Faculty, Staff and Student Publications
Publication Date
10-4-2024
Journal
Cancer Discovery
Abstract
Acute lymphoblastic leukemia expressing the gamma delta T-cell receptor (γδ T-ALL) is a poorly understood disease. We studied 200 children with γδ T-ALL from 13 clinical study groups to understand the clinical and genetic features of this disease. We found age and genetic drivers were significantly associated with outcome. γδ T-ALL diagnosed in children under 3 years of age was extremely high-risk and enriched for genetic alterations that result in both LMO2 activation and STAG2 inactivation. Mechanistically, using patient samples and isogenic cell lines, we show that inactivation of STAG2 profoundly perturbs chromatin organization by altering enhancer-promoter looping, resulting in deregulation of gene expression associated with T-cell differentiation. High-throughput drug screening identified a vulnerability in DNA repair pathways arising from STAG2 inactivation, which can be targeted by poly(ADP-ribose) polymerase inhibition. These data provide a diagnostic framework for classification and risk stratification of pediatric γδ T-ALL. Significance: Patients with acute lymphoblastic leukemia expressing the gamma delta T-cell receptor under 3 years old or measurable residual disease ≥1% at end of induction showed dismal outcomes and should be classified as having high-risk disease. The STAG2/LMO2 subtype was enriched in this very young age group. STAG2 inactivation may perturb chromatin conformation and cell differentiation and confer vulnerability to poly(ADP-ribose) polymerase inhibition.
Keywords
Humans, LIM Domain Proteins, Adaptor Proteins, Signal Transducing, Child, Preschool, Male, Female, Precursor T-Cell Lymphoblastic Leukemia-Lymphoma, Infant, Child, Cell Cycle Proteins, Gene Rearrangement, Proto-Oncogene Proteins
DOI
10.1158/2159-8290.CD-23-1452
PMID
38916500
PMCID
PMC11452281
PubMedCentral® Posted Date
4-4-2025
PubMedCentral® Full Text Version
Author MSS
Published Open-Access
yes
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Bioinformatics Commons, Biomedical Informatics Commons, Genetic Phenomena Commons, Medical Genetics Commons, Oncology Commons