Acute lymphoblastic leukemia-secreted miRNAs induce a proinflammatory microenvironment and promote the activation of hematopoietic progenitors.

Leukemogenesis is proposed to result from the continuous interplay between inducive bone marrow (BM) microenvironments and malignant precursor cells. Recent findings point toward an abnormal production of proinflammatory mediators within the BM from acute lymphoblastic leukemia (ALL) patients, although the mechanism underlying this phenomenon is uncertain. Here, we have identified 3 miRNAs, miR-146a-5p, miR-181b-5p, and miR-199b-3p, as potential candidates for TLR8 ligation, which are overexpressed in ALL and show agonist functional binding. When purified from ALL exosomes, they demonstrated their capacity of inducing cytokine production by both, hematopoietic and stromal BM cells. Of note, the exposure of BM cells from ALL patients to the proinflammatory milieu resulting from these miRNAs agonist activity revealed the proliferation of normal progenitors, while poor effects were recorded in the leukemic counterpart. The unconventional roles of the tumor-secreted miRNAs as TLR8 agonist ligands may provide a novel mechanism contributing a tumor-microenvironment feedback loop by switching on proinflammatory pathways that further activate normal hematopoietic precursors and support ALL progression. Secreted B-ALL TLR8-agonist miRNAs are involved in the promotion of proinflammatory microenvironments that target normal hematopoietic cells. B-lineage ALL cells secrete exosomes containing miRNAs endowed with the ability of functionally binding TLR8 in hematopoietic and BM mesenchymal stromal cells. Upon TLR8 signaling, the activation of the NF-kB pathway induces secretion of proinflammatory cytokines that, in turn, promotes cell proliferation in early hematopoietic cell populations, driving a tumor-microenvironment-hematopoietic activation feedback loop that may reduce the normal hematopoietic stem and progenitor cell compartment and facilitate cancer progression.

Screening Diabetic Retinopathy Using an Automated Retinal Image Analysis System in Independent and Assistive Use Cases in Mexico: Randomized Controlled Trial.

BACKGROUND: The automated screening of patients at risk of developing diabetic retinopathy represents an opportunity to improve their midterm outcome and lower the public expenditure associated with direct and indirect costs of common sight-threatening complications of diabetes. OBJECTIVE: This study aimed to develop and evaluate the performance of an automated deep learning-based system to classify retinal fundus images as referable and nonreferable diabetic retinopathy cases, from international and Mexican patients. In particular, we aimed to evaluate the performance of the automated retina image analysis (ARIA) system under an independent scheme (ie, only ARIA screening) and 2 assistive schemes (ie, hybrid ARIA plus ophthalmologist screening), using a web-based platform for remote image analysis to determine and compare the sensibility and specificity of the 3 schemes. METHODS: A randomized controlled experiment was performed where 17 ophthalmologists were asked to classify a series of retinal fundus images under 3 different conditions. The conditions were to (1) screen the fundus image by themselves (solo); (2) screen the fundus image after exposure to the retina image classification of the ARIA system (ARIA answer); and (3) screen the fundus image after exposure to the classification of the ARIA system, as well as its level of confidence and an attention map highlighting the most important areas of interest in the image according to the ARIA system (ARIA explanation). The ophthalmologists' classification in each condition and the result from the ARIA system were compared against a gold standard generated by consulting and aggregating the opinion of 3 retina specialists for each fundus image. RESULTS: The ARIA system was able to classify referable vs nonreferable cases with an area under the receiver operating characteristic curve of 98%, a sensitivity of 95.1%, and a specificity of 91.5% for international patient cases. There was an area under the receiver operating characteristic curve of 98.3%, a sensitivity of 95.2%, and a specificity of 90% for Mexican patient cases. The ARIA system performance was more successful than the average performance of the 17 ophthalmologists enrolled in the study. Additionally, the results suggest that the ARIA system can be useful as an assistive tool, as sensitivity was significantly higher in the experimental condition where ophthalmologists were exposed to the ARIA system's answer prior to their own classification (93.3%), compared with the sensitivity of the condition where participants assessed the images independently (87.3%; P=.05). CONCLUSIONS: These results demonstrate that both independent and assistive use cases of the ARIA system present, for Latin American countries such as Mexico, a substantial opportunity toward expanding the monitoring capacity for the early detection of diabetes-related blindness.

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 CXCR7hi 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.

An In Vitro Model of Mast Cell Recruitment and Activation by Breast Cancer Cells Supports Anti-Tumoral Responses.

Breast cancer (BrC) affects millions of women yearly. Mast cells (MCs) are common components of breast tumors with documented agonistic and antagonistic roles in tumor progression. Understanding the participation of MCs in BrC may lead to new therapies to control tumor growth. In this study, we looked into mechanistic models of MC responses triggered by BrC cells (BrCC), assessing both early degranulation and late transcriptional activities. We used aggressive and non-aggressive BrCC to model the progressive staging of the disease over HMC1 and LAD-2 human MC lines. We found that both MC lines were chemoattracted by all BrCC, but their activation was preferentially induced by aggressive lines, finding differences in their active transcriptional programs, both at basal level and after stimulation. Among those genes with altered expression were down-regulated SPP1, PDCD1, IL17A and TGFB1 and up-regulated KITLG and IFNG. A low expression of SPP1 and a high expression of KITLG and IFNG were associated with increased overall survival of BrC patients from public databases. The set of altered genes is more often associated with tumor stromas enriched with anti-tumoral signals, suggesting that MCs may participate in tumor control.

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.

An NFκB-dependent mechanism of tumor cell plasticity and lateral transmission of aggressive features.

Breast cancer is a complex disease exhibiting extensive inter- and intra-tumor heterogeneity. Inflammation is a well-known driver of cancer progression, often attributed to immune cells infiltrating the tumor stroma. However, tumor cells themselves are capable to secrete a variety of inflammatory molecules, of which we understand very little about their role in intra-clonal communication. We recently reported the capacity of triple negative cell lines to induce a cancer stem cell (CSC)-like phenotype and invasion properties into luminal cells, a mechanism mediated by pro-inflammatory cytokines that up-regulated the CXCL12/CXCR4/CXCR7 chemokine signaling axis. We performed transcriptional array analyses of CSCs-associated genes and cancer-inflammatory cell crosstalk genes and built regulatory networks with the data collected. We found a specific molecular signature segregating with the induced-invasive/stemness phenotype. Regulatory network analysis pointed out to an NFκB transcriptional signature, active in aggressive triple negative cells and in induced-invasive/CSC-like luminal cells. In agreement, NFκB inhibition abolished the induction of the stemness/invasive features. These data support an NFκB dependent mechanism of intra-clonal communication responsible for tumor cell plasticity leading the acquisition of cancer aggressive features. Understanding the communication between different tumor clones would help to find better therapeutic and prophylactic targets to prevent BrC progression and relapse.

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

Lineage fate decisions of hematopoietic cells depend on intrinsic factors and extrinsic signals provided by the bone marrow microenvironment, where they reside. Abnormalities in composition and function of hematopoietic niches have been proposed as key contributors of acute lymphoblastic leukemia (ALL) progression. Our previous experimental findings strongly suggest that pro-inflammatory cues contribute to mesenchymal niche abnormalities that result in maintenance of ALL precursor cells at the expense of normal hematopoiesis. Here, we propose a molecular regulatory network interconnecting the major communication pathways between hematopoietic stem and progenitor cells (HSPCs) and mesenchymal stromal cells (MSCs) within the BM. Dynamical analysis of the network as a Boolean model reveals two stationary states that can be interpreted as the intercellular contact status. Furthermore, simulations describe the molecular patterns observed during experimental proliferation and activation. Importantly, our model predicts instability in the CXCR4/CXCL12 and VLA4/VCAM1 interactions following microenvironmental perturbation due by temporal signaling from Toll like receptors (TLRs) ligation. Therefore, aberrant expression of NF-κB induced by intrinsic or extrinsic factors may contribute to create a tumor microenvironment where a negative feedback loop inhibiting CXCR4/CXCL12 and VLA4/VCAM1 cellular communication axes allows for the maintenance of malignant cells.

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.