Modeling the Pro-inflammatory Tumor Microenvironment in Acute Lymphoblastic Leukemia Predicts a Breakdown of Hematopoietic-Mesenchymal Communication Networks

The hematopoietic microenvironment: a network of niches for the development of all blood cell lineages

Blood cell formation (hematopoiesis) takes place mainly in the bone marrow, within the hematopoietic microenvironment, composed of a number of different cell types and their molecular products that together shape spatially organized and highly specialized microstructures called hematopoietic niches. From the earliest developmental stages and throughout the myeloid and lymphoid lineage differentiation pathways, hematopoietic niches play a crucial role in the preservation of cellular integrity and the regulation of proliferation and differentiation rates. Current evidence suggests that each blood cell lineage develops under specific, discrete niches that support committed progenitor and precursor cells and potentially cooperate with transcriptional programs determining the gradual lineage commitment and specification. This review aims to discuss recent advances on the cellular identity and structural organization of lymphoid, granulocytic, monocytic, megakaryocytic, and erythroid niches throughout the hematopoietic microenvironment and the mechanisms by which they interconnect and regulate viability, maintenance, maturation, and function of the developing blood cells.

Logical modelling of myelofibrotic microenvironment predicts dysregulated progenitor stem cell crosstalk

Primary myelofibrosis is an untreatable age-related disorder of haematopoiesis in which a break in the crosstalk between progenitor Haematopoietic Stem Cells (HSCs) and neighbouring mesenchymal stem cells causes HSCs to rapidly proliferate and migrate out of the bone marrow. Around 90% of patients harbour mutations in driver genes that all converge to overactivate haematopoietic JAK-STAT signalling, which is thought to be critical for disease progression, as well as microenvironment modification induced by chronic inflammation. The trigger to the initial event is unknown but dysregulated thrombopoietin (TPO) and Toll-Like Receptor (TLR) signalling are hypothesised to initiate chronic inflammation which then disrupts stem cell crosstalk. Using a systems biology approach, we have constructed an intercellular logical model that captures JAK-STAT signalling and key crosstalk channels between haematopoietic and mesenchymal stem cells. The aim of the model is to decipher how TPO and TLR stimulation can perturb the bone marrow microenvironment and dysregulate stem cell crosstalk. The model predicted conditions in which the disease was averted and established for both wildtype and ectopically JAK mutated simulations. The presence of TPO and TLR are both required to disturb stem cell crosstalk and result in the disease for wildtype. TLR signalling alone was sufficient to perturb the crosstalk and drive disease progression for JAK mutated simulations. Furthermore, the model predicts probabilities of disease onset for wildtype simulations that match clinical data. These predictions might explain why patients who test negative for the JAK mutation can still be diagnosed with PMF, in which continual exposure to TPO and TLR receptor activation may trigger the initial inflammatory event that perturbs the bone marrow microenvironment and induce disease onset.

Reducing Boolean networks with backward equivalence

BACKGROUND

Boolean Networks (BNs) are a popular dynamical model in biology where the state of each component is represented by a variable taking binary values that express, for instance, activation/deactivation or high/low concentrations. Unfortunately, these models suffer from the state space explosion, i.e., there are exponentially many states in the number of BN variables, which hampers their analysis.

RESULTS

We present Boolean Backward Equivalence (BBE), a novel reduction technique for BNs which collapses system variables that, if initialized with same value, maintain matching values in all states. A large-scale validation on 86 models from two online model repositories reveals that BBE is effective, since it is able to reduce more than 90% of the models. Furthermore, on such models we also show that BBE brings notable analysis speed-ups, both in terms of state space generation and steady-state analysis. In several cases, BBE allowed the analysis of models that were originally intractable due to the complexity. On two selected case studies, we show how one can tune the reduction power of BBE using model-specific information to preserve all dynamics of interest, and selectively exclude behavior that does not have biological relevance.

CONCLUSIONS

BBE complements existing reduction methods, preserving properties that other reduction methods fail to reproduce, and vice versa. BBE drops all and only the dynamics, including attractors, originating from states where BBE-equivalent variables have been initialized with different activation values The remaining part of the dynamics is preserved exactly, including the length of the preserved attractors, and their reachability from given initial conditions, without adding any spurious behaviours. Given that BBE is a model-to-model reduction technique, it can be combined with further reduction methods for BNs.

Target Control of Asynchronous Boolean Networks

We study the target control of asynchronous Boolean networks, to identify interventions that can drive the dynamics of a given Boolean network from any initial state to the desired target attractor. Based on the application time, the control can be realised with three types of perturbations, including instantaneous, temporary and permanent perturbations. We develop efficient methods to compute the target control for a given target attractor with these three types of perturbations. We compare our methods with the stable motif-based control method on a variety of real-life biological networks to evaluate their performance. We show that our methods scale well for large Boolean networks and they are able to identify a rich set of solutions with a small number of perturbations.

Single Cell Transcriptomics to Understand HSC Heterogeneity and Its Evolution upon Aging

Single-cell transcriptomic technologies enable the uncovering and characterization of cellular heterogeneity and pave the way for studies aiming at understanding the origin and consequences of it. The hematopoietic system is in essence a very well adapted model system to benefit from this technological advance because it is characterized by different cellular states. Each cellular state, and its interconnection, may be defined by a specific location in the global transcriptional landscape sustained by a complex regulatory network. This transcriptomic signature is not fixed and evolved over time to give rise to less efficient hematopoietic stem cells (HSC), leading to a well-documented hematopoietic aging. Here, we review the advance of single-cell transcriptomic approaches for the understanding of HSC heterogeneity to grasp HSC deregulations upon aging. We also discuss the new bioinformatics tools developed for the analysis of the resulting large and complex datasets. Finally, since hematopoiesis is driven by fine-tuned and complex networks that must be interconnected to each other, we highlight how mathematical modeling is beneficial for doing such interconnection between multilayered information and to predict how HSC behave while aging.

Identification of dynamic driver sets controlling phenotypical landscapes

Controlling phenotypical landscapes is of vital interest to modern biology. This task becomes highly demanding because cellular decisions involve complex networks engaging in crosstalk interactions. Previous work on control theory indicates that small sets of compounds can control single phenotypes. However, a dynamic approach is missing to determine the drivers of the whole network dynamics. By analyzing 35 biologically motivated Boolean networks, we developed a method to identify small sets of compounds sufficient to decide on the entire phenotypical landscape. These compounds do not strictly prefer highly related compounds and show a smaller impact on the stability of the attractor landscape. The dynamic driver sets include many intervention targets and cellular reprogramming drivers in human networks. Finally, by using a new comprehensive model of colorectal cancer, we provide a complete workflow on how to implement our approach to shift from in silico to in vitro guided experiments.

The Bone Marrow Niche in B-Cell Acute Lymphoblastic Leukemia: The Role of Microenvironment from Pre-Leukemia to Overt Leukemia

Genetic lesions predisposing to pediatric B-cell acute lymphoblastic leukemia (B-ALL) arise in utero, generating a clinically silent pre-leukemic phase. We here reviewed the role of the surrounding bone marrow (BM) microenvironment in the persistence and transformation of pre-leukemic clones into fully leukemic cells. In this context, inflammation has been highlighted as a crucial microenvironmental stimulus able to promote genetic instability, leading to the disease manifestation. Moreover, we focused on the cross-talk between the bulk of leukemic cells with the surrounding microenvironment, which creates a “corrupted” BM malignant niche, unfavorable for healthy hematopoietic precursors. In detail, several cell subsets, including stromal, endothelial cells, osteoblasts and immune cells, composing the peculiar leukemic niche, can actively interact with B-ALL blasts. Through deregulated molecular pathways they are able to influence leukemia development, survival, chemoresistance, migratory and invasive properties. The concept that the pre-leukemic and leukemic cell survival and evolution are strictly dependent both on genetic lesions and on the external signals coming from the microenvironment paves the way to a new idea of dual targeting therapeutic strategy.

Childhood Acute Leukemias in Developing Nations: Successes and Challenges

PURPOSE OF REVIEW

Acute leukemias represent a tremendous threat to public health around the globe and the main cause of death due to disease in scholar age children from developing nations. Here, we review their current status in Mexico, as a paradigm of study, and the major challenges to control systemic diseases like childhood cancer.

RECENT FINDINGS

A unique molecular epidemiology, late/low precision diagnosis, limited access to treatment, toxicity associated with therapy, continuous exposure to environmental risk factors, and the high frequency of early relapses are some of the factors cooperating to low rates of survival in low-to-medium-income countries. Deliberative dialogues and exhaustive programs have emerged as promising means of advancing evidence-informed policy, by providing a structured forum for key stakeholders to integrate scientific and pragmatic knowledge about complex health concerns. A system-wide strategy based on the comprehensive leukemia identity is essential for a meaningful decline in early childhood mortality.

TaBooN Boolean Network Synthesis Based on Tabu Search

Recent developments in Omics-technologies revolutionized the investigation of biology by producing molecular data in multiple dimensions and scale. This breakthrough in biology raises the crucial issue of their interpretation based on modelling. In this undertaking, network provides a suitable framework for modelling the interactions between molecules. Basically a Biological network is composed of nodes referring to the components such as genes or proteins, and the edges/arcs formalizing interactions between them. The evolution of the interactions is then modelled by the definition of a dynamical system. Among the different categories of network, the Boolean network offers a reliable qualitative framework for the modelling. Automatically synthesizing a Boolean network from experimental data therefore remains a necessary but challenging issue. In this study, we present Taboon, an original work-flow for synthesizing Boolean Networks from biological data. The methodology uses the data in the form of boolean profiles for inferring all the potential local formula inference. They combine to form the model space from which the most truthful model with regards to biological knowledge and experiments must be found. In the TaBooN work-flow the selection of the fittest model is achieved by a Tabu-search algorithm. TaBooN is an automated method for Boolean Network inference from.

Cell-surface heparan sulfate proteoglycans as multifunctional integrators of signaling in cancer

Proteoglycans (PGs) represent a large proportion of the components that constitute the extracellular matrix (ECM). They are a diverse group of glycoproteins characterized by a covalent link to a specific glycosaminoglycan type. As part of the ECM, heparan sulfate (HS)PGs participate in both physiological and pathological processes including cell recruitment during inflammation and the promotion of cell proliferation, adhesion and motility during development, angiogenesis, wound repair and tumor progression. A key function of HSPGs is their ability to modulate the expression and function of cytokines, chemokines, growth factors, morphogens, and adhesion molecules. This is due to their capacity to act as ligands or co-receptors for various signal-transducing receptors, affecting pathways such as FGF, VEGF, chemokines, integrins, Wnt, notch, IL-6/JAK-STAT3, and NF-κB. The activation of those pathways has been implicated in the induction, progression, and malignancy of a tumor. For many years, the study of signaling has allowed for designing specific drugs targeting these pathways for cancer treatment, with very positive results. Likewise, HSPGs have become the subject of cancer research and are increasingly recognized as important therapeutic targets. Although they have been studied in a variety of preclinical and experimental models, their mechanism of action in malignancy still needs to be more clearly defined. In this review, we discuss the role of cell-surface HSPGs as pleiotropic modulators of signaling in cancer and identify them as promising markers and targets for cancer treatment.

Dynamical modeling predicts an inflammation-inducible CXCR7+ B cell precursor with potential implications in lymphoid blockage pathologies

Background

The blockage at the early B lymphoid cell development pathway within the bone marrow is tightly associated with hematopoietic and immune diseases, where the disruption of basal regulatory networks prevents the continuous replenishment of functional B cells. Dynamic computational models may be instrumental for the comprehensive understanding of mechanisms underlying complex differentiation processes and provide novel prediction/intervention platforms to reinvigorate the system.

Methods

By reconstructing a three-module regulatory network including genetic transcription, intracellular transduction, and microenvironment communication, we have investigated the early B lineage cell fate decisions in normal and pathological settings. The early B cell differentiation network was simulated as a Boolean model and then transformed, using fuzzy logic, to a continuous model. We tested null and overexpression mutants to analyze the emergent behavior of the network. Due to its importance in inflammation, we investigated the effect of NFkB induction at different early B cell differentiation stages.

Results

While the exhaustive synchronous and asynchronous simulation of the early B cell regulatory network (eBCRN) reproduced the configurations of the hematopoietic progenitors and early B lymphoid precursors of the pathway, its simulation as a continuous model with fuzzy logics suggested a transient IL-7R⁺ ProB-to-Pre-B subset expressing pre-BCR and a series of dominant B-cell transcriptional factors. This conspicuous differentiating cell population up-regulated CXCR7 and reduced CXCR4 and FoxO1 expression levels. Strikingly, constant but intermediate NFkB signaling at specific B cell differentiation stages allowed stabilization of an aberrant CXCR7⁺ pre-B like phenotype with apparent affinity to proliferative signals, while under constitutive overactivation of NFkB, such cell phenotype was aberrantly exacerbated from the earliest stage of common lymphoid progenitors. Our mutant models revealed an abnormal delay in the BCR assembly upon NFkB activation, concomitant to sustained Flt3 signaling, down-regulation of Ebf1, Irf4 and Pax5 genes transcription, and reduced Ig recombination, pointing to a potential lineage commitment blockage.

Discussion

For the first time, an inducible CXCR7^hi B cell precursor endowed with the potential capability of shifting central lymphoid niches, is inferred by computational modeling. Its phenotype is compatible with that of leukemia-initiating cells and might be the foundation that bridges inflammation with blockage-related malignancies and a wide range of immunological diseases. Besides the predicted differentiation impairment, inflammation-inducible phenotypes open the possibility of newly formed niches colonized by the reported precursor. Thus, emergent bone marrow ecosystems are predicted following a pro-inflammatory induction, that may lead to hematopoietic instability associated to blockage pathologies.

Antifragility Predicts the Robustness and Evolvability of Biological Networks through Multi-Class Classification with a Convolutional Neural Network

Robustness and evolvability are essential properties to the evolution of biological networks. To determine if a biological network is robust and/or evolvable, it is required to compare its functions before and after mutations. However, this sometimes takes a high computational cost as the network size grows. Here, we develop a predictive method to estimate the robustness and evolvability of biological networks without an explicit comparison of functions. We measure antifragility in Boolean network models of biological systems and use this as the predictor. Antifragility occurs when a system benefits from external perturbations. By means of the differences of antifragility between the original and mutated biological networks, we train a convolutional neural network (CNN) and test it to classify the properties of robustness and evolvability. We found that our CNN model successfully classified the properties. Thus, we conclude that our antifragility measure can be used as a predictor of the robustness and evolvability of biological networks.

Silencing of lncRNA UCA1 curbs proliferation and accelerates apoptosis by repressing SIRT1 signals by targeting miR-204 in pediatric AML

The long noncoding RNA urothelial carcinoma-associated 1 (UCA1) has been reported to sustain the proliferation of acute myeloid leukemia (AML) cells through downregulating cell cycle regulators p27^kip1 . Yet, the foundational mechanism of UCA1 in AML pathologies remains unclear. Herein, we found an escalation of UCA1 expression and suppression of miR-204 expression in pediatric AML patients and cells. UCA1 silencing suppressed cell proliferative abilities, promoted apoptotic rates, decreased Ki67, and increased cleaved caspase-3 in AML cells. Moreover, UCA1 sponged miR-204 and suppressed its expression. UCA1 overexpression inversed the miR-204 suppressed proliferation and promoted apoptosis. UCA1 also boosted the expression of SIRT1, a miR-204 target, via the sponging interaction. Furthermore, miR-204 inhibited inducible nitric oxide synthase and cyclooxygenase-2 expression, while UCA1 overexpression inversed the inhibitory effects in AML cells. Our findings concluded that UCA1 downregulation repressed cell proliferation and promoted apoptosis through inactivating SIRT1 signals by upregulating miR-204 in pediatric AML.

Poor Prognosis Biomolecular Factors Are Highly Frequent in Childhood Acute Leukemias From Oaxaca, Mexico

OBJECTIVE

To investigate the cellular and molecular epidemiology of acute leukemias in vulnerable populations of children and adolescents in Oaxaca de Juarez, Mexico.

MATERIAL AND METHODS

Descriptive, cross-sectional and retrospective study, conducted from 2014 to 2018 in which profiles of molecular and immunophenotypic aberrations were investigated in children and adolescents diagnosed with acute leukemia, by evaluating 28 molecular abnormalities by HemaVision-Q28 multiplex RT-PCR kit and standardized EuroFlow Immunophenotyping of bone marrow cells.

RESULTS

We included 218 patients, with 82.5% younger than 14 years and 17.5% adolescents. The median age was 9 years and a main peak of incidence was recorded at age of 4 to 5 years. B-cell acute lymphoblastic leukemia was diagnosed in 70.64% of all cases, acute myeloid leukemia was in 22.48%, T-cell acute lymphoblastic leukemia in 6.42%, and mixed lineage acute leukemia in 0.46% of cases. Overall, chromosomal translocations were positive in 29.82% of cases. While 65.31% of patients with acute myeloid leukemia reported aberrancies, only in 18.83% of B-cell acute lymphoblastic leukemia cases genetic abnormalities were obvious. Surprisingly, most prevalent translocations in B-cell acute lymphoblastic leukemia were t(9;22) in 20.7%, followed by t(4;11) in 17.2% and t(6;11) in 13.8%, whereas patients with acute myeloid leukemia showed t(15;17) in 40.6% and t(8;21) in 21.9%. In contrast, an homogeneous expression of t(3;21) and t(6;11) was recorded for T-cell acute lymphoblastic leukemia and mixed lineage acute leukemia cases, respectively. Except for t(1;19), expressed only by pre-B cells, there was no association of any of the studied translocations with differentiation stages of the B-leukemic developmental pathway.

CONCLUSION

Our findings identify near 50% of patients with acute lymphoblastic leukemia at debut with high-risk translocations and poor prognosis in B-cell acute lymphoblastic leukemia as well as an unexpected increase of acute myeloid leukemia cases in young children, suggesting a molecular shift that support a higher incidence of poor prognosis cases in Oaxaca.

From Discrete to Continuous Modeling of Lymphocyte Development and Plasticity in Chronic Diseases

The molecular events leading to differentiation, development, and plasticity of lymphoid cells have been subject of intense research due to their key roles in multiple pathologies, such as lymphoproliferative disorders, tumor growth maintenance and chronic diseases. The emergent roles of lymphoid cells and the use of high-throughput technologies have led to an extensive accumulation of experimental data allowing the reconstruction of gene regulatory networks (GRN) by integrating biochemical signals provided by the microenvironment with transcriptional modules of lineage-specific genes. Computational modeling of GRN has been useful for the identification of molecular switches involved in lymphoid specification, prediction of microenvironment-dependent cell plasticity, and analyses of signaling events occurring downstream the activation of antigen recognition receptors. Among most common modeling strategies to analyze the dynamical behavior of GRN, discrete dynamic models are widely used for their capacity to capture molecular interactions when a limited knowledge of kinetic parameters is present. However, they are less powerful when modeling complex systems sensitive to biochemical gradients. To compensate it, discrete models may be transformed into regulatory networks that includes state variables and parameters varying within a continuous range. This approach is based on a system of differential equations dynamics with regulatory interactions described by fuzzy logic propositions. Here, we discuss the applicability of this method on modeling of development and plasticity processes of adaptive lymphocytes, and its potential implications in the study of pathological landscapes associated to chronic diseases.

Human Induced Pluripotent Stem Cells : Clinical Significance and Applications in Neurologic Diseases

The generation of human induced pluripotent stem cells (iPSCs) from somatic cells using gene transfer opens new areas for precision medicine with personalized cell therapy and encourages the discovery of essential platforms for targeted drug development. iPSCs retain the genome of the donor, may regenerate indefinitely, and undergo differentiation into virtually any cell type of interest using a range of published protocols. There has been enormous interest among researchers regarding the application of iPSC technology to regenerative medicine and human disease modeling, in particular, modeling of neurologic diseases using patient-specific iPSCs. For instance, Parkinson’s disease, Alzheimer’s disease, and spinal cord injuries may be treated with iPSC therapy or replacement tissues obtained from iPSCs. In this review, we discuss the work so far on generation and characterization of iPSCs and focus on recent advances in the use of human iPSCs in clinical setting.

Notch/CXCR4 Partnership in Acute Lymphoblastic Leukemia Progression

Acute lymphoblastic leukemia (ALL) is the most common cancer among children. Recent advances in chemotherapy have made ALL a curable hematological malignancy. In children, there is 25% chance of disease relapse, typically in the central nervous system. While in adults, there is a higher chance of relapse. ALL may affect B-cell or T-cell lineages. Different genetic alterations characterize the two ALL forms. Deregulated Notch, either Notch1 or Notch3, and CXCR4 receptor signaling are involved in ALL disease development and progression. By analyzing their relevant roles in the pathogenesis of the two ALL forms, new molecular mechanisms able to modulate cancer cell invasion may be visualized. Notably, the partnership between Notch and CXCR4 may have considerable implications in understanding the complexity of T- and B-ALL. These two receptor pathways intersect other critical signals in the proliferative, differentiation, and metabolic programs of lymphocyte transformation. Also, the identification of the crosstalks in leukemia-stroma interaction within the tumor microenvironment may unveil new targetable mechanisms in disease relapse. Further studies are required to identify new challenges and opportunities to develop more selective and safer therapeutic strategies in ALL progression, possibly contributing to improve conventional hematological cancer therapy.

T cell acute lymphoblastic leukemia (T-ALL): New insights into the cellular origins and infiltration mechanisms common and unique among hematologic malignancies

T-cell acute lymphoblastic leukemia (T-ALL) accounts for 15% and 25% of total childhood and adult ALL cases, respectively. During T-ALL, patients are at risk of organ infiltration by leukemic T-cells. Infiltration is a major consequence of disease relapse and correlates with poor prognosis. Transendothelial migration of leukemic cells is required to exit the blood stream into target organs. While mechanisms of normal T-cell transmigration are well known, the mechanisms of leukemic T-cell extravasation remain elusive; but involvement of chemokines, integrins and Notch signaling play critical roles. Here, we summarize current knowledge about molecular mechanisms of leukemic T-cell infiltration with special emphasis on the newly identified subtype early T-cell-progenitor (ETP)-ALL. Furthermore, we compare the extravasation potential of T-ALL cells with that of other hematologic malignancies such as B-ALL and acute myeloid leukemia (AML).

Pro-inflammatory-Related Loss of CXCL12 Niche Promotes Acute Lymphoblastic Leukemic Progression at the Expense of Normal Lymphopoiesis

Pediatric oncology, notably childhood acute lymphoblastic leukemia (ALL), is currently one of the health-leading concerns worldwide and a biomedical priority. Decreasing overall leukemia mortality in children requires a comprehensive understanding of its pathobiology. It is becoming clear that malignant cell-to-niche intercommunication and microenvironmental signals that control early cell fate decisions are critical for tumor progression. We show here that the mesenchymal stromal cell component of ALL bone marrow (BM) differ from its normal counterpart in a number of functional properties and may have a key role during leukemic development. A decreased proliferation potential, contrasting with the strong ability of producing pro-inflammatory cytokines and an aberrantly loss of CXCL12 and SCF, suggest that leukemic lymphoid niches in ALL BM are unique and may exclude normal hematopoiesis. Cell competence ex vivo assays within tridimensional coculture structures indicated a growth advantage of leukemic precursor cells and their niche remodeling ability by CXCL12 reduction, resulting in leukemic cell progression at the expense of normal niche-associated lymphopoiesis.