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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 Abstract

Abstract Background Preclinical in vivo cancer models are essential tools for investigating tumor progression and response to treatment prior to clinical trials. Although treatment modalities are regularly assessed in mice upon tumor growth in vivo, surgical resection remains challenging, particularly in the orthotopic site. Here, we report a successful surgical resection of glioblastoma (GBM) in patient-derived orthotopic xenografts (PDOXs). Methods We derived a cohort of 46 GBM PDOX models that faithfully recapitulate human disease in mice. We assessed the detection and quantification of intracranial tumors using magnetic resonance imaging (MRI).To evaluate feasibility of surgical resection in PDOXs, we selected two models representing histopathological features of GBM tumors, including diffuse growth into the mouse brain. Surgical resection in the mouse brains was performed based on MRI-guided coordinates. Survival study followed by MRI and immunohistochemistry-based evaluation of recurrent tumors allowed for assessment of clinically relevant parameters. Results We demonstrate the utility of MRI for the noninvasive assessment of in vivo tumor growth, preoperative programming of resection coordinates and follow-up of tumor recurrence. We report tumor detection by MRI in 90% of GBM PDOX models (36/40), of which 55% (22/40) can be reliably quantified during tumor growth. We show that a surgical resection protocol in mice carrying diffuse primary GBM tumors in the brain leads to clinically relevant outcomes. Similar to neurosurgery in patients, we achieved a near total to complete extent of tumor resection, and mice with resected tumors presented significantly increased survival. The remaining unresected GBM cells that invaded the normal mouse brain prior to surgery regrew tumors with similar histopathological features and tumor microenvironments to the primary tumors. Conclusions Our data positions GBM PDOXs developed in mouse brains as a valuable preclinical model for conducting therapeutic studies that involve surgical tumor resection. The high detectability of tumors by MRI across a substantial number of PDOX models in mice will allow for scalability of our approach toward specific tumor types for efficacy studies in precision medicine-oriented approaches. Additionally, these models hold promise for the development of enhanced image-guided surgery protocols.

Summary: Modeling tumor metabolism in vitro remains challenging. Here, we used galactose as an in vitro tool compound to mimic glycolytic limitation. In contrast to the established idea that high glycolytic flux reduces pyruvate kinase isozyme M2 (PKM2) activity to support anabolic processes, we have discovered that glycolytic limitation also affects PKM2 activity. Surprisingly, despite limited carbon availability and energetic stress, cells induce a near-complete block of PKM2 to divert carbons toward serine metabolism. Simultaneously, TCA cycle flux is sustained, and oxygen consumption is increased, supported by glutamine. Glutamine not only supports TCA cycle flux but also serine synthesis via distinct mechanisms that are directed through PKM2 inhibition. Finally, deleting mitochondrial one-carbon (1C) cycle reversed the PKM2 block, suggesting a potential formate-dependent crosstalk that coordinates mitochondrial 1C flux and cytosolic glycolysis to support cell survival and proliferation during nutrient-scarce conditions.

Summary: Metabolic rewiring is essential for cancer onset and progression. We previously showed that one-carbon metabolism-dependent formate production often exceeds the anabolic demand of cancer cells, resulting in formate overflow. Furthermore, we showed that increased extracellular formate concentrations promote the in vitro invasiveness of glioblastoma cells. Here, we substantiate these initial observations with ex vivo and in vivo experiments. We also show that exposure to exogeneous formate can prime cancer cells toward a pro-invasive phenotype leading to increased metastasis formation in vivo. Our results suggest that the increased local formate concentration within the tumor microenvironment can be one factor to promote metastases. Additionally, we describe a mechanistic interplay between formate-dependent increased invasiveness and adaptations of lipid metabolism and matrix metalloproteinase activity. Our findings consolidate the role of formate as pro-invasive metabolite and warrant further research to better understand the interplay between formate and lipid metabolism.

The evolutionary processes that drive universal therapeutic resistance in adult patients with diffuse glioma remain unclear1,2. Here we analysed temporally separated DNA-sequencing data and matched clinical annotation from 222 adult patients with glioma. By analysing mutations and copy numbers across the three major subtypes of diffuse glioma, we found that driver genes detected at the initial stage of disease were retained at recurrence, whereas there was little evidence of recurrence-specific gene alterations. Treatment with alkylating agents resulted in a hypermutator phenotype at different rates across the glioma subtypes, and hypermutation was not associated with differences in overall survival. Acquired aneuploidy was frequently detected in recurrent gliomas and was characterized by IDH mutation but without co-deletion of chromosome arms 1p/19q, and further converged with acquired alterations in the cell cycle and poor outcomes. The clonal architecture of each tumour remained similar over time, but the presence of subclonal selection was associated with decreased survival. Finally, there were no differences in the levels of immunoediting between initial and recurrent gliomas. Collectively, our results suggest that the strongest selective pressures occur during early glioma development and that current therapies shape this evolution in a largely stochastic manner.

Federated ML (FL) provides an alternative to train accurate and generalizable ML models, by only sharing numerical model updates. Here, the authors present the largest FL study to-date to generate an automatic tumor boundary detector for glioblastoma.

In glioblastoma (GBM), tumour‐associated microglia/macrophages (TAMs) represent the major cell type of the stromal compartment and contribute to tumour immune escape mechanisms. Thus, targeting TAMs is emerging as a promising strategy for immunotherapy. However, TAM heterogeneity and metabolic adaptation along GBM progression represent critical features for the design of effective TAM‐targeted therapies. Here, we comprehensively study the cellular and molecular changes of TAMs in the GL261 GBM mouse model, combining single‐cell RNA‐sequencing with flow cytometry and immunohistological analyses along GBM progression and in the absence of Acod1 (also known as Irg1), a key gene involved in the metabolic reprogramming of macrophages towards an anti‐inflammatory phenotype. Similarly to patients, we identify distinct TAM profiles, mainly based on their ontogeny, that reiterate the idea that microglia‐ and macrophage‐like cells show key transcriptional differences and dynamically adapt along GBM stages. Notably, we uncover decreased antigen‐presenting cell features and immune reactivity in TAMs along tumour progression that are instead enhanced in Acod1‐deficient mice. Overall, our results provide insight into TAM heterogeneity and highlight a novel role for Acod1 in TAM adaptation during GBM progression.

PurposeGlioblastoma (GBM) remains an incurable disease despite extensive treatment with surgical resection, irradiation, and temozolomide. In line with many other forms of aggressive cancers, GBM is currently under consideration as a target for immunotherapy. However, GBM tends to be nonimmunogenic and exhibits a microenvironment with few or no effector T cells, a relatively low nonsynonymous somatic mutational load, and a low predicted neoantigen burden. GBM also exploits a multitude of immunosuppressive strategies.Methods and materialsA number of immunotherapeutic approaches have been tested with disappointing results. A rationale exists to combine immunotherapy and radiation therapy, which can induce an immunogenic form of cell death with T-cell activation and tumor infiltration.ResultsVarious immunotherapy agents, including immune checkpoint modulators, transforming growth factor beta receptor inhibitors, and indoleamine-2,3-dioxygenase inhibitors, have been evaluated with irradiation in preclinical GBM models, with promising results, and are being further tested in clinical trials.ConclusionsThis review aims to present the basic rationale behind this emerging complementary therapeutic approach in GBM, appraise the current preclinical and clinical data, and discuss the future challenges in improving the antitumor immune response.

Adult diffuse gliomas are a diverse group of brain neoplasms that inflict a high emotional toll on patients and their families. The Cancer Genome Atlas and similar projects have provided a comprehensive understanding of the somatic alterations and molecular subtypes of glioma at diagnosis. However, gliomas undergo significant cellular and molecular evolution during disease progression. We review the current knowledge on the genomic and epigenetic abnormalities in primary tumors and after disease recurrence, highlight the gaps in the literature, and elaborate on the need for a new multi-institutional effort to bridge these knowledge gaps and how the Glioma Longitudinal Analysis Consortium (GLASS) aims to systemically catalog the longitudinal changes in gliomas. The GLASS initiative will provide essential insights into the evolution of glioma toward a lethal phenotype, with the potential to reveal targetable vulnerabilities and, ultimately, improved outcomes for a patient population in need.

Rat H-1 parvovirus (H-1PV) is in clinical development for oncolytic therapy. Here, Kulkarni et al. identify LAMC1 as a modulator of H-1PV cell attachment and entry and find that LAMC1 levels and H-1PV oncolytic activity correlate in 59 tested cancer cell lines.

Glioblastomas (GBMs) are highly invasive brain tumours, but the underlying mechanisms of GBM invasion are unclear. Here, the authors perform an RNA interference screen and identify AN1-Type Zinc Finger protein 3 (ZFAND3) as a regulator of GBM invasion, and find that it acts through the transcriptional regulation of invasion-related genes.

Summary: Glioblastoma (GBM) is the most aggressive primary brain tumor characterized by infiltrative growth of malignant glioma cells into the surrounding brain parenchyma. In this study, our analysis of GBM patient cohorts revealed a significantly higher expression of Glycosyltransferase 8 domain containing 1 (GLT8D1) compared to normal brain tissue and could be associated with impaired patient survival. Increased in vitro expression of GLT8D1 significantly enhanced migration of two different sphere-forming GBM cell lines. By in silico analysis we predicted the 3D-structure as well as the active site residues of GLT8D1. The introduction of point mutations in the predicted active site reduced its glycosyltransferase activity in vitro and consequently impaired GBM tumor cell migration. Examination of GLT8D1 interaction partners by LC-MS/MS implied proteins associated with cytoskeleton and intracellular transport as potential substrates. In conclusion, we demonstrated that the enzymatic activity of glycosyltransferase GLT8D1 promotes GBM cell migration.

Brain disorders represent 32% of the global disease burden, with 169 million Europeans affected. Constraint-based metabolic modelling and other approaches have been applied to predict new treatments for these and other diseases. Many recent studies focused on enhancing, among others, drug predictions by generating generic metabolic models of brain cells and on the contextualisation of the genome-scale metabolic models with expression data. Experimental flux rates were primarily used to constrain or validate the model inputs. Bi-cellular models were reconstructed to study the interaction between different cell types. This review highlights the evolution of genome-scale models for neurodegenerative diseases and glioma. We discuss the advantages and drawbacks of each approach and propose improvements, such as building bi-cellular models, tailoring the biomass formulations for glioma and refinement of the cerebrospinal fluid composition.

Summary: Tumor organoids and patient-derived orthotopic xenografts (PDOXs) are some of the most valuable pre-clinical tools in cancer research. In this protocol, we describe efficient derivation of organoids and PDOX models from glioma patient tumors. We provide detailed steps for organoid culture, intracranial implantation, and detection of tumors in the brain. We further present technical adjustments for standardized functional assays and drug testing.For complete details on the use and execution of this protocol, please refer to Golebiewska et al. (2020).

Cancer stem cells (CSCs) comprise a putative population that can drive growth and resistance. Here, in glioblastoma models the authors show that rather than being a distinct clonal entity, the CSC population represents a plastic state adoptable by most cancer cells via reversible state transitions induced by the microenvironment.

Purpose: Glioblastoma (GBM) remains an incurable disease despite extensive treatment with surgical resection, irradiation, and temozolomide. In line with many other forms of aggressive cancers, GBM is currently under consideration as a target for immunotherapy. However, GBM tends to be nonimmunogenic and exhibits a microenvironment with few or no effector T cells, a relatively low nonsynonymous somatic mutational load, and a low predicted neoantigen burden. GBM also exploits a multitude of immunosuppressive strategies. Methods and Materials: A number of immunotherapeutic approaches have been tested with disappointing results. A rationale exists to combine immunotherapy and radiation therapy, which can induce an immunogenic form of cell death with T-cell activation and tumor infiltration. Results: Various immunotherapy agents, including immune checkpoint modulators, transforming growth factor beta receptor inhibitors, and indoleamine-2,3-dioxygenase inhibitors, have been evaluated with irradiation in preclinical GBM models, with promising results, and are being further tested in clinical trials. Conclusions: This review aims to present the basic rationale behind this emerging complementary therapeutic approach in GBM, appraise the current preclinical and clinical data, and discuss the future challenges in improving the antitumor immune response.

The kynurenine pathway (KP) is the principal route of L-Tryptophan (TRP) catabolism leading to the production of kynurenine (KYN), the neuroprotectants, kynurenic acid (KYNA) and picolinic acid (PIC), and the excitotoxic neurotoxin, quinolinic acid (QUIN). The enzymes indoleamine 2,3-dioxygenase-1 (IDO-1), indoleamine 2, 3-dioxygenase-2 (IDO-2) and tryptophan 2,3-dioxygenase (TDO-2) initiate the first step of the KP. Downstream enzymes include kynureninase (KYNU), 3-hydroxyanthranilate 3,4-dioxygenase (3-HAAO), kynurenine hydroxylase (KMO) and 2-amino-3-carboxymuconate semialdehyde decarboxylase (ACMSD). Kynurenine aminotransferase-I (KAT-I) is one of the enzymes responsible for synthesising KYNA. Mounting evidence directly implicates that IDO-1 induction in various tumours is a crucial mechanism facilitating tumour immune evasion and persistence. However, the involvement of the downstream machinery of the KP in brain tumour progression remains unexplored. A complete characterisation of the KP in brain tumours and the role of the KP in maintaining homeostasis between neuroprotection and neurodegeneration in glioma has not yet been investigated. Here we report the first comprehensive characterisation of the KP in cultured human glioma cells and GBM patient plasma. Our qRT-PCR data revealed that interferon-gamma (IFN-γ) (100 IU/ml) stimulation significantly potentiated the expression of IDO-1 IDO-2, KYNU, 3-HAAO, KMO and significantly down-regulated ACMSD and KAT-I expression in cultured human glioma cells. HPLC analysis revealed that IFN-γ stimulation significantly increased KP activity (KYN/TRP ratio), and significantly lowered the KYNA/KYN neuroprotective ratio in human cultured glioma cells. Our HPLC and GCMS data revealed that KP activation was significantly higher and the concentrations of TRP, KYNA, QUIN and PIC and the KYNA/KYN ratio were significantly lower in GBM patient plasma (n = 18) compared to controls. These results provide further evidence for the involvement of the KP in glioma pathophysiology and highlights a potential role of KP products as novel and highly attractive therapeutic targets to evaluate for the treatment of brain tumours.

Malignant brain tumors remain uniformly fatal, even with the best-to-date treatment. For Glioblastoma (GBM), the most severe form of brain cancer in adults, the median overall survival is roughly over a year. New therapeutic options are urgently needed, yet recent clinical trials in the field have been largely disappointing. This is partially due to inappropriate preclinical model systems, which do not reflect the complexity of patient tumors. Furthermore, clinically relevant patient-derived models recapitulating the immune compartment are lacking, which represents a bottleneck for adequate immunotherapy testing. Emerging 3D organoid cultures offer innovative possibilities for cancer modeling. Here, we review available GBM organoid models amenable to a large variety of pre-clinical applications including functional bioassays such as proliferation and invasion, drug screening, and the generation of patient-derived orthotopic xenografts (PDOX) for validation of biological responses in vivo. We emphasize advantages and technical challenges in establishing immunocompetent ex vivo models based on co-cultures of GBM organoids and human immune cells. The latter can be isolated either from the tumor or from patient or donor blood as peripheral blood mononuclear cells (PBMCs). We also discuss the challenges to generate GBM PDOXs based on humanized mouse models to validate efficacy of immunotherapies in vivo. A detailed characterization of such models at the cellular and molecular level is needed to understand the potential and limitations for various immune activating strategies. Increasing the availability of immunocompetent GBM models will improve research on emerging immune therapeutic approaches against aggressive brain cancer.

Serine catabolism to formate supplies one-carbon units for biosynthesis. Here the authors show that formate production in murine cancers with high oxidative metabolism exceeds the biosynthetic demand and that high formate levels promotes invasion of cancer cells.

Background: The topological analysis of networks extracted from different types of “omics” data is a useful strategy for characterizing biologically meaningful properties of the complex systems underlying these networks. In particular, the biological significance of highly connected genes in diverse molecular networks has been previously determined using data from several model organisms and phenotypes. Despite such insights, the predictive potential of candidate hubs in gene co-expression networks in the specific context of cancer-related drug experiments remains to be deeply investigated. The examination of such associations may offer opportunities for the accurate prediction of anticancer drug responses. Methods: Here, we address this problem by: a) analyzing a co-expression network obtained from thousands of cancer cell lines, b) detecting significant network hubs, and c) assessing their capacity to predict drug sensitivity using data from thousands of drug experiments. We investigated the prediction capability of those genes using a multiple linear regression model, independent datasets, comparisons with other models and our own in vitro experiments. Results: These analyses led to the identification of 47 hub genes, which are implicated in a diverse range of cancer-relevant processes and pathways. Overall, encouraging agreements between predicted and observed drug sensitivities were observed in public datasets, as well as in our in vitro validations for four glioblastoma cell lines and four drugs. To facilitate further research, we share our hub-based drug sensitivity prediction model as an online tool. Conclusions: Our research shows that co-expression network hubs are biologically interesting and exhibit potential for predicting drug responses in vitro. These findings motivate further investigations about the relevance and application of our unbiased discovery approach in pre-clinical, translationally-oriented research.

Background: The topological analysis of networks extracted from different types of “omics” data is a useful strategy for characterizing biologically meaningful properties of the complex systems underlying these networks. In particular, the biological significance of highly connected genes in diverse molecular networks has been previously determined using data from several model organisms and phenotypes. Despite such insights, the predictive potential of candidate hubs in gene co-expression networks in the specific context of cancer-related drug experiments remains to be deeply investigated. The examination of such associations may offer opportunities for the accurate prediction of anticancer drug responses. Methods: Here, we address this problem by: a) analyzing a co-expression network obtained from thousands of cancer cell lines, b) detecting significant network hubs, and c) assessing their capacity to predict drug sensitivity using data from thousands of drug experiments. We investigated the prediction capability of those genes using a multiple linear regression model, independent datasets, comparisons with other models and our own in vitro experiments. Results: These analyses led to the identification of 47 hub genes, which are implicated in a diverse range of cancer-relevant processes and pathways. Overall, encouraging agreements between predicted and observed drug sensitivities were observed in public datasets, as well as in our in vitro validations for four glioblastoma cell lines and four drugs. To facilitate further research, we share our hub-based drug sensitivity prediction model as an online tool. Conclusions: Our research shows that co-expression network hubs are biologically interesting and exhibit potential for predicting drug responses in vitro. These findings motivate further investigations about the relevance and application of our unbiased discovery approach in pre-clinical, translationally-oriented research.

Abstract The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact to coordinate heart regeneration. To enable systematic insights into this phenomenon, we generated and integrated a dynamic co-expression network of heart regeneration in the zebrafish and linked systems-level properties to the underlying molecular events. Across multiple post-injury time points, the network displays topological attributes of biological relevance. We show that regeneration steps are mediated by modules of transcriptionally coordinated genes, and by genes acting as network hubs. We also established direct associations between hubs and validated drivers of heart regeneration with murine and human orthologs. The resulting models and interactive analysis tools are available at http://infused.vital-it.ch . Using a worked example, we demonstrate the usefulness of this unique open resource for hypothesis generation and in silico screening for genes involved in heart regeneration.

Cancer heterogeneity and progression are subject to complex interactions between neoplastic cells and their microenvironment, including the immune system. Although glioblastomas (GBMs) are classified as ‘cold tumours’ with very little lymphocyte infiltration, they can contain up to 30−40% of tumour-associated macrophages, reported to contribute to a supportive microenvironment that facilitates tumour proliferation, survival and migration. In GBM, tumour-associated macrophages comprise either resident parenchymal microglia, perivascular macrophages or peripheral monocyte-derived cells. They are recruited by GBMs and in turn release growth factors and cytokines that affect the tumour. Notably, tumour-associated microglia/macrophages (TAMs) acquire different expression programs, which shape the tumour microenvironment and contribute to GBM molecular subtyping. Further, emerging evidence highlights that TAM programs may adapt to specific tumour features and landscapes. Here, we review key evidence describing TAM transcriptional and functional heterogeneity in GBM. We propose that unravelling the intricate complexity and diversity of the myeloid compartment as well as understanding how different TAM subsets may affect tumour progression will possibly pave the way to new immune therapeutic avenues for GBM patients.