ArticleJCO precision oncology2023
Polygenic Pharmacogenomic Markers as Predictors of Toxicity Phenotypes in the Treatment of Acute Lymphoblastic Leukemia: A Single-Center Study.
Article in JCO precision oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 10 citations in OpenAlex.
- The impact of gene polymorphisms on the response of methotrexate-based treatments.European journal of clinical pharmacology · 2026Pooled it
- Influence of FPGS rs1544105 and GGH rs3758149 Gene Polymorphisms on Methotrexate Pharmacogenetics.Biochemical genetics · 2026Pooled it
- Pharmacogenetic Predictors of Chemotherapy Treatment-Related Toxicities in Paediatric and Adolescent Acute Lymphoblastic Leukemia: A Systematic Review, Meta-Analysis and Literature-Based Candidate Prioritization.Pharmaceuticals (Basel, Switzerland) · 2026Review
- The impact of asparaginase phenotype-related single nucleotide polymorphisms on prognosis in pediatric B-cell precursor acute lymphoblastic leukemia.European journal of medical research · 2025Article
- Omega-3 fatty acids and chemotherapy-induced toxicities: mechanisms and emerging evidence with a pediatric focus.Nutrition & metabolism · 2025Review
- Pharmacogenomics Applied to Acute Leukemias: Identifying Clinically Relevant Genetic Variants.Biomedicines · 2025Review
- Antihypertensives associated adverse events: a review of mechanisms and pharmacogenomic biomarkers available evidence in multi-ethnic populations.Frontiers in pharmacology · 2023Review
Corrections and comments
- Erratum issued
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
purposeAcute 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.
methodsThis 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.
resultsWe 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 (
conclusionOur 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.