Biology subjects

Bruce, J. N.

Publications and source records attributed to Bruce, J. N..

18 recordsLinked to original sources

bioRxiv2026

Expanding the therapeutic window of bacteria for cancer therapy

Engineered bacteria enable self-amplifying therapeutic delivery and immune activation, yet these same features drive systemic toxicity and off-target growth. Here, we create a "tumorobe" that overcomes these limitations by integrating reduced immunogenicity, tumour-restricted growth, and enhanced payload release. Specifically, we identify lipopolysaccharide modifications that reduce immunogenicity while preserving fitness, restrict growth to tumours using a hypoxia-lactate "AND" gate, and enhance extracellular payload release via lipoprotein deletion. This strain expands the maximum tolerated dose in a route-dependent manner by up to 1,000-fold. Across multiple murine models, including colorectal cancer and glioblastoma, the strain drives robust antitumour efficacy as both a standalone therapeutic and an immunotherapeutic delivery platform, achieving durable complete responses in up to 75% of colorectal tumours when armed with a cytokine payload. Together, these results establish a broadly applicable platform for safe and effective bacterial cancer therapy.

synthetic biology↗

bioRxiv2026

Paired Tumor Biopsies Reveal Spatiotemporal Myeloid Remodeling After Local Chemotherapy in Glioblastoma

BackgroundStandard-of-care chemotherapy for glioblastoma induces inflammation that may contribute to disease recurrence. Although recurrent tumors are enriched with myeloid cells, the early cellular response to chemotherapy and the mechanisms that initiate this inflammatory remodeling remain poorly understood. In particular, it is unknown how neoplastic and tumor-associated myeloid populations respond during the immediate post-treatment period, and whether tumor-associated myeloid cells directly experience chemotherapy-induced genotoxic stress that contributes to inflammatory state transitions. MethodsWe performed sequencing-based analysis of neoplastic and immune populations following topotecan exposure using multiple complementary model systems and time points. We first analyzed MRI-localized, paired pre- and post-treatment biopsies from a first-in-human trial of 28-day convection enhanced delivery (CED) of topotecan (n=5) using cell-type-deconvolved bulk-RNA-sequencing and immunofluorescence. We then treated syngeneic murine gliomas using an in vivo model of CED-topotecan and measured acute 3-day and 7-day treatment responses by single cell RNA-sequencing. We additionally conducted sequencing analysis of patient-derived slice cultures and in vitro human microglial and glioma cell lines following 24-hour topotecan treatment. ResultsIn paired human biopsies, CED-topotecan induced spatially restricted transcriptional remodeling within the infusion zone, characterized by suppression of proliferative tumor programs and enrichment of inflammatory, interferon, hypoxia, and mesenchymal signatures. Cell-type deconvolution and immunofluorescence linked this response to myeloid remodeling, including enrichment of monocyte-derived tumor-associated macrophage states, increased MARCO-positive myeloid populations, and pH2AX-positive genotoxic stress within Iba1-positive myeloid cells. In the murine CED model, topotecan prolonged survival and reduced tumor cellularity, while also inducing inflammatory and DNA-damage programs in tumor-associated macrophages that evolved by 7-days toward hypoxia, angiogenesis, TGF-{beta} signaling, and mesenchymal/tissue-remodeling programs. Human slice culture and in vitro microglial systems confirmed stress-coupled inflammatory and DNA-damage responses in human myeloid cells. ConclusionsChemotherapy exposure induces a spatially structured inflammatory myeloid response characterized by early genotoxic stress and inflammatory activation, with later emergence of mesenchymal and tissue-remodeling macrophage programs. Across model systems, our analysis supports a model in which chemotherapy-associated damage in both tumor and myeloid cells contributes to an evolving inflammatory microenvironment after treatment.

neuroscience↗

bioRxiv2026

Electrophysiologically Targeted Biopsies Reveal the Transcriptional Landscape of Focal Epilepsy

Up to 30% of patients with epilepsy have intractable seizures, yet the mechanisms of focal ictogenesis remain unclear. Tissue involvement in ictal regions is heterogeneous, with different regions playing distinct roles in ictogenesis, seizure propagation, and resistance to spread. These roles are reflected in electrophysiologic differences between the seizure focus and the ictal penumbra, where evidence of synaptic spread is present but excitatory firing is constrained by largely intact inhibition. Investigation of the disruption of the normal interplay between excitatory and inhibitory activity, thought to underlie ictogenesis across a range of epilepsy etiologies, is limited by network complexity and cellular heterogeneity in human tissue samples. In this study, we relate cellular and molecular alterations to excitatory-inhibitory disruption in network dynamics defined by electrophysiologic features. This work may aid in the identification of clinically relevant tissue biomarkers and support novel preclinical therapeutic approaches for treatment-resistant focal epilepsy disorders. We developed a novel intracranial EEG guided, MRI-localized approach to sample paired biopsies from 11 patients with drug-resistant focal epilepsy with diverse etiologies, which were then studied using single-nucleus RNA sequencing (snRNAseq) and immunohistochemistry (IHC). EEG recorded from stereotactically implanted depth arrays (sEEG) was used to identify regions of epileptic involvement, based on findings from prior simultaneous clinical and microelectrode recordings. This approach addresses the intrinsic heterogeneity due to etiology and cortical architecture through paired, within-patient comparisons. We identified distinct cell-type specific transcriptional signatures that differentiate cellular populations in the seizure focus and ictal penumbra in intractable focal epilepsies. Our findings provide a link between tissue composition and gene expression that correlate with electrographic features in a heterogeneous seizure landscape. Our findings support common pathways of seizure generation and spread that are conserved across disease etiologies. Relative depletion of interneuron populations in the seizure focus supports the hypothesis of disrupted inhibition as a driver of epileptiform activity in the seizure focus. The enrichment of plasticity-associated gene signatures in the penumbra suggests a complex interaction of these regions with the seizure focus, as well as the role of the penumbra in enabling or limiting seizure expansion. This study provides a novel methodology for tissue sampling in epilepsy and uncovers biologically relevant tissue signatures that provide grounds for future work in targeting cellular and molecular alterations present in focal epilepsies.

neuroscience↗

bioRxiv2025

Convection-enhanced delivery of dexamethasone in glioma suppresses myeloid inflammation while avoiding systemic toxicities

Dexamethasone is widely used to control cerebral edema and inflammation in glioblastoma, but its benefits are limited by systemic toxicities and adverse prognostic associations. We evaluated local administration of dexamethasone via convection-enhanced delivery (CED) to maximize intratumoral anti-inflammatory effects by increasing local corticosteroid exposure while minimizing systemic exposure. In two glioma mouse models, continuous intraparenchymal infusion of dexamethasone was well tolerated with no adverse effects. Pharmacokinetic analyses supported preferential intratumoral distribution and reduced systemic exposure with CED compared with systemic dosing. Single-nucleus RNA sequencing (snRNA-seq) and immunohistochemistry showed attenuation of glioma-associated inflammation with downregulation of reactive microglial/macrophage programs and reduced tumor-infiltrating myeloid cells with a morphology consistent with a less activated state. Experiments in human induced pluripotent stem cell (iPSC)-derived microglia confirmed that dexamethasone directly suppresses inflammatory gene expression, indicating a conserved mechanism across species. This inflammatory suppression was recapitulated in both immortalized microglial (HMC3) and macrophage (THP1) cell lines. These findings suggest that localized dexamethasone delivered by CED reprograms the glioma immune microenvironment and achieves control of inflammation without the systemic adverse effects associated with standard systemic dexamethasone therapy. This clinically translatable strategy may improve symptom management and provide a platform for integrating local immunomodulation with future glioblastoma therapies.

cancer biology↗

bioRxiv2025

A proteogenomic tool uncovers protein markers for human microglial states

Human microglial heterogeneity has been largely described using transcriptomic data. Here, we introduce a microglial proteomic data resource and a Cellular Indexing of Transcriptomes and Epitopes by Sequencing panel enhanced with antibodies targeting 17 microglial cell surface proteins (mCITE-Seq). We evaluated mCITE-Seq on HMC3 microglia-like cells, induced-pluripotent stem cell-derived microglia (iMG), and freshly isolated primary human microglia. We identified novel protein microglial markers such as CD51 and relate expression of 101 cell surface proteins to transcriptional programs. This results in the identification and validation of three protein marker combinations with which to purify microglia enriched with each of 23 transcriptional programs; for example, CD49D, HLA-DR and CD32 enrich for GPNMBhigh ("disease associated") microglia. Further, we identify and validate proteins - SIRPA, PDPN and CD162 - that differentiate microglia from infiltrating macrophages. The mCITE-Seq panel enables the transition from RNA-based classification and facilitates the functional characterization and harmonization of model systems.

neuroscience↗

bioRxiv2025

A therapeutic role for a regulatory glucose transporter1 (Glut1)-associated natural antisense transcript

The mammalian brain relies primarily on glucose for its energy needs. Delivery of this nutrient to the brain is mediated by the glucose transporter-1 (Glut1) protein. Low Glut1 thwarts glucose entry into the brain, causing an energy crisis and, triggering, in one instance, the debilitating neurodevelopmental condition - Glut1 deficiency syndrome (Glut1DS). Current treatments for Glut1DS are sub-optimal, as none address the root cause - low Glut1 - of the condition. Levels of this transporter must respond rapidly to the brains changing energy requirements. This necessitates fine-tuning its expression. Here we describe a long-noncoding RNA (lncRNA) antisense to Glut1 and show that it is involved in such regulation. Raising levels of the lncRNA had a concordant effect on Glut1 in cultured human cells and transgenic mice; reducing levels elicited the opposite effect. Delivering the lncRNA to Glut1DS model mice via viral vectors induced Glut1 expression, enhancing brain glucose levels to mitigate disease. Direct delivery of such a lncRNA to combat disease has not been reported previously and constitutes a unique therapeutic paradigm. Moreover, considering the importance of maintaining homeostatic Glut1 levels, calibrating transporter expression via the lncRNA could become broadly relevant to the myriad conditions, including Alzheimers disease, wherein Glut1 concentrations are perturbed.

neuroscience↗

bioRxiv2024

A pharmacological toolkit for human microglia identifies Topoisomerase I inhibitors as immunomodulators for Alzheimer's disease

AbstractWhile efforts to identify microglial subtypes have recently accelerated, the relation of transcriptomically defined states to function has been largely limited to in silico annotations. Here, we characterize a set of pharmacological compounds that have been proposed to polarize human microglia towards two distinct states - one enriched for AD and MS genes and another characterized by increased expression of antigen presentation genes. Using different model systems including HMC3 cells, iPSC-derived microglia and cerebral organoids, we characterize the effect of these compounds in mimicking human microglial subtypes in vitro. We show that the Topoisomerase I inhibitor Camptothecin induces a CD74high/MHChigh microglial subtype which is specialized in amyloid beta phagocytosis. Camptothecin suppressed amyloid toxicity and restored microglia back to their homeostatic state in a zebrafish amyloid model. Our work provides avenues to recapitulate human microglial subtypes in vitro, enabling functional characterization and providing a foundation for modulating human microglia in vivo.

neuroscience↗

bioRxiv2024

Glioma-Induced Alterations in Excitatory Neurons are Reversed by mTOR Inhibition

Gliomas are highly aggressive brain tumors characterized by poor prognosis and composed of diffusely infiltrating tumor cells that intermingle with non-neoplastic cells in the tumor microenvironment, including neurons. Neurons are increasingly appreciated as important reactive components of the glioma microenvironment, due to their role in causing hallmark glioma symptoms, such as cognitive deficits and seizures, as well as their potential ability to drive glioma progression. Separately, mTOR signaling has been shown to have pleiotropic effects in the brain tumor microenvironment, including regulation of neuronal hyperexcitability. However, the local cellular-level effects of mTOR inhibition on glioma-induced neuronal alterations are not well understood. Here we employed neuron-specific profiling of ribosome-bound mRNA via RiboTag, morphometric analysis of dendritic spines, and in vivo calcium imaging, along with pharmacological mTOR inhibition to investigate the impact of glioma burden and mTOR inhibition on these neuronal alterations. The RiboTag analysis of tumor-associated excitatory neurons showed a downregulation of transcripts encoding excitatory and inhibitory postsynaptic proteins and dendritic spine development, and an upregulation of transcripts encoding cytoskeletal proteins involved in dendritic spine turnover. Light and electron microscopy of tumor-associated excitatory neurons demonstrated marked decreases in dendritic spine density. In vivo two-photon calcium imaging in tumor-associated excitatory neurons revealed progressive alterations in neuronal activity, both at the population and single-neuron level, throughout tumor growth. This in vivo calcium imaging also revealed altered stimulus-evoked somatic calcium events, with changes in event rate, size, and temporal alignment to stimulus, which was most pronounced in neurons with high-tumor burden. A single acute dose of AZD8055, a combined mTORC1/2 inhibitor, reversed the glioma-induced alterations on the excitatory neurons, including the alterations in ribosome-bound transcripts, dendritic spine density, and stimulus evoked responses seen by calcium imaging. These results point to mTOR-driven pathological plasticity in neurons at the infiltrative margin of glioma - manifested by alterations in ribosome-bound mRNA, dendritic spine density, and stimulus-evoked neuronal activity. Collectively, our work identifies the pathological changes that tumor-associated excitatory neurons experience as both hyperlocal and reversible under the influence of mTOR inhibition, providing a foundation for developing therapies targeting neuronal signaling in glioma.

neuroscience↗

bioRxiv2023

Consensus scHPF Identifies Cell Type-Specific Drug Responses in Glioma by Integrating Large-Scale scRNA-seq

Single-cell transcriptomic analyses now frequently involve elaborate study designs including samples from multiple individuals, experimental conditions, perturbations, and batches from complex tissues. Dimensionality reduction is required to facilitate integration, interpretation, and statistical analysis. However, these datasets often include subtly different cellular subpopulations or state transitions, which are poorly described by clustering. We previously reported a Bayesian matrix factorization algorithm called single-cell hierarchical Poisson factorization (scHPF) that identifies gene co-expression patterns directly from single-cell RNA-seq (scRNA-seq) count matrices while accounting for transcript drop-out and noise. Here, we describe consensus scHPF, which analyzes scHPF models from multiple random initializations to identify the most robust gene signatures and automatically determine the number of factors for a given dataset. Consensus scHPF facilitates integration of complex datasets with highly multi-modal posterior distributions, resulting in factors that can be uniformly analyzed across individuals and conditions. To demonstrate the utility of consensus scHPF, we performed a meta-analysis of a large-scale scRNA-seq dataset from drug-treated, human glioma slice cultures generated from surgical specimens across three major cell types, 19 patients, 10 drug treatment conditions, and 52 samples. In addition to recapitulating previously reported cell type-specific drug responses from smaller studies, consensus scHPF identified disparate effects of the topoisomerase poisons etoposide and topotecan that are highly consistent with the distinct roles and expression patterns of their respective protein targets.

genomics↗

bioRxiv2023

A cell state specific metabolic vulnerability to GPX4-dependent ferroptosis in glioblastoma

Glioma cells hijack developmental transcriptional programs to control cell state. During neural development, lineage trajectories rely on specialized metabolic pathways. However, the link between tumor cell state and metabolic programs is poorly understood in glioma. Here we uncover a glioma cell state-specific metabolic liability that can be leveraged therapeutically. To model cell state diversity, we generated genetically engineered murine gliomas, induced by deletion of p53 alone (p53) or with constitutively active Notch signaling (N1IC), a pathway critical in controlling cellular fate. N1IC tumors harbored quiescent astrocyte-like transformed cell states while p53 tumors were predominantly comprised of proliferating progenitor-like cell states. N1IC cells exhibit distinct metabolic alterations, with mitochondrial uncoupling and increased ROS production rendering them more sensitive to inhibition of the lipid hydroperoxidase GPX4 and induction of ferroptosis. Importantly, treating patient-derived organotypic slices with a GPX4 inhibitor induced selective depletion of quiescent astrocyte-like glioma cell populations with similar metabolic profiles.

cancer biology↗

bioRxiv2023

Scalable co-sequencing of RNA and DNA from individual nuclei

The ideal technology for directly investigating the relationship between genotype and phenotype would analyze both RNA and DNA genome-wide and with single-cell resolution. However, existing tools lack the throughput required for comprehensive analysis of complex tumors and tissues. We introduce a highly scalable method for jointly profiling DNA and expression following nucleosome depletion (DEFND-seq). In DEFND-seq, nuclei are nucleosome-depleted, tagmented, and separated into individual droplets for mRNA and genomic DNA barcoding. Once nuclei have been depleted of nucleosomes, subsequent steps can be performed using the widely available 10x Genomics droplet microfluidic technology and commercial kits without experimental modification. We demonstrate the production of high-complexity mRNA and gDNA sequencing libraries from thousands of individual nuclei from both cell lines and archived surgical specimens for associating gene expression phenotypes with both copy number and single nucleotide variants.

genomics↗

bioRxiv2022

Biologically-informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post-treatment glioblastoma

Intratumoral heterogeneity poses a significant challenge to the diagnosis and treatment of glioblastoma (GBM). This heterogeneity is further exacerbated during GBM recurrence, as treatment-induced reactive changes produce additional intratumoral heterogeneity that is ambiguous to differentiate on clinical imaging. There is an urgent need to develop non-invasive approaches to map the heterogeneous landscape of histopathological alterations throughout the entire lesion for each patient. We propose to predictively fuse Magnetic Resonance Imaging (MRI) with the underlying intratumoral heterogeneity in recurrent GBM using machine learning (ML) by leveraging image-localized biopsies with their associated locoregional MRI features. To this end, we develop BioNet, a biologically-informed neural network model, to predict regional distributions of three tissue-specific gene modules: proliferating tumor, reactive/inflammatory cells, and infiltrated brain tissue. BioNet offers valuable insights into the integration of multiple implicit and qualitative biological domain knowledge, which are challenging to describe in mathematical formulations. BioNet performs significantly better than a range of existing methods on cross-validation and blind test datasets. Voxel-level prediction maps of the gene modules by BioNet help reveal intratumoral heterogeneity, which can improve surgical targeting of confirmatory biopsies and evaluation of neuro-oncological treatment effectiveness. The non-invasive nature of the approach can potentially facilitate regular monitoring of the gene modules over time, and making timely therapeutic adjustment. These results also highlight the emerging role of ML in precision medicine.

cancer biology↗

bioRxiv2022

Single-Cell Analysis of 5-ALA Intraoperative Labeling Specificity for Glioblastoma

Glioblastoma (GBM) is the most common and aggressive malignant primary brain tumor, and surgical resection is a key part of the standard-of-care. In fluorescence-guided surgery (FGS), fluorophores are used to differentiate tumor tissue from surrounding normal brain. The heme synthesis pathway converts 5-aminolevulinic acid (5-ALA), a fluorogenic substrate used for FGS, to fluorescent protoporphyrin IX (PpIX). The resulting fluorescence is thought to be specific to transformed glioma cells, but this specificity has not been examined at single-cell level. We performed paired single-cell imaging and RNA sequencing of individual cells (SCOPE-seq2) on human GBM surgical specimens with visible PpIX fluorescence from patients who received 5-ALA prior to surgery. SCOPE-seq2 allows us to simultaneously image PpIX fluorescence and unambiguously identify transformed glioma cells from single-cell RNA-seq (scRNA-seq). We observed that 5-ALA treatment results in labeling that is not specific to transformed tumor cells. In cell culture, we further demonstrated that untransformed cells can be labeled by 5-ALA directly or by PpIX secreted from surrounding transformed cells. In acute slice cultures from mouse glioma models, we showed that 5-ALA preferentially labels GBM tumor tissue over non-neoplastic brain tissue, and that this contrast is not due to blood-brain-barrier disruption. Taken together, our findings support the use of 5-ALA as an indicator of GBM tissue, but not as a specific marker of transformed glioma cells.

cancer biology↗

bioRxiv2020

Integrating single-cell RNA-seq and imaging with SCOPE-seq2

Live cell imaging allows direct observation and monitoring of phenotypes that are difficult to infer from transcriptomics. However, existing methods for linking microscopy and single-cell RNA-seq (scRNA-seq) have limited scalability. Here, we describe an upgraded version of Single Cell Optical Phenotyping and Expression (SCOPE-seq2) for combining single-cell imaging and expression profiling, with substantial improvements in throughput, molecular capture efficiency, linking accuracy, and compatibility with standard microscopy instrumentation. We introduce improved optically decodable mRNA capture beads and implement a more scalable and simplified optical decoding process. We demonstrate the utility of SCOPE-seq2 for fluorescence, morphological, and expression profiling of individual primary cells from a human glioblastoma (GBM) surgical sample, revealing relationships between simple imaging features and cellular identity, particularly among malignantly transformed tumor cells.Competing Interest StatementZ.L., J.Y. and P.A.S. are listed as inventors on patent applications filed by Columbia University related to the work described here.View Full Text

systems biology↗

bioRxiv2020

Deconvolution of Cell Type-Specific Drug Responses in Human Tumor Tissue with Single-Cell RNA-seq

Precision oncology requires the timely selection of effective drugs for individual patients. An ideal platform would enable rapid screening of cell type-specific drug sensitivities directly in patient tumor tissue and reveal strategies to overcome intratumoral heterogeneity. Here we combine multiplexed drug perturbation in acute slice culture from freshly resected tumors with single-cell RNA sequencing (scRNA-seq) to profile transcriptome-wide drug responses. We applied this approach to glioblastoma (GBM) and demonstrated that acute slice cultures from individual patients recapitulate the cellular and molecular features of the originating tumor tissue. Detailed investigation of etoposide, a topoisomerase poison, and the histone deacetylase (HDAC) inhibitor panobinostat in acute slice cultures revealed cell type-specific responses across multiple patients, including unexpected effects on the immune microenvironment. We anticipate that this approach will facilitate rapid, personalized drug screening to identify effective therapies for solid tumors.

cancer biology↗

bioRxiv2019

Single-cell based elucidation of molecularly-distinct glioblastoma states and drug sensitivity

Glioblastoma heterogeneity and plasticity remain controversial, with proposed subtypes representing the average of highly heterogeneous admixtures of independent transcriptional states. Single-cell, protein-activity-based analysis allowed full quantification of >6,000 regulatory and signaling proteins, thus providing a previously unattainable single-cell characterization level. This helped identify four novel, molecularly distinct subtypes that successfully harmonize across multiple GBM datasets, including previously published bulk and single-cell profiles and single cell profiles from seven orthotopic PDX models, representative of prior subtype diversity. GBM is thus characterized by the plastic coexistence of single cells in two mutually-exclusive developmental lineages, with additional stratification provided by their proliferative potential. Consistently, all previous subtypes could be recapitulated by single-cell mixtures drawn from newly identified states. Critically, drug sensitivity was predicted and validated as highly state-dependent, both in single-cell assays from patient-derived explants and in PDX models, suggesting that successful treatment requires combinations of multiple drugs targeting these distinct tumor states.\n\nSignificanceWe propose a new, 4-subtype GBM classification, which harmonizes across bulk and single-cell datasets. Single-cell mixtures from these subtypes effectively recapitulate all prior classifications, suggesting that the latter are a byproduct of GBM heterogeneity. Finally, we predict single-cell level activity of three clinically-relevant drugs, and validate them in patient-derived explant.

systems biology↗

bioRxiv2018

De novo Gene Signature Identification from Single-Cell RNA-Seq with Hierarchical Poisson Factorization

Common approaches to gene signature discovery in single cell RNA-sequencing (scRNA-seq) depend upon predefined structures like clusters or pseudo-temporal order, require prior normalization, or do not account for the sparsity of single cell data. We present single cell Hierarchical Poisson Factorization (scHPF), a Bayesian factorization method that adapts Hierarchical Poisson Factorization [1] for de novo discovery of both continuous and discrete expression patterns from scRNA-seq. scHPF does not require prior normalization and captures statistical properties of single cell data better than other methods in benchmark datasets. Applied to scRNA-seq of the core and margin of a high-grade glioma, scHPF uncovers marked differences in the abundance of glioma subpopulations across tumor regions and subtle, regionally-associated expression biases within glioma subpopulations. scHFP revealed an expression signature that was spatially biased towards the glioma-infiltrated margins and associated with inferior survival in glioblastoma.

systems biology↗

bioRxiv2018

Single-Cell Transcriptome Analysis of Lineage Diversity and Microenvironment in High-Grade Glioma

BackgroundDespite extensive molecular characterization, we lack a comprehensive understanding of lineage identity, differentiation, and proliferation in high-grade gliomas (HGGs). We sampled the cellular milieu of HGGs with massively-parallel single-cell RNA-Seq.\n\nResultsWhile HGG cells can resemble glia or even immature neurons and form branched lineage structures, mesenchymal transformation results in unstructured populations. Glioma cells in a subset of mesenchymal tumors lose their neural lineage identity, express inflammatory genes, and co-exist with marked myeloid infiltration, reminiscent of molecular interactions between glioma and immune cells established in animal models. Additionally, we discovered a tight coupling between lineage resemblance and proliferation among malignantly transformed cells. Glioma cells that resemble oligodendrocyte progenitors, which proliferate in the brain, are often found in the cell cycle. Conversely, glioma cells that resemble astrocytes, neuroblasts, and oligodendrocytes, which are non-proliferative in the brain, are generally non-cycling in tumors.\n\nConclusionsThese studies reveal a relationship between cellular identity and proliferation in HGG and distinct population structures that reflects the extent of neural and non-neural lineage resemblance among malignantly transformed cells.

cancer biology↗