Stem cell-associated heterogeneity in Glioblastoma results from intrinsic tumor plasticity shaped by the microenvironment

The identity and unique capacity of cancer stem cells (CSC) to drive tumor growth and resistance have been challenged in brain tumors. Here we report that cells expressing CSC-associated cell membrane markers in Glioblastoma (GBM) do not represent a clonal entity defined by distinct functional properties and transcriptomic profiles, but rather a plastic state that most cancer cells can adopt. We show that phenotypic heterogeneity arises from non-hierarchical, reversible state transitions, instructed by the microenvironment and is predictable by mathematical modeling. Although functional stem cell properties were similar in vitro, accelerated reconstitution of heterogeneity provides a growth advantage in vivo, suggesting that tumorigenic potential is linked to intrinsic plasticity rather than CSC multipotency. The capacity of any given cancer cell to reconstitute tumor heterogeneity cautions against therapies targeting CSC-associated membrane epitopes. Instead inherent cancer cell plasticity emerges as a novel relevant target for treatment.publishedVersio

Global parameter estimation methods for stochastic biochemical systems

<p>Abstract</p> <p>Background</p> <p>The importance of stochasticity in cellular processes having low number of molecules has resulted in the development of stochastic models such as chemical master equation. As in other modelling frameworks, the accompanying rate constants are important for the end-applications like analyzing system properties (e.g. robustness) or predicting the effects of genetic perturbations. Prior knowledge of kinetic constants is usually limited and the model identification routine typically includes parameter estimation from experimental data. Although the subject of parameter estimation is well-established for deterministic models, it is not yet routine for the chemical master equation. In addition, recent advances in measurement technology have made the quantification of genetic substrates possible to single molecular levels. Thus, the purpose of this work is to develop practical and effective methods for estimating kinetic model parameters in the chemical master equation and other stochastic models from single cell and cell population experimental data.</p> <p>Results</p> <p>Three parameter estimation methods are proposed based on the maximum likelihood and density function distance, including probability and cumulative density functions. Since stochastic models such as chemical master equations are typically solved using a Monte Carlo approach in which only a finite number of Monte Carlo realizations are computationally practical, specific considerations are given to account for the effect of finite sampling in the histogram binning of the state density functions. Applications to three practical case studies showed that while maximum likelihood method can effectively handle low replicate measurements, the density function distance methods, particularly the cumulative density function distance estimation, are more robust in estimating the parameters with consistently higher accuracy, even for systems showing multimodality.</p> <p>Conclusions</p> <p>The parameter estimation methodologies described in this work have provided an effective and practical approach in the estimation of kinetic parameters of stochastic systems from either sparse or dense cell population data. Nevertheless, similar to kinetic parameter estimation in other modelling frameworks, not all parameters can be estimated accurately, which is a common problem arising from the lack of complete parameter identifiability from the available data.</p

Stochastic Drift in Mitochondrial DNA Point Mutations: A Novel Perspective Ex Silico

The mitochondrial free radical theory of aging (mFRTA) implicates Reactive Oxygen Species (ROS)-induced mutations of mitochondrial DNA (mtDNA) as a major cause of aging. However, fifty years after its inception, several of its premises are intensely debated. Much of this uncertainty is due to the large range of values in the reported experimental data, for example on oxidative damage and mutational burden in mtDNA. This is in part due to limitations with available measurement technologies. Here we show that sample preparations in some assays necessitating high dilution of DNA (single molecule level) may introduce significant statistical variability. Adding to this complexity is the intrinsically stochastic nature of cellular processes, which manifests in cells from the same tissue harboring varying mutation load. In conjunction, these random elements make the determination of the underlying mutation dynamics extremely challenging. Our in silico stochastic study reveals the effect of coupling the experimental variability and the intrinsic stochasticity of aging process in some of the reported experimental data. We also show that the stochastic nature of a de novo point mutation generated during embryonic development is a major contributor of different mutation burdens in the individuals of mouse population. Analysis of simulation results leads to several new insights on the relevance of mutation stochasticity in the context of dividing tissues and the plausibility of ROS ”vicious cycle” hypothesis

Single-cell transcriptomics reveals distinct inflammation-induced microglia signatures

Microglia are specialized parenchymal‐resident phagocytes of the central nervous system (CNS) that actively support, defend and modulate the neural environment. Dysfunctional microglial responses are thought to worsen CNS diseases; nevertheless, their impact during neuroinflammatory processes remains largely obscure. Here, using a combination of single‐cell RNA sequencing and multicolour flow cytometry, we comprehensively profile microglia in the brain of lipopolysaccharide (LPS)‐injected mice. By excluding the contribution of other immune CNS‐resident and peripheral cells, we show that microglia isolated from LPS‐injected mice display a global downregulation of their homeostatic signature together with an upregulation of inflammatory genes. Notably, we identify distinct microglial activated profiles under inflammatory conditions, which greatly differ from neurodegenerative disease‐associated profiles. These results provide insights into microglial heterogeneity and establish a resource for the identification of specific phenotypes in CNS disorders, such as neuroinflammatory and neurodegenerative diseases

New insights into the early mechanisms of epileptogenesis in a zebrafish model of Dravet syndrome

Abstract Objective: To pinpoint the earliest cellular defects underlying seizure onset (epileptogenic period) during perinatal brain development in a new zebrafish model of Dravet syndrome (DS) and to investigate potential disease-modifying activity of the 5HT2 receptor agonist fenfluramine. Methods: We used CRISPR/Cas9 mutagenesis to introduce a missense mutation, designed to perturb ion transport function in all channel isoforms, into scn1lab, the zebrafish orthologue of SCN1A (encoding voltage-gated sodium channel alpha subunit 1). We performed behavioral analysis and electroencephalographic recordings to measure convulsions and epileptiform discharges, followed by single-cell RNA-Seq, morphometric analysis of transgenic reporter-labeled γ-aminobutyric acidergic (GABAergic) neurons, and pharmacological profiling of mutant larvae. Results: Homozygous mutant (scn1labmut/mut ) larvae displayed spontaneous seizures with interictal, preictal, and ictal discharges (mean = 7.5 per 20-minute recording; P < .0001; one-way analysis of variance). Drop-Seq analysis revealed a 2:1 shift in the ratio of glutamatergic to GABAergic neurons in scn1labmut/mut larval brains versus wild type (WT), with dynamic changes in neuronal, glial, and progenitor cell populations. To explore disease pathophysiology further, we quantified dendritic arborization in GABAergic neurons and observed a 40% reduction in arbor number compared to WT (P < .001; n = 15 mutant, n = 16 WT). We postulate that the significant reduction in inhibitory arbors causes an inhibitory to excitatory neurotransmitter imbalance that contributes to seizures and enhanced electrical brain activity in scn1labmut/mut larvae (high-frequency range), with subsequent GABAergic neuronal loss and astrogliosis. Chronic fenfluramine administration completely restored dendritic arbor numbers to normal in scn1labmut/mut larvae, whereas similar treatment with the benzodiazepine diazepam attenuated seizures, but was ineffective in restoring neuronal cytoarchitecture. BrdU labeling revealed cell overproliferation in scn1labmut/mut larval brains that were rescued by fenfluramine but not diazepam. Significance: Our findings provide novel insights into early mechanisms of DS pathogenesis, describe dynamic cell population changes in the scn1labmut/mut brain, and present first-time evidence for potential disease modification by fenfluramine. Keywords: Dravet syndrome; epileptogenesis; fenfluramine; sodium channel; zebrafish

Neural Stem Cells of Parkinson's Disease Patients Exhibit Aberrant Mitochondrial Morphology and Functionality.

Summary Emerging evidence suggests that Parkinson's disease (PD), besides being an age-associated disorder, might also have a neurodevelopment component. Disruption of mitochondrial homeostasis has been highlighted as a crucial cofactor in its etiology. Here, we show that PD patient-specific human neuroepithelial stem cells (NESCs), carrying the LRRK2-G2019S mutation, recapitulate key mitochondrial defects previously described only in differentiated dopaminergic neurons. By combining high-content imaging approaches, 3D image analysis, and functional mitochondrial readouts we show that LRRK2-G2019S mutation causes aberrations in mitochondrial morphology and functionality compared with isogenic controls. LRRK2-G2019S NESCs display an increased number of mitochondria compared with isogenic control lines. However, these mitochondria are more fragmented and exhibit decreased membrane potential. Functional alterations in LRRK2-G2019S cultures are also accompanied by a reduced mitophagic clearance via lysosomes. These findings support the hypothesis that preceding mitochondrial developmental defects contribute to the manifestation of the PD pathology later in life

Neural Stem Cells of Parkinson's Disease Patients Exhibit Aberrant Mitochondrial Morphology and Functionality

Summary: Emerging evidence suggests that Parkinson's disease (PD), besides being an age-associated disorder, might also have a neurodevelopment component. Disruption of mitochondrial homeostasis has been highlighted as a crucial cofactor in its etiology. Here, we show that PD patient-specific human neuroepithelial stem cells (NESCs), carrying the LRRK2-G2019S mutation, recapitulate key mitochondrial defects previously described only in differentiated dopaminergic neurons. By combining high-content imaging approaches, 3D image analysis, and functional mitochondrial readouts we show that LRRK2-G2019S mutation causes aberrations in mitochondrial morphology and functionality compared with isogenic controls. LRRK2-G2019S NESCs display an increased number of mitochondria compared with isogenic control lines. However, these mitochondria are more fragmented and exhibit decreased membrane potential. Functional alterations in LRRK2-G2019S cultures are also accompanied by a reduced mitophagic clearance via lysosomes. These findings support the hypothesis that preceding mitochondrial developmental defects contribute to the manifestation of the PD pathology later in life. : Walter, Bolognin and colleagues show the detection of mitochondrial phenotypes in NESCs derived from Parkinson's disease (PD) patients carrying the LRRK2-G2019S mutation. This supports the use of stem cells as a relevant model to study PD-associated mitochondrial defects associated to PD. Keywords: Parkinson's disease, LRRK2, neurodevelopment, stem cells, mitochondria, autophagy, mitophag

Stem cell-associated heterogeneity in Glioblastoma results from intrinsic tumor plasticity shaped by the microenvironment

The identity and unique capacity of cancer stem cells (CSC) to drive tumor growth and resistance have been challenged in brain tumors. Here we report that cells expressing CSC-associated cell membrane markers in Glioblastoma (GBM) do not represent a clonal entity defined by distinct functional properties and transcriptomic profiles, but rather a plastic state that most cancer cells can adopt. We show that phenotypic heterogeneity arises from non-hierarchical, reversible state transitions, instructed by the microenvironment and is predictable by mathematical modeling. Although functional stem cell properties were similar in vitro, accelerated reconstitution of heterogeneity provides a growth advantage in vivo, suggesting that tumorigenic potential is linked to intrinsic plasticity rather than CSC multipotency. The capacity of any given cancer cell to reconstitute tumor heterogeneity cautions against therapies targeting CSC-associated membrane epitopes. Instead inherent cancer cell plasticity emerges as a novel relevant target for treatment

Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts

Abstract Background A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials. Methods Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry, and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors. Results We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood–brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components. Conclusions Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment. Graphical Abstrac