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Profiling histone post-translational modifications to identify signatures of epigenetic drug response in T-cell acute lymphoblastic leukemia
Laboratory of Pharmaceutical Biotechnology, Ghent University, Ghent, Belgium; Cancer Research Institute Ghent (CRIG), Ghent, Belgium.
Cancer Research Institute Ghent (CRIG), Ghent, Belgium; Department of Biomolecular Medicine, Ghent University, Ghent, Belgium.
Umeå University, Faculty of Medicine, Department of Medical Biosciences. Umeå University, Faculty of Medicine, Department of Clinical Microbiology.
Umeå University, Faculty of Medicine, Department of Medical Biosciences. Umeå University, Faculty of Medicine, Department of Clinical Microbiology.
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2026 (English)In: Scientific Reports, E-ISSN 2045-2322, Vol. 16, no 1, article id 15029Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer Nature, 2026. Vol. 16, no 1, article id 15029
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Hematology
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URN: urn:nbn:se:umu:diva-253404DOI: 10.1038/s41598-026-44665-4ISI: 001766796100003PubMedID: 41882219Scopus ID: 2-s2.0-105039218267OAI: oai:DiVA.org:umu-253404DiVA, id: diva2:2063189
Funder
Swedish Cancer SocietyCancerforskningsfonden i NorrlandSwedish Childhood Cancer FoundationAvailable from: 2026-05-28 Created: 2026-05-28 Last updated: 2026-05-28Bibliographically approved

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Refhagen, NinaLandfors, MattiasDegerman, Sofie

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