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Provez, L.

Publications and source records attributed to Provez, L..

2 recordsLinked to original sources

Profiling histone post-translational modifications to identify signatures of epigenetic drug response in T-cell acute lymphoblastic leukemia

Epigenetic modifications are dynamic and reversible, making them attractive targets for therapeutic intervention in cancer. Although several epigenetic drugs (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 epidrug 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 epidrugs including anthracyclines, histone deacetylase inhibitors, and DNA methyltransferase inhibitors. 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, we our analysis revealed substantial discepancies 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. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/673463v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1b15092org.highwire.dtl.DTLVardef@20bed5org.highwire.dtl.DTLVardef@1d0a687org.highwire.dtl.DTLVardef@1652999_HPS_FORMAT_FIGEXP M_FIG C_FIG Global hPTM profiling of 21 T-ALL cell lines was performed using LC-MS/MS, as previously published by Provez et al. In parallel, the 21 cell lines were treated with a dilution series of nine epidrugs, categorized into three distinct classes, to determine their IC50 values. Finally, Spearman correlation analysis was performed to assess the relationship between hPTM levels and drug sensitivity. Figure created with Biorender.com.

cancer biology↗

An interactive mass spectrometry atlas of histone posttranslational modifications in T-cell acute leukemia

The holistic nature of omics studies makes them ideally suited to generate hypotheses on health and disease. Sequencing-based genomics and mass spectrometry (MS)-based proteomics are linked through epigenetic regulation mechanisms. However, epigenomics is currently mainly focused on DNA methylation status using sequencing technologies, while studying histone posttranslational modifications (hPTMs) using MS is lagging, partly because reuse of raw data is impractical. Yet, targeting hPTMs using epidrugs is an established promising research avenue in cancer treatment. Therefore, we here present the most comprehensive MS-based preprocessed hPTM atlas to date, including 21 T-cell acute lymphoblastic leukemia (T-ALL) cell lines. We present the data in an intuitive and browsable single licensed Progenesis QIP project and provide all essential quality metrics, allowing users to assess the quality of the data, edit individual peptides, try novel annotation algorithms and export both peptide and protein data for downstream analyses, exemplified by the PeptidoformViz tool. This data resource sets the stage for generalizing MS-based histone analysis and provides the first reusable histone dataset for epidrug development.

cancer biology↗