Biology subjects

Glauche, I.

Publications and source records attributed to Glauche, I..

16 recordsLinked to original sources

bioRxiv2026

Leukemic fitness predicts treatment-free remission and guides adaptive therapy in chronic myeloid leukemia

Chronic myeloid leukemia is controlled by tyrosine kinase inhibitors, yet only about half of well-responding patients who stop therapy remain in long-term remission, and currently it cannot be predicted who will relapse. Mechanistic models reproduce both outcomes but rely on many parameters and longitudinal immune measurements, limiting clinical use. Here we derive a minimal two-equation model in which the immune compartment is eliminated by a quasi-steady-state argument and retained implicitly as a tumor load-dependent kill rate. This reduction lowers the parameter count from fourteen to eight, requires no direct immune measurements, and preserves the two key features of immune-leukemia interaction: a switch-like per-capita kill rate and a bell-shaped immune window peaking at deep remission. A complete analytical treatment shows that a patient's long-term outcome depends on a single quantity, the leukemic fitness, defined as the ratio of leukemic proliferation to maximal immune-mediated killing. Values above one render the cure steady state unstable, whereas values below one make it stable and therefore attainable; the rate-limiting step is depletion of the quiescent stem cell reservoir below a separatrix, reproducing the clinical link between treatment duration and remission level with durable remission after cessation. Fitted to 75 patients of the DESTINY trial, the minimal model matches the fit quality of its more detailed predecessors. Leukemic fitness estimated from time courses up to treatment cessation, including the dose-reduction period, is associated with outcome, with discrimination improving further when six months of post-cessation data are added. Guided by this single parameter, we design two personalized strategies: extended full-dose therapy for low-fitness patients who have not yet crossed the separatrix, and maintenance dosing for high-fitness patients. Leukemic fitness is thus a clinical predictor that can be estimated from routine monitoring data, and a minimally parametrized model is enough to turn patient trajectories into personalized treatment decisions.

systems biology↗

bioRxiv2025

Long-term clonal analysis using stochastic models reveals heterogeneity and quiescence of hematopoietic stem cells

Hematopoietic stem cells (HSCs) maintain lifelong production of blood by balancing self-renewal and differentiation. However, certain aspects of their divisional dynamics, namely the role of quiescence and the intrinsic heterogeneity of the HSC pool, are not completely understood. High-resolution clonal tracking provides a powerful resource to investigate such dynamics as the data captures patterns of clonal persistence, dilution and late clonal emergence. Here, we apply mechanistic mathematical modeling to longitudinal clonal data from non-human primates to explore structural requirements that underlie the observed dynamical patterns. We show that models treating HSCs as a single, homogeneous population can explain the gradual loss of clonal diversity, but fail to reproduce clone size distributions and the long-term persistence of small and late-appearing clones. To address this, we propose a stochastic, two-compartment model in which HSCs transition reversibly between an actively cycling state and a quiescent, potentially niche-bound state. Compared to the simpler one-compartment model, this advanced framework provides a substantially improved fit for different metrics, consistently captures clone size distributions and explains the delayed activation and sustained coexistence of small and large clones. These results provide quantitative evidence that heterogeneity within the HSC pool, particularly the existence of a reversible quiescent state, is critical to account for clonal aspects of long-term hematopoiesis. Our findings highlight how clonal data can uncover underlying regulatory mechanisms and supports a central role for niche-mediated HSC quiescence in maintaining stable and diverse blood production over time. HighlightsO_LIClonal data offers a robust approach to explore hematopoietic stem cell dynamics C_LIO_LIHomogeneous HSC population cannot reproduce observed long-term clonal patterns C_LIO_LINiche-mediated quiescence improves model fit across different clonality metrics C_LIO_LIModel results suggest reversible transition between HSC quiescence and activation C_LI

bioinformatics↗

bioRxiv2024

Predicting treatment-free remission outcomes in Chronic Myeloid Leukemia patients using an integrated model of tumor-immune dynamics

The interactions between tumor and the immune system are main factors in determining cancer treatment outcomes. In Chronic Myeloid Leukemia (CML), considerable evidence shows that the dynamics between residual leukemia and the patients immune system can result in either sustained disease control, leading to treatment-free remission (TFR), or disease recurrence. The question remains how to integrate mechanistic and data-driven models to support prediction of treatment outcomes. Starting from classical ecological modeling concepts, which allow to explicitly account for immune interactions at the cellular level, we incorporate time-course data on natural killer (NK) cell number, function, and their tumor-induced suppression into our general model of CML treatment. We identify relevant time scales governing treatment and immune response, enabling refined model calibration using tumor and NK cell time courses from different datasets. While the model successfully describes patient-specific response dynamics, critical parameters for predicting treatment outcome remain uncertain. However, by explicitly incorporating tumor load changes in response to TKI dose alterations, these parameters can be estimated and used to derive model predictions for treatment cessation. Further exploring dynamic changes in the number of functional immune cells, we suggest specific measurement strategies of immune effector cell populations to enhance prediction accuracy for CML recurrence following treatment cessation. The generalizability and flexibility of our approach represent a significant step towards quantitative, personalized medicine that integrates tumor-immune dynamics to guide clinical decisions and optimize dynamic cancer therapies.

systems biology↗

bioRxiv2024

Mathematical modeling unveils the timeline of CAR-T cell therapy and macrophage-mediated cytokine release syndrome

Chimeric antigen receptor (CAR)-T cell therapy holds significant potential for cancer treatment, although disease relapse and cytokine release syndrome (CRS) remain as frequent clinical challenges. To better understand the mechanisms underlying the temporal dynamics of CAR-T cell therapy response and CRS, we developed a novel multi-layer mathematical model incorporating antigen-mediated CAR-T cell expansion, antigen-negative resistance, and macrophage-associated cytokine release. Three key mechanisms of macrophage activation are considered: release of damage-associated molecular patterns, antigen-binding mediated activation, and CD40-CD40L contact. The model accurately describes 25 patient time courses with different responses and IL-6 cytokine kinetics. We successfully link the dynamic shape of the response to interpretable model parameters and investigate the influence of CAR-T cell dose and initial tumor burden on the occurrence of CRS and treatment outcome. By disentangling the timeline of macrophage activation, the model identified distinct contributions of each activation mechanism, suggesting the CD40-CD40L axis as a major driver of CRS and a clinically feasible target to control the activation process and modulate cytokine peak height. Our multi-layer model provides a comprehensive framework for understanding the complex interactions between CAR-T cells, tumor cells, and macrophages during therapy.

systems biology↗

bioRxiv2022

A ROS-dependent mechanism to drive progression through S phase

Long considered as cytotoxic reagents, reactive oxygen species (ROS) at the right concentration promote cell proliferation in cell culture, stem cells and model organisms. However, how ROS signaling is coordinated with cell cycle progression and integrated into the cell cycle control machinery on the molecular level remains unsolved. Here, we report oscillations of mitochondrial ROS during the cell cycle that target cyclin-dependent kinase 2 (CDK2). Chemical and metabolic interference with ROS production decrease T-loop phosphorylation on CDK2, impeding its full activation and thus efficient DNA replication. ROS regulate CDK2 activity through oxidation of a conserved cysteine residue in close proximity to the T-loop, which prevents binding of the T-loop phosphatase KAP. Together our data reveal how ROS couple mitochondrial metabolism to DNA replication and cell cycle progression, and provide a solution to the longstanding conundrum of how KAP activity towards CDKs can be cell cycle-regulated.

cell biology↗

bioRxiv2021

Clonal reconstruction from co-occurrence of vector integration sites allows accurate quantification of expanding clones in vivo

High transduction rates of viral vectors in gene therapies (GT) and experimental hematopoiesis ensure a high frequency of gene delivery, although multiple integration events can occur in the same cell. Therefore, tracing of integration sites (IS) leads to misquantification of the true clonal spectrum and limits safety considerations in GT. Hence, we use correlations between repeated measurements of IS abundances to estimate their mutual similarity and identify clusters of co-occurring IS, for which we assume a clonal origin. We evaluate the performance, robustness and specificity of our methodology using clonal simulations. The reconstruction methods, implemented and provided as an R-package, are further applied to experimental clonal mixes and to a preclinical model of hematopoietic GT. Our results demonstrate that clonal reconstruction from IS data allows to overcome systematic biases in the clonal quantification as an essential prerequisite for the assessment of safety and long-term efficacy of GT involving integrative vectors.

cancer biology↗

bioRxiv2020

Age-independent influence of hematopoietic stem and progenitor cell populations during hematopoietic reconstitution

Hematopoietic stem cell transplantation (HSCT) following myeloablative conditioning represents the only curative treatment option to overcome numerous hematologic malignancies. Despite the overall clinical success to achieve reconstitution of the blood system in many patients, the length of the aplastic phase until recovery response remains a critical parameter for patient survival. Fatal infections are the major risk factor for immunocompromised individuals and in many cases lead to transplant related morbidity and mortality. Therefore, we hypothesized that transplants from young donors might be beneficial for the spatiotemporal blood reconstitution in comparison to old grafts. Here we report on our multicolor-coded barcode system (BC32) to track hematopoietic stem and progenitor cell (HSPC) populations in a murine model of HSCT. By using different experimental settings of young and aged donor and recipient animals we compared the influence of age on graft composition, leukocyte recovery and more precisely, the contribution of individual HSPC subpopulations to the process. We show that blood reconstitution is substantially driven and maintained by HSCs and MPPs, while the latter accounted for higher output rates than HSCs, confirmed by FACS and NGS analyses. Reconstitution patterns were highly polyclonal and stable in all animals aside from variability between individual animals. This leads to the conclusion that HSPCs home, engraft and differentiate independently of donor and recipient age in our experimental conditions. Our findings add to ongoing efforts to expand the application of HSCT in older individuals while minimizing therapy related risks resulting from intensive myeloablative conditioning or incomplete blood reconstitution.

cell biology↗

bioRxiv2020

Mathematical modelling of megakaryopoiesis in Mpl-deficient and continuously thrombopoietin-stimulated mice points to an unknown control mechanism

Thrombopoietin (TPO) is the ligand of the Mpl receptor and the key regulator of megakaryopoiesis and platelet production. A loss or gain of the TPO-receptor function affects haematopoiesis and results in severe diseases in humans. Appropriate mouse strains are available to mimic both myeloproliferative neoplasm (MPN) and congenital amegakaryocytic thrombocytopenia (CAMT) resulting from TPO overexpression or knockout of TPO receptor Mpl on megakaryocytes and platelets, respectively. However, at a quantitative level it is not understood, how the known regulations can establish the impaired but stable disease phenotypes. Starting out from an established mathematical model for megakaryopoiesis, we aim to adapt it to both the healthy situation and to distinct diseased phenotypes mimicking MPN. We thereby identify, that some of the model parameters are invariant with respect to the mouse strain while others have to be estimated in a strain-dependent manner. A systematic process of parameter identification provides strong evidence that the well-known excess production of megakaryocytes and early progenitors in MPN is either directly contingent on Mpl expression of platelets and megakaryocytes or, alternatively, that the knockout of Mpl is not as precisely restricted to megakaryocytes and platelets but may also effect their progenitors. In conclusion, our analysis hints towards an opaque control mechanism rendering megakaryopoiesis at a yet unknown level, and awaiting further experimental evaluation.

systems biology↗

bioRxiv2020

TraCurate: efficiently curating cell tracks

TraCurate is an open-source software tool to curate and manually annotate cell tracking data from time-lapse microscopy. Although many studies of cellular behavior require high-quality, long-term observations across generations of cells, automated cell tracking is often imperfect and typically yields fragmented results that still contain many errors. TraCurate provides the functionality for the curation and correction of cell tracking data with minimal user interaction and expenditure of time and supports the extraction of complete cell tracks and cellular genealogies from experimental data. Source code and binary packages for Linux, macOS and Windows are available at https://tracurate.gitlab.io/, as well as all other complementary tools described herein.

bioinformatics↗

bioRxiv2020

UFMylation regulates translational homeostasis and cell cycle progression

UFMylation, the posttranslational modification of proteins with ubiquitin fold modifier 1 (UFM1) is essential for metazoan life and is associated with multiple human diseases. Although UFMylation has been linked to endoplasmic reticulum (ER) stress, its biological functions and relevant cellular targets beyond the ER are obscure. Here, we show that UFMylation directly controls translation and cell division in a manner otherwise known for cellular homeostasis-sensing pathways such as mTOR. By combining cell cycle analyses, mass spectrometry and ribosome profiling we demonstrate that UFMylation is required for eIF4F translation initiation complex assembly and recruitment of the ribosome. Interference with UFMylation shuts down global translation, which is sensed by cyclin D1 and halts the cell cycle independently of integrated stress response signalling. Our findings establish UFMylation as a key regulator of translation and uncover a pathway that couples translational homeostasis to cell cycle progression via a ubiquitin-like modification.

cell biology↗

bioRxiv2019

Proliferative behavior of hematopoietic stem cells revisited: No evidence for mitotic memory

The proliferative activity of adult hematopoietic stem cells (HSCs) is controversially discussed. Inducible fluorescent histone 2B fusion protein (H2B-FP) transgenic mice are important tools for tracking the mitotic history of murine HSCs in label dilution experiments. A recent study proposed that the most primitive HSCs divide only four times, to then enter permanent quiescence. We observed that background fluorescence due to leaky H2B-FP expression, occurring in all H2B-FP transgenes independent of label induction, accumulated with age in primitive HSCs with high repopulation potential. We argue that this background had been misinterpreted as retention of induced label and permanent quiescence. We found cell division-independent half-lives of H2B-FPs to be short, which had led to overestimation of HSC divisional activity. Our data do not support HSC mitotic memory and entry into permanent quiescence after few divisions, but show that primitive HSCs of adult mice continue to cycle rarely.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC=\"FIGDIR/small/745729v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (30K):\norg.highwire.dtl.DTLVardef@1b97626org.highwire.dtl.DTLVardef@fbc702org.highwire.dtl.DTLVardef@1c66b60org.highwire.dtl.DTLVardef@1b38f69_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2019

Inferring immunological control mechanisms from TKI dose alterations in CML patients

Recent clinical findings in chronic myeloid leukemia (CML) patients suggest that the risk of molecular recurrence after stopping tyrosine kinase inhibitors (TKI) treatment substantially depend on an individual, leukemia-specific immune response. However, it is still not possible to prospectively identify patients that will most likely remain in a long-term treatment free remission (TFR). Here, we use a mathematical model for CML, which explicitly includes an anti-leukemic (presumably immunological) effect and apply it to a set of patients (n=60) for whom BCR-ABL/ABL time courses had been quantified before and after TKI stop. We demonstrate that such a feedback control is conceptually necessary to explain long-term remission as observed in about half of the patients. Based on simulation results we classify the patient data sets into three different groups according to their predicted immune system configuration. While one class of patients requires a complete CML eradication to achieve TFR, other patients are able to control the leukemia after treatment cessation. Among them, we identified a third class of patients, which only maintains TFR if an optimal balance between leukemia abundance and immunological activation is achieved before treatment cessation. Further, we demonstrate that the immune response classification of the patients cannot be obtained solely from BCR-ABL measurements before treatment cessation. However, our results strongly suggest that changes in the BCR-ABL dynamics arising after system perturbations, such as TKI dose reduction, holds the information to predict the individual outcome after treatment cessation.

systems biology↗

bioRxiv2019

genBaRcode - a comprehensive R package for genetic barcode analysis

MotivationGenetic barcodes have been established as an efficient method to trace clonal progeny of uniquely labeled cells by introducing artificial genetic sequences into the corresponding genomes. The assessment of those sequences, relies on next generation sequencing and the subsequent analysis aiming to identify sequences of interest and correctly quantifying their abundance.\n\nResultsWe developed the genBaRcode package as a toolbox combining the flexibility of digesting next generation sequencing reads with or without a sophisticated barcode structure, with a variety of error correction approaches and the availability of several types of visualization routines. Furthermore, a graphical user interface was incorporated to allow also less experienced R users package-based analyses. Finally, the provided tool is intended to bridge the gap between generating and analyzing barcode data and thereby supporting the establishment of standardized and reproducible analysis strategies.\n\nAvailabilityThe genBaRcode package is available at CRAN (https://cran.r-project.org/pack-age=genBaRcode).\n\nContactlars.thielecke@tu-dresden.de

bioinformatics↗

bioRxiv2018

To cure or not to cure: consequences of immunological interactions in CML treatment

Recent clinical findings in Chronic Myeloid Leukemia (CML) patients suggest that the number and function of immune effector cells are modulated by Tyrosine Kinase Inhibitors (TKI) treatment. There is further evidence that the success or failure of treatment cessation at least partly depends on the patients immunological constitution. Here, we propose a general ODE model to functionally describe the interactions between immune effector cells with leukemic cells during the TKI treatment of CML. In total, we consider 20 different sub-models, which assume different functional interactions between immune effector and leukemic cells. We show that quantitative criteria, which are purely based on the quality of model fitting, are not able to identify optimal models. On the other hand, the application of qualitative criteria based on a dynamical system framework allowed us to identify nine of those models as more suitable than the others to describe clinically observed patterns and, thereby, to derive conclusion about the underlying mechanisms. Additionally, including aspects of early CML onset, we can demonstrate that certain critical parameters, such as the strength of immune response or leukemia proliferation rate, need to change during CML growth prior to diagnosis, leading to bifurcations that alter the attractor landscape. Finally, we show that the crucial parameters determining the outcome of treatment cessation are not identifiable with tumor load data only, thereby highlighting the need to measure immune cell number and function to properly derive mathematical models with predictive power.

systems biology↗

bioRxiv2018

Hematopoietic Stem Cell Dynamics are Regulated by Progenitor Demand: Lessons from a Quantitative Modeling Approach

The prevailing view on murine hematopoiesis and on hematopoietic stem cells (HSC) in particular derives from experiments that are related to regeneration after irradiation and HSC transplantation. However, over the past years, different experimental techniques have been developed to investigate hematopoiesis under homeostatic conditions, thereby providing access to proliferation and differentiation rates of hematopoietic stem and progenitor cells in the unperturbed situation. Moreover, it has become clear that hematopoiesis undergoes distinct changes during aging with large effects on HSC abundance, lineage contribution, asymmetry of division and self-renewal potential. However, it is currently not fully resolved how stem and progenitor cells interact to respond to varying demands and how this balance is altered by an aging-induced shift in HSC polarity.\n\nHere, we present an in-silico model to investigate the dynamics of HSC response to varying demand. By introducing an internal feedback between stem and progenitor cells, the model is suited to consistently describe both hematopoietic homeostasis and regeneration, including the limited regulation of HSCs in the homeostatic situation. The model further explains the age-dependent increase in phenotypic HSCs as a consequence of the cells inability to preserve divisional asymmetry.\n\nOur model suggests a dynamically regulated population of intrinsically asymmetrically dividing HSCs as suitable control mechanism that adheres with many qualitative and quantitative findings on hematopoietic recovery after stress and aging. The modeling approach thereby illustrates how a mathematical formalism can support the conceptual and the quantitative understanding of regulatory principles in HSC biology.

systems biology↗

bioRxiv2018

Hematopoietic stem cells differentiate into restricted myeloid progenitors before cell division

Hematopoietic stem cells (HSCs) continuously replenish all blood cell types through a series of differentiation steps that involve the generation of lineage-committed progenitors as well as necessary expansion due to repeated cell divisions. However, whether cell division in HSCs precedes differentiation is unclear. To this end, we used an HSC cell tracing approach and Ki67RFP knock-in mice to assess simultaneously divisional history, cell cycle progression, and differentiation of adult HSCs in vivo. Our results reveal that HSCs are able to differentiate into restricted progenitors, especially common myeloid progenitors, restricted megakaryocyte-erythroid progenitors (PreMEs) and pre-megakaryocyte progenitors (PreMegs), without undergoing cell division and even before entering the S phase of the cell cycle. Additionally, the phenotype of the undivided but differentiated progenitors correlated with expression of lineage-specific genes that manifested as functional differences between HSCs and restricted progenitors. Thus, HSC fate decisions appear to be uncoupled from physical cell division. Our results facilitate a better understanding of the mechanisms that control fate decisions in hematopoietic cells. Our data, together with separate findings from embryonic stem cells, suggest that cell division and fate choice are independent processes in pluripotent and multipotent stem cells.

cell biology↗