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Landau, D. A.

Publications and source records attributed to Landau, D. A..

At least 19 recordsLinked to original sources

Cell autonomous inflammation in VEXAS is mediated by cGAS-STING

VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) is a severe adult-onset inflammatory disease caused by somatic mutations that reduce cytoplasmic activity of UBA1, the primary initiating enzyme for ubiquitylation. How this hypomorphic state drives cell-intrinsic immune activation in mature myeloid cells is unknown. Using unbiased multi-omic, biochemical, and cell biological analyses of model systems and patient-derived cells, we show that loss of cytoplasmic UBA1 activity convergently disrupts endoplasmic reticulum- associated degradation (ERAD) and mitochondrial homeostasis. ERAD failure arises from preferential under-charging of ERAD E2 enzymes, explaining hallmark VEXAS features, including ER-derived vacuoles and unfolded protein response activation, and promotes accumulation of the ERAD substrate STING. Simultaneously, mitochondrial dysfunction drives cytosolic leakage of mitochondrial DNA, inducing cGAS-dependent STING signaling and inflammatory cytokine production. STING inhibition or reversal of mitochondrial DNA leakage resolves multi-cytokine inflammation in VEXAS models and patient myeloid cells, establishing the cGAS-STING pathway as a therapeutically actionable vulnerability.

genetics↗

Large-scale single-cell phylogenetic mapping of clonal evolution in the human aging esophagus

The human somatic genome evolves throughout our lifespan, producing mosaic individuals comprising clones harboring different mutations across tissues. While clonal expansions in the hematopoietic system have been extensively characterized and reported to be nearly ubiquitous, clonal mosaicism (CM) has more recently also been described across multiple solid tissues. However, outstanding questions remain about the parameters and processes of human somatic evolution in non-cancerous solid human tissues, including when clones arise, how they evolve over time, and what mechanisms lead to their expansion. Questions of timing and clonal dynamics can be addressed through phylogenetic reconstruction, which serves as a temporal microscope, while uncovering the mechanisms of expansion necessitates simultaneous phenotypic profiling. To address this gap, here we develop Single-cell Miniaturized Automated Reverse Transcription and Primary Template-directed Amplification (SMART-PTA) for joint single-cell whole-genome and whole-transcriptome sequencing for large scale and cost efficient interrogation of solid tissue CM. We established a workflow that generates hundreds of matched single-cell whole genome and transcriptome libraries within a week. We profiled phenotypically normal esophagus tissue from four aged donors and used somatic variants to build high-resolution single-cell lineages from >2,700 cells with accompanying transcriptomic information, reconstructing >70 years of somatic evolution. T cell expansions identified from T cell receptor (TCR) sequences validated the clonal structure of the single-nucleotide variant (SNV)-based phylogenies and phylogenetic cross-correlation analysis showed that epithelial cells had higher degrees of shared ancestry by spatial location compared to immune cells. Mapping mutation signatures to the phylogenetic tree revealed the emergence of tobacco/alcohol exposure-related signatures later in life, consistent with the donors exposure histories. We identified variants in driver genes that were previously reported in the phenotypically normal esophagus, detecting clonal expansions harboring mutations in genes including TP53 and FAT1. We mapped the evolution of clones with both monoallelic as well as biallelic TP53 loss, including a clone associated with high expression of cell cycling genes and higher chromosome instability. Leveraging the matched transcriptome data, we uncovered cell type biases in mutant clones, with a higher proportion of TP53 or FAT1-mutant cells in an earlier basal epithelial cell state compared to wild-type cells. We further observed copy-neutral loss of heterozygosity (CNLOH) events on chromosome 9q that spanned the NOTCH1 locus in up to [~]35% of epithelial cells. Mapping CNLOH events to the phylogenetic tree revealed a striking pattern in which CNLOH was separately acquired many times, reflecting convergent evolution. Cells with CNLOH events were biased towards the earlier basal epithelial state, suggestive of a selective advantage that leads to prevalent recurrence of chr9q CNLOH. Together, we demonstrate that SMART-PTA is an efficient, scalable approach for single-cell whole-genome and whole-transcriptome profiling to build phenotypically annotated single-cell phylogenies with enough throughput and power for application to normal tissue somatic evolution. Moreover, we reconstruct the evolutionary history of the esophageal epithelium at high scale and resolution, providing a window into the dynamics and processes that shape clonal expansions in phenotypically normal tissues throughout a lifespan.

genomics↗

Paired plus-minus sequencing is an ultra-high throughput and accurate method for dual strand sequencing of DNA molecules

Distinguishing real biological variation in the form of single-nucleotide variants (SNVs) from errors is a major challenge for genome sequencing technologies. This is particularly true in settings where SNVs are at low frequency such as cancer detection through liquid biopsy, or human somatic mosaicism. State-of-the-art molecular denoising approaches for DNA sequencing rely on duplex sequencing, where both strands of a single DNA molecule are sequenced to discern true variants from errors arising from single stranded DNA damage. However, such duplex approaches typically require massive over-sequencing to overcome low capture rates of duplex molecules. To address these challenges, we introduce paired plus-minus sequencing (ppmSeq) technology, in which both DNA strands are partitioned and clonally amplified on sequencing beads through emulsion PCR. In this reaction, both strands of a double-stranded DNA molecule contribute to a single sequencing read, allowing for a duplex yield that scales linearly with sequencing coverage across a wide range of inputs (1.8-98 ng). We benchmarked ppmSeq against current duplex sequencing technologies, demonstrating superior duplex recovery with ppmSeq, with a rate of 44%{+/-}5.5% (compared to [~]5-11% for leading duplex technologies). Using both genomic as well as cell-free DNA, we established error rates for ppmSeq, which had residual SNV detection error rates as low as 7.98x10-8 for gDNA (using an end-repair protocol with dideoxy nucleotides) and 3.5x10-7{+/-}7.5x10-8 for cell-free DNA. To test the capabilities of ppmSeq for error-corrected whole-genome sequencing (WGS) for clinical application, we assessed circulating tumor DNA (ctDNA) detection for disease monitoring in cancer patients. We demonstrated that ppmSeq enables powerful tumor-informed ctDNA detection at concentrations of 10-4 across most cancers, parts per million sensitivity in cancers with high mutation burden, and further increased sensitivity with higher sequencing depth. We then leveraged genome-wide trinucleotide mutation patterns characteristic of urothelial (APOBEC3-related and platinum exposure-related signatures) and lung (tobacco-exposure-related signatures) cancers to perform tumor-naive ctDNA detection, showing that ppmSeq can identify a disease-specific signal in plasma cell-free DNA without a matched tumor, and that this signal correlates with imaging-based disease metrics. Altogether, ppmSeq provides an error-corrected, cost-efficient and scalable approach for high-fidelity WGS that can be harnessed for challenging clinical applications and emerging frontiers in human somatic genetics where high accuracy is required for mutation identification.

genomics↗

Ontogeny Dictates Oncogenic Potential, Lineage Hierarchy, and Therapy Response in Pediatric Leukemia

Accumulating evidence links pediatric cancers to prenatal transformation events, yet the influence of the developmental stage on oncogenesis remains elusive. We investigated how hematopoietic stem cell developmental stages affect leukemic transformation, disease progression, and therapy response using a novel, humanized model of NUP98::NSD1-driven pediatric acute myeloid leukemia, that is particularly aggressive with WT1 co-mutations. Fetal-derived hematopoietic stem cells readily transform into leukemia, and WT1 mutations further enhance stemness and alter lineage hierarchy. In contrast, stem cells from later developmental stages become progressively resistant to transformation. Single-cell analyses revealed that fetal-origin leukemia stem cells exhibit greater quiescence and reliance on oxidative phosphorylation than their postnatal counterparts. These differences drive distinct therapeutic responses, despite identical oncogenic mutations. In patients, onco-fetal transcriptional programs correlate with worse outcomes. By targeting key vulnerabilities of fetal-origin leukemia cells, we identified combination therapies that significantly reduce aggressiveness, highlighting the critical role of ontogeny in pediatric cancer treatment.

cancer biology↗

Measuring Longitudinal Genome-wide Clonal Evolution of Pediatric Acute Lymphoblastic Leukemia at Single-Cell Resolution

Approximately 15-20% of children with acute lymphoblastic leukemia (pALL) are not cured despite years of treatment with more than ten chemotherapeutic agents, yet bulk sequencing reveals minimal somatic variation that could explain genetic treatment resistance. Using error-corrected bulk sequencing, and primary template-directed amplification (PTA)-enabled single-cell exome and whole-genome sequencing, we discovered much more genetic diversity in pALL. Individual leukemic cells harbor 3.7-fold more mutations (mean 3,553) than detected in bulk samples (mean 965). Many ETV6-RUNX1 patients harbor multiple independent ras-mutated clones, and we also identified convergent evolution of JAK2 mutations as well as copy number alterations. PTA-based phylogenetic analysis of over 150 single-cell genomes linked heritable phenotypes to specific genetic alterations and identified low-frequency clones harboring mutations in treatment resistance-associated genes (ITGA9, NTRK3, SULF2) that increased in frequency during treatment. These findings reveal extensive hidden genetic diversity in pALL while providing a framework for the early detection of high-risk leukemic populations.

cancer biology↗

Genotype-to-phenotype mapping of somatic clonal mosaicism via single-cell co-capture of DNA mutations and mRNA transcripts

Somatic mosaicism is a hallmark of malignancy that is also pervasively observed in human physiological aging, with clonal expansions of cells harboring mutations in recurrently mutated driver genes. Bulk sequencing of tissue microdissection captures mutation frequencies, but cannot distinguish which mutations co-occur in the same clones to reconstruct clonal architectures, nor phenotypically profile clonal populations to delineate how driver mutations impact cellular behavior. To address these challenges, we developed single-cell Genotype-to-Phenotype sequencing (scG2P) for high-throughput, highly-multiplexed, single-cell joint capture of recurrently mutated genomic regions and mRNA phenotypic markers in cells or nuclei isolated from solid tissues. We applied scG2P to aged esophagus samples from five individuals with high alcohol and tobacco exposure and observed a clonal landscape dominated by a large number of clones with a single driver event, but only rare clones with two driver mutations. NOTCH1 mutants dominate the clonal landscape and are linked to stunted epithelial differentiation, while TP53 mutants and double-driver mutants promote clonal expansion through both differentiation biases and increased cell cycling. Thus, joint single-cell highly multiplexed capture of somatic mutations and mRNA transcripts enables high resolution reconstruction of clonal architecture and associated phenotypes in solid tissue somatic mosaicism.

genomics↗

Single-cell genotype-phenotype mapping identifies therapeutic vulnerabilities in VEXAS syndrome

Somatic evolution leads to the emergence of clonal diversity across tissues with broad implications for human health. A striking example of somatic evolution is the VEXAS (Vacuoles E1 enzyme X-linked Autoinflammatory Somatic) syndrome, caused by somatic UBA1 mutations in hematopoietic stem cells (HSCs), inducing treatment-refractory, systemic inflammation. However, the mechanisms that lead to survival and expansion of mutant HSCs are unknown, limiting the development of effective therapies. The lack of animal or cellular models of UBA1-mutant HSCs has hindered such mechanistic understanding, mandating analysis of primary human VEXAS samples, which harbor admixtures of wild-type and UBA1-mutant HSCs. To address these challenges, we applied single-cell multi-omics to comprehensively define mutant UBA1-induced transcriptome, chromatin accessibility and signaling pathway alterations in VEXAS patients, allowing for the direct comparison of mutant versus wild-type cells within the same environment. We confirmed the expected enrichment of UBA1M41V/T mutations in myeloid cells, and additionally discovered that these mutations were also prevalent in Natural Killer (NK) cells in VEXAS patients, providing new insights into disease phenotypes. Through mapping genotypes to molecular phenotypes, including transcriptome, chromatin accessibility, cell surface protein or intracellular protein profiles, in HSCs, we found that UBA1M41V/T-mutant cells showed an increased inflammation signature (interferon alpha and gamma response pathways), as well as activation of unfolded protein response (UPR) via pro-survival, but not pro-apoptotic, mediators of the PERK pathway, compared to UBA1 wild-type HSCs. Ex vivo validation experiments showed that inhibiting UBA1 in normal CD34+ or using UBA1-mutant HSCs led to PERK pathway up-regulation, increased myeloid differentiation and cell survival, which was reversed by PERK inhibition. Thus, we demonstrated that human VEXAS HSCs show cell-intrinsic inflammatory phenotypes and survive the proteomic stress caused by compromised ubiquitination through PERK-mediated activation of the UPR. Together, these analyses nominate PERK pathway inhibition as a potential new therapeutic strategy for eradicating the VEXAS-inducing clone, demonstrating the power of single-cell multi-omics profiling of primary patient sample to enable genotype-to-phenotype somatic mapping for the discovery of novel candidates for clinical intervention.

genomics↗

CRISPRmap: Sequencing-free optical pooled screens mapping multi-omic phenotypes in cells and tissue

Pooled genetic screens are powerful tools to study gene function in a high-throughput manner. Typically, sequencing-based screens require cell lysis, which limits the examination of critical phenotypes such as cell morphology, protein subcellular localization, and cell-cell/tissue interactions. In contrast, emerging optical pooled screening methods enable the investigation of these spatial phenotypes in response to targeted CRISPR perturbations. In this study, we report a multi-omic optical pooled CRISPR screening method, which we have named CRISPRmap. Our method combines a novel in situ CRISPR guide identifying barcode readout approach with concurrent multiplexed immunofluorescence and in situ RNA detection. CRISPRmap barcodes are detected and read out through combinatorial hybridization of DNA oligos, enhancing barcode detection efficiency, while reducing both dependency on third party proprietary sequencing reagents and assay cost. Notably, we conducted a multi-omic base-editing screen in a breast cancer cell line on core DNA damage repair genes involved in the homologous recombination and Fanconi anemia pathways investigating how nucleotide variants in those genes influence DNA damage signaling and cell cycle regulation following treatment with ionizing radiation or DNA damaging agents commonly used for cancer therapy. Approximately a million cells were profiled with our multi-omic approach, providing a comprehensive phenotypic assessment of the functional consequences of the studied variants. CRISPRmap enabled us to pinpoint likely-pathogenic patient-derived mutations that were previously classified as variants of unknown clinical significance. Furthermore, our approach effectively distinguished barcodes of a pooled library in tumor tissue, and we coupled it with cell-type and molecular phenotyping by cyclic immunofluorescence. Multi-omic spatial analysis of how CRISPR-perturbed cells respond to various environmental cues in the tissue context offers the potential to significantly expand our understanding of tissue biology in both health and disease.

genomics↗

Breast Cancer Macrophage Heterogeneity and Self-renewal are Determined by Spatial Localization

Tumor-infiltrating macrophages support critical steps in tumor progression, and their accumulation in the tumor microenvironment (TME) is associated with adverse outcomes and therapeutic resistance across human cancers. In the TME, macrophages adopt diverse phenotypic alterations, giving rise to heterogeneous immune activation states and induction of cell cycle. While the transcriptional profiles of these activation states are well-annotated across human cancers, the underlying signals that regulate macrophage heterogeneity and accumulation remain incompletely understood. Here, we leveraged a novel ex vivo organotypic TME (oTME) model of breast cancer, in vivo murine models, and human samples to map the determinants of functional heterogeneity of TME macrophages. We identified a subset of F4/80highSca-1+ self-renewing macrophages maintained by type-I interferon (IFN) signaling and requiring physical contact with cancer-associated fibroblasts. We discovered that the contact-dependent self-renewal of TME macrophages is mediated via Notch4, and its inhibition abrogated tumor growth of breast and ovarian carcinomas in vivo, as well as lung dissemination in a PDX model of triple-negative breast cancer (TNBC). Through spatial multi-omic profiling of protein markers and transcriptomes, we found that the localization of macrophages further dictates functionally distinct but reversible phenotypes, regardless of their ontogeny. Whereas immune-stimulatory macrophages (CD11C+CD86+) populated the tumor epithelial nests, the stroma-associated macrophages (SAMs) were proliferative, immunosuppressive (Sca-1+CD206+PD-L1+), resistant to CSF-1R depletion, and associated with worse patient outcomes. Notably, following cessation of CSF-1R depletion, macrophages rebounded primarily to the SAM phenotype, which was associated with accelerated growth of mammary tumors. Our work reveals the spatial determinants of macrophage heterogeneity in breast cancer and highlights the disruption of macrophage self-renewal as a potential new therapeutic strategy.

cancer biology↗

Defining ancestry, heritability and plasticity of cellular phenotypes in somatic evolution

The broad application of single-cell RNA sequencing has revealed transcriptional cell state heterogeneity across diverse healthy and malignant somatic tissues. Recent advances in lineage tracing technologies have further enabled the simultaneous capture of cell transcriptional state along with cellular ancestry thus enabling the study of somatic evolution at an unprecedented resolution; however, new analytical approaches are needed to fully harness these data. Here we introduce PATH (Phylogenetic Analysis of Transcriptional Heritability), an analytical framework, which draws upon classic approaches in species evolution, to quantify heritability and plasticity of somatic phenotypes, including transcriptional states. The PATH framework further allows for the inference of cell state transition dynamics by linking a model of cellular evolutionary dynamics with our measure of heritability versus plasticity. We evaluate the robustness of this approach by testing a range of biological and technical features in simulations of somatic evolution. We then apply PATH to characterize previously published and newly generated single-cell phylogenies, reconstructed from either native or artificial lineage markers, with matching cellular state profiling. PATH recovered developmental relationships in mouse embryogenesis, and revealed how anatomic proximity influences neural relatedness in the developing zebrafish brain. In cancer, PATH dissected the heritability of the epithelial-to-mesenchymal transition in a mouse model of pancreatic cancer, and the heritability versus plasticity of transcriptionally-defined cell states in human glioblastoma. Finally, PATH revealed phenotypic heritability patterns in a phylogeny reconstructed from single-cell whole genome sequencing of a B-cell acute lymphoblastic leukemia patient sample. Altogether, by bringing together perspectives from evolutionary biology and emerging single-cell technologies, PATH formally connects the analysis of cell state diversity and somatic evolution, providing quantification of critical aspects of these processes and replacing qualitative conceptions of "plasticity" with quantitative measures of cell state transitions and heritability.

evolutionary biology↗

Whole genome error-corrected sequencing for sensitive circulating tumor DNA cancer monitoring

Circulating cell-free DNA (ccfDNA) sequencing for low-burden cancer monitoring is limited by sparsity of circulating tumor DNA (ctDNA), the abundance of genomic material within a plasma sample, and pre-analytical error rates due to library preparation, and sequencing errors. Sequencing costs have historically favored the development of deep targeted sequencing approaches for overcoming sparsity in ctDNA detection, but these techniques are limited by the abundance of ccfDNA in samples, which imposes a ceiling on the maximal depth of coverage in targeted panels. Whole genome sequencing (WGS) is an orthogonal approach to ctDNA detection that can overcome the low abundance of ccfDNA by supplanting sequencing depth with breadth, integrating signal across the entire tumor mutation landscape. However, the higher cost of WGS limits the practical depth of coverage and hinders broad adoption. Lower sequencing costs may thus allow for enhanced ctDNA cancer monitoring via WGS. We therefore applied emerging lower-cost WGS (Ultima Genomics, 1USD/Gb) to plasma samples at [~]120x coverage. Copy number and single nucleotide variation profiles were comparable between matched Ultima and Illumina datasets, and the deeper WGS coverage enabled ctDNA detection at the parts per million range. We further harnessed these lower sequencing costs to implement duplex error-corrected sequencing at the scale of the entire genome, demonstrating a [~]1,500x decrease in errors in the plasma of patient-derived xenograft mouse models, and error rates of [~]10-7 in patient plasma samples. We leveraged this highly de-noised plasma WGS to undertake cancer monitoring in the more challenging context of resectable melanoma without matched tumor sequencing. In this context, duplex-corrected WGS allowed us to harness known mutational signature patterns for disease monitoring without matched tumors, paving the way for de novo cancer monitoring.

genomics↗

Type 1 interferon remodels normal and neoplastic hematopoiesis in human

Inflammation perturbs evolutionary dynamics of hematopoietic stem cell (HSC) clones in clonal hematopoiesis and myeloid neoplasms. We studied HSCs, progenitors and immune cells from patients with myeloproliferative neoplasm (MPN) at baseline and following interferon- (IFN) treatment, the only MPN therapy to deplete clonal stem cells. We focused on essential thrombocythemia, an informative model of early-phase neoplastic hematopoiesis. We integrated somatic genotyping, transcriptomes, immunophenotyping, and chromatin accessibility across single cells. IFN simultaneously activated HSCs into two polarized states, a lymphoid progenitor expansion associated with an anti-inflammatory state and an IFN-specific inflammatory granulocytic progenitor (IGP) state derived directly from HSCs. The augmented lymphoid differentiation balanced the typical MPN-induced myeloid bias, associated with normalized blood counts. Clonal fitness upon IFN exposure was due to resistance of clonal stem cells to differentiate into IGPs. These results support a paradigm wherein inflammation perturbs clonal dynamics by HSC induction into the precipitous IGP differentiation program. One-Sentence SummaryInflammation accelerates clonal evolution by driving stem cell differentiation into an alternate interferon--induced progenitor state.

cancer biology↗

Single-cell multi-omics defines the cell-type specific impact of splicing aberrations in human hematopoietic clonal outgrowths

RNA splicing factors are recurrently affected by alteration-of-function mutations in clonal blood disorders, highlighting the importance of splicing regulation in hematopoiesis. However, our understanding of the impact of dysregulated RNA splicing has been hampered by the inability to distinguish mutant and wildtype cells in primary patient samples, the cell-type complexity of the hematopoietic system, and the sparse and biased coverage of splice junctions by short-read sequencing typically used in single-cell RNA sequencing. To overcome these limitations, we developed GoT-Splice by integrating Genotyping of Transcriptomes (GoT) with enhanced efficiency long-read single-cell transcriptome profiling, as well as proteogenomics (with CITE-seq). This allowed for the simultaneous single-cell profiling of gene expression, cell surface protein markers, somatic mutation status, and RNA splicing. We applied GoT-Splice to bone marrow progenitors from patients with myelodysplastic syndrome (MDS) affected by mutations in the most prevalent mutated RNA splicing factor - the core RNA splicing factor SF3B1. High-resolution mapping of SF3B1mut vs. SF3B1wt hematopoietic progenitors revealed a fitness advantage of SF3B1mut cells in the megakaryocytic-erythroid lineage, resulting in an expansion of SF3B1mut erythroid progenitor (EP) cells. SF3B1mut EP cells exhibited upregulation of genes involved in regulation of cell cycle and mRNA translation. Long-read single-cell transcriptomes revealed the previously reported increase of aberrant 3 splicing site usage in SF3B1mut cells. However, the ability to profile splicing within individual cell populations uncovered distinct cryptic 3 splice site usage across different progenitor populations, as well as stage-specific aberrant splicing during erythroid maturation. Lastly, as splice factor mutations occur in clonal hematopoiesis (CH) with increased risk of neoplastic transformation, we applied GoT-Splice to CH samples. These data revealed that the erythroid lineage bias, as well as cell-type specific cryptic 3 splice site usage in SF3B1mut cells, precede overt MDS. Collectively, we present an expanded multi-omics single-cell toolkit to define the cell-type specific impact of somatic mutations on RNA splicing, from the earliest phases of clonal outgrowths to overt neoplasia, directly in human samples.

cancer biology↗

Jak2V617F Reversible Activation Shows an Essential Requirement for Jak2V617F in Myeloproliferative Neoplasms

Janus kinases (JAKs) mediate cytokine signaling, cell growth and hematopoietic differentiation.1 Gain-of-function mutations activating JAK2 signaling are seen in the majority of myeloproliferative neoplasm (MPN) patients, most commonly due to the JAK2V617F driver allele.2 While clinically-approved JAK inhibitors improve symptoms and outcomes in MPNs, remissions are rare, and mutant allele burden does not substantively change with chronic JAK inhibitor therapy in most patients.3, 4 This has been postulated to be due to incomplete dependence on constitutive JAK/STAT signaling, alternative signaling pathways, and/or the presence of cooperating disease alleles;5 however we hypothesize this is due to the inability of current JAK inhibitors to potently and specifically abrogate mutant JAK2 signaling. We therefore developed a conditionally inducible mouse model allowing for sequential activation, and then inactivation, of Jak2V617F from its endogenous locus using a Dre-rox/Cre-lox dual orthogonal recombinase system. Deletion of oncogenic Jak2V617Fabrogates the MPN disease phenotype, induces mutant-specific cell loss including in hematopoietic stem/progenitor cells, and extends overall survival to an extent not observed with pharmacologic JAK inhibition. Furthermore, reversal of Jak2V617F in MPN cells with antecedent loss of Tet26, 7 abrogates the MPN phenotype and inhibits mutant stem cell persistence suggesting cooperating epigenetic-modifying alleles do not alter dependence on mutant JAK/STAT signaling. Our results suggest that mutant-specific inhibition of JAK2V617F represents the best therapeutic approach for JAK2V617F-mutant MPN and demonstrate the therapeutic relevance of a dual-recombinase system to assess mutant-specific oncogenic dependencies in vivo.

cancer biology↗

Integrated Single-Cell Genotyping and Chromatin Accessibility Charts JAK2V617F Human Hematopoietic Differentiation

In normal somatic tissue differentiation, changes in chromatin accessibility govern priming and commitment of precursors towards cellular fates. In turn, somatic mutations can disrupt differentiation topologies leading to abnormal clonal outgrowth. However, defining the impact of somatic mutations on the epigenome in human samples is challenging due to admixed mutated and wildtype cells. To chart how somatic mutations disrupt epigenetic landscapes in human clonal outgrowths, we developed Genotyping of Targeted loci with single-cell Chromatin Accessibility (GoT-ChA). This high-throughput, broadly accessible platform links genotypes to chromatin accessibility at single-cell resolution, across thousands of cells within a single assay. We applied GoT-ChA to CD34+ cells from myeloproliferative neoplasm (MPN) patients with JAK2V617F-mutated hematopoiesis, where the JAK2 mutation is known to perturb hematopoietic differentiation. Differential accessibility analysis between wildtype and JAK2V617F mutant progenitors revealed both cell-intrinsic and cell state-specific shifts within mutant hematopoietic precursors. An early subset of mutant hematopoietic stem and progenitor cells (HSPCs) exhibited a cell-intrinsic pro-inflammatory signature characterized by increased NF-{kappa}B and JUN/FOS transcription factor motif accessibility. In addition, mutant HSPCs showed increased myeloid/erythroid epigenetic priming, preceding increased erythroid and megakaryocytic cellular output. Erythroid progenitors displayed aberrant regulation of the {gamma}-globin locus, providing an intrinsic epigenetic basis for the dysregulated fetal hemoglobin expression observed in MPNs. In contrast, megakaryocytic progenitors exhibited a more specialized inflammatory chromatin landscape relative to early HSPCs, with increased accessibility of pro-fibrotic JUN/FOS transcription factors. Notably, analysis of myelofibrosis patients treated with JAK inhibitors revealed an overall loss of mutant-specific phenotypes without modifying clonal burden, consistent with clinical responses. Finally, expansion of the multi-modality capability of GoT-ChA to integrate mitochondrial genome profiling and cell surface protein expression measurement enabled genotyping imputation and discovery of aberrant cellular phenotypes. Collectively, we show that the JAK2V617F mutation leads to epigenetic rewiring in a cell-intrinsic and cell type-specific manner. We envision that GoT-ChA will thus serve as a foundation for broad future explorations to uncover the critical link between mutated somatic genotypes and epigenetic alterations across clonal populations in malignant and non-malignant contexts.

cancer biology↗

Integrated protein and transcriptome high-throughput spatial profiling

Spatial transcriptomics and proteomics have independently transformed our understanding of complex biological processes; however, integration of these modalities is currently limited. To overcome this challenge, we developed Spatial PrOtein and Transcriptome Sequencing (SPOTS) for high-throughput integration of transcriptome and protein profiling within the spatial context. Applying SPOTS to spleen and breast cancer samples revealed that spatially-resolved multi-omic integration provides a comprehensive perspective on key biological processes in health and disease.

genomics↗

Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGE uses deep learning and a ctDNA-specific feature space to increase SNV signal to noise enrichment in WGS by 300X compared to our previous noise suppression platform MRDetect. MRD-EDGE also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1Gb to 200Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal to noise enrichment in MRD-EDGE enables de novo mutation calling in melanoma without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition.

genomics↗

Epigenetically bistable regions across neuron-specific genes govern neuron eligibility to a coding ensemble in the hippocampus

Episodic memories are stored in distributed neurons but how eligibility of individual neurons to coding ensembles is determined remains elusive. We identified thousands of predominantly bistable (CpG methylated or unmethylated) regions within neuronal gene bodies, established during the development of the mouse hippocampal dentate gyrus. Reducing DNA methylation and the proportion of the methylated epialleles at bistable regions compromised novel context-induced neuronal activation and spatial memory. Conversely, increasing methylation and the frequency of the methylated epialleles at bistable regions enhanced intrinsic excitability and spatial memory but impaired spatial working memory, indicating that the developmentally established methylated-unmethylated epiallelic balance at bistable regions is essential for proper neuronal excitability and hippocampal cognitive functions. Single-nucleus profiling revealed the enrichment of specific epialleles from a subset of bistable regions, primarily exonic, in encoding neurons. We propose a model in which epigenetically bistable regions create neuron heterogeneity, and specific constellations of exonic epialleles dictate, via modulating neuronal excitability, eligibility to a coding ensemble.

neuroscience↗