Single-Cell Analyses Reveal Megakaryocyte-Biased Hematopoiesis in Myelofibrosis and Identify Mutant Clone-Specific Targets.

Myelofibrosis is a severe myeloproliferative neoplasm characterized by increased numbers of abnormal bone marrow megakaryocytes that induce fibrosis, destroying the hematopoietic microenvironment. To determine the cellular and molecular basis for aberrant megakaryopoiesis in myelofibrosis, we performed single-cell transcriptome profiling of 135,929 CD34+ lineage- hematopoietic stem and progenitor cells (HSPCs), single-cell proteomics, genomics, and functional assays. We identified a bias toward megakaryocyte differentiation apparent from early multipotent stem cells in myelofibrosis and associated aberrant molecular signatures. A sub-fraction of myelofibrosis megakaryocyte progenitors (MkPs) are transcriptionally similar to healthy-donor MkPs, but the majority are disease specific, with distinct populations expressing fibrosis- and proliferation-associated genes. Mutant-clone HSPCs have increased expression of megakaryocyte-associated genes compared to wild-type HSPCs, and we provide early validation of G6B as a potential immunotherapy target. Our study paves the way for selective targeting of the myelofibrosis clone and illustrates the power of single-cell multi-omics to discover tumor-specific therapeutic targets and mediators of tissue fibrosis.

Clinical utility of investigations in triple-negative thrombocytosis: A real-world, multicentre evaluation of UK practice.

Diagnosis of essential thrombocythaemia (ET) is challenging in patients lacking JAK2/CALR/MPL mutations. In a retrospective evaluation of 320 patients with 'triple-negative thrombocytosis', we assessed utility of bone marrow histology (90.9% of patients) and myeloid gene panel (MGP, 55.6%). Supportive histology ('myeloproliferative neoplasm-definite/probable', 36.8%) was associated with higher platelet counts and varied between centres. 14.6% MGP revealed significant variants: 3.4% JAK2/CALR/MPL and 11.2% other myeloid genes. Final clinical diagnosis was strongly predicted by histology, not MGP. 23.7% received cytoreduction (17.6% under 60 years). Real-world 'triple-negative' ET diagnosis currently depends heavily on histology; we advocate caution in MGP-negative cases and that specific guidelines are needed.

Loss of COP9 signalosome genes at 2q37 is associated with IMiD resistance in multiple myeloma.

The acquisition of a multidrug refractory state is a major cause of mortality in myeloma. Myeloma drugs that target the cereblon (CRBN) protein include widely used immunomodulatory drugs (IMiDs), and newer CRBN E3 ligase modulator drugs (CELMoDs), in clinical trials. CRBN genetic disruption causes resistance and poor outcomes with IMiDs. Here, we investigate alternative genomic associations of IMiD resistance, using large whole-genome sequencing patient datasets (n = 522 cases) at newly diagnosed, lenalidomide (LEN)-refractory and lenalidomide-then-pomalidomide (LEN-then-POM)-refractory timepoints. Selecting gene targets reproducibly identified by published CRISPR/shRNA IMiD resistance screens, we found little evidence of genetic disruption by mutation associated with IMiD resistance. However, we identified a chromosome region, 2q37, containing COP9 signalosome members COPS7B and COPS8, copy loss of which significantly enriches between newly diagnosed (incidence 5.5%), LEN-refractory (10.0%), and LEN-then-POM-refractory states (16.4%), and may adversely affect outcomes when clonal fraction is high. In a separate dataset (50 patients) with sequential samples taken throughout treatment, we identified acquisition of 2q37 loss in 16% cases with IMiD exposure, but none in cases without IMiD exposure. The COP9 signalosome is essential for maintenance of the CUL4-DDB1-CRBN E3 ubiquitin ligase. This region may represent a novel marker of IMiD resistance with clinical utility.

Quantitative interpretation of bone marrow biopsies in MPN-What's the point in a molecular age?

The diagnosis of myeloproliferative neoplasms (MPN) requires the integration of clinical, morphological, genetic and immunophenotypic findings. Recently, there has been a transformation in our understanding of the cellular and molecular mechanisms underlying disease initiation and progression in MPN. This has been accompanied by the widespread application of high-resolution quantitative molecular techniques. By contrast, microscopic interpretation of bone marrow biopsies by haematologists/haematopathologists remains subjective and qualitative. However, advances in tissue image analysis and artificial intelligence (AI) promise to transform haematopathology. Pioneering studies in bone marrow image analysis offer to refine our understanding of the boundaries between reactive samples and MPN subtypes and better capture the morphological correlates of high-risk disease. They also demonstrate potential to improve the evaluation of current and novel therapeutics for MPN and other blood cancers. With increased therapeutic targeting of diverse molecular, cellular and extra-cellular components of the marrow, these approaches can address the unmet need for improved objective and quantitative measures of disease modification in the context of clinical trials. This review focuses on the state-of-the-art in image analysis/AI of bone marrow tissue, with an emphasis on its potential to complement and inform future clinical studies and research in MPN.

Perspective: Pivotal translational hematology and therapeutic insights in chronic myeloid hematopoietic stem cell malignancies.

Despite much of the past 2 years being engulfed by the devastating consequences of the SAR-CoV-2 pandemic, significant progress, even breathtaking, occurred in the field of chronic myeloid malignancies. Some of this was show-cased at the 15th Post-American Society of Hematology (ASH) and the 25th John Goldman workshops on myeloproliferative neoplasms (MPN) held on 9th-10th December 2020 and 7th-10th October 2021, respectively. The inaugural Post-ASH MPN workshop was set out in 2006 by John Goldman (deceased) and Tariq Mughal to answer emerging translational hematology and therapeutics of patients with these malignancies. Rather than present a resume of the discussions, this perspective focuses on some of the pivotal translational hematology and therapeutic insights in these diseases.

A Phase 2a cohort expansion study to assess the safety, tolerability, and preliminary efficacy of CXD101 in patients with advanced solid-organ cancer expressing HR23B or lymphoma.

BACKGROUND: This Phase 2a dose expansion study was performed to assess the safety, tolerability and preliminary efficacy of the maximum tolerated dose of the oral histone de-acetylase (HDAC) inhibitor CXD101 in patients with relapsed / refractory lymphoma or advanced solid organ cancers and to assess HR23B protein expression by immunohistochemistry as a biomarker of HDAC inhibitor sensitivity. METHODS: Patients with advanced solid-organ cancers with high HR23B expression or lymphomas received CXD101 at the recommended phase 2 dose (RP2D). Key exclusions: corrected QT > 450 ms, neutrophils < 1.5 × 109/L, platelets < 75 × 109/L, ECOG > 1. Baseline HR23B expression was assessed by immunohistochemistry. RESULTS: Fifty-one patients enrolled between March 2014 and September 2019, 47 received CXD101 (19 solid-organ cancer, 28 lymphoma). Thirty-four patients received ≥80% RP2D. Baseline characteristics: median age 57.4 years, median prior lines 3, male sex 57%. The most common grade 3-4 adverse events were neutropenia (32%), thrombocytopenia (17%), anaemia (13%), and fatigue (9%) with no deaths on CXD101. No responses were seen in solid-organ cancers, with disease stabilisation in 36% or patients; the overall response rate in lymphoma was 17% with disease stabilisation in 52% of patients. Median progression-free survival was 1.2 months (95% confidence interval (CI) 1.2-5.4) in solid-organ cancers and 2.6 months (95%CI 1.2-5.6) in lymphomas. HR23B status did not predict response. CONCLUSIONS: CXD101 showed acceptable tolerability with efficacy seen in Hodgkin lymphoma, T-cell lymphoma and follicular lymphoma. Further studies assessing combination approaches are warranted. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT01977638 . Registered 07 November 2013.

A phase II study to assess the safety and efficacy of the dual mTORC1/2 inhibitor vistusertib in relapsed, refractory DLBCL.

Patients with relapsed or refractory diffuse large B-cell lymphoma (DLBCL) who are unfit for or relapsed postautologous stem-cell transplantation have poor outcomes. Historically, mTORC1 inhibitors have produced responses in approximately 30% of patients in this setting. mTORC1 inhibitor efficacy may be limited by resistance mechanisms including AKT activation by mTORC2. To date, dual mTORC1/2 inhibitors targeting both the TORC1 and TORC2 complexes have not been investigated in DLBCL. This phase II trial investigated the oral dual mTORC1/2 inhibitor vistusertib in an intermittent dosing schedule of 125 mg b.d. for 2 days per week. Thirty patients received vistusertib and six received vistusertib-rituximab for up to six cycles (28-day cycles). Two partial responses were achieved on monotherapy. Durations of response were 57 and 62 days, respectively, for these patients. 19% had stable disease within six cycles. In the monotherapy arm, the median progression-free survival was1.69 (95% confidence interval [CI] 1.61-2.14) months and median overall survival was 6.58 (95% CI 3.81-not reached) months, respectively. The median duration of response or stable disease across the trial duration was 153 days (95% CI 112-not reached). Tumour responses according to positron emission tomography/computed tomography versus computed tomography were concordant. There were no differences noted in tumour volume response according to cell of origin by either gene expression profiling or immunohistochemistry. Vistusertib ± rituximab was well tolerated; across 36 patients 86% of adverse events were grade (G) 1-2. Common vistusertib-related adverse events were similar to those described with mTORC1 inhibitors: nausea (47% G1-2), diarrhoea (27% G1-2, 6% G3), fatigue (30% G1-2, 3% G3), mucositis (25% G1-2, 6% G3), vomiting (17% G1-2), and dyspepsia (14% G1-2). Dual mTORC1/2 inhibitors do not clearly confer an advantage over mTORC1 inhibitors in relapsed or refractory DLBCL. Potential resistance mechanisms are discussed within.

A proinflammatory stem cell niche drives myelofibrosis through a targetable galectin-1 axis.

Myeloproliferative neoplasms are stem cell-driven cancers associated with a large burden of morbidity and mortality. Most patients present with early-stage disease, but a substantial proportion progress to myelofibrosis or secondary leukemia, advanced cancers with a poor prognosis and high symptom burden. Currently, it remains difficult to predict progression, and therapies that reliably prevent or reverse fibrosis are lacking. A major bottleneck to the discovery of disease-modifying therapies has been an incomplete understanding of the interplay between perturbed cellular and molecular states. Several cell types have individually been implicated, but a comprehensive analysis of myelofibrotic bone marrow is lacking. We therefore mapped the cross-talk between bone marrow cell types in myelofibrotic bone marrow. We found that inflammation and fibrosis are orchestrated by a "quartet" of immune and stromal cell lineages, with basophils and mast cells creating a TNF signaling hub, communicating with megakaryocytes, mesenchymal stromal cells, and proinflammatory fibroblasts. We identified the ß-galactoside-binding protein galectin-1 as a biomarker of progression to myelofibrosis and poor survival in multiple patient cohorts and as a promising therapeutic target, with reduced myeloproliferation and fibrosis in vitro and in vivo and improved survival after galectin-1 inhibition. In human bone marrow organoids, TNF increased galectin-1 expression, suggesting a feedback loop wherein the proinflammatory myeloproliferative neoplasm clone creates a self-reinforcing niche, fueling progression to advanced disease. This study provides a resource for studying hematopoietic cell-niche interactions, with relevance for cancer-associated inflammation and disorders of tissue fibrosis.

Nasopharyngeal myeloid sarcoma as a manifestation of acute monomyelocytic leukaemia.

This case report describes the case of a man in his seventies presenting with a nasopharyngeal deposit of myeloid sarcoma associated with acute monomyelocytic leukaemia. He presented with right nasal obstruction associated with unilateral pulsatile tinnitus. CT and MRI scans of sinuses identified a moderately restricting mucosal swelling of the right torus tubarius, and a biopsy of the lesion diagnosed a nasal deposit of myeloid sarcoma.

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.

Multi-Scale Graphical Representation of Cell Environment.

We present a multi-scale graphical network that can capture the relevant representations of individual cell morphology, topological structure of cell communities in a tissue image, as well as whole slide level attributes. This helps to effectively merge the disease relevant cell morphology to the overall topological context within the sample, within one unified deep framework. From the explainability point of view, instead of empirical design, the graphs are designed with biomedical considerations in mind in order to have translational validity. We also provide a clinically interpretable visualisation of the cells and their micro- and macro-environment by leveraging label noise reduction. We demonstrate the efficacy of our methodology on myeloproliferative neoplasms (MPN), a haematopoietic stem cell disorder as an exemplar test case. The proposed method achieves an encouraging performance in the robust separation of different MPN subtypes in this exciting new dataset as part of this work.

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.

Application of Single-Cell Approaches to Study Myeloproliferative Neoplasm Biology.

Philadelphia-negative myeloproliferative neoplasms (MPNs) are an excellent tractable disease model of a number of aspects of human cancer biology, including genetic evolution, tissue-associated fibrosis, and cancer stem cells. In this review, we discuss recent insights into MPN biology gained from the application of a number of new single-cell technologies to study human disease, with a specific focus on single-cell genomics, single-cell transcriptomics, and digital pathology.

Learning Cellular Phenotypes through Supervision.

Image-based cell phenotyping is an important and open problem in computational pathology. The two principal challenges are: 1) making the cell cluster properties insensitive to experimental settings (like seed point and feature selection) and 2) ensuring that the phenotypes emerging are biologically relevant and support clinical reporting. To gauge robustness, we first compare the consistency of the phenotypes using self-supervised and supervised features. Through case classification, we analyse the relevance of the self-supervised and supervised feature sets with respect to the clinical diagnosis. In addition, we demonstrate how we can add model explainability through Shapley values to identify more disease relevant cellular phenotypes and measure their importance in context of the disease. Here, myeloproliferative neoplasms, a haematopoietic stem cell disorder, where one particular cell type is of diagnostic relevance is used as an exemplar. The experiments conducted on a set of bone marrow trephines demonstrate an improvement of 7.4 % in accuracy for case classification using cellular phenotypes derived from the supervised scenario.

Mechanisms of lymphatic metastasis in human colorectal adenocarcinoma.

The invasion of lymphatic vessels by colorectal cancer (CRC) and its subsequent spread to draining lymph nodes is a key determinant of prognosis in this common and frequently fatal malignancy. Although tumoural lymphangiogenesis is assumed to contribute to this process, review of the current literature fails to support any notion of a simple correlation between lymphatic vessel density and CRC metastasis. Furthermore, attempts to correlate the expression of various lymphangiogenic growth factors, most notably VEGF-C and VEGF-D, with the lymphatic metastasis of CRC have provided contradictory results. Recent evidence from animal and human models of tumour metastasis suggests that complex functional and biochemical interactions between the microvasculature of tumours and other cell types within the tumour microenvironment may play a pivotal role in the behaviour of commonly metastasizing tumours. Indeed, previous insights into tumoural blood vessels have provided candidate markers of tumoural angiogenesis that are currently the subject of intense investigation as future therapeutic targets. In this review article we survey the current evidence relating lymphangiogenesis and lymphangiogenic growth factor production to metastasis by CRC, and attempt to provide some insight into the apparent discrepancies within the literature. In particular, we also discuss some new and provocative insights into the properties of tumoural lymphatics suggesting that they have specific expression profiles distinct from those of normal lymphatic vessels and that appear to promote metastasis. These findings raise the exciting prospect of future biomarkers of lymphatic metastasis and identify potential targets for new generation anti-tumour therapies.

Artificial intelligence-based morphological fingerprinting of megakaryocytes: a new tool for assessing disease in MPN patients.

Accurate diagnosis and classification of myeloproliferative neoplasms (MPNs) requires integration of clinical, morphological, and genetic findings. Despite major advances in our understanding of the molecular and genetic basis of MPNs, the morphological assessment of bone marrow trephines (BMT) is critical in differentiating MPN subtypes and their reactive mimics. However, morphological assessment is heavily constrained by a reliance on subjective, qualitative, and poorly reproducible criteria. To improve the morphological assessment of MPNs, we have developed a machine learning approach for the automated identification, quantitative analysis, and abstract representation of megakaryocyte features using reactive/nonneoplastic BMT samples (n = 43) and those from patients with established diagnoses of essential thrombocythemia (n = 45), polycythemia vera (n = 18), or myelofibrosis (n = 25). We describe the application of an automated workflow for the identification and delineation of relevant histological features from routinely prepared BMTs. Subsequent analysis enabled the tissue diagnosis of MPN with a high predictive accuracy (area under the curve = 0.95) and revealed clear evidence of the potential to discriminate between important MPN subtypes. Our method of visually representing abstracted megakaryocyte features in the context of analyzed patient cohorts facilitates the interpretation and monitoring of samples in a manner that is beyond conventional approaches. The automated BMT phenotyping approach described here has significant potential as an adjunct to standard genetic and molecular testing in established or suspected MPN patients, either as part of the routine diagnostic pathway or in the assessment of disease progression/response to treatment.