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

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.

Machine Learning-Assisted Classification of Paraffin-Embedded Brain Tumors with Raman Spectroscopy.

Raman spectroscopy (RS) has demonstrated its utility in neurooncological diagnostics, spanning from intraoperative tumor detection to the analysis of tissue samples peri- and postoperatively. In this study, we employed Raman spectroscopy (RS) to monitor alterations in the molecular vibrational characteristics of a broad range of formalin-fixed, paraffin-embedded (FFPE) intracranial neoplasms (including primary brain tumors and meningiomas, as well as brain metastases) and considered specific challenges when employing RS on FFPE tissue during the routine neuropathological workflow. We spectroscopically measured 82 intracranial neoplasms on CaF2 slides (in total, 679 individual measurements) and set up a machine learning framework to classify spectral characteristics by splitting our data into training cohorts and external validation cohorts. The effectiveness of our machine learning algorithms was assessed by using common performance metrics such as AUROC and AUPR values. With our trained random forest algorithms, we distinguished among various types of gliomas and identified the primary origin in cases of brain metastases. Moreover, we spectroscopically diagnosed tumor types by using biopsy fragments of pure necrotic tissue, a task unattainable through conventional light microscopy. In order to address misclassifications and enhance the assessment of our models, we sought out significant Raman bands suitable for tumor identification. Through the validation phase, we affirmed a considerable complexity within the spectroscopic data, potentially arising not only from the biological tissue subjected to a rigorous chemical procedure but also from residual components of the fixation and paraffin-embedding process. The present study demonstrates not only the potential applications but also the constraints of RS as a diagnostic tool in neuropathology, considering the challenges associated with conducting vibrational spectroscopic analysis on formalin-fixed, paraffin-embedded (FFPE) tissue.

Glioma subtype classification from histopathological images using in-domain and out-of-domain transfer learning: An experimental study.

We provide in this paper a comprehensive comparison of various transfer learning strategies and deep learning architectures for computer-aided classification of adult-type diffuse gliomas. We evaluate the generalizability of out-of-domain ImageNet representations for a target domain of histopathological images, and study the impact of in-domain adaptation using self-supervised and multi-task learning approaches for pretraining the models using the medium-to-large scale datasets of histopathological images. A semi-supervised learning approach is furthermore proposed, where the fine-tuned models are utilized to predict the labels of unannotated regions of the whole slide images (WSI). The models are subsequently retrained using the ground-truth labels and weak labels determined in the previous step, providing superior performance in comparison to standard in-domain transfer learning with balanced accuracy of 96.91% and F1-score 97.07%, and minimizing the pathologist's efforts for annotation. Finally, we provide a visualization tool working at WSI level which generates heatmaps that highlight tumor areas; thus, providing insights to pathologists concerning the most informative parts of the WSI.

Cell adhesion affects the properties of interstitial fluid flow: A study using multiscale poroelastic composite modeling.

In this study, we conduct a multiscale, multiphysics modeling of the brain gray matter as a poroelastic composite. We develop a customized representative volume element based on cytoarchitectural features that encompass important microscopic components of the tissue, namely the extracellular space, the capillaries, the pericapillary space, the interstitial fluid, cell-cell and cell-capillary junctions, and neuronal and glial cell bodies. Using asymptotic homogenization and direct numerical simulation, the effective properties at the tissue level are identified based on microscopic properties. To analyze the influence of various microscopic elements on the effective/macroscopic properties and tissue response, we perform sensitivity analyses on cell junction (cluster) stiffness, cell junction diameter (dimensions), and pericapillary space width. The results of this study suggest that changes in cell adhesion can greatly affect both mechanical and hydraulic (interstitial fluid flow and porosity) features of brain tissue, consistent with the effects of neurodegenerative diseases.

Computational Assessment of Spectral Heterogeneity within Fresh Glioblastoma Tissue Using Raman Spectroscopy and Machine Learning Algorithms.

Understanding and classifying inherent tumor heterogeneity is a multimodal approach, which can be undertaken at the genetic, biochemical, or morphological level, among others. Optical spectral methods such as Raman spectroscopy aim at rapid and non-destructive tissue analysis, where each spectrum generated reflects the individual molecular composition of an examined spot within a (heterogenous) tissue sample. Using a combination of supervised and unsupervised machine learning methods as well as a solid database of Raman spectra of native glioblastoma samples, we succeed not only in distinguishing explicit tumor areas-vital tumor tissue and necrotic tumor tissue can correctly be predicted with an accuracy of 76%-but also in determining and classifying different spectral entities within the histomorphologically distinct class of vital tumor tissue. Measurements of non-pathological, autoptic brain tissue hereby serve as a healthy control since their respective spectroscopic properties form an individual and reproducible cluster within the spectral heterogeneity of a vital tumor sample. The demonstrated decipherment of a spectral glioblastoma heterogeneity will be valuable, especially in the field of spectroscopically guided surgery to delineate tumor margins and to assist resection control.

Blocking TGF-ß- and Epithelial-to-Mesenchymal Transition (EMT)-mediated activation of vessel-associated mural cells in glioblastoma impacts tumor angiogenesis.

Glioblastoma (GBM) is the most common malignant primary brain tumor in adults. GBM displays excessive and unfunctional vascularization which may, among others, be a reason for its devastating prognosis. Pericytes have been identified as the major component of the irregular vessel structure in GBM. In vitro data suggest an epithelial-to-mesenchymal transition (EMT)-like activation of glioma-associated pericytes, stimulated by GBM-secreted TGF-ß, to be involved in the formation of a chaotic and dysfunctional tumor vasculature. This study investigated whether TGF-ß impacts the function of vessel associated mural cells (VAMCs) in vivo via the induction of the EMT transcription factor SLUG and whether this is associated with the development of GBM-associated vascular abnormalities. Upon preventing the TGF-ß-/SLUG-mediated EMT induction in VAMCs, the number of PDGFRß and αSMA positive cells was significantly reduced, regardless of whether TGF-ß secretion by GBM cells was blocked or whether SLUG was specifically knocked out in VAMCs. The reduced amount of PDGFRß+ or αSMA+ cells observed under those conditions correlated with a lower vessel density and fewer vascular abnormalities. Our data provide evidence that the SLUG-mediated modulation of VAMC activity is induced by GBM-secreted TGF-߬ and that activated VAMCs are key contributors in neo-angiogenic processes. We suggest that a pathologically altered activation of GA-Peris in the tumor microenvironment is responsible for the unstructured tumor vasculature. There is emerging evidence that vessel normalization alleviates tumor hypoxia, reduces tumor-associated edema and improves drug delivery. Therefore, avoiding the generation of an unstructured and non-functional tumor vasculature during tumor recurrence might be a promising treatment approach for GBM and identifies pericytes as a potential novel therapeutic target.

Impact of Formalin- and Cryofixation on Raman Spectra of Human Tissues and Strategies for Tumor Bank Inclusion.

Reliable training of Raman spectra-based tumor classifiers relies on a substantial sample pool. This study explores the impact of cryofixation (CF) and formalin fixation (FF) on Raman spectra using samples from surgery sites and a tumor bank. A robotic Raman spectrometer scans samples prior to the neuropathological analysis. CF samples showed no significant spectral deviations, appearance, or disappearance of peaks, but an intensity reduction during freezing and subsequent recovery during the thawing process. In contrast, FF induces sustained spectral alterations depending on molecular composition, albeit with good signal-to-noise ratio preservation. These observations are also reflected in the varying dual-class classifier performance, initially trained on native, unfixed samples: The Matthews correlation coefficient is 81.0% for CF and 58.6% for FF meningioma and dura mater. Training on spectral differences between original FF and pure formalin spectra substantially improves FF samples' classifier performance (74.2%). CF is suitable for training global multiclass classifiers due to its consistent spectrum shape despite intensity reduction. FF introduces changes in peak relationships while preserving the signal-to-noise ratio, making it more suitable for dual-class classification, such as distinguishing between healthy and malignant tissues. Pure formalin spectrum subtraction represents a possible method for mathematical elimination of the FF influence. These findings enable retrospective analysis of processed samples, enhancing pathological work and expanding machine learning techniques.

CLN3 deficiency leads to neurological and metabolic perturbations during early development.

Juvenile neuronal ceroid lipofuscinosis (or Batten disease) is an autosomal recessive, rare neurodegenerative disorder that affects mainly children above the age of 5 yr and is most commonly caused by mutations in the highly conserved CLN3 gene. Here, we generated cln3 morphants and stable mutant lines in zebrafish. Although neither morphant nor mutant cln3 larvae showed any obvious developmental or morphological defects, behavioral phenotyping of the mutant larvae revealed hyposensitivity to abrupt light changes and hypersensitivity to pro-convulsive drugs. Importantly, in-depth metabolomics and lipidomics analyses revealed significant accumulation of several glycerophosphodiesters (GPDs) and cholesteryl esters, and a global decrease in bis(monoacylglycero)phosphate species, two of which (GPDs and bis(monoacylglycero)phosphates) were previously proposed as potential biomarkers for CLN3 disease based on independent studies in other organisms. We could also demonstrate GPD accumulation in human-induced pluripotent stem cell-derived cerebral organoids carrying a pathogenic variant for CLN3 Our models revealed that GPDs accumulate at very early stages of life in the absence of functional CLN3 and highlight glycerophosphoinositol and BMP as promising biomarker candidates for pre-symptomatic CLN3 disease.

Systematic assessment of tumor necrosis at baseline in cervical cancer - An independent factor associated with poor outcome.

Cervical cancer (CC) is a leading challenge in oncology worldwide, with high prevalence and mortality rates in young adults, most prominent in low to middle-income countries with marginal screening facilities. From the prospectively collected BioRAIDS (NCT02428842) cohort of primary squamous CC conducted in 7 European countries, a central pathology review was carried out on 294 patients' tumors. The focus was on identification of tumor-stromal characteristics such as CD8+, CD45+, CD68+ staining cells, PD-L1 expression, tumor infiltrating lymphocytes (TILs) together with the degree of tumor necrosis. Both (FIGO-2018) stage (I-II/III-IV) as well as tumor necrosis were highly significantly associated with Progression-free Survival (PFS); with tumor necrosis scoring as most potent independent factor in a multivariable analysis (p < 0.001). Tumor necrosis can be assessed in the very first diagnostic biopsyand our data suggest that this rapid, simple and cost-effective biomarker, should be routinely assessed prior to treatment decisions.

Fiber deprivation and microbiome-borne curli shift gut bacterial populations and accelerate disease in a mouse model of Parkinson's disease.

Parkinson's disease (PD) is a neurological disorder characterized by motor dysfunction, dopaminergic neuron loss, and alpha-synuclein (αSyn) inclusions. Many PD risk factors are known, but those affecting disease progression are not. Lifestyle and microbial dysbiosis are candidates in this context. Diet-driven gut dysbiosis and reduced barrier function may increase exposure of enteric neurons to toxins. Here, we study whether fiber deprivation and exposure to bacterial curli, a protein cross-seeding with αSyn, individually or together, exacerbate disease in the enteric and central nervous systems of a transgenic PD mouse model. We analyze the gut microbiome, motor behavior, and gastrointestinal and brain pathologies. We find that diet and bacterial curli alter the microbiome and exacerbate motor performance, as well as intestinal and brain pathologies, but to different extents. Our results shed important insights on how diet and microbiome-borne insults modulate PD progression via the gut-brain axis and have implications for lifestyle management of PD.

Correlative light and electron microscopy to explore the lytic immunological synapse between natural killer cells and cancer cells.

Cytotoxic lymphocytes, such as natural killer (NK) cells and cytotoxic T cells, can recognize and kill tumor cells by establishing a highly specialized cell-cell contact called the immunological synapse. The formation and lytic activity of the immunological synapse are accompanied by local changes in the organization, dynamics and molecular composition of the cell membrane, as well as the polarization of various cellular components, such as the cytoskeleton, vesicles and organelles. Characterization and understanding of the molecular and cellular processes underlying immunological synapse formation and activity requires the combination of complementary types of information provided by different imaging modalities, the correlation of which can be difficult. Correlative light and electron microscopy (CLEM) allows for the accurate correlation of functional information provided by fluorescent light microscopy with ultrastructural features provided by high-resolution electron microscopy. In this chapter, we present a detailed protocol describing each step to generate cell-cell conjugates between NK cells and cancer cells, and to analyze these conjugates by CLEM using separate confocal laser-scanning and transmission electron microscopes.

A Th17 cell-intrinsic glutathione/mitochondrial-IL-22 axis protects against intestinal inflammation.

Although the intestinal tract is a major site of reactive oxygen species (ROS) generation, the mechanisms by which antioxidant defense in gut T cells contribute to intestinal homeostasis are currently unknown. Here we show, using T cell-specific ablation of the catalytic subunit of glutamate cysteine ligase (Gclc), that the ensuing loss of glutathione (GSH) impairs the production of gut-protective IL-22 by Th17 cells within the lamina propria. Although Gclc ablation does not affect T cell cytokine secretion in the gut of mice at steady-state, infection with C. rodentium increases ROS, inhibits mitochondrial gene expression and mitochondrial function in Gclc-deficient Th17 cells. These mitochondrial deficits affect the PI3K/AKT/mTOR pathway, leading to reduced phosphorylation of the translation repressor 4E-BP1. As a consequence, the initiation of translation is restricted, resulting in decreased protein synthesis of IL-22. Loss of IL-22 results in poor bacterial clearance, enhanced intestinal damage, and high mortality. ROS-scavenging, reconstitution of IL-22 expression or IL-22 supplementation in vivo prevent the appearance of these pathologies. Our results demonstrate the existence of a previously unappreciated role for Th17 cell-intrinsic GSH coupling to promote mitochondrial function, IL-22 translation and signaling. These data reveal an axis that is essential for maintaining the integrity of the intestinal barrier and protecting it from damage caused by gastrointestinal infection.

Tumor-derived GDF-15 blocks LFA-1 dependent T cell recruitment and suppresses responses to anti-PD-1 treatment.

Immune checkpoint blockade therapy is beneficial and even curative for some cancer patients. However, the majority don't respond to immune therapy. Across different tumor types, pre-existing T cell infiltrates predict response to checkpoint-based immunotherapy. Based on in vitro pharmacological studies, mouse models and analyses of human melanoma patients, we show that the cytokine GDF-15 impairs LFA-1/ß2-integrin-mediated adhesion of T cells to activated endothelial cells, which is a pre-requisite of T cell extravasation. In melanoma patients, GDF-15 serum levels strongly correlate with failure of PD-1-based immune checkpoint blockade therapy. Neutralization of GDF-15 improves both T cell trafficking and therapy efficiency in murine tumor models. Thus GDF-15, beside its known role in cancer-related anorexia and cachexia, emerges as a regulator of T cell extravasation into the tumor microenvironment, which provides an even stronger rationale for therapeutic anti-GDF-15 antibody development.

Neurooncology: 2023 update.

This article presents some of the author's neuropathological highlights in the field on neuro-oncology research encountered in 2022. Major advances were made in the development of more precise, faster, easier, less invasive and unbiased diagnostic tools ranging from immunohistochemical prediction of 1p/19q loss in diffuse glioma, methylation analyses in CSF samples, molecular profiling for CNS lymphoma, proteomic analyses of recurrent glioblastoma, integrated molecular diagnostics for better stratification in meningioma, intraoperative profiling making use of Raman effect or methylation analysis, to finally, the assessment of histological slides by means of machine learning for the prediction of molecular tumor features. In addition, as the discovery of a new tumor entity may also be a highlight for the neuropathology community, the newly described high-grade glioma with pleomorphic and pseudopapillary features (HPAP) has been selected for this article. Regarding new innovative treatment approaches, a drug screening platform for brain metastasis is presented. Although diagnostic speed and precision is steadily increasing, clinical prognosis for patients with malignant tumors affecting the nervous system remains largely unchanged over the last decade, therefore future neuro-oncological research focus should be put on how the amazing developments presented in this article can be more sustainably applied to positively impact patient prognosis.

Actin cytoskeleton depolymerization increases matrix metalloproteinase gene expression in breast cancer cells by promoting translocation of cysteine-rich protein 2 to the nucleus.

The actin cytoskeleton plays a critical role in cancer cell invasion and metastasis; however, the coordination of its multiple functions remains unclear. Actin dynamics in the cytoplasm control the formation of invadopodia, which are membrane protrusions that facilitate cancer cell invasion by focusing the secretion of extracellular matrix-degrading enzymes, including matrix metalloproteinases (MMPs). In this study, we investigated the nuclear role of cysteine-rich protein 2 (CRP2), a two LIM domain-containing F-actin-binding protein that we previously identified as a cytoskeletal component of invadopodia, in breast cancer cells. We found that F-actin depolymerization stimulates the translocation of CRP2 into the nucleus, resulting in an increase in the transcript levels of pro-invasive and pro-metastatic genes, including several members of the MMP gene family. We demonstrate that in the nucleus, CRP2 interacts with the transcription factor serum response factor (SRF), which is crucial for the expression of MMP-9 and MMP-13. Our data suggest that CRP2 and SRF cooperate to modulate of MMP expression levels. Furthermore, Kaplan-Meier analysis revealed a significant association between high-level expression of SRF and shorter overall survival and distant metastasis-free survival in breast cancer patients with a high CRP2 expression profile. Our findings suggest a model in which CRP2 mediates the coordination of cytoplasmic and nuclear processes driven by actin dynamics, ultimately resulting in the induction of invasive and metastatic behavior in breast cancer cells.

Single-cell transcriptomics of NRAS-mutated melanoma transitioning to drug resistance reveals P2RX7 as an indicator of early drug response.

Treatment options for patients with NRAS-mutant melanoma are limited and lack an efficient targeted drug combination that significantly increases overall and progression-free survival. In addition, targeted therapy success is hampered by the inevitable emergence of drug resistance. A thorough understanding of the molecular processes driving cancer cells' escape mechanisms is crucial to tailor more efficient follow-up therapies. We performed single-cell RNA sequencing of NRAS-mutant melanoma treated with MEK1/2 plus CDK4/6 inhibitors to decipher transcriptional transitions during the development of drug resistance. Cell lines resuming full proliferation (FACs [fast-adapting cells]) and cells that became senescent (SACs [slow-adapting cells]) over prolonged treatment were identified. The early drug response was characterized by transitional states involving increased ion signaling, driven by upregulation of the ATP-gated ion channel P2RX7. P2RX7 activation was associated with improved therapy responses and, in combination with targeted drugs, could contribute to the delayed onset of acquired resistance in NRAS-mutant melanoma.

Effects of Minocycline Hydrochloride as an Adjuvant Therapy for a Guided Bone Augmentation Procedure in The Rat Calvarium.

This in vivo study reports the influence of minocycline-HCl administration on extra-skeletal bone generation in a Guided Bone Augmentation model, utilizing titanium caps placed on the intact as well as perforated calvaria of rats. The test group was administered 0.5 mg/mL minocycline-HCl with the drinking water, and the amount of bone tissue in the caps was quantified at three time points (4, 8 and 16 weeks). A continuously increased tissue fill was observed in all groups over time. The administration of minocycline-HCl as well as perforation of the calvaria increased this effect, especially with regard to mineralization. The strongest tissue augmentation, with 1.8 times that of the untreated control group, and, at the same time, the most mineralized tissue (2.3× over untreated control), was produced in the combination of both treatments, indicating that systemic administration of minocycline-HCl has an accelerating and enhancing effect on vertical bone augmentation.

Propagative α-synuclein seeds as serum biomarkers for synucleinopathies.

Abnormal α-synuclein aggregation is a key pathological feature of a group of neurodegenerative diseases known as synucleinopathies, which include Parkinson's disease (PD), dementia with Lewy bodies and multiple system atrophy (MSA). The pathogenic ß-sheet seed conformation of α-synuclein is found in various tissues, suggesting potential as a biomarker, but few studies have been able to reliably detect these seeds in serum samples. In this study, we developed a modified assay system, called immunoprecipitation-based real-time quaking-induced conversion (IP/RT-QuIC), which enables the detection of pathogenic α-synuclein seeds in the serum of individuals with synucleinopathies. In our internal first and second cohorts, IP/RT-QuIC showed high diagnostic performance for differentiating PD versus controls (area under the curve (AUC): 0.96 (95% confidence interval (CI) 0.95-0.99)/AUC: 0.93 (95% CI 0.84-1.00)) and MSA versus controls (AUC: 0.64 (95% CI 0.49-0.79)/AUC: 0.73 (95% CI 0.49-0.98)). IP/RT-QuIC also showed high diagnostic performance in differentiating individuals with PD (AUC: 0.86 (95% CI 0.74-0.99)) and MSA (AUC: 0.80 (95% CI 0.65-0.97)) from controls in a blinded external cohort. Notably, amplified seeds maintained disease-specific properties, allowing the differentiation of samples from individuals with PD versus MSA. In summary, here we present a novel platform that may allow the detection of individuals with synucleinopathies using serum samples.

Digital PCR cluster predictor: a universal R-package and shiny app for the automated analysis of multiplex digital PCR data.

Digital polymerase chain reaction (dPCR) is an emerging technology that enables accurate and sensitive quantification of nucleic acids. Most available dPCR systems have two channel optics, with ad hoc software limited to the analysis of single and duplex assays. Although multiplexing strategies were developed, variable assay designs, dPCR systems, and the analysis of low DNA input data restricted the ability for a universal automated clustering approach. To overcome these issues, we developed dPCR Cluster Predictor (dPCP), an R package and a Shiny app for automated analysis of up to 4-plex dPCR data. dPCP can analyse and visualize data generated by multiple dPCR systems carrying out accurate and fast clustering not influenced by the amount and integrity of input of nucleic acids. With the companion Shiny app, the functionalities of dPCP can be accessed through a web browser.

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

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.