Abstract
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.
Data availability
Cell line mass spectrometry raw data and analysis files were obtained from the ProteomeXchange Consortium (http://www.proteomexchange.org) under the dataset identifier PXD031500. Mass spectrometry raw data (*.wiff and *.scan files) and analysis files from the T-ALL PDX models generated in this study have been deposited to the ProteomeXchange Consortium via the PRIDE65 partner repository with the dataset identifier PXD067935 and https://doi.org/10.6019/PXD06793. The data is currently accessible with the token ywBECfsz6hWu and will be made publicly available after publication. All analysis scripts to process data and re-create figures are available at https://github.com/lcorvele/pharmacoepigenetics.
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Acknowledgements
This study has been supported by grants from The Research Foundation Flanders (FWO) awarded to L.C. (1SF2622N) and M.D. (12E9716N) and a preclinical research grant from Stand Up To Cancer (Kom Op Tegen Kanker-Flanders) awarded to P.V.V. PDX models were generated with technical support from the PDXGhent core facility, with financial support from The Research Foundation Flanders (FWO) for medium-scale research infrastructure, Ghent University and Cancer Research Institute Ghent (CRIG). Additional support was provided by The Swedish Childhood Cancer Foundation, the Swedish Cancer Society, the Cancer Research Foundation in Northern Sweden, and the Medical Faculty of Umeå University. The PER-117 cell line was kindly provided by the PCH Oncology Biobank (Prof. Rishi S. Kotecha) which is funded by the Western Australian Future Health Research and Innovation Fund.
Funding
Fonds Wetenschappelijk Onderzoek, 1SF2622N,12E9716N, Western Australian Future Health and Innovation Fund, Government of Western Australia, Cancerfonden, Cancerforskningsfonden i Norrland, Barncancerfonden, Cancer Research Institute Ghent, Kom op tegen Kanker
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L.C.: conceptualization, in vitro and ex vivo treatment, histone sample preparation, data acquisition, data analysis, writing. L.P.: conceptualization, in vitro treatment, PDX generation and in vivo treatment, writing. O.S.: in vitro treatment, writing. B.L.: cell culture. N.R. DNA methylation analysis. S.D.: DNA methylation analysis and co-supervision. M.L.: DNA methylation analysis. W.S.: PDX generation and biobanking. A.D.M.: data analysis and writing. R.S.K.: provision of cell line material. B.D.M. and T.L.: collection of patient samples and clinical data collection. S.G.: co-supervision. D.D.: co-supervision. P.V.V.: conceptualization, supervision. M.D.: conceptualization, writing, supervision.
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Corveleyn, L., Provez, L., Satilmis, O. et al. Profiling histone post-translational modifications to identify signatures of epigenetic drug response in T-cell acute lymphoblastic leukemia. Sci Rep (2026). https://doi.org/10.1038/s41598-026-44665-4
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DOI: https://doi.org/10.1038/s41598-026-44665-4
