Biology subjects

Itzykson, R.

Publications and source records attributed to Itzykson, R..

4 recordsLinked to original sources

bioRxiv2026

Chemical Proteomics of Residual Acute Myeloid Leukemia Cells Reveals Therapeutic Vulnerabilities

Venetoclax combined with azacitidine has improved treatment outcomes in acute myeloid leukemia (AML), yet relapse and treatment persistence remain major clinical challenges. To investigate proteomic mechanisms associated with venetoclax-azacitidine response and adaptation, we applied a multi-layer combinatorial proteome integral solubility/stability alteration analysis (CoPISA) strategy in SKM-1 AML cells. Cells were treated with venetoclax, azacitidine, their combination, or vehicle control and profiled across four orthogonal layers: short-term lysate CoPISA, short-term intact-cell CoPISA, long-term intact-cell CoPISA after 5 days of treatment, and long-term expression proteomics of surviving cells. The venetoclax-azacitidine combination induced treatment-specific protein solubility and abundance changes that were not fully reproduced by either single agent. Long-term surviving cells displayed extensive proteomic remodeling, consistent with the emergence of an adaptive drug-tolerant state, although contributions from pre-existing resilient cell populations cannot be excluded. Integration of short- and long-term solubility changes with abundance remodeling revealed distinct adaptive regimes, including retained biochemical targets, dosage-compensated targets, sensitive-state-specific targets, and remodeled adaptive targets. This framework prioritized candidate resistance-associated proteins, including NRP2, RPL18, PLP2, RPS28, and NOTCH1. NRP2 emerged as a top candidate across all proteomics layers, consistently showing increased abundance. Overall, this study shows that combining CoPISA with expression proteomics can resolve temporally distinct proteomic states of venetoclax-azacitidine response and identify candidate adaptive vulnerabilities in AML.

cancer biology↗

bioRxiv2024

CXCL8 secreted by immature granulocytes inhibits wildtype hematopoiesis in chronic myelomonocytic leukemia

Chronic myelomonocytic leukemia (CMML) is a severe myeloid malignancy with limited therapeutic options. Single-cell analysis of clonal architecture demonstrated early clonal dominance with few residual wildtype hematopoietic stem cells. Circulating myeloid cells of the leukemic clone and the cytokines they produce generate a deleterious inflammatory climate. Our hypothesis is that therapeutic control of the inflammatory component in CMML could contribute to stepping down disease progression. The present study explores the contribution of immature granulocytes (iGRANs) to CMML progression. iGRANs can be detected and quantified in the peripheral blood of patients by spectral and conventional flow cytometry. Their accumulation is a potent and independent poor prognostic factor. These cells belong to the leukemic clone and behave as myeloid-derived suppressor cells. Bulk and single cell RNA sequencing revealed a pro-inflammatory status of iGRAN that secrete multiple cytokines of which CXCL8 at the highest level. This cytokine inhibits the proliferation of wildtype but not CMML hematopoietic stem and progenitor cells (HSPCs) in which CXCL8 receptors are epigenetically downregulated. CXCL8 receptor inhibitors and CXCL8 blockade restore wildtype HSPC proliferation, suggesting that relieving CXCL8 selective pressure on wildtype HSPCs is a potential strategy to slow CMML progression and restore some healthy hematopoiesis.

cancer biology↗

bioRxiv2024

Targeting Heterochromatin Eliminates Malignant Stem Cells in Chronic Myelomonocytic Leukemia Through Reactivation of Retroelements and Innate Immune pathways

Chronic myelomonocytic leukemia (CMML) is a severe myeloid malignancy affecting the elderly, for which therapeutic options are limited. DNA hypomethylating agents (HMAs) provide transient responses, failing to eradicate the malignant clone. Hematopoietic stem cell (HSC) aging involves heterochromatin reorganization, evidenced by alterations in histone marks H3K9me2 and H3K9me3. These repressive marks together with DNA methylation are essential for suppressing transposable elements (TEs). In solid cancers, the antitumor efficacy of HMAs involves the derepression of TEs, mimicking a state of viral infection. In this study, we demonstrate a significant disorganization of heterochromatin in CMML HSCs and progenitors (HSPCs) characterized by an increase in the repressive mark H3K9me2, mainly at the level of TEs, and a repression of immune and age-associated transcripts. Combining HMAs with G9A/GLP H3K9me2 methyltransferase inhibitors reactivates these pathways, selectively targeting mutated cells while preserving wild-type HSCs, thus offering new therapeutic avenues for this severe myeloid malignancy.

cancer biology↗

bioRxiv2022

Frugal alignment-free identification of FLT3-internal tandem duplications with FiLT3r

BackgroundInternal tandem duplications in the FLT3 gene, termed FLT3-ITDs, are useful molecular markers in acute myeloid leukemia (AML) for patient risk stratification and follow-up. FLT3-ITDs are increasingly screened through high-throughput sequencing (HTS) raising the need for robust and efficient algorithms. We developed a new algorithm, which performs no alignment and uses little resources, to identify and quantify FLT3-ITDs in HTS data. ResultsOur algorithm (FiLT3r) focuses on the k-mers from reads covering FLT3 exons 14 and 15. We show that those k-mers bring enough information to accurately detect, determine the length and quantify FLT3-ITD duplications. We compare the performances of FiLT3r to state-of-the-art alternatives and to fragment analysis, the gold standard method, on a cohort of 185 AML patients sequenced with capture-based HTS. On this dataset FiLT3r is more precise (no false positive nor false negative) than the other software evaluated. We also assess the software on public RNA-Seq data, which confirms the previous results and shows that FiLT3r requires little resources compared to other software. ConclusionFiLT3r is a free software available at https://gitlab.univ-lille.fr/filt3r/filt3r. The repository also contains a Snakefile to reproduce our experiments. We show that FiLT3r detects FLT3-ITDs better than other software while using less memory and time.

bioinformatics↗