Faculty, Staff and Student Publications
Publication Date
5-15-2024
Journal
Clinical Cancer Research
Abstract
PURPOSE: Mutations in the ATM gene are common in multiple cancers, but clinical studies of therapies targeting ATM-aberrant cancers have yielded mixed results. Refinement of ATM loss of function (LOF) as a predictive biomarker of response is urgently needed.
EXPERIMENTAL DESIGN: We present the first disclosure and preclinical development of a novel, selective ATR inhibitor, ART0380, and test its antitumor activity in multiple preclinical cancer models. To refine ATM LOF as a predictive biomarker, we performed a comprehensive pan-cancer analysis of ATM variants in patient tumors and then assessed the ATM variant-to-protein relationship. Finally, we assessed a novel ATM LOF biomarker approach in retrospective clinical data sets of patients treated with platinum-based chemotherapy or ATR inhibition.
RESULTS: ART0380 had potent, selective antitumor activity in a range of preclinical cancer models with differing degrees of ATM LOF. Pan-cancer analysis identified 10,609 ATM variants in 8,587 patient tumors. Cancer lineage-specific differences were seen in the prevalence of deleterious (Tier 1) versus unknown/benign (Tier 2) variants, selective pressure for loss of heterozygosity, and concordance between a deleterious variant and ATM loss of protein (LOP). A novel ATM LOF biomarker approach that accounts for variant classification, relationship to ATM LOP, and tissue-specific penetrance significantly enriched for patients who benefited from platinum-based chemotherapy or ATR inhibition.
CONCLUSIONS: These data help to better define ATM LOF across tumor types in order to optimize patient selection and improve molecularly targeted therapeutic approaches for patients with ATM LOF cancers.
Keywords
Animals, Humans, Mice, Antineoplastic Agents, Ataxia Telangiectasia Mutated Proteins, Biomarkers, Tumor, Cell Line, Tumor, Loss of Function Mutation, Neoplasms, Xenograft Model Antitumor Assays
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Medical Sciences Commons, Oncology Commons
Comments
Supplementary Materials
Data Availability Statement
PMID: 38416404