With the ever increasing use of computational models in the biosciences, the need to share models and reproduce the results of published studies efficiently and easily is becoming more important. To this end, various standards have been proposed that can be used to describe models, simulations, data or other essential information in a consistent fashion. These constitute various separate components required to reproduce a given published scientific result.

Despite their known transforming properties, the effects of leukemogenic FLT3-ITD mutations on hematopoietic stem and multipotent progenitor cells and on hematopoietic differentiation are not well understood. We report a mouse model harboring an ITD in the murine Flt3 locus that develops myeloproliferative disease resembling CMML and further identified FLT3-ITD mutations in a subset of human CMML. These findings correlated with an increase in number, cell cycling, and survival of multipotent stem and progenitor cells in an ITD dose-dependent manner in animals that exhibited alterations within their myeloid progenitor compartments and a block in normal B cell development. This model provides insights into the consequences of constitutive signaling by an oncogenic tyrosine kinase on hematopoietic progenitor quiescence, function, and cell fate.

Approximately 18% of acute myeloid leukemia (AML) cases express a fusion transcript. However, few fusions are recurrent across AML and the identification of these rare chimeras is of interest to characterize AML patients. Here, we studied the transcriptome of 8 adult AML patients with poorly described chromosomal translocation(s), with the aim of identifying novel and rare fusion transcripts. We integrated RNA-sequencing data with multiple approaches including computational analysis, Sanger sequencing, fluorescence in situ hybridization and in vitro studies to assess the oncogenic potential of the ZEB2-BCL11B chimera. We detected 7 different fusions with partner genes involving transcription factors (OAZ-MAFK, ZEB2-BCL11B), tumor suppressors (SAV1-GYPB, PUF60-TYW1, CNOT2-WT1) and rearrangements associated with the loss of NF1 (CPD-PXT1, UTP6-CRLF3). Notably, ZEB2-BCL11B rearrangements co-occurred with FLT3 mutations and were associated with a poorly differentiated or mixed phenotype leukemia. Although the fusion alone did not transform murine c-Kit+ bone marrow cells, 45.4% of 14q32 non-rearranged AML cases were also BCL11B-positive, suggesting a more general and complex mechanism of leukemogenesis associated with BCL11B expression. Overall, by combining different approaches, we described rare fusion events contributing to the complexity of AML and we linked the expression of some chimeras to genomic alterations hitting known genes in AML.

Altered transcription is a cardinal feature of acute myeloid leukemia (AML); however, exactly how mutations synergize to remodel the epigenetic landscape and rewire three-dimensional DNA topology is unknown. Here, we apply an integrated genomic approach to a murine allelic series that models the two most common mutations in AML: Flt3-ITD and Npm1c. We then deconvolute the contribution of each mutation to alterations of the epigenetic landscape and genome organization, and infer how mutations synergize in the induction of AML. Our studies demonstrate that Flt3-ITD signals to chromatin to alter the epigenetic environment and synergizes with mutations in Npm1c to alter gene expression and drive leukemia induction. These analyses also allow the identification of long-range cis-regulatory circuits, including a previously unknown superenhancer of Hoxa locus, as well as larger and more detailed gene-regulatory networks, driven by transcription factors including PU.1 and IRF8, whose importance we demonstrate through perturbation of network members.

Natural products that contain ortho-quinones show great potential as anticancer agents but have been largely discarded from clinical development because their redox-cycling behaviour results in general systemic toxicity. Here we report conjugation of ortho-quinones to a carrier, which simultaneously masks their underlying redox activity. C-benzylation at a quinone carbonyl forms a redox-inactive benzyl ketol. Upon a specific enzymatic trigger, an acid-promoted, self-immolative C-C bond-cleaving 1,6-elimination mechanism releases the redox-active hydroquinone inside cells. By using a 5-lipoxygenase modulator, β-lapachone, we created cathepsin-B-cleavable quinone prodrugs. We applied the strategy for intracellular release of β-lapachone upon antibody-mediated delivery. Conjugation of protected β-lapachone to Gem-IgG1 antibodies, which contain the variable region of gemtuzumab, results in homogeneous, systemically non-toxic and conditionally stable CD33+-specific antibody-drug conjugates with in vivo efficacy against a xenograft murine model of acute myeloid leukaemia. This protection strategy could allow the use of previously overlooked natural products as anticancer agents, thus extending the range of drugs available for next-generation targeted therapeutics.

Recurrent gene mutations often cooperate in a predefined stepwise and synergistic manner to alter global transcription, through directly or indirectly remodeling epigenetic landscape on linear and three-dimensional (3D) scales. Here, we present a multiomics data integration approach to investigate the impact of gene mutational synergy on transcription, chromatin states, and 3D chromatin organization in a murine leukemia model. This protocol provides an executable framework to study epigenetic remodeling induced by cooperating gene mutations and to identify the critical regulatory network involved. For complete details on the use and execution of this protocol, please refer to Yun et al. (2021).

Leukaemia stem cells (LSCs) are the critical seed for the growth of haematological malignancies, driving the clonal expansion that enables disease initiation, relapse and often resistance. Specifically, they display inherent phenotypic and epigenetic plasticity resulting in complex heterogenic diseases. In this review, we discuss the key principles of deregulation of epigenetic processes that shape this disease evolution. We consider measures to define and quantify clonal heterogeneity, combining information from recent studies assessing mutational, transcriptional and epigenetic landscapes at single cell resolution in myeloid neoplasms (MN). We highlight the importance of integrating epigenetic and genetic information to better understand inter- and intra-patient heterogeneity and discuss how this understanding further informs evolution and progression trajectories and subsequent clinical response in MN. Under this topic, we also discuss efforts to identify mechanisms of resistance, by longitudinal analyses of patient samples. Finally, we highlight how we might target these aberrant epigenetic processes for better therapeutic outcomes and to potentially eradicate LSCs.

Haematopoietic stem cells (HSC) reside in the bone marrow microenvironment (BMM), where they respond to extracellular calcium [eCa2+] via the G-protein coupled calcium-sensing receptor (CaSR). Here we show that a calcium gradient exists in this BMM, and that [eCa2+] and response to [eCa2+] differ between leukaemias. CaSR influences the location of MLL-AF9+ acute myeloid leukaemia (AML) cells within this niche and differentially impacts MLL-AF9+ AML versus BCR-ABL1+ leukaemias. Deficiency of CaSR reduces AML leukaemic stem cells (LSC) 6.5-fold. CaSR interacts with filamin A, a crosslinker of actin filaments, affects stemness-associated factors and modulates pERK, β-catenin and c-MYC signaling and intracellular levels of [Ca2+] in MLL-AF9+ AML cells. Combination treatment of cytarabine plus CaSR-inhibition in various models may be superior to cytarabine alone. Our studies suggest CaSR to be a differential and targetable factor in leukaemia progression influencing self-renewal of AML LSC via [eCa2+] cues from the BMM.

Epigenetic regulators, such as EZH2, are frequently mutated in cancer, and loss-of-function EZH2 mutations are common in myeloid malignancies. We have examined the importance of cellular context for Ezh2 loss during the evolution of acute myeloid leukemia (AML), where we observed stage-specific and diametrically opposite functions for Ezh2 at the early and late stages of disease. During disease maintenance, WT Ezh2 exerts an oncogenic function that may be therapeutically targeted. In contrast, Ezh2 acts as a tumor suppressor during AML induction. Transcriptional analysis explains this apparent paradox, demonstrating that loss of Ezh2 derepresses different expression programs during disease induction and maintenance. During disease induction, Ezh2 loss derepresses a subset of bivalent promoters that resolve toward gene activation, inducing a feto-oncogenic program that includes genes such as Plag1, whose overexpression phenocopies Ezh2 loss to accelerate AML induction in mouse models. Our data highlight the importance of cellular context and disease phase for the function of Ezh2 and its potential therapeutic implications.

No abstract available

As cardiac cell models become increasingly complex, a correspondingly complex 'genealogy' of inherited parameter values has also emerged. The result has been the loss of a direct link between model parameters and experimental data, limiting both reproducibility and the ability to re-fit to new data. We examine the ability of approximate Bayesian computation (ABC) to infer parameter distributions in the seminal action potential model of Hodgkin and Huxley, for which an immediate and documented connection to experimental results exists. The ability of ABC to produce tight posteriors around the reported values for the gating rates of sodium and potassium ion channels validates the precision of this early work, while the highly variable posteriors around certain voltage dependency parameters suggests that voltage clamp experiments alone are insufficient to constrain the full model. Despite this, Hodgkin and Huxley's estimates are shown to be competitive with those produced by ABC, and the variable behaviour of posterior parametrized models under complex voltage protocols suggests that with additional data the model could be fully constrained. This work will provide the starting point for a full identifiability analysis of commonly used cardiac models, as well as a template for informative, data-driven parametrization of newly proposed models.

Chaste is an open-source C++ library for computational biology that has well-developed cardiac electrophysiology tissue simulation support. In this paper, we introduce the features available for performing cardiac electrophysiology action potential simulations using a wide range of models from the Physiome repository. The mathematics of the models are described in CellML, with units for all quantities. The primary idea is that the model is defined in one place (the CellML file), and all model code is auto-generated at compile or run time; it never has to be manually edited. We use ontological annotation to identify model variables describing certain biological quantities (membrane voltage, capacitance, etc.) to allow us to import any relevant CellML models into the Chaste framework in consistent units and to interact with them via consistent interfaces. This approach provides a great deal of flexibility for analysing different models of the same system. Chaste provides a wide choice of numerical methods for solving the ordinary differential equations that describe the models. Fixed-timestep explicit and implicit solvers are provided, as discussed in previous work. Here we introduce the Rush-Larsen and Generalized Rush-Larsen integration techniques, made available via symbolic manipulation of the model equations, which are automatically rearranged into the forms required by these approaches. We have also integrated the CVODE solvers, a 'gold standard' for stiff systems, and we have developed support for symbolic computation of the Jacobian matrix, yielding further increases in the performance and accuracy of CVODE. We discuss some of the technical details of this work and compare the performance of the available numerical methods. Finally, we discuss how this is generalized in our functional curation framework, which uses a domain-specific language for defining complex experiments as a basis for comparison of model behavior.

Loss-of-function mutations of cyclic-AMP response element binding protein, binding protein (CREBBP) are prevalent in lymphoid malignancies. However, the tumour suppressor functions of CREBBP remain unclear. We demonstrate that loss of Crebbp in murine haematopoietic stem and progenitor cells (HSPCs) leads to increased development of B-cell lymphomas. This is preceded by accumulation of hyperproliferative lymphoid progenitors with a defective DNA damage response (DDR) due to a failure to acetylate p53. We identify a premalignant lymphoma stem cell population with decreased H3K27ac, which undergoes transcriptional and genetic evolution due to the altered DDR, resulting in lymphomagenesis. Importantly, when Crebbp is lost later in lymphopoiesis, cellular abnormalities are lost and tumour generation is attenuated. We also document that CREBBP mutations may occur in HSPCs from patients with CREBBP-mutated lymphoma. These data suggest that earlier loss of Crebbp is advantageous for lymphoid transformation and inform the cellular origins and subsequent evolution of lymphoid malignancies.

CellML is an XML based language for representing mathematical models, in a machine-independent form which is suitable for their exchange between different authors, and for archival in a model repository. Allowing for the exchange and archival of models in a computer readable form is a key strategic goal in bioinformatics, because of the associated improvements in scientific record accuracy, the faster iterative process of scientific development, and the ability to combine models into large integrative models.However, for CellML models to be useful, tools which can process them correctly are needed. Due to some of the more complex features present in CellML models, such as imports, developing code ab initio to correctly process models can be an onerous task. For this reason, there is a clear and pressing need for an application programming interface (API), and a good implementation of that API, upon which tools can base their support for CellML.

Acute myeloid leukemia (AML) is the most common acute leukemia in adults and has an unacceptably low cure rate. In recent years, a number of new treatment strategies and compounds were developed for the treatment of AML. There were several randomized controlled clinical trials with the objective to improve patients' management and patients' outcome in AML. Unfortunately, these trials are not always directly comparable since they do not measure the same outcomes, and currently there are no core outcome sets that can be used to guide outcome selection and harmonization in this disease area. The HARMONY (Healthcare Alliance for Resourceful Medicine Offensive against Neoplasms in Hematology) Alliance is a public-private European network established in 2017 and currently includes 53 partners and 32 associated members from 22 countries. Amongst many other goals of the HARMONY Alliance, Work Package 2 focuses on defining outcomes that are relevant to each hematological malignancy. Accordingly, this pilot study will be performed to define a core outcome set in AML.

Clinical recommendations for Acute Myeloid Leukemia (AML) classification and risk-stratification remain heavily reliant on cytogenetic findings at diagnosis, which are present in <50% of patients. Using comprehensive molecular profiling data from 3,653 patients we characterize and validate 16 molecular classes describing 100% of AML patients. Each class represents diverse biological AML subgroups, and is associated with distinct clinical presentation, likelihood of response to induction chemotherapy, risk of relapse and death over time. Secondary AML-2, emerges as the second largest class (24%), associates with high-risk disease, poor prognosis irrespective of flow Minimal Residual Disease (MRD) negativity, and derives significant benefit from transplantation. Guided by class membership we derive a 3-tier risk-stratification score that re-stratifies 26% of patients as compared to standard of care. This results in a unified framework for disease classification and risk-stratification in AML that relies on information from cytogenetics and 32 genes. Last, we develop an open-access patient-tailored clinical decision support tool.

Histone acetyltransferases (HATs) catalyze the transfer of an acetyl group from acetyl-CoA to lysine residues of histones and play a central role in transcriptional regulation in diverse biological processes. Dysregulation of HAT activity can lead to human diseases including developmental disorders and cancer. Through genome-wide CRISPR-Cas9 screens, we identified several HATs of the MYST family as fitness genes for acute myeloid leukemia (AML). Here we investigate the essentiality of lysine acetyltransferase KAT7 in AMLs driven by the MLL-X gene fusions. We found that KAT7 loss leads to a rapid and complete loss of both H3K14ac and H4K12ac marks, in association with reduced proliferation, increased apoptosis, and differentiation of AML cells. Acetyltransferase activity of KAT7 is essential for the proliferation of these cells. Mechanistically, our data propose that acetylated histones provide a platform for the recruitment of MLL-fusion-associated adaptor proteins such as BRD4 and AF4 to gene promoters. Upon KAT7 loss, these factors together with RNA polymerase II rapidly dissociate from several MLL-fusion target genes that are essential for AML cell proliferation, including MEIS1, PBX3, and SENP6. Our findings reveal that KAT7 is a plausible therapeutic target for this poor prognosis AML subtype.

The Computational Modeling in Biology Network (COMBINE) is a consortium of groups involved in the development of open community standards and formats used in computational modeling in biology. COMBINE's aim is to act as a coordinator, facilitator, and resource for different standardization efforts whose domains of use cover related areas of the computational biology space. In this perspective article, we summarize COMBINE, its general organization, and the community standards and other efforts involved in it. Our goals are to help guide readers toward standards that may be suitable for their research activities, as well as to direct interested readers to relevant communities where they can best expect to receive assistance in how to develop interoperable computational models.

It is currently unclear whether Merlin/NF2 suppresses tumorigenesis by activating upstream components of the Hippo pathway at the plasma membrane or by inhibiting the E3 ubiquitin ligase CRL4(DCAF1) in the nucleus. We found that derepressed CRL4(DCAF1) promotes YAP- and TEAD-dependent transcription by ubiquitylating and, thereby, inhibiting Lats1 and 2 in the nucleus. Genetic epistasis experiments and analysis of tumor-derived missense mutations indicate that this signaling connection sustains the oncogenicity of Merlin-deficient tumor cells. Analysis of clinical samples confirms that this pathway operates in NF2-mutant tumors. We conclude that derepressed CRL4(DCAF1) promotes activation of YAP by inhibiting Lats1 and 2 in the nucleus.

Computational modeling of cardiac cellular electrophysiology has a long history, and many models are now available for different species, cell types, and experimental preparations. This success brings with it a challenge: how do we assess and compare the underlying hypotheses and emergent behaviors so that we can choose a model as a suitable basis for a new study or to characterize how a particular model behaves in different scenarios? We have created an online resource for the characterization and comparison of electrophysiological cell models in a wide range of experimental scenarios. The details of the mathematical model (quantitative assumptions and hypotheses formulated as ordinary differential equations) are separated from the experimental protocol being simulated. Each model and protocol is then encoded in computer-readable formats. A simulation tool runs virtual experiments on models encoded in CellML, and a website (https://chaste.cs.ox.ac.uk/WebLab) provides a friendly interface, allowing users to store and compare results. The system currently contains a sample of 36 models and 23 protocols, including current-voltage curve generation, action potential properties under steady pacing at different rates, restitution properties, block of particular channels, and hypo-/hyperkalemia. This resource is publicly available, open source, and free, and we invite the community to use it and become involved in future developments. Investigators interested in comparing competing hypotheses using models can make a more informed decision, and those developing new models can upload them for easy evaluation under the existing protocols, and even add their own protocols.