNPs: TYMS-rs151264360/FPGS-rs1544105/GSTM1-GSTM5-rs3754446), neurologic ( P = .0005, 3 SNPs: DCTD-rs6829021/SLC28A3-rs17343066/CTPS1-rs12067645), endocrine ( P = 4.77E-08, 3 SNPs: AKR1C3-rs1937840/TYMS-rs2853539/CTH-rs648743), and heme toxicities ( P = .053, 3 SNPs: CYP3A5-rs776746/ABCB1-rs4148737/CTPS1-rs12067645). CONCLUSION Our results imply that instead of a single-SNP approach, SNP-SNP combinations in multiple genes in drug pathways increases the robustness of prediction of toxicity. These results further provide promising SNP models that can help establish clinically relevant biomarkers allowing for greater individualization of cancer therapy to maximize efficacy and minimize toxicity for each patient.

Background: This study aimed to characterize bodily injury patterns associated with helmet usage by comparing trauma sustained by helmeted and helmetless cyclists admitted to a large US health-care system. Materials and Methods: A prospective trauma registry associated with a large regional United States health-care network was queried for bicycle injuries resulting in hospital admission over a 5-year period. Data pertaining to helmet usage, demographics, injury description (s), Abbreviated Injury Scale score, Injury Severity Score, and hospital length of stay were collected from 140 patients treated for bicycle-related injuries. Mann–Whitney tests were performed. Results: Fifty-six of the injured cyclists were helmeted (40%) and 84 were not helmeted (60%). A significantly greater proportion of helmeted cyclists exhibited abrasions and a higher incidence of injury across all injury types (P =

Introduction: Despite cure rates in acute lymphoblastic leukemia (ALL) exceeding 90% in clinical trials, morbidity due to drug toxicities is high. Genetic polymorphisms can influence gene expression and activity, impacting pharmacokinetics and causing inter-individual variation in drug levels, which contributes to toxicity if levels are high or relapse if levels are low. We hypothesize that pharmacogenomic testing will identify patient specific variations in genes involved in metabolism of cytotoxic agents. This knowledge will allow clinicians to optimize therapy by providing pharmacogenomics based biomarkers related to increased toxicities. Data has shown that treatment interruptions and omissions due to toxicities affect outcomes and morbidities in children with cancer. Objective : To correlate pharmacogenomic biomarkers with toxicity phenotypes in children receiving therapy for ALL. Methods: This cross-sectional study involved subjects at a tertiary academic center (Fig. 1A). Subjects aged 1 year to 26 years with ALL treated after May 2012 were eligible. A total of 75 patients treated between 2012 and 2020 were included. Pharmacogenomic testing was performed on peripheral blood. Genomic DNA was tested for 118 single-nucleotide polymorphisms (SNP) in 55 genes for transport and metabolism of cytarabine, vincristine, methotrexate, dauno/doxorubicin, and mercaptopurine/thioguanine were analyzed using the Sequenom-based genotyping that uses MALDI-TOF based chemistry. SNPs were tested using logistic regression models for association with toxicities in additive, dominant, and recessive modes of inheritance. CTCAE v4.0 was used for grading all toxicities during the first 100 days of therapy. For endocrine (endo) and neurological (neuro) toxicities, 25 patients exhibited between grade 1-3 toxicities. For gastrointestinal (GI) toxicities, 25 patients exhibited between grade 2-3 toxicities. For hematological (heme) toxicities, 11 patients exhibited between grade 2-4 toxicities. Odds ratio and 95% confidence interval were calculated for each test and SNPs with association P-value 0, 0 or Results: For a GI toxicity score derived from 3 SNPs (TYMS-rs151264360, FPGS-rs1544105, and GSTM5-rs3754446), patients with >0 score had 79% incidence of GI toxicity (N=67) as compared to 10% in patients with score of 0 and 8% in patients with score 0; no toxicity was observed in patients with neurotoxicity score of 0 (p=4.7E-08, Fig. 1E). None of the patients with a score of Discussion: We identified germline SNPs predictive of toxicity phenotypes in a cohort of 75 subjects with ALL. The results of our multivariable SNP combination analysis suggest susceptibility to chemotherapy-induced toxicities is likely multigenic in nature. Instead of a single SNP approach, identification of combinations of mutations in drug pathways increases the robustness of predicting a patient's response to chemotherapy. Our results provide promising SNP models that can help establish clinically relevant biomarkers allowing for individualization of cancer therapy to optimize treatment for each patient. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

BackgroundDespite considerable health and environmental benefits, cycling is also associated with a risk of injury. Yet, variation in the patterns of cycling trauma which manifests by gender, age, ...