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Epigenetic modifications are dynamic and reversible, making them attractive targets for therapeutic intervention in cancer. Although several drugs targeting epigenetic modifications (epidrugs) have been clinically approved, their application in T-cell acute lymphoblastic leukemia (T-ALL) remains limited, and predictive biomarkers of response are lacking. Here, we present a mass spectrometry (MS)-based pharmacoepigenetic approach to profile histone post-translational modifications (hPTMs) to identify signatures associated with drug sensitivity in T-ALL . Baseline hPTM landscapes were previously established by our group for 21 T-ALL cell lines using liquid chromatography–tandem mass spectrometry (LC–MS/MS). Here, we treated these cell lines with a panel of nine drugs including histone deacetylase inhibitors and DNA methyltransferase inhibitors (epidrugs), alongside anthracyclines, which were included due to their known chromatin-related effects. Correlation of cell viability data with hPTM levels revealed distinct hPTM signatures linked to sensitivity for each drug class. These signatures were subsequently evaluated in T-ALL patient-derived xenograft (PDX) models. However, our analysis revealed substantial discrepancies in hPTM sensitivity signatures compared to those observed in vitro. Co-variation network analysis highlighted divergence in hPTM-hPTM correlation between the two models, underscoring limitations of cell lines for modeling dynamic epigenetic regulation in vivo. Our findings establish a framework for MS-based hPTM profiling in T-ALL and emphasize the importance of model selection in developing predictive epigenetic biomarkers.

Current intensive treatment of pediatric T-cell acute lymphoblastic leukemia (T-ALL) has substantial side effects, highlighting a need for novel biomarkers to improve risk stratification. Canonical biomarkers, such as genetics and immunophenotype, are largely not used in pediatric T-ALL stratification. This study aimed to validate the prognostic relevance of DNA methylation CpG island methylator phenotype (CIMP) risk stratification in 2 pediatric T-ALL patient cohorts: the Nordic Society of Paediatric Haematology (NOPHO) ALL2008 T-ALL study cohort (n = 192) and the Dutch Childhood Oncology Group (DCOG) ALL-10/ALL-11 validation cohorts (n = 156). Both cohorts revealed that combining CIMP classification at diagnosis with measurable residual disease (MRD) at treatment day 29 (D29) or 33 (D33) significantly improved outcome prediction. The poor prognosis subgroup, characterized by CIMP low/D29 or D33 MRD ≥ 0.1%, had a cumulative incidence of relapse (pCIR5yr) of 29% and 23% and overall survival (pOS5yr) of 59.7% and 65.4%, in NOPHO and DCOG, respectively. Conversely, a good prognosis subgroup was also identified representing CIMP high/D29 or D33 MRD < 0.1% with pCIR5yr of 0% and 3.4% and pOS5yr of 98.2% and 94.8%, in NOPHO and DCOG, respectively. For NOPHO, MRD was also evaluated on D15, and the relapse prediction accuracy of CIMP/D29 MRD (0.79) and CIMP/D15 MRD (0.75) classification was comparable, indicating potential for earlier stratification. The evaluation of the biology behind the CIMP subgroups revealed associations with transcriptome profiles, genomic aberrations, and mitotic history, suggesting distinct routes for leukemia development. In conclusion, integrating MRD assessment with the novel CIMP biomarker has the potential to improve risk stratification in pediatric T-ALL and guide future therapeutic decisions.