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Abelson, S.

Publications and source records attributed to Abelson, S..

10 recordsLinked to original sources

Multi-platform reassessment of human mitochondrial DNA methylation reveals signals consistent with technical artifacts

The existence and functional relevance of mitochondrial DNA methylation remain controversial. Here, we systematically profiled cytosine methylation and hydroxymethylation across human brain and blood tissues spanning healthy and malignant states using orthogonal sequencing approaches that avoid chemical conversion during library preparation. While nuclear DNA exhibited canonical methylation patterns, mitochondrial DNA consistently showed negligible signal, indistinguishable from background technical noise. By mapping cytosine-guanine sites between mitochondrial DNA and nuclear-embedded mitochondrial sequences, we demonstrate the potential of these nuclear counterparts to confound not only cytosine methylation but also hydroxymethylation measurements, corroborating and extending prior findings implicating nuclear contamination as a potential source of apparent mitochondrial epigenetic signals. Additional technical factors that inflate apparent mtDNA methylation signals were identified, including sequence context biases, flow cell chemistries, and coverage-dependent discrepancies between the heavy and light strands. Collectively, these results provide convergent evidence against the presence of biologically meaningful cytosine methylation or hydroxymethylation in mitochondrial DNA. These findings caution against interpreting apparent mtDNA methylation signals in human adult tissues as meaningful without rigorous orthogonal validation and comprehensive consideration of technical and analytical confounding factors.

bioinformatics↗

A Pan-Cancer Single-Cell Compendium of Intratumoural Heterogeneity.

Intratumoural heterogeneity remains one of the most formidable challenges in oncology, driving treatment resistance, disease progression, and poor patient outcomes. To uncover the cellular programs that define tumour composition and diversity, we interrogated over 3.6 million single cells derived from more than 1,000 primary and metastatic tumours spanning 14 diverse cancer types. Through the identification and quantification of coordinated gene expression programs, we delineated heterogeneous cancer cell states, exhibiting unique and clinically significant associations with patient survival. Integration with high-resolution spatial transcriptomics identified prognostic cancer cell states marked by aggressive transcriptional programs, co-localizing with invasive histological features and significantly enriched in metastatic settings. Functional drug perturbation screening uncovered drug vulnerabilities specific to distinct cancer cell states, supporting both direct targeting strategies and therapeutic reprogramming toward less aggressive cellular phenotypes. Collectively, this study offers novel insights into the relationship between intratumoural transcriptional heterogeneity, spatial organization, clinical outcomes, and therapeutic vulnerabilities.

cancer biology↗

Multi-selective RAS(ON) Inhibition Targets Oncogenic RAS Mutations and Overcomes RAS/MAPK-Mediated Resistance to FLT3 and BCL2 Inhibitors in Acute Myeloid Leukemia

Aberrant activation of the RAS/MAPK signaling limits the clinical efficacy of several targeted therapies in acute myeloid leukemia (AML). In FLT3-mutant AML, the selection of clones harboring heterogeneous RAS mutations drives resistance to FLT3 inhibitors (FLT3i). RAS activation is also associated with resistance to other AML targeted therapies, including the BCL2 inhibitor venetoclax. Despite the critical need to inhibit RAS/MAPK signaling in AML, no targeted therapies have demonstrated clinical benefit in RAS-driven AML. To address this unmet need, we investigated the preclinical activity of RMC-7977, a multi-selective inhibitor of GTP-bound active [RAS(ON)] isoforms of mutant and wild-type RAS in AML models. RMC-7977 exhibited potent antiproliferative and pro-apoptotic activity across AML cell lines with MAPK-activating signaling mutations. In cell line models with acquired FLT3i resistance due to secondary RAS mutations, treatment with RMC-7977 restored sensitivity to FLT3i. Similarly, RMC-7977 effectively reversed resistance to venetoclax in RAS-addicted cell line models with both RAS wild-type and mutant genetic backgrounds. In murine patient-derived xenograft models of RAS-mutant AML, RMC-7977 was well tolerated and significantly suppressed leukemic burden in combination with gilteritinib or venetoclax. Our findings strongly support clinical investigation of broad-spectrum RAS(ON) inhibition in AML to treat and potentially prevent drug resistance due to activated RAS signaling.

cancer biology↗

In vivo validation of the palmitoylation cycle as a therapeutic target in NRAS-mutant cancer

Ras proteins are functionally dependent on one or more lipid modifications.1,2 The dynamic palmitoylation of N-Ras by DHHC palmitoyl acyltransferases and depalmitoylation by ABHD17 serine hydrolases is essential for the growth of NRAS-mutant acute myeloid leukemia (AML) cells.3-6 Here we show that ABD778, an in vivo-active ABHD17 inhibitor, selectively reduces the growth of NRAS-mutant AML and melanoma cell lines and is synergistic with the MEK inhibitor PD0325901 (PD901; mirdametinib). Mechanistically, ABD778 and PD901 induce deep and durable suppression of mitogen activated protein kinase (MAPK) pathway activation. Co-treatment extended the survival of mice transplanted with NrasG12D AMLs, which acquired by-pass mutations at relapse that conferred drug resistance and restored MAPK activation. ABD778 augmented the anti-leukemia activity of PI3 kinase, pan-Ras tri-complex, and FLT3 inhibitors, and restored gilteritinib sensitivity in a patient-derived xenograft model of FLT3 inhibitor resistance. These studies validate the palmitoylation cycle as a therapeutic target in NRAS-mutant cancers.

cancer biology↗

Blood-based Epigenetic Instability Linked to Human Aging and Disease

The abundance, dynamics, and context-dependent heterogeneity of DNA methylation--where a pattern considered abnormal in one cell type may be normal in another--poses challenges in identifying methylation abnormalities linked to disease risk. Through genome-wide analyses, we identified CpG sites with remarkably consistent methylation profiles in healthy whole blood, predominantly existing in an unmethylated state. We examined alterations at these epigenetically stable loci in diverse cohorts, including those with cardiovascular disease and hematological cancers. Our findings reveal methylation pattern disruption in myeloid and lymphoid malignancies, correlating with clonal burden fluctuations during leukemia treatment. In non-cancer cohorts, we observed that normally stable CpG sites exhibited progressive instability with advancing age, which was also associated with the onset of cardiovascular disease and decreased survival rates. This study links DNA methylation instability with the expansion of risk-prone blood cells and highlights its role as a biomarker for both cancer and cardiovascular disease.

genetics↗

Hematopoietic Tet2 inactivation enhances the response to checkpoint blockade immunotherapy

Somatic mutations inactivating TET2 are among the most common drivers of clonal hematopoiesis (CH). While TET2 inactivation is associated with monocyte-derived inflammation and improved chimeric antigen-receptor-T cell function, its impact on immunotherapy response is unknown. In our mouse model, hematopoietic Tet2 mutation enhanced immune checkpoint blockade (ICB) response. Enhanced ICB response with Tet2 mutation required phagocytes, CD4 and CD8 T cells. Mechanistically, in Tet2-mutant tumor-infiltrating leukocytes (TILs), ICB preferentially induced anti-tumor states and restricted cell states linked to tumor progression. Tet2-mutant monocytes activated costimulatory programs, while Tet2-mutant T cells showed enhanced T cell memory signatures, lesser exhaustion and decreased regulatory phenotype. Our murine data was clinically relevant, since we found that melanomas from patients with TET2 driver mutation-CH (TET2-CH) showed enhanced immune infiltration, T cell activation, and T cell memory programs. In melanoma patients treated with ICB, TET2-CH was associated with 6-fold greater odds of clinical benefit. Collectively, our data establishes that hematopoietic Tet2 inactivation primes leukocytes for anti-tumor states associated with immunotherapy response and provides a potential biomarker for personalized therapy.

cancer biology↗

FLT3 is genetically essential for ITD-mutated leukemic stem cells but dispensable for human hematopoietic stem cells

Leukemic stem cells (LSCs) fuel acute myeloid leukemia (AML) growth and relapse, but therapies tailored towards eradicating LSCs without harming healthy hematopoietic stem cells (HSCs) are lacking. FLT3 is considered an important therapeutic target due to frequent mutation in AML and association with relapse. However, there has been limited clinical success with FLT3 targeting, suggesting either that FLT3 is not a vulnerability in LSC, or that more potent inhibition is required, a scenario where HSC toxicity could become limiting. We tested these possibilities by ablating FLT3 using CRISPR/Cas9-mediated FLT3 knock-out (FLT3-KO) in human LSCs and HSCs followed by functional xenograft assays. FLT3-KO in LSCs from FLT3-ITD mutated, but not FLT3-WT AMLs, resulted in short-term leukemic grafts of FLT-3-KO edited cells that disappeared by 12 weeks. By contrast, FLT3-KO in HSCs from fetal liver, cord blood and adult bone marrow did not impair multilineage hematopoiesis in primary and secondary xenografts. Our study establishes FLT3 as an ideal therapeutic target where ITD+ LSC are eradicated upon FLT3 deletion, while HSCs are spared. These findings support the development of more potent FLT3-targeting drugs or gene-editing approaches for LSC eradication to improve clinical outcomes. KEY POINTSThe FLT3 gene is essential for ITD-mutated leukemic stem cells (LSCs) to establish and propagate leukemia. Normal human hematopoietic stem cells (HSCs) do not require FLT3 to engraft and sustain hematopoiesis. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=179 SRC="FIGDIR/small/601363v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@b77f56org.highwire.dtl.DTLVardef@109011dorg.highwire.dtl.DTLVardef@282e04org.highwire.dtl.DTLVardef@1e51e3b_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Pan-cancer classification of single cells in the tumour microenvironment

Single-cell RNA sequencing reveals valuable insights into cellular heterogeneity within tumour microenvironments (TMEs), paving the way for a deep understanding of cellular mechanisms contributing to cancer. However, high heterogeneity among the same cancer types and low transcriptomic variation in immune cell subsets present challenges for accurate, high-resolution confirmation of cells identities. Here we present scATOMIC; a modular annotation tool for malignant and non-malignant cells. We trained scATOMIC on >250,000 cancer, immune, and stromal cells defining a pan-cancer reference across 19 common cancer types and employed a novel hierarchical approach, outperforming current classification methods. We extensively confirmed scATOMICs accuracy on 198 tumour biopsies and 54 blood samples encompassing >420,000 cancer and a variety of TME cells. Lastly, we demonstrate scATOMICs practical significance to accurately subset breast cancers into clinically relevant subtypes and predict tumours primary origin across metastatic cancers. Our approach represents a broadly applicable strategy to analyze multicellular cancer TMEs.

bioinformatics↗

SmMIP-tools: a computational toolset for processing and analysis of single-molecule molecular inversion probes derived data

Single-molecule molecular inversion probes (smMIPs) provides a modular and cost-effective platform for high-multiplex targeted next-generation sequencing (NGS). Nevertheless, translating the raw smMIP-derived sequencing data into accurate and meaningful information currently requires proficient computational skills and a large amount of computational work, prohibiting wide-scale adoption of smMIP-based technologies. To enable easy, efficient, and accurate interrogation of smMIP-derived data, we developed SmMIP-tools, a computational toolset that combines the critical analytic steps for smMIP data interpretation into a single computational pipeline. Here, we describe in detail two of the softwares major components. The first is a read processing tool that performs quality control steps, generates read-smMIP linkages and retrieves molecular tags. The second is an error-aware variant caller capable of detecting single nucleotide variants (SNVs) and short insertions and deletions (indels). Using a cell-line DNA dilution series and a cohort of blood cancer patients, we benchmarked SmMIP-tools and evaluated its performance against clinical sequencing reports. We anticipate that SmMIP-tools will increase accessibility to smMIP-technology, enabling cost-effective genetic research to push personalized medicine forward.

genomics↗

Interacting evolutionary pressures drive mutation dynamics and health outcomes in aging blood

A small population of self-renewing, hematopoietic stem cells continuously reconstitutes our immune system. As we age, these cells, or their pluripotent descendants, accumulate somatic mutations; some of these mutations provide selection advantages and increase in frequency in the peripheral blood cell population. This process of positive selection, deemed age-related clonal hematopoiesis (ARCH), is associated with increased risk for cardiac disease and blood malignancies, like acute myeloid leukemia (AML). However, it remains unclear why some people with ARCH do not progress to AML, even when their blood cells harbor well-known AML driver mutations. Here, we examine whether negative selection can play a role in determining AML progression by modelling the complex interplay of positive and negative selective processes. Using a novel approach combining deep learning and population genetic models, we detect pervasive negative selection in targeted sequence data from the blood of 92 pre-AML individuals and 385 healthy controls. We find that the relative proportion of passenger to driver mutations is critical in determining if the selective advantage conferred to a cell by a known driver mutation is able to overwhelm negative selection acting on passenger mutations and allow clones harbouring disease-predisposing mutations to rise to dominance. We find that a subset of non-driver genes is enriched for mildly damaging mutations in healthy individuals fitting purifying models of evolution suggesting that mutations in these genes might confer a protective role against disease-predisposing clonal expansions. Through exploring non drivercentric models of evolution, we show how different classes of evolution act to shape hematopoietic dynamics and subsequent health outcome which may better inform disease prediction and unveil novel therapeutic targets. We anticipate that our results and modelling techniques can be broadly applied to identify both driver mutations and those mildly damaging passenger mutations, as well as help understand the early evolution of cancer in other cells and tissues.

cancer biology↗