Generation of glioblastoma in mice engrafted with human cytomegalovirus-infected astrocytes.

Mounting evidence is identifying human cytomegalovirus (HCMV) as a potential oncogenic virus. HCMV has been detected in glioblastoma multiforme (GB). Herewith, we present the first experimental evidence for the generation of CMV-Elicited Glioblastoma Cells (CEGBCs) possessing glioblastoma-like traits that lead to the formation of glioblastoma in orthotopically xenografted mice. In addition to the already reported oncogenic HCMV-DB strain, we isolated three HCMV clinical strains from GB tissues that transformed HAs toward CEGBCs and generated spheroids from CEGBCs that resulted in the appearance of glioblastoma-like tumors in xenografted mice. These tumors were nestin-positive mostly in the invasive part surrounded by GFAP-positive reactive astrocytes. The glioblastoma immunohistochemistry phenotype was confirmed by EGFR and cMet gene amplification in the tumor parallel to the detection of HCMV IE and UL69 genes and proteins. Our results fit with an HCMV-induced glioblastoma model of oncogenesis in vivo which will open the door to new therapeutic approaches and assess the anti-HCMV treatment as well as immunotherapy in fighting GB which is characterized by poor prognosis.

New insights into the role of thrombospondin-1 in glioblastoma development.

Glioblastoma (GB), the most malignant subtype of diffuse glioma, is highly aggressive, invasive and vascularized. Its median survival is still short even with maximum standard care. There is a need to identify potential new molecules and mechanisms, that are involved in the interactions of GB cells with the tumor microenvironment (TME), for therapeutic intervention. Thrombospondin-1 (TSP1) is a multi-faceted matricellular protein which plays a significant role in development, physiology and pathology including cancer. Recent studies have pinpoint an important role of TSP1 in GB development which will be summarized and discussed herein. We will discuss studies, mainly from preclinical research, which should lead to a deeper understanding of TSP1's role in GB development. We will also discuss some issues with regard to the use of this knowledge for the clinic.

Shadow imaging for panoptical visualization of brain tissue in vivo.

Progress in neuroscience research hinges on technical advances in visualizing living brain tissue with high fidelity and facility. Current neuroanatomical imaging approaches either require tissue fixation (electron microscopy), do not have cellular resolution (magnetic resonance imaging) or only give a fragmented view (fluorescence microscopy). Here, we show how regular light microscopy together with fluorescence labeling of the interstitial fluid in the extracellular space provide comprehensive optical access in real-time to the anatomical complexity and dynamics of living brain tissue at submicron scale. Using several common fluorescence microscopy modalities (confocal, light-sheet and 2-photon microscopy) in mouse organotypic and acute brain slices and the intact mouse brain in vivo, we demonstrate the value of this straightforward 'shadow imaging' approach by revealing neurons, microglia, tumor cells and blood capillaries together with their complete anatomical tissue contexts. In addition, we provide quantifications of perivascular spaces and the volume fraction of the extracellular space of brain tissue in vivo.

Structural Properties of CXCL4L1 and Its Recognition of the CXCR3 N-Terminus.

Chemokine CXCL4L1, a homologue of CXCL4, is a more potent antiangiogenic ligand. Its structural property is correlated with the downstream receptor binding. The two chemokines execute their functions by binding the receptors of CXCR3A and CXCR3B. The receptors differ by an extra 51-residue extension in the CXCR3B N-terminus. To understand the binding specificity, a GB1 protein scaffold was used to carry different CXCR3 extracellular elements, and artificial CXCL4 and CXCL4L1 monomers were engineered for the binding assay. We first characterized the molten globule property of CXCL4L1. The structural property causes the CXCL4L1 tetramer to dissociate into monomers in low concentrations, but native CXCL4 adopts a stable tetramer structure in solution. In the titration experiments, the combination of the CXCR3A N-terminus and receptor extracellular loop 2 provided moderate and comparable binding affinities to CXCL4 and CXCL4L1, while sulfation on the CXCR3A N-terminal tyrosine residues provided binding specificity. However, the CXCR3B N-terminal extension did not show significant enhancement in the binding of CXCL4 or CXCL4L1. This result indicates that the tendency to form a chemokine monomer and the binding affinity together contribute the high antiangiogenic activity of CXCL4L1.

Challenges in glioblastoma research: focus on the tumor microenvironment.

Glioblastoma (GBM) is the most deadly type of malignant brain tumor, despite extensive molecular analyses of GBM cells. In recent years, the tumor microenvironment (TME) has been recognized as an important player and therapeutic target in GBM. However, there is a need for a full and integrated understanding of the different cellular and molecular components involved in the GBM TME and their interactions for the development of more efficient therapies. In this review, we provide a comprehensive report of the GBM TME, which assembles the contributions of physicians and translational researchers working on brain tumor pathology and therapy in France. We propose a holistic view of the subject by delineating the specific features of the GBM TME at the cellular, molecular, and therapeutic levels.

Deep learning model for automatic segmentation of lungs and pulmonary metastasis in small animal MR images.

Lungs are the most frequent site of metastases growth. The amount and size of pulmonary metastases acquired from MRI imaging data are the important criteria to assess the efficacy of new drugs in preclinical models. While efficient solutions both for MR imaging and the downstream automatic segmentation have been proposed for human patients, both MRI lung imaging and segmentation in preclinical animal models remains challenging due to the physiological motion (respiratory and cardiac movements), to the low amount of protons in this organ and to the particular challenge of precise segmentation of metastases. As a consequence post-mortem analysis is currently required to obtain information on metastatic volume. In this work, we have developed a complete methodological pipeline for automated analysis of lungs and metastases in mice, consisting of an MR sequence for image acquisition and a deep learning method for automatic segmentation of both lungs and metastases. On one hand, we optimized an MR sequence for mouse lung imaging with high contrast for high detection sensitivity. On the other hand we developed DeepMeta, a multiclass U-Net 3+ deep learning model to automatically segment the images. To assess if the proposed deep learning pipeline is able to provide an accurate segmentation of both lungs and pulmonary metastases, we have longitudinally imaged mice with fast- and slow-growing metastasis. Fifty-five balb/c mice were injected with two different derivatives of renal carcinoma cells. Mice were imaged with a SG-bSSFP (self-gated balanced steady state free precession) sequence at different time points after the injection of cancer cells. Both lung and metastases segmentations were manually performed by experts. DeepMeta was trained to perform lung and metastases segmentation based on the resulting ground truth annotations. Volumes of lungs and of pulmonary metastases as well as the number of metastases per mouse were measured on a separate test dataset of MR images. Thanks to the SG method, the 3D bSSFP images of lungs were artifact-free, enabling the downstream detection and serial follow-up of metastases. Moreover, both lungs and metastases segmentation was accurately performed by DeepMeta as soon as they reached the volume of ∼ 0.02 m m 3 . Thus we were able to distinguish two groups of mice in terms of number and volume of pulmonary metastases as well as in terms of the slow versus fast patterns of growth of metastases. We have shown that our methodology combining SG-bSSFP with deep learning, enables processing of the whole animal lungs and is thus a viable alternative to histology alone.

Lactate dehydrogenases promote glioblastoma growth and invasion via a metabolic symbiosis.

Lactate is a central metabolite in brain physiology but also contributes to tumor development. Glioblastoma (GB) is the most common and malignant primary brain tumor in adults, recognized by angiogenic and invasive growth, in addition to its altered metabolism. We show herein that lactate fuels GB anaplerosis by replenishing the tricarboxylic acid (TCA) cycle in absence of glucose. Lactate dehydrogenases (LDHA and LDHB), which we found spatially expressed in GB tissues, catalyze the interconversion of pyruvate and lactate. However, ablation of both LDH isoforms, but not only one, led to a reduction in tumor growth and an increase in mouse survival. Comparative transcriptomics and metabolomics revealed metabolic rewiring involving high oxidative phosphorylation (OXPHOS) in the LDHA/B KO group which sensitized tumors to cranial irradiation, thus improving mouse survival. When mice were treated with the antiepileptic drug stiripentol, which targets LDH activity, tumor growth decreased. Our findings unveil the complex metabolic network in which both LDHA and LDHB are integrated and show that the combined inhibition of LDHA and LDHB strongly sensitizes GB to therapy.

Connexins orchestrate progression of breast cancer metastasis to the brain by promoting FAK activation.

Brain metastasis is a complication of increasing incidence in patients with breast cancer at advanced disease stage. It is a severe condition characterized by a rapid decline in quality of life and poor prognosis. There is a critical clinical need to develop effective therapies to prevent and treat brain metastases. Here, we describe a unique and robust spontaneous preclinical model of breast cancer metastasis to the brain (4T1-BM2) in mice that has been instrumental in uncovering molecular mechanisms guiding metastatic dissemination and colonization of the brain. Key experimental findings were validated in the additional murine D2A1-BM2 model and in human MDA231-BrM2 model. Gene expression analyses and functional studies, coupled with clinical transcriptomic and histopathological investigations, identified connexins (Cxs) and focal adhesion kinase (FAK) as master molecules orchestrating breast cancer colonization of the brain. Cx31 promoted homotypic tumor cell adhesion, heterotypic tumor-astrocyte interaction, and FAK phosphorylation. FAK signaling prompted NF-κB activation inducing Lamc2 expression and laminin 332 (laminin 5) deposition, α6 integrin-mediated adhesion, and sustained survival and growth within brain parenchyma. In the MDA231-BrM2 model, the human homologous molecules CX43, LAMA4, and α3 integrin were involved. Systemic treatment with FAK inhibitors reduced brain metastasis progression. In conclusion, we report a spontaneous model of breast cancer metastasis to the brain and identified Cx-mediated FAK-NF-κB signaling as a mechanism promoting cell-autonomous and microenvironmentally controlled cell survival for brain colonization. Considering the limited therapeutic options for brain metastatic disease in cancer patients, we propose FAK as a therapeutic candidate to further pursue in the clinic.

Practical identifiability analysis of a mechanistic model for the time to distant metastatic relapse and its application to renal cell carcinoma.

Distant metastasis-free survival (DMFS) curves are widely used in oncology. They are classically analyzed using the Kaplan-Meier estimator or agnostic statistical models from survival analysis. Here we report on a method to extract more information from DMFS curves using a mathematical model of primary tumor growth and metastatic dissemination. The model depends on two parameters, α and µ, respectively quantifying tumor growth and dissemination. We assumed these to be lognormally distributed in a patient population. We propose a method for identification of the parameters of these distributions based on least-squares minimization between the data and the simulated survival curve. We studied the practical identifiability of these parameters and found that including the percentage of patients with metastasis at diagnosis was critical to ensure robust estimation. We also studied the impact and identifiability of covariates and their coefficients in α and µ, either categorical or continuous, including various functional forms for the latter (threshold, linear or a combination of both). We found that both the functional form and the coefficients could be determined from DMFS curves. We then applied our model to a clinical dataset of metastatic relapse from kidney cancer with individual data of 105 patients. We show that the model was able to describe the data and illustrate our method to disentangle the impact of three covariates on DMFS: a categorical one (Führman grade) and two continuous ones (gene expressions of the macrophage mannose receptor 1 (MMR) and the G Protein-Coupled Receptor Class C Group 5 Member A (GPRC5a) gene). We found that all had an influence in metastasis dissemination (µ), but not on growth (α).

Different cardiovascular and pulmonary phenotypes for single- and double-knock-out mice deficient in BMP9 and BMP10.

AIMS: BMP9 and BMP10 mutations were recently identified in patients with pulmonary arterial hypertension, but their specific roles in the pathogenesis of the disease are still unclear. We aimed to study the roles of BMP9 and BMP10 in cardiovascular homeostasis and pulmonary hypertension using transgenic mouse models deficient in Bmp9 and/or Bmp10. METHODS AND RESULTS: Single- and double-knockout mice for Bmp9 (constitutive) and/or Bmp10 (tamoxifen inducible) were generated. Single-knock-out (KO) mice developed no obvious age-dependent phenotype when compared with their wild-type littermates. However, combined deficiency in Bmp9 and Bmp10 led to vascular defects resulting in a decrease in peripheral vascular resistance and blood pressure and the progressive development of high-output heart failure and pulmonary hemosiderosis. RNAseq analysis of the lungs of the double-KO mice revealed differential expression of genes involved in inflammation and vascular homeostasis. We next challenged these mice to chronic hypoxia. After 3 weeks of hypoxic exposure, Bmp10-cKO mice showed an enlarged heart. However, although genetic deletion of Bmp9 in the single- and double-KO mice attenuated the muscularization of pulmonary arterioles induced by chronic hypoxia, we observed no differences in Bmp10-cKO mice. Consistent with these results, endothelin-1 levels were significantly reduced in Bmp9 deficient mice but not Bmp10-cKO mice. Furthermore, the effects of BMP9 on vasoconstriction were inhibited by bosentan, an endothelin receptor antagonist, in a chick chorioallantoic membrane assay. CONCLUSIONS: Our data show redundant roles for BMP9 and BMP10 in cardiovascular homeostasis under normoxic conditions (only combined deletion of both Bmp9 and Bmp10 was associated with severe defects) but highlight specific roles under chronic hypoxic conditions. We obtained evidence that BMP9 contributes to chronic hypoxia-induced pulmonary vascular remodelling, whereas BMP10 plays a role in hypoxia-induced cardiac remodelling in mice.

TGF-ß promotes microtube formation in glioblastoma through thrombospondin 1.

BACKGROUND: Microtubes (MTs), cytoplasmic extensions of glioma cells, are important cell communication structures promoting invasion and treatment resistance through network formation. MTs are abundant in chemoresistant gliomas, in particular, glioblastomas (GBMs), while they are uncommon in chemosensitive IDH-mutant and 1p/19q co-deleted oligodendrogliomas. The aim of this study was to identify potential signaling pathways involved in MT formation. METHODS: Bioinformatics analysis of TCGA was performed to analyze differences between GBM and oligodendroglioma. Patient-derived GBM stem cell lines were used to investigate MT formation under transforming growth factor-beta (TGF-ß) stimulation and inhibition in vitro and in vivo in an orthotopic xenograft model. RNA sequencing and proteomics were performed to detect commonalities and differences between GBM cell lines stimulated with TGF-ß. RESULTS: Analysis of TCGA data showed that the TGF-ß pathway is highly activated in GBMs compared to oligodendroglial tumors. We demonstrated that TGF-ß1 stimulation of GBM cell lines promotes enhanced MT formation and communication via calcium signaling. Inhibition of the TGF-ß pathway significantly reduced MT formation and its associated invasion in vitro and in vivo. Downstream of TGF-ß, we identified thrombospondin 1 (TSP1) as a potential mediator of MT formation in GBM through SMAD activation. TSP1 was upregulated upon TGF-ß stimulation and enhanced MT formation, which was inhibited by TSP1 shRNAs in vitro and in vivo. CONCLUSION: TGF-ß and its downstream mediator TSP1 are important mediators of the MT network in GBM and blocking this pathway could potentially help to break the complex MT-driven invasion/resistance network.

LRP-1 Matricellular Receptor Involvement in Triple Negative Breast Cancer Tumor Angiogenesis.

BACKGROUND: LRP-1 is a multifunctional scavenger receptor belonging to the LDLR family. Due to its capacity to control pericellular levels of various growth factors and proteases, LRP-1 plays a crucial role in membrane proteome dynamics, which appears decisive for tumor progression. METHODS: LRP-1 involvement in a TNBC model was assessed using an RNA interference strategy in MDA-MB-231 cells. In vivo, tumorigenic and angiogenic effects of LRP-1-repressed cells were evaluated using an orthotopic xenograft model and two angiogenic assays (Matrigel® plugs, CAM). DCE-MRI, FMT, and IHC were used to complete a tumor longitudinal follow-up and obtain morphological and functional vascular information. In vitro, HUVECs' angiogenic potential was evaluated using a tumor secretome, subjected to a proteomic analysis to highlight LRP-1-dependant signaling pathways. RESULTS: LRP-1 repression in MDA-MB-231 tumors led to a 60% growth delay because of, inter alia, morphological and functional vascular differences, confirmed by angiogenic models. In vitro, the LRP-1-repressed cells secretome restrained HUVECs' angiogenic capabilities. A proteomics analysis revealed that LRP-1 supports tumor growth and angiogenesis by regulating TGF-ß signaling and plasminogen/plasmin system. CONCLUSIONS: LRP-1, by its wide spectrum of interactions, emerges as an important matricellular player in the control of cancer-signaling events such as angiogenesis, by supporting tumor vascular morphology and functionality.

Experimental and computational modeling for signature and biomarker discovery of renal cell carcinoma progression.

BACKGROUND: Renal Cell Carcinoma (RCC) is difficult to treat with 5-year survival rate of 10% in metastatic patients. Main reasons of therapy failure are lack of validated biomarkers and scarce knowledge of the biological processes occurring during RCC progression. Thus, the investigation of mechanisms regulating RCC progression is fundamental to improve RCC therapy. METHODS: In order to identify molecular markers and gene processes involved in the steps of RCC progression, we generated several cell lines of higher aggressiveness by serially passaging mouse renal cancer RENCA cells in mice and, concomitantly, performed functional genomics analysis of the cells. Multiple cell lines depicting the major steps of tumor progression (including primary tumor growth, survival in the blood circulation and metastatic spread) were generated and analyzed by large-scale transcriptome, genome and methylome analyses. Furthermore, we performed clinical correlations of our datasets. Finally we conducted a computational analysis for predicting the time to relapse based on our molecular data. RESULTS: Through in vivo passaging, RENCA cells showed increased aggressiveness by reducing mice survival, enhancing primary tumor growth and lung metastases formation. In addition, transcriptome and methylome analyses showed distinct clustering of the cell lines without genomic variation. Distinct signatures of tumor aggressiveness were revealed and validated in different patient cohorts. In particular, we identified SAA2 and CFB as soluble prognostic and predictive biomarkers of the therapeutic response. Machine learning and mathematical modeling confirmed the importance of CFB and SAA2 together, which had the highest impact on distant metastasis-free survival. From these data sets, a computational model predicting tumor progression and relapse was developed and validated. These results are of great translational significance. CONCLUSION: A combination of experimental and mathematical modeling was able to generate meaningful data for the prediction of the clinical evolution of RCC.

Tumor Cell Invasion and the Tumor Microenvironment: Special Focus on Brain Tumors.

Tumor cell invasion is a major issue in oncology since it leads to tumor dissemination and recurrence. In glioblastomas, invasion is an important characteristic, making the disease difficult to treat since tumor recurrence occurs from invasive areas at the borders of the resection cavity. We are discussing herein some of the principal mechanisms at a cellular and molecular level that are involved in glioblastoma invasion. These mechanisms are comprising tumor cell intrinsic factors as well as extrinsic factors and cues produced by the tumor microenvironment. Therapeutically interfering with tumor cell invasion may be useful to improve the clinical outcomes of glioblastoma patients.

SLIT2/ROBO signaling in tumor-associated microglia and macrophages drives glioblastoma immunosuppression and vascular dysmorphia.

SLIT2 is a secreted polypeptide that guides migration of cells expressing Roundabout 1 and 2 (ROBO1 and ROBO2) receptors. Herein, we investigated SLIT2/ROBO signaling effects in gliomas. In patients with glioblastoma (GBM), SLIT2 expression increased with malignant progression and correlated with poor survival and immunosuppression. Knockdown of SLIT2 in mouse glioma cells and patient-derived GBM xenografts reduced tumor growth and rendered tumors sensitive to immunotherapy. Tumor cell SLIT2 knockdown inhibited macrophage invasion and promoted a cytotoxic gene expression profile, which improved tumor vessel function and enhanced efficacy of chemotherapy and immunotherapy. Mechanistically, SLIT2 promoted microglia/macrophage chemotaxis and tumor-supportive polarization via ROBO1- and ROBO2-mediated PI3K-γ activation. Macrophage Robo1 and Robo2 deletion and systemic SLIT2 trap delivery mimicked SLIT2 knockdown effects on tumor growth and the tumor microenvironment (TME), revealing SLIT2 signaling through macrophage ROBOs as a potentially novel regulator of the GBM microenvironment and immunotherapeutic target for brain tumors.

The Normal and Brain Tumor Vasculature: Morphological and Functional Characteristics and Therapeutic Targeting.

Glioblastoma is among the most common tumor of the central nervous system in adults. Overall survival has not significantly improved over the last decade, even with optimizing standard therapeutic care including extent of resection and radio- and chemotherapy. In this article, we review features of the brain vasculature found in healthy cerebral tissue and in glioblastoma. Brain vessels are of various sizes and composed of several vascular cell types. Non-vascular cells such as astrocytes or microglia also interact with the vasculature and play important roles. We also discuss in vitro engineered artificial blood vessels which may represent useful models for better understanding the tumor-vessel interaction. Finally, we summarize results from clinical trials with anti-angiogenic therapy alone or in combination, and discuss the value of these approaches for targeting glioblastoma.

Co-culture of Glioblastoma Stem-like Cells on Patterned Neurons to Study Migration and Cellular Interactions.

Glioblastomas (GBMs), grade IV malignant gliomas, are one of the deadliest types of human cancer because of their aggressive characteristics. Despite significant advances in the genetics of these tumors, how GBM cells invade the healthy brain parenchyma is not well understood. Notably, it has been shown that GBM cells invade the peritumoral space via different routes; the main interest of this paper is the route along white matter tracts (WMTs). The interactions of tumor cells with the peritumoral nervous cell components are not well characterized. Herein, a method has been described that evaluates the impact of neurons on GBM cell invasion. This paper presents an advanced co-culture in vitro assay that mimics WMT invasion by analyzing the migration of GBM stem-like cells on neurons. The behavior of GBM cells in the presence of neurons is monitored by using an automated tracking procedure with open-source and free-access software. This method is useful for many applications, in particular, for functional and mechanistic studies as well as for analyzing the effects of pharmacological agents that can block GBM cell migration on neurons.