Biology subjects

Itzykson, R.

Publications and source records attributed to Itzykson, R..

3 recordsLinked to original sources

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↗