Epigenetic therapy induces transcription of inverted SINEs and ADAR1 dependency.

Cancer therapies that target epigenetic repressors can mediate their effects by activating retroelements within the human genome. Retroelement transcripts can form double-stranded RNA (dsRNA) that activates the MDA5 pattern recognition receptor1-6. This state of viral mimicry leads to loss of cancer cell fitness and stimulates innate and adaptive immune responses7,8. However, the clinical efficacy of epigenetic therapies has been limited. To find targets that would synergize with the viral mimicry response, we sought to identify the immunogenic retroelements that are activated by epigenetic therapies. Here we show that intronic and intergenic SINE elements, specifically inverted-repeat Alus, are the major source of drug-induced immunogenic dsRNA. These inverted-repeat Alus are frequently located downstream of 'orphan' CpG islands9. In mammals, the ADAR1 enzyme targets and destabilizes inverted-repeat Alu dsRNA10, which prevents activation of the MDA5 receptor11. We found that ADAR1 establishes a negative-feedback loop, restricting the viral mimicry response to epigenetic therapy. Depletion of ADAR1 in patient-derived cancer cells potentiates the efficacy of epigenetic therapy, restraining tumour growth and reducing cancer initiation. Therefore, epigenetic therapies trigger viral mimicry by inducing a subset of inverted-repeats Alus, leading to an ADAR1 dependency. Our findings suggest that combining epigenetic therapies with ADAR1 inhibitors represents a promising strategy for cancer treatment.

Prediction of acute myeloid leukaemia risk in healthy individuals.

The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without any detectable early symptoms and patients usually present with the acute complications of bone marrow failure1. The onset of such de novo AML cases is typically preceded by the accumulation of somatic mutations in preleukaemic haematopoietic stem and progenitor cells (HSPCs) that undergo clonal expansion2,3. However, recurrent AML mutations also accumulate in HSPCs during ageing of healthy individuals who do not develop AML, a phenomenon referred to as age-related clonal haematopoiesis (ARCH)4-8. Here we use deep sequencing to analyse genes that are recurrently mutated in AML to distinguish between individuals who have a high risk of developing AML and those with benign ARCH. We analysed peripheral blood cells from 95 individuals that were obtained on average 6.3 years before AML diagnosis (pre-AML group), together with 414 unselected age- and gender-matched individuals (control group). Pre-AML cases were distinct from controls and had more mutations per sample, higher variant allele frequencies, indicating greater clonal expansion, and showed enrichment of mutations in specific genes. Genetic parameters were used to derive a model that accurately predicted AML-free survival; this model was validated in an independent cohort of 29 pre-AML cases and 262 controls. Because AML is rare, we also developed an AML predictive model using a large electronic health record database that identified individuals at greater risk. Collectively our findings provide proof-of-concept that it is possible to discriminate ARCH from pre-AML many years before malignant transformation. This could in future enable earlier detection and monitoring, and may help to inform intervention.

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

MOTIVATION: Single-molecule molecular inversion probes (smMIPs) provide an exceptionally cost-effective and modular approach for routine or large-cohort next-generation sequencing. However, processing the derived raw data to generate highly accurate variants calls remains challenging. RESULTS: We introduce SmMIP-tools, a comprehensive computational method that promotes the detection of single nucleotide variants and short insertions and deletions from smMIP-based sequencing. Our approach delivered near-perfect performance when benchmarked against a set of known mutations in controlled experiments involving DNA dilutions and outperformed other commonly used computational methods for mutation detection. Comparison against clinically approved diagnostic testing of leukaemia patients demonstrated the ability to detect both previously reported variants and a set of pathogenic mutations that did not pass detection by clinical testing. Collectively, our results indicate that increased performance can be achieved when tailoring data processing and analysis to its related technology. The feasibility of using our method in research and clinical settings to benefit from low-cost smMIP technology is demonstrated. AVAILABILITY AND IMPLEMENTATION: The source code for SmMIP-tools, its manual and additional scripts aimed to foster large-scale data processing and analysis are all available on github (https://github.com/abelson-lab/smMIP-tools). Raw sequencing data generated in this study have been submitted to the European Genome-Phenome Archive (EGA; https://ega-archive.org) and can be accessed under accession number EGAS00001005359. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Tracing the origins of relapse in acute myeloid leukaemia to stem cells.

In acute myeloid leukaemia, long-term survival is poor as most patients relapse despite achieving remission. Historically, the failure of therapy has been thought to be due to mutations that produce drug resistance, possibly arising as a consequence of the mutagenic properties of chemotherapy drugs. However, other lines of evidence have pointed to the pre-existence of drug-resistant cells. For example, deep sequencing of paired diagnosis and relapse acute myeloid leukaemia samples has provided direct evidence that relapse in some cases is generated from minor genetic subclones present at diagnosis that survive chemotherapy, suggesting that resistant cells are generated by evolutionary processes before treatment and are selected by therapy. Nevertheless, the mechanisms of therapy failure and capacity for leukaemic regeneration remain obscure, as sequence analysis alone does not provide insight into the cell types that are fated to drive relapse. Although leukaemia stem cells have been linked to relapse owing to their dormancy and self-renewal properties, and leukaemia stem cell gene expression signatures are highly predictive of therapy failure, experimental studies have been primarily correlative and a role for leukaemia stem cells in acute myeloid leukaemia relapse has not been directly proved. Here, through combined genetic and functional analysis of purified subpopulations and xenografts from paired diagnosis/relapse samples, we identify therapy-resistant cells already present at diagnosis and two major patterns of relapse. In some cases, relapse originated from rare leukaemia stem cells with a haematopoietic stem/progenitor cell phenotype, while in other instances relapse developed from larger subclones of immunophenotypically committed leukaemia cells that retained strong stemness transcriptional signatures. The identification of distinct patterns of relapse should lead to improved methods for disease management and monitoring in acute myeloid leukaemia. Moreover, the shared functional and transcriptional stemness properties that underlie both cellular origins of relapse emphasize the importance of developing new therapeutic approaches that target stemness to prevent relapse.

Clonal hematopoiesis confers an increased mortality risk in orthotopic heart transplant recipients.

Novel risk stratification and non-invasive surveillance methods are needed in orthotopic heart transplant (OHT) to reduce morbidity and mortality post-transplant. Clonal hematopoiesis (CH) refers to the acquisition of specific gene mutations in hematopoietic stem cells linked to enhanced inflammation and worse cardiovascular outcomes. The purpose of this study was to investigate the association between CH and OHT. Blood samples were collected from 127 OHT recipients. Error-corrected sequencing was used to detect CH-associated mutations. We evaluated the association between CH and acute cellular rejection, CMV infection, cardiac allograft vasculopathy (CAV), malignancies, and survival. CH mutations were detected in 26 (20.5%) patients, mostly in DNMT3A, ASXL1, and TET2. Patients with CH showed a higher frequency of CAV grade 2 or 3 (0% vs. 18%, p < .001). Moreover, a higher mortality rate was observed in patients with CH (11 [42%] vs. 15 [15%], p = .008) with an adjusted hazard ratio of 2.9 (95% CI, 1.4-6.3; p = .003). CH was not associated with acute cellular rejection, CMV infection or malignancies. The prevalence of CH in OHT recipients is higher than previously reported for the general population of the same age group, with an associated higher prevalence of CAV and mortality.

Clinical significance of clonal hematopoiesis in the setting of autologous stem cell transplantation for lymphoma.

Autologous stem cell transplantation (ASCT) remains a key therapeutic strategy for treating patients with relapsed or refractory non-Hodgkin and Hodgkin lymphoma. Clonal hematopoiesis (CH) has been proposed as a major contributor not only to the development of therapy-related myeloid neoplasms but also to inferior overall survival (OS) in patients who had undergone ASCT. Herein, we aimed to investigate the prognostic implications of CH after ASCT in a cohort of 420 lymphoma patients using ultra-deep, highly sensitive error-correction sequencing. CH was identified in the stem cell product samples of 181 patients (43.1%) and was most common in those with T-cell lymphoma (72.2%). The presence of CH was associated with a longer time to neutrophil and platelet recovery. Moreover, patients with evidence of CH had inferior 5-year OS from the time of first relapse (39.4% vs. 45.8%, p = .043) and from the time of ASCT (51.8% vs. 59.3%, p = .018). The adverse prognostic impact of CH was not due to therapy-related myeloid neoplasms, the incidence of which was low in our cohort (10-year cumulative incidence of 3.3% vs. 3.0% in those with and without CH, p = .445). In terms of specific-gene mutations, adverse OS was mostly associated with PPM1D mutations (hazard ratio (HR) 1.74, 95% confidence interval (CI) 1.13-2.67, p = .011). In summary, we found that CH is associated with an increased risk of non-lymphoma-related death after ASCT, which suggests that lymphoma survivors with CH may need intensified surveillance strategies to prevent and treat late complications.

High efficiency error suppression for accurate detection of low-frequency variants.

Detection of cancer-associated somatic mutations has broad applications for oncology and precision medicine. However, this becomes challenging when cancer-derived DNA is in low abundance, such as in impure tissue specimens or in circulating cell-free DNA. Next-generation sequencing (NGS) is particularly prone to technical artefacts that can limit the accuracy for calling low-allele-frequency mutations. State-of-the-art methods to improve detection of low-frequency mutations often employ unique molecular identifiers (UMIs) for error suppression; however, these methods are highly inefficient as they depend on redundant sequencing to assemble consensus sequences. Here, we present a novel strategy to enhance the efficiency of UMI-based error suppression by retaining single reads (singletons) that can participate in consensus assembly. This 'Singleton Correction' methodology outperformed other UMI-based strategies in efficiency, leading to greater sensitivity with high specificity in a cell line dilution series. Significant benefits were seen with Singleton Correction at sequencing depths ≤16 000×. We validated the utility and generalizability of this approach in a cohort of >300 individuals whose peripheral blood DNA was subjected to hybrid capture sequencing at ∼5000× depth. Singleton Correction can be incorporated into existing UMI-based error suppression workflows to boost mutation detection accuracy, thus improving the cost-effectiveness and clinical impact of NGS.

Age-related clonal hematopoiesis: implications for hematopoietic stem cell transplantation.

PURPOSE OF REVIEW: Over the past decade, advances in hematopoietic stem cell transplantation (HSCT) have enabled older individuals to undergo the procedure as well as to serve as donors. Recently, aging has been linked with the development of age-related clonal hematopoiesis (ARCH), defined as the gradual clonal expansion of hematopoietic stem and progenitor cells (HSPC) carrying recurrent disruptive genetic variants in individuals without a diagnosis of hematologic malignancy. Here we will review the implications of ARCH in the context of HSCT. RECENT FINDINGS: ARCH is highly prevalent in the general population and commonly involves genes that are recurrently mutated in hematologic malignancies. Nevertheless, the vast majority of individuals with ARCH will not develop overt hematologic disease in their lifetime. The presence of ARCH may increase the risk of therapy-related myeloid neoplasms (t-MN) in individuals undergoing autologous HSCT. In the setting of allogeneic HSCT, ARCH present in the donor may contribute to adverse outcomes such as unexplained cytopenias posttransplant and donor cell leukemia. SUMMARY: A better understanding of the hematopoietic milieu of HSCT recipients and of the importance of ARCH in the context of the replicative pressures imposed on transplanted HSPCs is needed in order to optimize conditioning regimens, donor selection and clinical outcomes post-HSCT.

CD24(+) cells fuel rapid tumor growth and display high metastatic capacity.

INTRODUCTION: Breast tumors are comprised of distinct cancer cell populations which differ in their tumorigenic and metastatic capacity. Characterization of cell surface markers enables investigators to distinguish between cancer stem cells and their counterparts. CD24 is a well-known cell surface marker for mammary epithelial cells isolation, recently it was suggested as a potential prognostic marker in a wide variety of malignancies. Here, we demonstrate that CD24(+) cells create intra-tumor heterogeneity, and display highly metastatic properties. METHODS: The mammary carcinoma Mvt1 cells were sorted into CD24(-) and CD24(+) cells. Both subsets were morphologically and phenotypically characterized, and tumorigenic capacity was assessed via orthotopic inoculation of each subset into the mammary fat pad of wild-type and MKR mice. The metastatic capacity of each subset was determined with the tail vein metastasis assay. The role of CD24 in tumorigenesis was further examined with shRNA technology. GFP-labeled cells were monitored in vivo for differentiation. The genetic profile of each subset was analyzed using RNA sequencing. RESULTS: CD24(+) cells displayed a more spindle-like cytoplasm. The cells formed mammospheres in high efficiency and CD24(+) tumors displayed rapid growth in both WT and MKR mice, and were more metastatic than CD24- cells. Interestingly, CD24-KD in CD24+ cells had no effect both in vitro and in vivo on the various parameters studied. Moreover, CD24(+) cells gave rise in vivo to the CD24(-) that comprised the bulk of the tumor. RNA-seq analysis revealed enrichment of genes and pathways of the extracellular matrix in the CD24(+) cells. CONCLUSION: CD24(+) cells account for heterogeneity in mammary tumors. CD24 expression at early stages of the cancer process is an indication of a highly invasive tumor. However, CD24 is not a suitable therapeutic target; instead we suggest here new potential targets accounting for early differentiated cancer cells tumorigenic capacity.

Eureka-DMA: an easy-to-operate graphical user interface for fast comprehensive investigation and analysis of DNA microarray data.

BACKGROUND: In the past decade, the field of molecular biology has become increasingly quantitative; rapid development of new technologies enables researchers to investigate and address fundamental issues quickly and in an efficient manner which were once impossible. Among these technologies, DNA microarray provides methodology for many applications such as gene discovery, diseases diagnosis, drug development and toxicological research and it has been used increasingly since it first emerged. Multiple tools have been developed to interpret the high-throughput data produced by microarrays. However, many times, less consideration has been given to the fact that an extensive and effective interpretation requires close interplay between the bioinformaticians who analyze the data and the biologists who generate it. To bridge this gap and to simplify the usability of such tools we developed Eureka-DMA - an easy-to-operate graphical user interface that allows bioinformaticians and bench-biologists alike to initiate analyses as well as to investigate the data produced by DNA microarrays. RESULTS: In this paper, we describe Eureka-DMA, a user-friendly software that comprises a set of methods for the interpretation of gene expression arrays. Eureka-DMA includes methods for the identification of genes with differential expression between conditions; it searches for enriched pathways and gene ontology terms and combines them with other relevant features. It thus enables the full understanding of the data for following testing as well as generating new hypotheses. Here we show two analyses, demonstrating examples of how Eureka-DMA can be used and its capability to produce relevant and reliable results. CONCLUSIONS: We have integrated several elementary expression analysis tools to provide a unified interface for their implementation. Eureka-DMA's simple graphical user interface provides effective and efficient framework in which the investigator has the full set of tools for the visualization and interpretation of the data with the option of exporting the analysis results for later use in other platforms. Eureka-DMA is freely available for academic users and can be downloaded at http://blue-meduza.org/Eureka-DMA.

Chronic TNF in the aging microenvironment exacerbates Tet2 loss-of-function myeloid expansion.

ABSTRACT: Somatic mutations in the TET2 gene occur more frequently with age, imparting an intrinsic hematopoietic stem cells (HSCs) advantage and contributing to a phenomenon termed clonal hematopoiesis of indeterminate potential (CHIP). Individuals with TET2-mutant CHIP have a higher risk of developing myeloid neoplasms and other aging-related conditions. Despite its role in unhealthy aging, the extrinsic mechanisms driving TET2-mutant CHIP clonal expansion remain unclear. We previously showed an environment containing tumor necrosis factor (TNF) favors TET2-mutant HSC expansion in vitro. We therefore postulated that age-related increases in TNF also provide an advantage to HSCs with TET2 mutations in vivo. To test this hypothesis, we generated mixed bone marrow chimeric mice of old wild-type (WT) and TNF-/- genotypes reconstituted with WT CD45.1+ and Tet2-/- CD45.2+ HSCs. We show that age-associated increases in TNF dramatically increased the expansion of Tet2-/- cells in old WT recipient mice, with strong skewing toward the myeloid lineage. This aberrant myelomonocytic advantage was mitigated in old TNF-/- recipient mice, suggesting that TNF signaling is essential for the expansion Tet2-mutant myeloid clones. Examination of human patients with rheumatoid arthritis with clonal hematopoiesis revealed that hematopoietic cells carrying certain mutations, including in TET2, may be sensitive to reduced TNF bioactivity following blockade with adalimumab. This suggests that targeting TNF may reduce the burden of some forms of CHIP. To our knowledge, this is the first evidence to demonstrate that TNF has a causal role in driving TET2-mutant CHIP in vivo. These findings highlight TNF as a candidate therapeutic target to control TET2-mutant CHIP.

Clonal haematopoiesis is associated with major adverse cardiovascular events in patients with hypertrophic cardiomyopathy.

AIMS: The heterogeneous phenotype of hypertrophic cardiomyopathy (HCM) is still not fully understood. Clonal haematopoiesis (CH) is emerging as a cardiovascular risk factor potentially associated with adverse clinical events. The prevalence, phenotype and outcomes related to CH in HCM patients were evaluated. METHODS AND RESULTS: Patients with HCM and available biospecimens from the Peter Munk Cardiac Centre Cardiovascular Biobank were subjected to targeted sequencing for 35 myeloid genes associated with CH. CH prevalence, clinical characteristics, morphological phenotypes assessed by echocardiogram and cardiac magnetic resonance and outcomes were assessed. All patients were evaluated for a 71-plex cytokines/chemokines, troponin I and B-type natriuretic peptide analysis. Major adverse cardiovascular events (MACE) were defined as appropriate implantable cardioverter-defibrillator shock, stroke, cardiac arrest, orthotopic heart transplant and death. Among the 799 patients, CH was found in 183 (22.9%) HCM patients with sarcomeric germline mutations. HCM patients with CH were more symptomatic and with a higher burden of fibrosis than those without CH. CH was associated with MACE in those HCM patients with sarcomeric germline mutations (adjusted hazard ratio [HR] 6.89, 95% confidence interval [CI] 1.78-26.6; p = 0.005), with the highest risk among those that had DNMT3A, TET2 and ASXL1 mutations (adjusted HR 5.76, 95% CI 1.51-21.94; p = 0.010). Several cytokines (IL-1ra, IL-6, IL-17F, TGFα, CCL21, CCL1, CCL8, and CCL17), and troponin I were upregulated in gene-positive HCM patients with CH. CONCLUSIONS: These results indicate that CH in patients with HCM is associated with worse clinical outcomes. In the absence of CH, gene-positive patients with HCM have lower rates of MACE.

Mutations in myeloid transcription factors and activated signaling genes predict chronic myeloid leukemia outcomes.

ABSTRACT: Advancements in genomics are transforming the clinical management of chronic myeloid leukemia (CML) toward precision medicine. The impact of somatic mutations on treatment outcomes is still under debate. We studied the association of somatic mutations in epigenetic modifier genes and activated signaling/myeloid transcription factors (AS/MTFs) with disease progression and treatment failure in patients with CML after tyrosine kinase inhibitor (TKI) therapy. A total of 394 CML samples were sequenced, including 254 samples collected at initial diagnosis and 140 samples taken during follow-up. Single-molecule molecular inversion probe (smMIP)-based next-generation sequencing (NGS) was conducted targeting recurrently mutated loci in 40 genes, with a limit of detection of 0.2%. Seventy mutations were detected in 57 diagnostic samples (22.4%), whereas 64 mutations were detected in 39 of the follow-up samples (27.9%). Carrying any mutation at initial diagnosis was associated with worse outcomes after TKI therapy, particularly in AS/MTF genes. Patients having these mutations at initial diagnosis and treated with imatinib showed higher risks of treatment failure (hazard ratio, 2.53; 95% confidence interval, 1.13-5.66; P = .0239). The adverse prognostic impact of the mutations was not clear for patients treated with second-generation TKIs. The multivariate analysis affirmed that mutations in AS/MTF genes independently serve as adverse prognostic factors for molecular response, failure-free survival, and progression risk. Additionally, there was an observable nonsignificant trend indicating a heightened risk of progression to advanced disease and worse overall survival. In conclusion, mutations in the AS/MTF genes using smMIP-based NGS can help identify patients with a potential risk of both treatment failure and progression and may help upfront TKI selection.

Intratumoral heterogeneity in the self-renewal and tumorigenic differentiation of ovarian cancer.

Resistance to anticancer therapy has been attributed to interindividual differences in gene expression pathways among tumors, and to the existence within tumors of cancer stem cells with self-renewal capacity. In previous studies, we have demonstrated that the human embryonic stem cell (hESC)-derived cellular microenvironment in immunocompromised mice enables functional distinction of heterogeneous tumor cells, including cells that do not grow into a tumor in conventional direct tumor xenograft platform. In the current study, we use clonally expanded subpopulations derived from ovarian clear cell carcinoma of a single tumor, to demonstrate striking intratumoral phenotypic heterogeneity that is dynamically dependent on the tumor growth microenvironment. Each of six clonally expanded subpopulations displays a different level of morphologic and tumorigenic differentiation, wherein growth in the hESC-derived microenvironment favors growth of CD44+ aldehyde dehydrogenase positive pockets of self-renewing cells that sustain tumor growth through a process of tumorigenic differentiation into CD44- aldehyde dehydrogenase negative derivatives. Strikingly, these derivative cells display microenvironment-dependent plasticity with the capacity to restore self-renewal and CD44 expression. Such intratumoral heterogeneity and plasticity at the level of the key properties of self-renewal and tumorigenic differentiation suggests that a paradigm shift is needed in the approach to anticancer therapy, with the aim of turning malignant growth into a chronic manageable disorder, based on continual monitoring of these tumor growth properties. The hESC-based in vivo model renders intratumoral heterogeneity in the self-renewal and tumorigenic differentiation amenable to biological analysis as well as anticancer therapy testing.

Pan-cancer classification of single cells in the tumour microenvironment.

Single-cell RNA sequencing can reveal 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 >300,000 cancer, immune, and stromal cells defining a pan-cancer reference across 19 common cancers and employ a hierarchical approach, outperforming current classification methods. We extensively confirm scATOMIC's accuracy on 225 tumour biopsies encompassing >350,000 cancer and a variety of TME cells. Lastly, we demonstrate scATOMIC's 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 analyse multicellular cancer TMEs.

Clonal haematopoiesis is associated with higher mortality in patients with cardiogenic shock.

AIMS: Cardiogenic shock (CS) with variable systemic inflammation may be responsible for patient heterogeneity and the exceedingly high mortality rate. Cardiovascular events have been associated with clonal haematopoiesis (CH) where specific gene mutations in haematopoietic stem cells lead to clonal expansion and the development of inflammation. This study aims to assess the prevalence of CH and its association with survival in a population of CS patients in a quaternary centre. METHODS AND RESULTS: We compared the frequency of CH mutations among 341 CS patients and 345 ambulatory heart failure (HF) patients matched for age, sex, ejection fraction, and HF aetiology. The association of CH with survival and levels of circulating inflammatory cytokines was analysed. We detected 266 CH mutations in 149 of 686 (22%) patients. CS patients had a higher prevalence of CH-related mutations than HF patients (odds ratio 1.5; 95% confidence interval [CI] 1.0-2.1, p = 0.02) and was associated with decreased survival (30 days: hazard ratio [HR] 2.7; 95% CI 1.3-5.7, p = 0.006; 90 days: HR 2.2; 95% CI 1.3-3.9, p = 0.003; and 3 years: HR 1.7; 95% CI 1.1-2.8, p = 0.01). TET2 or ASXL1 mutations were associated with lower survival in CS patients at all time-points (p ≤ 0.03). CS patients with TET2 mutations had higher circulating levels of SCD40L, interferon-γ, interleukin-4, and tumour necrosis factor-α (p ≤ 0.04), while those with ASXL1 mutations had decreased levels of CCL7 (p = 0.03). CONCLUSIONS: Cardiogenic shock patients have high frequency of CH, notably mutations in TET2 and ASXL1. This was associated with reduced survival and dysregulation of circulating inflammatory cytokines in those CS patients with CH.

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

Age-related clonal hematopoiesis (ARCH) is characterized by age-associated accumulation of somatic mutations in hematopoietic stem cells (HSCs) or their pluripotent descendants. HSCs harboring driver mutations will be positively selected and cells carrying these mutations will rise in frequency. While ARCH is a known risk factor for blood malignancies, such as Acute Myeloid Leukemia (AML), why some people who harbor ARCH driver mutations do not progress to AML remains unclear. Here, we model the interaction of positive and negative selection in deeply sequenced blood samples from individuals who subsequently progressed to AML, compared to healthy controls, using deep learning and population genetics. Our modeling allows us to discriminate amongst evolutionary classes with high accuracy and captures signatures of purifying selection in most individuals. Purifying selection, acting on benign or mildly damaging passenger mutations, appears to play a critical role in preventing disease-predisposing clones from rising to dominance and is associated with longer disease-free survival. Through exploring a range of evolutionary models, we show how different classes of selection shape clonal dynamics and health outcomes thus enabling us to better identify individuals at a high risk of malignancy.

Mapping the cellular origin and early evolution of leukemia in Down syndrome.

Children with Down syndrome have a 150-fold increased risk of developing myeloid leukemia, but the mechanism of predisposition is unclear. Because Down syndrome leukemogenesis initiates during fetal development, we characterized the cellular and developmental context of preleukemic initiation and leukemic progression using gene editing in human disomic and trisomic fetal hematopoietic cells and xenotransplantation. GATA binding protein 1 (GATA1) mutations caused transient preleukemia when introduced into trisomy 21 long-term hematopoietic stem cells, where a subset of chromosome 21 microRNAs affected predisposition to preleukemia. By contrast, progression to leukemia was independent of trisomy 21 and originated in various stem and progenitor cells through additional mutations in cohesin genes. CD117+/KIT proto-oncogene (KIT) cells mediated the propagation of preleukemia and leukemia, and KIT inhibition targeted preleukemic stem cells.

Integration of intra-sample contextual error modeling for improved detection of somatic mutations from deep sequencing.

Sensitive mutation detection by next-generation sequencing is critical for early cancer detection, monitoring minimal/measurable residual disease (MRD), and guiding precision oncology. Nevertheless, because of artifacts introduced during library preparation and sequencing, the detection of low-frequency variants at high specificity is problematic. Here, we present Espresso, an error suppression method that considers local sequence features to accurately detect single-nucleotide variants (SNVs). Compared to other advanced error suppression techniques, Espresso consistently demonstrated lower numbers of false-positive mutation calls and greater sensitivity. We demonstrated Espresso's superior performance in detecting MRD in the peripheral blood of patients with acute myeloid leukemia (AML) throughout their treatment course. Furthermore, we showed that accurate mutation calling in a small number of informative genomic loci might provide a cost-efficient strategy for pragmatic risk prediction of AML development in healthy individuals. More broadly, we aim for Espresso to aid with accurate mutation detection in many other research and clinical settings.