RESUMEN
Hyperleukocytosis is an emergency of acute leukemia leading to blood hyperviscosity, potentially resulting in life-threatening microvascular obstruction, or leukostasis. Due to the high number of red cells in the circulation, hematocrit/hemoglobin levels (Hct/Hgb) are major drivers of blood viscosity, but how Hct/Hgb mediates hyperviscosity in acute leukemia remains unknown. In vivo hemorheological studies are difficult to conduct and interpret due to issues related to visualizing and manipulating the microvasculature. To that end, a multi-vessel microfluidic device recapitulating the size-scale and geometry of the microvasculature was designed to investigate how Hct/Hgb interacts with acute leukemia to induce "in vitro" leukostasis. Using patient samples and cell lines, the degree of leukostasis was different among leukemia immunophenotypes with respect to white blood cell (WBC) count and Hct/Hgb. Among lymphoid immunophenotypes, severe anemia is protective against in vitro leukostasis and Hct/Hgb thresholds became apparent above which in vitro leukostasis significantly increased, to a greater extent with B-cell acute lymphoblastic leukemia (ALL) versus T-cell ALL. In vitro leukostasis in acute myeloid leukemia was primarily driven by WBC with little interaction with Hct/Hgb. This sets the stage for prospective clinical studies assessing how red cell transfusion may affect leukostasis risk in immunophenotypically different acute leukemia patients.
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Viscosidad Sanguínea , Transfusión de Eritrocitos , Humanos , Microvasos , Leucostasis/etiología , Hematócrito , Leucemia Mieloide Aguda/terapia , Leucemia Mieloide Aguda/sangre , Femenino , Masculino , Hemoglobinas/análisisRESUMEN
Induced pluripotent stem cells (iPSCs) hold great promise in regenerative medicine; however, few algorithms of quality control at the earliest stages of differentiation have been established. Despite lipids having known functions in cell signaling, their role in pluripotency maintenance and lineage specification is underexplored. We investigated the changes in iPSC lipid profiles during the initial loss of pluripotency over the course of spontaneous differentiation using the co-registration of confocal microscopy and matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging. We identified phosphatidylethanolamine (PE) and phosphatidylinositol (PI) species that are highly informative of the temporal stage of differentiation and can reveal iPS cell lineage bifurcation occurring metabolically. Several PI species emerged from the machine learning analysis of MS data as the early metabolic markers of pluripotency loss, preceding changes in the pluripotency transcription factor Oct4. The manipulation of phospholipids via PI 3-kinase inhibition during differentiation manifested in the spatial reorganization of the iPS cell colony and elevated expression of NCAM-1. In addition, the continuous inhibition of phosphatidylethanolamine N-methyltransferase during differentiation resulted in the enhanced maintenance of pluripotency. Our machine learning analysis highlights the predictive power of lipidomic metrics for evaluating the early lineage specification in the initial stages of spontaneous iPSC differentiation.
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Células Madre Pluripotentes Inducidas , Humanos , Linaje de la Célula , Diferenciación Celular , Espectrometría de Masa por Láser de Matriz Asistida de Ionización Desorción , Transducción de SeñalRESUMEN
Human induced pluripotent stem cells (iPSCs) hold great promise for reducing the mortality of cardiovascular disease by cellular replacement of infarcted cardiomyocytes (CMs). CM differentiation via iPSCs is a lengthy multiweek process and is highly subject to batch-to-batch variability, presenting challenges in current cell manufacturing contexts. Real-time, label-free control quality attributes (CQAs) are required to ensure efficient iPSC-derived CM manufacturing. In this work, we report that live oxygen consumption rate measurements are highly predictive CQAs of CM differentiation outcome as early as the first 72 h of the differentiation protocol with an accuracy of 93%. Oxygen probes are already incorporated in commercial bioreactors, thus methods presented in this work are easily translatable to the manufacturing setting. Detecting deviations in the CM differentiation trajectory early in the protocol will save time and money for both manufacturers and patients, bringing iPSC-derived CM one step closer to clinical use.
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Células Madre Pluripotentes Inducidas , Humanos , Miocitos Cardíacos/metabolismo , Diferenciación Celular , Células Cultivadas , Consumo de OxígenoRESUMEN
A T cell clone is able to distinguish Ags in the form of peptide-MHC complexes with high specificity and sensitivity; however, how subtle differences in peptide-MHC structures translate to distinct T cell effector functions remains unknown. We hypothesized that mitochondrial positioning and associated calcium responses play an important role in T cell Ag recognition. We engineered a microfluidic system to precisely manipulate and synchronize a large number of cell-cell pairing events, which provided simultaneous real-time signaling imaging and organelle tracking with temporal precision. In addition, we developed image-derived metrics to quantify calcium response and mitochondria movement. Using myelin proteolipid altered peptide ligands and a hybridoma T cell line derived from a mouse model of experimental autoimmune encephalomyelitis, we observed that Ag potency modulates calcium response at the single-cell level. We further developed a partial least squares regression model, which highlighted mitochondrial positioning as a strong predictor of calcium response. The model revealed T cell mitochondria sharply alter direction within minutes following exposure to agonist peptide Ag, changing from accumulation at the immunological synapse to retrograde movement toward the distal end of the T cell body. By quantifying mitochondria movement as a highly dynamic process with rapidly changing phases, our result reconciles conflicting prior reports of mitochondria positioning during T cell Ag recognition. We envision applying this pipeline of methodology to study cell interactions between other immune cell types to reveal important signaling phenomenon that is inaccessible because of data-limited experimental design.
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Antígenos de Diferenciación de Linfocitos T/inmunología , Linfocitos T CD4-Positivos/inmunología , Calcio/metabolismo , Técnicas Analíticas Microfluídicas/métodos , Mitocondrias/metabolismo , Animales , Línea Celular Tumoral , Encefalomielitis Autoinmune Experimental/inmunología , Humanos , Hibridomas , Ratones , Transducción de Señal/inmunologíaRESUMEN
The complexity of morphogenesis poses a fundamental challenge to understanding the mechanisms governing the formation of biological patterns and structures. Over the past century, numerous processes have been identified as critically contributing to morphogenetic events, but the interplay between the various components and aspects of pattern formation have been much harder to grasp. The combination of traditional biology with mathematical and computational methods has had a profound effect on our current understanding of morphogenesis and led to significant insights and advancements in the field. In particular, the theoretical concepts of reaction-diffusion systems and positional information, proposed by Alan Turing and Lewis Wolpert, respectively, dramatically influenced our general view of morphogenesis, although typically in isolation from one another. In recent years, agent-based modeling has been emerging as a consolidation and implementation of the two theories within a single framework. Agent-based models (ABMs) are unique in their ability to integrate combinations of heterogeneous processes and investigate their respective dynamics, especially in the context of spatial phenomena. In this review, we highlight the benefits and technical challenges associated with ABMs as tools for examining morphogenetic events. These models display unparalleled flexibility for studying various morphogenetic phenomena at multiple levels and have the important advantage of informing future experimental work, including the targeted engineering of tissues and organs.
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Morfogénesis , Análisis de Sistemas , Apoptosis , Proliferación Celular , Modelos BiológicosRESUMEN
The side population (SP) assay, a technique used in cancer and stem cell research, assesses the activity of ABC transporters on Hoechst staining in the presence and absence of transporter inhibition, identifying SP and non-SP cell (NSP) subpopulations by differential staining intensity. The interpretation of the assay is complicated because the transporter-mediated mechanisms fail to account for cell-to-cell variability within a population or adequately control the direct role of transporter activity on staining intensity. We hypothesized that differences in dye kinetics at the single-cell level, such as ABCG2 transporter-mediated efflux and DNA binding, are responsible for the differential cell staining that demarcates SP/NSP identity. We report changes in A549 phenotype during time in culture and with TGFß treatment that correlate with SP size. Clonal expansion of individually sorted cells re-established both SP and NSPs, indicating that SP membership is dynamic. To assess the validity of a purely kinetics-based interpretation of SP/NSP identity, we developed a computational approach that simulated cell staining within a heterogeneous cell population; this exercise allowed for the direct inference of the role of transporter activity and inhibition on cell staining. Our simulated SP assay yielded appropriate SP responses for kinetic scenarios in which high transporter activity existed in a portion of the cells and little differential staining occurred in the majority of the population. With our approach for single-cell analysis, we observed SP and NSP cells at both ends of a transporter activity continuum, demonstrating that features of transporter activity as well as DNA content are determinants of SP/NSP identity.
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Transportador de Casetes de Unión a ATP, Subfamilia G, Miembro 2/metabolismo , Bioensayo/métodos , Citometría de Flujo/métodos , Microscopía Fluorescente/métodos , Proteínas de Neoplasias/metabolismo , Células de Población Lateral/citología , Células de Población Lateral/metabolismo , Cinética , Tasa de Depuración Metabólica , Modelos Biológicos , Células de Población Lateral/clasificaciónRESUMEN
Quantifying the magnitude and dynamics of protein oxidation during cell signaling is technically challenging. Computational modeling provides tractable, quantitative methods to test hypotheses of redox mechanisms that may be simultaneously operative during signal transduction. The interleukin-4 (IL-4) pathway, which has previously been reported to induce reactive oxygen species and oxidation of PTP1B, may be controlled by several other putative mechanisms of redox regulation; widespread proteomic thiol oxidation observed via 2D redox differential gel electrophoresis upon IL-4 treatment suggests more than one redox-sensitive protein implicated in this pathway. Through computational modeling and a model selection strategy that relied on characteristic STAT6 phosphorylation dynamics of IL-4 signaling, we identified reversible protein tyrosine phosphatase (PTP) oxidation as the primary redox regulatory mechanism in the pathway. A systems-level model of IL-4 signaling was developed that integrates synchronous pan-PTP oxidation with ROS-independent mechanisms. The model quantitatively predicts the dynamics of IL-4 signaling over a broad range of new redox conditions, offers novel hypotheses about regulation of JAK/STAT signaling, and provides a framework for interrogating putative mechanisms involving receptor-initiated oxidation.
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Interleucina-4/metabolismo , Transducción de Señal/fisiología , Biología de Sistemas/métodos , Algoritmos , Humanos , Células Jurkat , Modelos Biológicos , Oxidación-Reducción , Proteínas Tirosina FosfatasasRESUMEN
Pluripotent embryonic stem cells (ESCs) have the unique ability to differentiate into cells from all germ lineages, making them a potentially robust cell source for regenerative medicine therapies, but difficulties in predicting and controlling ESC differentiation currently limit the development of therapies and applications from such cells. A common approach to induce the differentiation of ESCs in vitro is via the formation of multicellular aggregates known as embryoid bodies (EBs), yet cell fate specification within EBs is generally considered an ill-defined and poorly controlled process. Thus, the objective of this study was to use rules-based cellular modeling to provide insight into which processes influence initial cell fate transitions in 3-dimensional microenvironments. Mouse embryonic stem cells (D3 cell line) were differentiated to examine the temporal and spatial patterns associated with loss of pluripotency as measured through Oct4 expression. Global properties of the multicellular aggregates were accurately recapitulated by a physics-based aggregation simulation when compared to experimentally measured physical parameters of EBs. Oct4 expression patterns were analyzed by confocal microscopy over time and compared to simulated trajectories of EB patterns. The simulations demonstrated that loss of Oct4 can be modeled as a binary process, and that associated patterns can be explained by a set of simple rules that combine baseline stochasticity with intercellular communication. Competing influences between Oct4+ and Oct4- neighbors result in the observed patterns of pluripotency loss within EBs, establishing the utility of rules-based modeling for hypothesis generation of underlying ESC differentiation processes. Importantly, the results indicate that the rules dominate the emergence of patterns independent of EB structure, size, or cell division. In combination with strategies to engineer cellular microenvironments, this type of modeling approach is a powerful tool to predict stem cell behavior under a number of culture conditions that emulate characteristics of 3D stem cell niches.
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Microambiente Celular/fisiología , Modelos Biológicos , Células Madre Pluripotentes/fisiología , Animales , Línea Celular , Biología Computacional/métodos , Simulación por Computador , Cuerpos Embrioides/citología , Cuerpos Embrioides/fisiología , Células Madre Embrionarias/citología , Células Madre Embrionarias/fisiología , Ratones , Células Madre Pluripotentes/citología , Transducción de SeñalRESUMEN
Bioelectric signals possess the ability to robustly control and manipulate patterning during embryogenesis and tissue-level regeneration. Endogenous local and global electric fields function as a spatial 'pre-pattern', controlling cell fates and tissue-scale anatomical boundaries; however, the mechanisms facilitating these robust multiscale outcomes are poorly characterized. Computational modeling addresses the need to predict in vitro patterning behavior and further elucidate the roles of cellular bioelectric signaling components in patterning outcomes. Here, we modified a previously designed image pattern recognition algorithm to distinguish unique spatial features of simulated non-excitable bioelectric patterns under distinct cell culture conditions. This algorithm was applied to comparisons between simulated patterns and experimental microscopy images of membrane potential (Vmem) across cultured human iPSC colonies. Furthermore, we extended the prediction to a novel co-culture condition in which cell sub-populations possessing different ionic fluxes were simulated; the defining spatial features were recapitulated in vitro with genetically modified colonies. These results collectively inform strategies for modeling multiscale spatial characteristics that emerge in multicellular systems, characterizing the molecular contributions to heterogeneity of membrane potential in non-excitable cells, and enabling downstream engineered bioelectrical tissue design.
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Células Madre Pluripotentes Inducidas , Potenciales de la Membrana , Humanos , Células Madre Pluripotentes Inducidas/citología , Células Madre Pluripotentes Inducidas/metabolismo , Potenciales de la Membrana/fisiología , Algoritmos , Simulación por Computador , Modelos Biológicos , Técnicas de CocultivoRESUMEN
Human brain organoids produce anatomically relevant cellular structures and recapitulate key aspects of in vivo brain function, which holds great potential to model neurological diseases and screen therapeutics. However, the long growth time of 3D systems complicates the culturing of brain organoids and results in heterogeneity across samples hampering their applications. We developed an integrated platform to enable robust and long-term culturing of 3D brain organoids. We designed a mesofluidic bioreactor device based on a reaction-diffusion scaling theory, which achieves robust media exchange for sufficient nutrient delivery in long-term culture. We integrated this device with longitudinal tracking and machine learning-based classification tools to enable non-invasive quality control of live organoids. This integrated platform allows for sample pre-selection for downstream molecular analysis. Transcriptome analyses of organoids revealed that our mesofluidic bioreactor promoted organoid development while reducing cell death. Our platform thus offers a generalizable tool to establish reproducible culture standards for 3D cellular systems for a variety of applications beyond brain organoids.
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Mesenchymal stem/stromal cell (MSC) therapies have had limited success so far in clinical trials due in part to heterogeneity in immune-responsive phenotypes. Therefore, techniques to characterize these properties of MSCs are needed during biomanufacturing. Imaging cell shape, or morphology, has been found to be associated with MSC immune responsivity-but a direct relationship between single-cell morphology and function has not been established. We used label-free differential phase contrast imaging and matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to evaluate single-cell morphology and explore relationships with lipid metabolic immune response. In interferon gamma (IFN-γ)-stimulated MSCs, we found higher lipid abundances from the ceramide-1-phosphate (C1P), phosphatidylcholine (PC), LysoPC, and triglyceride (TAG) families that are involved in cell immune function. Furthermore, we identified differences in lipid signatures in morphologically defined MSC subpopulations. The use of single-cell optical imaging coupled with single-cell spatial lipidomics could assist in optimizing the MSC production process and improve mechanistic understanding of manufacturing process effects on MSC immune activity and heterogeneity.
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OBJECTIVE: Inflammation plays a central role in atherosclerosis. However, the detailed changes in the composition and quantity of leukocytes in the arterial wall during atherogenesis are not fully understood in part because of the lack of suitable methods and animal models. METHODS AND RESULTS: We developed a 10-fluorochrome, 13-parameter flow cytometry method to quantitate 7 major leukocyte subsets in a single digested arterial wall sample. Apolipoprotein E-deficient mice underwent left carotid artery (LCA) partial ligation and were fed a high-fat diet for 4 to 28 days. Monocyte/macrophages, dendritic cells, granulocytes, natural killer cells, and CD4 T cells significantly infiltrated the LCA as early as 4 days. Monocyte/macrophages and dendritic cells decreased between 7 and 14 days, whereas T-cell numbers remained steady. Leukocyte numbers peaked at 7 days, preceding atheroma formation at 14 days. B cells entered LCA by 14 days. Control right carotid and sham-ligated LCAs showed no significant infiltrates. Polymerase chain reaction and ELISA arrays showed that expression of proinflammatory cytokines and chemokines peaked at 7 and 14 days postligation, respectively. CONCLUSION: This is the first quantitative description of leukocyte number and composition over the life span of murine atherosclerosis. These results show that disturbed flow induces rapid and dynamic leukocyte accumulation in the arterial wall during the initiation and progression of atherosclerosis.
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Arterias Carótidas/inmunología , Enfermedades de las Arterias Carótidas/inmunología , Citometría de Flujo , Inmunofenotipificación/métodos , Leucocitos/inmunología , Animales , Apolipoproteínas E/deficiencia , Apolipoproteínas E/genética , Arterias Carótidas/fisiopatología , Arterias Carótidas/cirugía , Enfermedades de las Arterias Carótidas/etiología , Enfermedades de las Arterias Carótidas/genética , Enfermedades de las Arterias Carótidas/fisiopatología , Quimiocinas/genética , Quimiocinas/metabolismo , Citocinas/genética , Citocinas/metabolismo , Dieta Alta en Grasa , Modelos Animales de Enfermedad , Progresión de la Enfermedad , Ensayo de Inmunoadsorción Enzimática , Técnica del Anticuerpo Fluorescente , Inmunidad Innata , Mediadores de Inflamación/metabolismo , Recuento de Leucocitos , Leucocitos/clasificación , Ligadura , Ratones , Ratones Noqueados , Reacción en Cadena de la Polimerasa , Flujo Sanguíneo Regional , Factores de TiempoRESUMEN
Adoptive T-cell transfer therapy relies upon in vitro expansion of autologous cytotoxic T cells that are capable of tumor recognition. The success of this cell-based therapy depends on the specificity and responsiveness of the T cell clones before transfer. During ex vivo expansion, CD8+ T cells present signs of replicative senescence and loss of function. The transfer of nonresponsive senescent T cells is a major bottleneck for the success of adoptive T-cell transfer therapy. Quantitative methods for assessing cellular age and responsiveness will facilitate the development of appropriate cell expansion and selection protocols. Although several biomarkers of lymphocyte senescence have been identified, these proteins in isolation are not sufficient to determine the age-dependent responsiveness of T cells. We have developed a multivariate model capable of extracting combinations of markers that are the most informative to predict cellular age. To acquire signaling information with high temporal resolution, we designed a microfluidic chip enabling parallel lysis and fixation of stimulated cell samples on-chip. The acquisition of 25 static biomarkers and 48 dynamic signaling measurements at different days in culture, integrating single-cell and population based information, allowed the multivariate regression model to accurately predict CD8+ T-cell age. From surface marker expression and early phosphorylation events following T-cell receptor stimulation, the model successfully predicts days in culture and number of population doublings with R2=0.91 and 0.98, respectively. Furthermore, we found that impairment of early signaling events following T cell receptor stimulation because of long term culture allows prediction of costimulatory molecules CD28 and CD27 expression levels and the number of population divisions in culture from a limited subset of signaling proteins. The multivariate analysis highlights the information content of both averaged biomarker values and heterogeneity metrics for prediction of cellular age within a T cell population.
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Biomarcadores/metabolismo , Senescencia Celular , Linfocitos T Citotóxicos/citología , Linfocitos T Citotóxicos/metabolismo , Adulto , Antígenos CD28/metabolismo , Complejo CD3/metabolismo , Membrana Celular/efectos de los fármacos , Membrana Celular/metabolismo , Proliferación Celular/efectos de los fármacos , Forma de la Célula/efectos de los fármacos , Células Cultivadas , Senescencia Celular/efectos de los fármacos , Bases de Datos de Proteínas , Quinasas MAP Reguladas por Señal Extracelular/metabolismo , Citometría de Flujo , Humanos , Interleucina-2/farmacología , Activación de Linfocitos/efectos de los fármacos , Microfluídica , Análisis Multivariante , Fosforilación/efectos de los fármacos , Receptores de Antígenos de Linfocitos T/metabolismo , Transducción de Señal/efectos de los fármacos , Linfocitos T Citotóxicos/efectos de los fármacos , Linfocitos T Citotóxicos/enzimología , Factores de Tiempo , Adulto JovenRESUMEN
Head and neck squamous cell carcinoma (HNSCC) cells are highly heterogeneous in their metabolism and typically experience elevated reactive oxygen species (ROS) levels such as superoxide and hydrogen peroxide (H2O2) in the tumor microenvironment. Tumor cells survive under these chronic oxidative conditions by upregulating antioxidant systems. To investigate the heterogeneity of cellular responses to chemotherapeutic H2O2 generation in tumor and healthy tissue, we leveraged single-cell RNA-sequencing (scRNA-seq) data to perform redox systems-level simulations of quinone-cycling ß-lapachone treatment as a source of NQO1-dependent rapid superoxide and hydrogen peroxide (H2O2) production. Transcriptomic data from 10 HNSCC patient tumors was used to populate over 4000 single-cell antioxidant enzymatic network models of drug metabolism. The simulations reflected significant systems-level differences between the redox states of healthy and cancer cells, demonstrating in some patient samples a targetable cancer cell population or in others statistically indistinguishable effects between non-malignant and malignant cells. Subsequent multivariate analyses between healthy and malignant cellular models pointed to distinct contributors of redox responses between these phenotypes. This model framework provides a mechanistic basis for explaining mixed outcomes of NAD(P)H:quinone oxidoreductase 1 (NQO1)-bioactivatable therapeutics despite the tumor specificity of these drugs as defined by NQO1/catalase expression and highlights the role of alternate antioxidant components in dictating drug-induced oxidative stress.
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During development, cells undergo symmetry breaking into differentiated subpopulations that self-organize into complex structures.1,2,3,4,5 However, few tools exist to recapitulate these behaviors in a controllable and coupled manner.6,7,8,9 Here, we engineer a stochastic recombinase genetic switch tunable by small molecules to induce programmable symmetry breaking, commitment to downstream cell fates, and morphological self-organization. Inducers determine commitment probabilities, generating tunable subpopulations as a function of inducer dosage. We use this switch to control the cell-cell adhesion properties of cells committed to each fate.10,11 We generate a wide variety of 3D morphologies from a monoclonal population and develop a computational model showing high concordance with experimental results, yielding new quantitative insights into the relationship between cell-cell adhesion strengths and downstream morphologies. We expect that programmable symmetry breaking, generating precise and tunable subpopulation ratios and coupled to structure formation, will serve as an integral component of the toolbox for complex tissue and organoid engineering.
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Ingeniería , Organoides , Adhesión Celular , Diferenciación Celular , ProbabilidadRESUMEN
While microscopy-based cellular assays, including microfluidics, have significantly advanced over the last several decades, there has not been concurrent development of widely-accessible techniques to analyze time-dependent microscopy data incorporating phenomena such as fluid flow and dynamic cell adhesion. As such, experimentalists typically rely on error-prone and time-consuming manual analysis, resulting in lost resolution and missed opportunities for innovative metrics. We present a user-adaptable toolkit packaged into the open-source, standalone Interactive Cellular assay Labeled Observation and Tracking Software (iCLOTS). We benchmark cell adhesion, single-cell tracking, velocity profile, and multiscale microfluidic-centric applications with blood samples, the prototypical biofluid specimen. Moreover, machine learning algorithms characterize previously imperceptible data groupings from numerical outputs. Free to download/use, iCLOTS addresses a need for a field stymied by a lack of analytical tools for innovative, physiologically-relevant assays of any design, democratizing use of well-validated algorithms for all end-user biomedical researchers who would benefit from advanced computational methods.
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Inteligencia Artificial , Microfluídica , Microscopía , Programas Informáticos , Células SanguíneasRESUMEN
Advances in multiagent chemotherapy have led to recent improvements in survival for patients with acute lymphoblastic leukemia (ALL); however, a significant fraction do not respond to frontline chemotherapy or later relapse with recurrent disease, after which long-term survival rates remain low. To develop new, effective treatment options for these patients, we conducted a series of high-throughput combination drug screens to identify chemotherapies that synergize in a lineage-specific manner with MRX-2843, a small molecule dual MERTK and FLT3 kinase inhibitor currently in clinical testing for treatment of relapsed/refractory leukemias and solid tumors. Using experimental and computational approaches, we found that MRX-2843 synergized strongly-and in a ratio-dependent manner-with vincristine to inhibit both B-ALL and T-ALL cell line expansion. Based on these findings, we developed multiagent lipid nanoparticle formulations of these drugs that not only delivered defined drug ratios intracellularly in T-ALL, but also improved anti-leukemia activity following drug encapsulation. Synergistic and additive interactions were recapitulated in primary T-ALL patient samples treated with MRX-2843 and vincristine nanoparticle formulations, suggesting their clinical relevance. Moreover, the nanoparticle formulations reduced disease burden and prolonged survival in an orthotopic murine xenograft model of early thymic precursor T-ALL (ETP-ALL), with both agents contributing to therapeutic activity in a dose-dependent manner. In contrast, nanoparticles containing MRX-2843 alone were ineffective in this model. Thus, MRX-2843 increased the sensitivity of ETP-ALL cells to vincristine in vivo. In this context, the additive particles, containing a higher dose of MRX-2843, provided more effective disease control than the synergistic particles. In contrast, particles containing an even higher, antagonistic ratio of MRX-2843 and vincristine were less effective. Thus, both the drug dose and the ratio-dependent interaction between MRX-2843 and vincristine significantly impacted therapeutic activity in vivo. Together, these findings present a systematic approach to high-throughput combination drug screening and multiagent drug delivery that maximizes the therapeutic potential of combined MRX-2843 and vincristine in T-ALL and describe a novel translational agent that could be used to enhance therapeutic responses to vincristine in patients with T-ALL. This broadly generalizable approach could also be applied to develop other constitutively synergistic combination products for the treatment of cancer and other diseases.
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Leucemia de Células T , Leucemia-Linfoma Linfoblástico de Células Precursoras , Leucemia-Linfoma Linfoblástico de Células T Precursoras , Humanos , Animales , Ratones , Vincristina/uso terapéutico , Leucemia-Linfoma Linfoblástico de Células T Precursoras/tratamiento farmacológico , Leucemia-Linfoma Linfoblástico de Células Precursoras/tratamiento farmacológico , Leucemia-Linfoma Linfoblástico de Células Precursoras/patología , Leucemia de Células T/tratamiento farmacológico , Ciclo Celular , Inhibidores de Proteínas Quinasas/farmacología , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéuticoRESUMEN
The obesity pandemic currently affects more than 70 million Americans and more than 650 million individuals worldwide. In addition to increasing susceptibility to pathogenic infections (eg, SARS-CoV-2), obesity promotes the development of many cancer subtypes and increases mortality rates in most cases. We and others have demonstrated that, in the context of B-cell acute lymphoblastic leukemia (B-ALL), adipocytes promote multidrug chemoresistance. Furthermore, others have demonstrated that B-ALL cells exposed to the adipocyte secretome alter their metabolic states to circumvent chemotherapy-mediated cytotoxicity. To better understand how adipocytes impact the function of human B-ALL cells, we used a multi-omic RNA-sequencing (single-cell and bulk transcriptomic) and mass spectroscopy (metabolomic and proteomic) approaches to define adipocyte-induced changes in normal and malignant B cells. These analyses revealed that the adipocyte secretome directly modulates programs in human B-ALL cells associated with metabolism, protection from oxidative stress, increased survival, B-cell development, and drivers of chemoresistance. Single-cell RNA sequencing analysis of mice on low- and high-fat diets revealed that obesity suppresses an immunologically active B-cell subpopulation and that the loss of this transcriptomic signature in patients with B-ALL is associated with poor survival outcomes. Analyses of sera and plasma samples from healthy donors and those with B-ALL revealed that obesity is associated with higher circulating levels of immunoglobulin-associated proteins, which support observations in obese mice of altered immunological homeostasis. In all, our multi-omics approach increases our understanding of pathways that may promote chemoresistance in human B-ALL and highlight a novel B-cell-specific signature in patients associated with survival outcomes.
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COVID-19 , Leucemia-Linfoma Linfoblástico de Células Precursoras , Humanos , Animales , Ratones , Proteómica , SARS-CoV-2 , Obesidad/complicaciones , Obesidad/metabolismoRESUMEN
There is an evolutionary advantage in having multiple components with overlapping functionality (i.e degeneracy) in organisms. While theoretical considerations of degeneracy have been well established in neural networks using information theory, the same concepts have not been developed for differential systems, which form the basis of many biochemical reaction network descriptions in systems biology. Here we establish mathematical definitions of degeneracy, complexity and robustness that allow for the quantification of these properties in a system. By exciting a dynamical system with noise, the mutual information associated with a selected observable output and the interacting subspaces of input components can be used to define both complexity and degeneracy. The calculation of degeneracy in a biological network is a useful metric for evaluating features such as the sensitivity of a biological network to environmental evolutionary pressure. Using a two-receptor signal transduction network, we find that redundant components will not yield high degeneracy whereas compensatory mechanisms established by pathway crosstalk will. This form of analysis permits interrogation of large-scale differential systems for non-identical, functionally equivalent features that have evolved to maintain homeostasis during disruption of individual components.
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Modelos Biológicos , Biología de Sistemas/métodos , Algoritmos , Animales , Evolución Biológica , Homeostasis/genética , Homeostasis/fisiología , Transducción de Señal/genética , Transducción de Señal/fisiologíaRESUMEN
Although doxorubicin toxicity in cancer cells is multifactorial, the enzymatic bioactivation of the drug can significantly contribute to its cytotoxicity. Previous research has identified most of the components that comprise the doxorubicin bioactivation network; however, adaptation of the network to changes in doxorubicin treatment or to patient-specific changes in network components is much less understood. To investigate the properties of the coupled reduction/oxidation reactions of the doxorubicin bioactivation network, we analyzed metabolic differences between two patient-derived acute lymphoblastic leukemia (ALL) cell lines exhibiting varied doxorubicin sensitivities. We developed computational models that accurately predicted doxorubicin bioactivation in both ALL cell lines at high and low doxorubicin concentrations. Oxygen-dependent redox cycling promoted superoxide accumulation while NADPH-dependent reductive conversion promoted semiquinone doxorubicin. This fundamental switch in control is observed between doxorubicin sensitive and insensitive ALL cells and between high and low doxorubicin concentrations. We demonstrate that pharmacological intervention strategies can be employed to either enhance or impede doxorubicin cytotoxicity in ALL cells due to the switching that occurs between oxygen-dependent superoxide generation and NADPH-dependent doxorubicin semiquinone formation.