Single-cell multi-omics identifies chronic inflammation as a driver of TP53-mutant leukemic evolution

Understanding the genetic and nongenetic determinants of tumor protein 53 (TP53)-mutation-driven clonal evolution and subsequent transformation is a crucial step toward the design of rational therapeutic strategies. Here we carry out allelic resolution single-cell multi-omic analysis of hematopoietic stem/progenitor cells (HSPCs) from patients with a myeloproliferative neoplasm who transform to TP53-mutant secondary acute myeloid leukemia (sAML). All patients showed dominant TP53 ‘multihit’ HSPC clones at transformation, with a leukemia stem cell transcriptional signature strongly predictive of adverse outcomes in independent cohorts, across both TP53-mutant and wild-type (WT) AML. Through analysis of serial samples, antecedent TP53-heterozygous clones and in vivo perturbations, we demonstrate a hitherto unrecognized effect of chronic inflammation, which suppressed TP53 WT HSPCs while enhancing the fitness advantage of TP53-mutant cells and promoted genetic evolution. Our findings will facilitate the development of risk-stratification, early detection and treatment strategies for TP53-mutant leukemia, and are of broad relevance to other cancer types

Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies

A lack of models that recapitulate the complexity of human bone marrow has hampered mechanistic studies of normal and malignant hematopoiesis and the validation of novel therapies. Here, we describe a step-wise, directed-differentiation protocol in which organoids are generated from induced pluripotent stem cells committed to mesenchymal, endothelial, and hematopoietic lineages. These 3D structures capture key features of human bone marrow— stroma, lumen-forming sinusoids, and myeloid cells including proplatelet-forming megakaryocytes. The organoids supported the engraftment and survival of cells from patients with blood malignancies, including cancer types notoriously difficult to maintain ex vivo. Fibrosis of the organoid occurred following TGFβ stimulation and engraftment with myelofibrosis but not healthy donor–derived cells, validating this platform as a powerful tool for studies of malignant cells and their interactions within a human bone marrow–like milieu. This enabling technology is likely to accelerate the discovery and prioritization of novel targets for bone marrow disorders and blood cancers. SIGNIFICANCE: We present a human bone marrow organoid that supports the growth of primary cells from patients with myeloid and lymphoid blood cancers. This model allows for mechanistic studies of blood cancers in the context of their microenvironment and provides a much-needed ex vivo tool for the prioritization of new therapeutics.</p

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.

Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19

Genetic lineage tracing in clonal haematopoiesis and myeloproliferative neoplasms

Clonal haematopoiesis (CH) is a common age-related condition in which somatic mutations accumulate in haematopoietic stem and progenitor cells (HSPCs), leading to the clonal expansion of mutated cells. This process has been causatively linked with atherosclerotic cardiovascular disease and related complications, while it has also been associated with an increased risk of development of myeloid neoplasms, including myeloproliferative neoplasms (MPNs). This DPhil thesis aimed to investigate the pathogenesis of CH and MPNs utilising genetic lineage tracing. I initially focused on the study of granulocytes (as the most abundant type of myeloid cells) against germline DNA through a twin study in a pair of monozygotic twins who presented with adult-onset CALR mutant MPN. I aimed to investigate the origin of their premalignant clones and their subsequent molecular evolution. Lineage tracing of the MPN clone by whole genome sequencing revealed a common clonal origin of the MPN clone, which occurred in utero followed by twin-to-twin transplacental transmission and subsequent similar disease latency. In the next part of the project, I focused on the study of granulocytes against platelets as a surrogate of the megakaryocyte lineage. The aim of this part of my work was to assess whether platelet-biased CH exists in humans and determine its prevalence in normal individuals and myeloid neoplasms. Targeted detection of JAK2V617F and other mutations commonly involved in CH and MPN revealed the presence of platelet-biased/restricted CH, accounting for a significant proportion of the overall prevalence of CH. In conclusion, this DPhil thesis highlights the importance of genetic lineage tracing in CH and MPNs and provides insight into their molecular pathogenesis. It introduces a novel model of MPN pathogenesis, involving a prolonged disease latency between the acquisition of the premalignant MPN clone and the development of established disease, thus opening the potential for early diagnosis and preventive precision treatment strategies. It also describes for the first time presence of platelet-biased CH with direct clinical implications in the detection of CH and relevance within the wider context of diagnosis and monitoring of haematological disorders

In utero origin of myelofibrosis presenting in adult monozygotic twins

The latency between acquisition of an initiating somatic driver mutation by a single-cell and clinical presentation with cancer is largely unknown. We describe a remarkable case of monozygotic twins presenting with CALR mutation-positive myeloproliferative neoplasms (MPNs) (aged 37 and 38 years), with a clinical phenotype of primary myelofibrosis. The CALR mutation was absent in T cells and dermal fibroblasts, confirming somatic acquisition. Whole-genome sequencing lineage tracing revealed a common clonal origin of the CALR-mutant MPN clone, which occurred in utero followed by twin-to-twin transplacental transmission and subsequent similar disease latency. Index sorting and single-colony genotyping revealed phenotypic hematopoietic stem cells (HSCs) as the likely MPN-propagating cell. Furthermore, neonatal blood spot analysis confirmed in utero origin of the JAK2V617F mutation in a patient presenting with polycythemia vera (aged 34 years). These findings provide a unique window into the prolonged evolutionary dynamics of MPNs and fitness advantage exerted by MPN-associated driver mutations in HSCs

Continuous Indexing of Fibrosis (CIF): improving the assessment and classification of MPN patients.

The grading of fibrosis in myeloproliferative neoplasms (MPN) is an important component of disease classification, prognostication and monitoring. However, current fibrosis grading systems are only semi-quantitative and fail to fully capture sample heterogeneity. To improve the quantitation of reticulin fibrosis, we developed a machine learning approach using bone marrow trephine (BMT) samples (n = 107) from patients diagnosed with MPN or a reactive marrow. The resulting Continuous Indexing of Fibrosis (CIF) enhances the detection and monitoring of fibrosis within BMTs, and aids MPN subtyping. When combined with megakaryocyte feature analysis, CIF discriminates between the frequently challenging differential diagnosis of essential thrombocythemia (ET) and pre-fibrotic myelofibrosis with high predictive accuracy [area under the curve = 0.94]. CIF also shows promise in the identification of MPN patients at risk of disease progression; analysis of samples from 35 patients diagnosed with ET and enrolled in the Primary Thrombocythemia-1 trial identified features predictive of post-ET myelofibrosis (area under the curve = 0.77). In addition to these clinical applications, automated analysis of fibrosis has clear potential to further refine disease classification boundaries and inform future studies of the micro-environmental factors driving disease initiation and progression in MPN and other stem cell disorders