A Patient-Derived Cell Atlas Informs Precision Targeting of Glioblastoma

Biomimetic Approach of Brain Vasculature Rapidly Characterizes Inter- and Intra-Patient Migratory Diversity of Glioblastoma

Glioblastomas exhibit remarkable heterogeneity at various levels, including motility modes and mechanoproperties that contribute to tumor resistance and recurrence. In a recent study using gridded micropatterns mimicking the brain vasculature, glioblastoma cell motility modes, mechanical properties, formin content, and substrate chemistry are linked. Now is presented, SP2G (SPheroid SPreading on Grids), an analytic platform designed to identify the migratory modes of patient-derived glioblastoma cells and rapidly pinpoint the most invasive sub-populations. Tumorspheres are imaged as they spread on gridded micropatterns and analyzed by this semi-automated, open-source, Fiji macro suite that characterizes migration modes accurately. SP2G can reveal intra-patient motility heterogeneity with molecular correlations to specific integrins and EMT markers. This system presents a versatile and potentially pan-cancer workflow to detect diverse invasive tumor sub-populations in patient-derived specimens and offers a valuable tool for therapeutic evaluations at the individual patient level.

Multi-omics analysis identifies repurposing bortezomib in the treatment of kidney-, nervous system-, and hematological cancers

Repurposing of FDA-approved drugs is a quick and cost-effective alternative to de novo drug development. Here, we identify genes involved in bortezomib sensitivity, predict cancer types that may benefit from treatment with bortezomib, and evaluate the mechanism-of-action of bortezomib in breast cancer (BT-474 and ZR-75-30), melanoma (A-375), and glioblastoma (A-172) cells in vitro. Cancer cell lines derived from cancers of the blood, kidney, nervous system, and skin were found to be significantly more sensitive to bortezomib than other organ systems. The in vitro studies confirmed that although bortezomib effectively inhibited the β5 catalytic site in all four cell lines, cell cycle arrest was only induced in G2/M phase and apoptosis in A-375 and A-172 after 24h. The genomic and transcriptomic analyses identified 33 genes (e.g. ALDH18A1, ATAD2) associated with bortezomib resistance. Taken together, we identified biomarkers predictive of bortezomib sensitivity and cancer types that might benefit from treatment with bortezomib.

Multi-omics and pharmacological characterization of patient-derived glioma cell lines

Glioblastoma (GBM) is the most common brain tumor and remains incurable. Primary GBM cultures are widely used tools for drug screening, but there is a lack of genomic and pharmacological characterization for these primary GBM cultures. Here, we collect 50 patient-derived glioma cell (PDGC) lines and characterize them by whole genome sequencing, RNA sequencing, and drug response screening. We identify three molecular subtypes among PDGCs: mesenchymal (MES), proneural (PN), and oxidative phosphorylation (OXPHOS). Drug response profiling reveals that PN subtype PDGCs are sensitive to tyrosine kinase inhibitors, whereas OXPHOS subtype PDGCs are sensitive to histone deacetylase inhibitors, oxidative phosphorylation inhibitors, and HMG-CoA reductase inhibitors. PN and OXPHOS subtype PDGCs stably form tumors in vivo upon intracranial transplantation into immunodeficient mice, whereas most MES subtype PDGCs fail to form tumors in vivo. In addition, PDGCs cultured by serum-free medium, especially long-passage PDGCs, carry MYC/MYCN amplification, which is rare in GBM patients. Our study provides a valuable resource for understanding primary glioma cell cultures and clinical translation and highlights the problems of serum-free PDGC culture systems that cannot be ignored.

A clinically applicable connectivity signature for glioblastoma includes the tumor network driver CHI3L1

Tumor microtubes (TMs) connect glioma cells to a network with considerable relevance for tumor progression and therapy resistance. However, the determination of TM-interconnectivity in individual tumors is challenging and the impact on patient survival unresolved. Here, we establish a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells using a dye uptake methodology, and validate it with recording of cellular calcium epochs and clinical correlations. Astrocyte-like and mesenchymal-like GB cells have the highest connectivity signature scores in scRNA-sequenced patient-derived xenografts and patient samples. In large GB cohorts, TM-network connectivity correlates with the mesenchymal subtype and dismal patient survival. CHI3L1 gene expression serves as a robust molecular marker of connectivity and functionally influences TM networks. The connectivity signature allows insights into brain tumor biology, provides a proof-of-principle that tumor cell TM-connectivity is relevant for patients' prognosis, and serves as a robust prognostic biomarker.

Proteasome Inhibitors against Glioblastoma-Overview of Molecular Mechanisms of Cytotoxicity, Progress in Clinical Trials, and Perspective for Use in Personalized Medicine

Proteasome inhibitors are moieties targeting the proteolytic activity of a proteasome, with demonstrated efficacy in certain hematological malignancies and candidate drugs in other types of cancer, including glioblastoma (GBM). They disturb the levels of proteasome-regulated proteins and lead to the cell cycle inhibition and apoptosis of GBM cells. The accumulation of cell cycle inhibitors p21 and p27, and decreased levels of prosurvival molecules NFKB, survivin, and MGMT, underlie proteasome inhibitors' cytotoxicity when used alone or in combination with the anti-GBM cytostatic drug temozolomide (TMZ). The evidence gathered in preclinical studies substantiated the design of clinical trials that employed the two most promising proteasome inhibitors, bortezomib and marizomib. The drug safety profile, maximum tolerated dose, and interaction with other drugs were initially evaluated, mainly in recurrent GBM patients. A phase III study on newly diagnosed GBM patients who received marizomib as an adjuvant to the Stupp protocol was designed and completed in 2021, with the Stupp protocol receiving patients as a parallel control arm. The data from this phase III study indicate that marizomib does not improve the PFS and OS of GBM patients; however, further analysis of the genetic and epigenetic background of each patient tumor may shed some light on the sensitivity of individual patients to proteasome inhibition. The mutational and epigenetic makeup of GBM cells, like genetic alterations to TP53 and PTEN, or MGMT promoter methylation levels may actually determine the response to proteasome inhibition.

Multi-omic integration of DNA methylation and gene expression data reveals molecular vulnerabilities in glioblastoma

Glioblastoma (GBM) is one of the most aggressive types of cancer and exhibits profound genetic and epigenetic heterogeneity, making the development of an effective treatment a major challenge. The recent incorporation of molecular features into the diagnosis of patients with GBM has led to an improved categorization into various tumour subtypes with different prognoses and disease management. In this work, we have exploited the benefits of genome-wide multi-omic approaches to identify potential molecular vulnerabilities existing in patients with GBM. Integration of gene expression and DNA methylation data from both bulk GBM and patient-derived GBM stem cell lines has revealed the presence of major sources of GBM variability, pinpointing subtype-specific tumour vulnerabilities amenable to pharmacological interventions. In this sense, inhibition of the AP-1, SMAD3 and RUNX1/RUNX2 pathways, in combination or not with the chemotherapeutic agent temozolomide, led to the subtype-specific impairment of tumour growth, particularly in the context of the aggressive, mesenchymal-like subtype. These results emphasize the involvement of these molecular pathways in the development of GBM and have potential implications for the development of personalized therapeutic approaches.

Inference of glioblastoma migration and proliferation rates using single time-point images

Cancer cell migration is a driving mechanism of invasion in solid malignant tumors. Anti-migratory treatments provide an alternative approach for managing disease progression. However, we currently lack scalable screening methods for identifying novel anti-migratory drugs. To this end, we develop a method that can estimate cell motility from single end-point images in vitro by estimating differences in the spatial distribution of cells and inferring proliferation and diffusion parameters using agent-based modeling and approximate Bayesian computation. To test the power of our method, we use it to investigate drug responses in a collection of 41 patient-derived glioblastoma cell cultures, identifying migration-associated pathways and drugs with potent anti-migratory effects. We validate our method and result in both in silico and in vitro using time-lapse imaging. Our proposed method applies to standard drug screen experiments, with no change needed, and emerges as a scalable approach to screen for anti-migratory drugs.

Screening MT1-MMP Activity and Inhibition in Three-Dimensional Tumor Spheroids

Membrane type 1 matrix metalloproteinase (MT1-MMP) has been shown to be crucial for tumor angiogenesis, invasion, and metastasis, and thus MT1-MMP is a high priority target for potential cancer therapies. To properly evaluate MT1-MMP inhibitors, a screening protocol is desired by which enzyme activity can be quantified in a tumor microenvironment-like model system. In the present study, we applied a fluorogenic, collagen model triple-helical substrate to quantify MT1-MMP activity for tumor spheroids embedded in a collagen hydrogel. The substrate was designed to be MT1-MMP selective and to possess fluorescent properties compatible with cell-based assays. The proteolysis of the substrate correlated to glioma spheroid invasion. In turn, the application of either small molecule or protein-based MMP inhibitors reduced proteolytic activity and glioma spheroid invasion. The presence of MT1-MMP in glioma spheroids was confirmed by western blotting. Thus, spheroid invasion was dependent on MT1-MMP activity, and inhibitors of MT1-MMP and invasion could be conveniently screened in a high-throughput format. The combination of the fluorogenic, triple-helical substrate, the three-dimensional tumor spheroids embedded in collagen, and Hit-Pick software resulted in an easily adaptable in vivo-like tumor microenvironment for rapidly processing inhibitor potential for anti-cancer use.

Glioblastoma stem cells express non-canonical proteins and exclusive mesenchymal-like or non-mesenchymal-like protein signatures

Glioblastoma (GBM) cancer stem cells (GSCs) contribute to GBM's origin, recurrence, and resistance to treatment. However, the understanding of how mRNA expression patterns of GBM subtypes are reflected at global proteome level in GSCs is limited. To characterize protein expression in GSCs, we performed in-depth proteogenomic analysis of patient-derived GSCs by RNA-sequencing and mass-spectrometry. We quantified > 10 000 proteins in two independent GSC panels and propose a GSC-associated proteomic signature characterizing two distinct phenotypic conditions; one defined by proteins upregulated in proneural and classical GSCs (GPC-like), and another by proteins upregulated in mesenchymal GSCs (GM-like). The GM-like protein set in GBM tissue was associated with necrosis, recurrence, and worse overall survival. Through proteogenomics, we discovered 252 non-canonical peptides in the GSCs, i.e., protein sequences that are variant or derive from genome regions previously considered non-protein-coding, including variants of the heterogeneous ribonucleoproteins implicated in RNA splicing. In summary, GSCs express two protein sets that have an inverse association with clinical outcomes in GBM. The discovery of non-canonical protein sequences questions existing gene models and pinpoints new protein targets for research in GBM.

Translational significance of CDKN2A/B homozygous deletion in isocitrate dehydrogenase-mutant astrocytoma

Isocitrate dehydrogenase (IDH) 1 or 2 mutations confer a favorable prognosis compared to IDH-wildtype in astrocytoma, frequently denoting a lower grade malignancy. However, recent molecular profiling has identified specific aggressive tumor subgroups with clear clinical prognostic implications that are independent of histologic grading. The homozygous deletion of CDKN2A/B is the strongest implicated independent indicator of the poor prognosis within IDH-mutant astrocytoma, and the identification of this alteration in these lower histologic grade tumors transforms their biology toward an aggressive grade 4 phenotype clinically. CDKN2A/B homozygous deletion is now sufficient to define a grade 4 tumor in IDH-mutant astrocytomas regardless of histologic appearance, yet there are currently no effective molecularly informed targeted therapies for these tumors. The biological impact of CDKN2A/B homozygous deletion in IDH-mutant tumors and the optimal treatment strategy for this molecular subgroup remains insufficiently explored. Here we review the current understanding of the translational significance of homozygous deletion of CDKN2A/B gene expression in IDH-mutant astrocytoma and associated diagnostic and therapeutic implications.

Pharmacological Landscape of FDA-Approved Anticancer Drugs Reveals Sensitivities to Ixabepilone, Romidepsin, Omacetaxine, and Carfilzomib in Aggressive Meningiomas

PURPOSE

To date, there are no systemic treatment options for patients with recurrent or refractory meningioma.

EXPERIMENTAL DESIGN

To identify effective drugs, we performed a large-scale drug screening using FDA-approved drugs on several meningioma cell lines. The impact of the top four compounds was assessed on cell viability, proliferation, colony formation, migration, and apoptosis. In addition, the antineoplastic effects of the selected drugs were validated in a heterotopic xenograft mouse model.

RESULTS

Analyses of the viability of meningioma cells treated with 119 antineoplastic FDA-approved drugs resulted in categorization into sensitive and resistant drug-response groups based on the mean IC50 values and peak serum concentrations (Cmax) in patients. Eighty drugs, including 15 alkylating agents, 14 antimetabolites, and 13 tyrosine kinase inhibitors, were classified as resistant (IC50 > Cmax). The sensitive drug-response group (n = 29, IC50 < Cmax) included RNA/protein synthesis inhibitors, proteasome inhibitors, topoisomerase, tyrosine-kinase, and partial histone deacetylase and microtubule inhibitors. The IC50 value of the four most effective compounds (carfilzomib, omacetaxine, ixabepilone, and romidepsin) ranged from 0.12 to 9.5 nmol/L. Most of them caused cell-cycle arrest in the G2-M-phase and induced apoptosis. Furthermore, all drugs except romidepsin significantly inhibited tumor growth in vivo. The strongest antineoplastic effect was observed for ixabepilone, which reduced tumor volume by 86%.

CONCLUSIONS

In summary, a large-scale drug screening provides a comprehensive insight into the anti-meningioma activities of FDA-approved drugs, and identified carfilzomib, omacetaxine, ixabepilone, and romidepsin as novel potent antineoplastic agents for the treatment of aggressive meningiomas. The most pronounced effects were observed with ixabepilone mandating for further clinical investigation.

Studies on Biological and Molecular Effects of Small-Molecule Kinase Inhibitors on Human Glioblastoma Cells and Organotypic Brain Slices

Glioblastoma is the most common and aggressive primary brain tumor. Multiple genetic and epigenetic alterations in several major signaling pathways—including the phosphoinositide 3-kinases (PI3K)/AKT/mTOR and the Raf/MEK/ERK pathway—could be found. We therefore aimed to investigate the biological and molecular effects of small-molecule kinase inhibitors that may interfere with those pathways. For this purpose, patient-derived glioblastoma cells were challenged with dactolisib, ipatasertib, MK-2206, regorafenib, or trametinib. To determine the effects of the small-molecule kinase inhibitors, assays of cell proliferation and apoptosis and immunoblot analyses were performed. To further investigate the effects of ipatasertib on organotypic brain slices harboring glioblastoma cells, the tumor growth was estimated. In addition, the network activity in brain slices was assessed by electrophysiological field potential recordings. Multi-kinase inhibitor regorafenib and both MK-2206 and dactolisib were very effective in all preclinical tumor models, while with respect to trametinib, two cell lines were found to be highly resistant. Only in HROG05 cells, ipatasertib showed anti-tumoral effects in vitro and in organotypic brain slices. Additionally, ipatasertib diminished synchronous network activity in organotypic brain slices. Overall, our data suggest that ipatasertib was only effective in selected tumor models, while especially regorafenib and MK-2206 presented a uniform response pattern.

A Targeted Proteomics Approach for Screening Serum Biomarkers Observed in the Early Stage of Type I Endometrial Cancer

Endometrial cancer (EC) is the most common gynecologic malignancy, and it arises in the inner part of the uterus. Identification of serum biomarkers is essential for diagnosing the disease at an early stage. In this study, we selected 44 healthy controls and 44 type I EC at tumor stage 1, and we used the Immuno-oncology panel and the Target 96 Oncology III panel to simultaneously detect the levels of 92 cancer-related proteins in serum, using a proximity extension assay. By applying this methodology, we identified 20 proteins, associated with the outcome at binary logistic regression, with a p-value below 0.01 for the first panel and 24 proteins with a p-value below 0.02 for the second one. The final multivariate logistic regression model, combining proteins from the two panels, generated a model with a sensitivity of 97.67% and a specificity of 83.72%. These results support the use of the proposed algorithm after a validation phase.

Drug Repurposing, a Fast-Track Approach to Develop Effective Treatments for Glioblastoma

Glioblastoma (GBM) remains one of the most difficult tumors to treat. The mean overall survival rate of 15 months and the 5-year survival rate of 5% have not significantly changed for almost 2 decades. Despite progress in understanding the pathophysiology of the disease, no new effective treatments to combine with radiation therapy after surgical tumor debulking have become available since the introduction of temozolomide in 1999. One of the main reasons for this is the scarcity of compounds that cross the blood-brain barrier (BBB) and reach the brain tumor tissue in therapeutically effective concentrations. In this review, we focus on the role of the BBB and its importance in developing brain tumor treatments. Moreover, we discuss drug repurposing, a drug discovery approach to identify potential effective candidates with optimal pharmacokinetic profiles for central nervous system (CNS) penetration and that allows rapid implementation in clinical trials. Additionally, we provide an overview of repurposed candidate drug currently being investigated in GBM at the preclinical and clinical levels. Finally, we highlight the importance of phase 0 trials to confirm tumor drug exposure and we discuss emerging drug delivery technologies as an alternative route to maximize therapeutic efficacy of repurposed candidate drug.

Novel cancer gene discovery using a forward genetic screen in RCAS-PDGFB-driven gliomas

BACKGROUND

Malignant gliomas, the most common malignant brain tumors in adults, represent a heterogeneous group of diseases with poor prognosis. Retroviruses can cause permanent genetic alterations that modify genes close to the viral integration site.

METHODS

Here we describe the use of a high-throughput pipeline coupled to the commonly used tissue-specific retroviral RCAS-TVA mouse tumor model system. Utilizing next-generation sequencing, we show that retroviral integration sites can be reproducibly detected in malignant stem cell lines generated from RCAS-PDGFB-driven glioma biopsies.

RESULTS

A large fraction of common integration sites contained genes that have been dysregulated or misexpressed in glioma. Others overlapped with loci identified in previous glioma-related forward genetic screens, but several novel putative cancer-causing genes were also found. Integrating retroviral tagging and clinical data, Ppfibp1 was highlighted as a frequently tagged novel glioma-causing gene. Retroviral integrations into the locus resulted in Ppfibp1 upregulation, and Ppfibp1-tagged cells generated tumors with shorter latency on orthotopic transplantation. In human gliomas, increased PPFIBP1 expression was significantly linked to poor prognosis and PDGF treatment resistance.

CONCLUSIONS

Altogether, the current study has demonstrated a novel approach to tagging glioma genes via forward genetics, validating previous results, and identifying PPFIBP1 as a putative oncogene in gliomagenesis.

Comprehensive analysis of microglia gene and subpathway signatures for glioma prognosis and drug screening: linking microglia to glioma

Glioma is the most common malignant tumors in the brain. Previous studies have revealed that, as the innate immune cells in nervous system, microglia cells were involved in glioma pathology. And, the resident microglia displayed its specific biological roles which distinguished with peripheral macrophages. In this study, an integrated analysis was performed based on public resource database to explore specific biological of microglia within glioma. Through comprehensive analysis, the biological characterization underlying two conditions, glioma microglia compared to glioma macrophage (MicT/MacT) as well as glioma microglia compared to normal microglia (MicT/MicN), were revealed. Notably, nine core MicT/MicN genes displayed closely associations with glioma recurrence and prognosis, such as P2RY2, which was analyzed in more than 2800 glioma samples from 25 studies. Furthermore, we applied a random walk based strategy to identify microglia specific subpathways and developed SubP28 signature for glioma prognostic analysis. Multiple validation data sets confirmed the predictive performance of SubP28 and involvement in molecular subtypes. The associations between SuP28 score and microglia M1/M2 polarization were also explored for both GBM and LGG types. Finally, a comprehensive drug-subpathway network was established for screening candidate medicable molecules (drugs) and identifying therapeutic subpathway targets. In conclusions, the comprehensive analysis of microglia related gene and functional signatures in glioma pathobiologic events by large-scale data sets displayed a framework to dissect inner connection between microglia and glioma, and identify robust signature for glioma clinical implications.

Prognostic Features of the Tumor Immune Microenvironment in Glioma and Their Clinical Applications: Analysis of Multiple Cohorts

Glioma is the most common malignant tumor of the central nervous system. Tumor purity is a source of important prognostic factor for glioma patients, showing the key roles of the microenvironment in glioma prognosis. In this study, we systematically screened functional characterization related to the tumor immune microenvironment and constructed a risk model named Glioma MicroEnvironment Functional Signature (GMEFS) based on eight cohorts. The prognostic value of the GMEFS model was also verified in another two glioma cohorts, glioblastoma (GBM) and low-grade glioma (LGG) cohorts, from The Cancer Genome Atlas (TCGA). Nomograms were established in the training and testing cohorts to validate the clinical use of this model. Furthermore, the relationships between the risk score, intrinsic molecular subtypes, tumor purity, and tumor-infiltrating immune cell abundance were also evaluated. Meanwhile, the performance of the GMEFS model in glioma formation and glioma recurrence was systematically analyzed based on 16 glioma cohorts from the Gene Expression Omnibus (GEO) database. Based on multiple-cohort integrated analysis, risk subpathway signatures were identified, and a drug–subpathway association network was further constructed to explore candidate therapy target regions. Three subpathways derived from Focal adhesion (path: 04510) were identified and contained known targets including platelet derived growth factor receptor alpha (PDGFRA), epidermal growth factor receptor (EGFR), and erb-b2 receptor tyrosine kinase 2 (ERBB2). In conclusion, the novel functional signatures identified in this study could serve as a robust prognostic biomarker, and this study provided a framework to identify candidate therapeutic target regions, which further guide glioma patients’ clinical decision.

Real-time evaluation of glioblastoma growth in patient-specific zebrafish xenografts

BACKGROUND

Patient-derived xenograft (PDX) models of glioblastoma (GBM) are a central tool for neuro-oncology research and drug development, enabling the detection of patient-specific differences in growth, and in vivo drug response. However, existing PDX models are not well suited for large-scale or automated studies. Thus, here, we investigate if a fast zebrafish-based PDX model, supported by longitudinal, AI-driven image analysis, can recapitulate key aspects of glioblastoma growth and enable case-comparative drug testing.

METHODS

We engrafted 11 GFP-tagged patient-derived GBM IDH wild-type cell cultures (PDCs) into 1-day-old zebrafish embryos, and monitored fish with 96-well live microscopy and convolutional neural network analysis. Using light-sheet imaging of whole embryos, we analyzed further the invasive growth of tumor cells.

RESULTS

Our pipeline enables automatic and robust longitudinal observation of tumor growth and survival of individual fish. The 11 PDCs expressed growth, invasion and survival heterogeneity, and tumor initiation correlated strongly with matched mouse PDX counterparts (Spearman R = 0.89, p < 0.001). Three PDCs showed a high degree of association between grafted tumor cells and host blood vessels, suggesting a perivascular invasion phenotype. In vivo evaluation of the drug marizomib, currently in clinical trials for GBM, showed an effect on fish survival corresponding to PDC in vitro and in vivo marizomib sensitivity.

CONCLUSIONS

Zebrafish xenografts of GBM, monitored by AI methods in an automated process, present a scalable alternative to mouse xenograft models for the study of glioblastoma tumor initiation, growth, and invasion, applicable to patient-specific drug evaluation.

ATRX-Deficient High-Grade Glioma Cells Exhibit Increased Sensitivity to RTK and PDGFR Inhibitors

High-grade glioma, including anaplastic astrocytoma and glioblastoma (GBM) patients, have a poor prognosis due to the lack of effective treatments. Therefore, the development of new therapeutic strategies to treat these gliomas is urgently required. Given that high-grade gliomas frequently harbor mutations in the SNF2 family chromatin remodeler ATRX, we performed a screen to identify FDA-approved drugs that are toxic to ATRX-deficient cells. Our findings reveal that multi-targeted receptor tyrosine kinase (RTK) and platelet-derived growth factor receptor (PDGFR) inhibitors cause higher cellular toxicity in high-grade glioma ATRX-deficient cells. Furthermore, we demonstrate that a combinatorial treatment of RTKi with temozolomide (TMZ)-the current standard of care treatment for GBM patients-causes pronounced toxicity in ATRX-deficient high-grade glioma cells. Our findings suggest that combinatorial treatments with TMZ and RTKi may increase the therapeutic window of opportunity in patients who suffer high-grade gliomas with ATRX mutations. Thus, we recommend incorporating the ATRX status into the analyses of clinical trials with RTKi and PDGFRi.

Proteomics and metabolomics approach in adult and pediatric glioma diagnostics

The diagnosis of glioma is mainly based on imaging methods that do not distinguish between stage and subtype prior to histopathological analysis. Patients with gliomas are generally diagnosed in the symptomatic stage of the disease. Additionally, healing scar tissue may be mistakenly identified based on magnetic resonance imaging (MRI) as a false positive tumor recurrence in postoperative patients. Current knowledge of molecular alterations underlying gliomagenesis and identification of tumoral biomarkers allow for their use as discriminators of the state of the organism. Moreover, a multiomics approach provides the greatest spectrum and the ability to track physiological changes and can serve as a minimally invasive method for diagnosing asymptomatic gliomas, preceding surgery and allowing for the initiation of prophylactic treatment. It is important to create a vast biomarker library for adults and pediatric patients due to their metabolic differences. This review focuses on the most promising proteomic, metabolomic and lipidomic glioma biomarkers, their pathways, the interactions, and correlations that can be considered characteristic of tumor grade or specific subtype.

MYCMI-7: A Small MYC-Binding Compound that Inhibits MYC: MAX Interaction and Tumor Growth in a MYC-Dependent Manner

Deregulated expression of MYC family oncogenes occurs frequently in human cancer and is often associated with aggressive disease and poor prognosis. While MYC is a highly warranted target, it has been considered "undruggable," and no specific anti-MYC drugs are available in the clinic. We recently identified molecules named MYCMIs that inhibit the interaction between MYC and its essential partner MAX. Here we show that one of these molecules, MYCMI-7, efficiently and selectively inhibits MYC:MAX and MYCN:MAX interactions in cells, binds directly to recombinant MYC, and reduces MYC-driven transcription. In addition, MYCMI-7 induces degradation of MYC and MYCN proteins. MYCMI-7 potently induces growth arrest/apoptosis in tumor cells in a MYC/MYCN-dependent manner and downregulates the MYC pathway on a global level as determined by RNA sequencing. Sensitivity to MYCMI-7 correlates with MYC expression in a panel of 60 tumor cell lines and MYCMI-7 shows high efficacy toward a collection of patient-derived primary glioblastoma and acute myeloid leukemia (AML) ex vivo cultures. Importantly, a variety of normal cells become G₁ arrested without signs of apoptosis upon MYCMI-7 treatment. Finally, in mouse tumor models of MYC-driven AML, breast cancer, and MYCN-amplified neuroblastoma, treatment with MYCMI-7 downregulates MYC/MYCN, inhibits tumor growth, and prolongs survival through apoptosis with few side effects. In conclusion, MYCMI-7 is a potent and selective MYC inhibitor that is highly relevant for the development into clinically useful drugs for the treatment of MYC-driven cancer.

Significance

Our findings demonstrate that the small-molecule MYCMI-7 binds MYC and inhibits interaction between MYC and MAX, thereby hampering MYC-driven tumor cell growth in culture and in vivo while sparing normal cells.

Image-Based Annotation of Chemogenomic Libraries for Phenotypic Screening

Phenotypical screening is a widely used approach in drug discovery for the identification of small molecules with cellular activities. However, functional annotation of identified hits often poses a challenge. The development of small molecules with narrow or exclusive target selectivity such as chemical probes and chemogenomic (CG) libraries, greatly diminishes this challenge, but non-specific effects caused by compound toxicity or interference with basic cellular functions still pose a problem to associate phenotypic readouts with molecular targets. Hence, each compound should ideally be comprehensively characterized regarding its effects on general cell functions. Here, we report an optimized live-cell multiplexed assay that classifies cells based on nuclear morphology, presenting an excellent indicator for cellular responses such as early apoptosis and necrosis. This basic readout in combination with the detection of other general cell damaging activities of small molecules such as changes in cytoskeletal morphology, cell cycle and mitochondrial health provides a comprehensive time-dependent characterization of the effect of small molecules on cellular health in a single experiment. The developed high-content assay offers multi-dimensional comprehensive characterization that can be used to delineate generic effects regarding cell functions and cell viability, allowing an assessment of compound suitability for subsequent detailed phenotypic and mechanistic studies.

DDRugging glioblastoma: understanding and targeting the DNA damage response to improve future therapies

Glioblastoma is the most frequently diagnosed type of primary brain tumour in adults. These aggressive tumours are characterised by inherent treatment resistance and disease progression, contributing to ~ 190 000 brain tumour-related deaths globally each year. Current therapeutic interventions consist of surgical resection followed by radiotherapy and temozolomide chemotherapy, but average survival is typically around 1 year, with < 10% of patients surviving more than 5 years. Recently, a fourth treatment modality of intermediate-frequency low-intensity electric fields [called tumour-treating fields (TTFields)] was clinically approved for glioblastoma in some countries after it was found to increase median overall survival rates by ~ 5 months in a phase III randomised clinical trial. However, beyond these treatments, attempts to establish more effective therapies have yielded little improvement in survival for patients over the last 50 years. This is in contrast to many other types of cancer and highlights glioblastoma as a recognised tumour of unmet clinical need. Previous work has revealed that glioblastomas contain stem cell-like subpopulations that exhibit heightened expression of DNA damage response (DDR) factors, contributing to therapy resistance and disease relapse. Given that radiotherapy, chemotherapy and TTFields-based therapies all impact DDR mechanisms, this Review will focus on our current knowledge of the role of the DDR in glioblastoma biology and treatment. We also discuss the potential of effective multimodal targeting of the DDR combined with standard-of-care therapies, as well as emerging therapeutic targets, in providing much-needed improvements in survival rates for patients.

Systems Biology Approaches to Decipher the Underlying Molecular Mechanisms of Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is one of the most malignant central nervous system tumors, showing a poor prognosis and low survival rate. Therefore, deciphering the underlying molecular mechanisms involved in the progression of the GBM and identifying the key driver genes responsible for the disease progression is crucial for discovering potential diagnostic markers and therapeutic targets. In this context, access to various biological data, development of new methodologies, and generation of biological networks for the integration of multi-omics data are necessary for gaining insights into the appearance and progression of GBM. Systems biology approaches have become indispensable in analyzing heterogeneous high-throughput omics data, extracting essential information, and generating new hypotheses from biomedical data. This review provides current knowledge regarding GBM and discusses the multi-omics data and recent systems analysis in GBM to identify key biological functions and genes. This knowledge can be used to develop efficient diagnostic and treatment strategies and can also be used to achieve personalized medicine for GBM.

A Functional Precision Medicine Pipeline Combines Comparative Transcriptomics and Tumor Organoid Modeling to Identify Bespoke Treatment Strategies for Glioblastoma

Li Fraumeni syndrome (LFS) is a hereditary cancer predisposition syndrome caused by germline mutations in TP53. TP53 is the most common mutated gene in human cancer, occurring in 30-50% of glioblastomas (GBM). Here, we highlight a precision medicine platform to identify potential targets for a GBM patient with LFS. We used a comparative transcriptomics approach to identify genes that are uniquely overexpressed in the LFS GBM patient relative to a cancer compendium of 12,747 tumor RNA sequencing data sets, including 200 GBMs. STAT1 and STAT2 were identified as being significantly overexpressed in the LFS patient, indicating ruxolitinib, a Janus kinase 1 and 2 inhibitors, as a potential therapy. The LFS patient had the highest level of STAT1 and STAT2 expression in an institutional high-grade glioma cohort of 45 patients, further supporting the cancer compendium results. To empirically validate the comparative transcriptomics pipeline, we used a combination of adherent and organoid cell culture techniques, including ex vivo patient-derived organoids (PDOs) from four patient-derived cell lines, including the LFS patient. STAT1 and STAT2 expression levels in the four patient-derived cells correlated with levels identified in the respective parent tumors. In both adherent and organoid cultures, cells from the LFS patient were among the most sensitive to ruxolitinib compared to patient-derived cells with lower STAT1 and STAT2 expression levels. A spheroid-based drug screening assay (3D-PREDICT) was performed and used to identify further therapeutic targets. Two targeted therapies were selected for the patient of interest and resulted in radiographic disease stability. This manuscript supports the use of comparative transcriptomics to identify personalized therapeutic targets in a functional precision medicine platform for malignant brain tumors.

p53-Mediated Radiosensitization of 177Lu-DOTATATE in Neuroblastoma Tumor Spheroids

p53 is involved in DNA damage response and is an exciting target for radiosensitization in cancer. Targeted radionuclide therapy against somatostatin receptors with 177Lu-DOTATATE is currently being explored as a treatment for neuroblastoma. The aim of this study was to investigate the novel p53-stabilizing peptide VIP116 in neuroblastoma, both as monotherapy and together with 177Lu-DOTATATE. Five neuroblastoma cell lines, including two patient-derived xenograft (PDX) lines, were characterized in monolayer cultures. Four out of five were positive for 177Lu-DOTATATE uptake. IC50 values after VIP116 treatments correlated with p53 status, ranging between 2.8-238.2 μM. IMR-32 and PDX lines LU-NB-1 and LU-NB-2 were then cultured as multicellular tumor spheroids and treated with 177Lu-DOTATATE and/or VIP116. Spheroid growth was inhibited in all spheroid models for all treatment modalities. The most pronounced effects were observed for combination treatments, mediating synergistic effects in the IMR-32 model. VIP116 and combination treatment increased p53 levels with subsequent induction of p21, Bax and cleaved caspase 3. Combination treatment resulted in a 14-fold and 1.6-fold induction of MDM2 in LU-NB-2 and IMR-32 spheroids, respectively. This, together with differential MYCN signaling, may explain the varying degree of synergy. In conclusion, VIP116 inhibited neuroblastoma cell growth, potentiated 177Lu-DOTATATE treatment and could, therefore, be a feasible treatment option for neuroblastoma.

Proximity Extension Assay in Combination with Next-Generation Sequencing for High-throughput Proteome-wide Analysis

Understanding the dynamics of the human proteome is crucial for developing biomarkers to be used as measurable indicators for disease severity and progression, patient stratification, and drug development. The Proximity Extension Assay (PEA) is a technology that translates protein information into actionable knowledge by linking protein-specific antibodies to DNA-encoded tags. In this report we demonstrate how we have combined the unique PEA technology with an innovative and automated sample preparation and high-throughput sequencing readout enabling parallel measurement of nearly 1500 proteins in 96 samples generating close to 150,000 data points per run. This advancement will have a major impact on the discovery of new biomarkers for disease prediction and prognosis and contribute to the development of the rapidly evolving fields of wellness monitoring and precision medicine.

Comparative epigenetic analysis of tumour initiating cells and syngeneic EPSC-derived neural stem cells in glioblastoma

Epigenetic mechanisms which play an essential role in normal developmental processes, such as self-renewal and fate specification of neural stem cells (NSC) are also responsible for some of the changes in the glioblastoma (GBM) genome. Here we develop a strategy to compare the epigenetic and transcriptional make-up of primary GBM cells (GIC) with patient-matched expanded potential stem cell (EPSC)-derived NSC (iNSC). Using a comparative analysis of the transcriptome of syngeneic GIC/iNSC pairs, we identify a glycosaminoglycan (GAG)-mediated mechanism of recruitment of regulatory T cells (Tregs) in GBM. Integrated analysis of the transcriptome and DNA methylome of GBM cells identifies druggable target genes and patient-specific prediction of drug response in primary GIC cultures, which is validated in 3D and in vivo models. Taken together, we provide a proof of principle that this experimental pipeline has the potential to identify patient-specific disease mechanisms and druggable targets in GBM.

Codependency and mutual exclusivity for gene community detection from sparse single-cell transcriptome data

Single-cell RNA-seq (scRNA-seq) can be used to characterize cellular heterogeneity in thousands of cells. The reconstruction of a gene network based on coexpression patterns is a fundamental task in scRNA-seq analyses, and the mutual exclusivity of gene expression can be critical for understanding such heterogeneity. Here, we propose an approach for detecting communities from a genetic network constructed on the basis of coexpression properties. The community-based comparison of multiple coexpression networks enables the identification of functionally related gene clusters that cannot be fully captured through differential gene expression-based analysis. We also developed a novel metric referred to as the exclusively expressed index (EEI) that identifies mutually exclusive gene pairs from sparse scRNA-seq data. EEI quantifies and ranks the exclusive expression levels of all gene pairs from binary expression patterns while maintaining robustness against a low sequencing depth. We applied our methods to glioblastoma scRNA-seq data and found that gene communities were partially conserved after serum stimulation despite a considerable number of differentially expressed genes. We also demonstrate that the identification of mutually exclusive gene sets with EEI can improve the sensitivity of capturing cellular heterogeneity. Our methods complement existing approaches and provide new biological insights, even for a large, sparse dataset, in the single-cell analysis field.

MDM2/X Inhibitors as Radiosensitizers for Glioblastoma Targeted Therapy

Inhibition of the MDM2/X-p53 interaction is recognized as a potential anti-cancer strategy, including the treatment of glioblastoma (GB). In response to cellular stressors, such as DNA damage, the tumor suppression protein p53 is activated and responds by mediating cellular damage through DNA repair, cell cycle arrest and apoptosis. Hence, p53 activation plays a central role in cell survival and the effectiveness of cancer therapies. Alterations and reduced activity of p53 occur in 25-30% of primary GB tumors, but this number increases drastically to 60-70% in secondary GB. As a result, reactivating p53 is suggested as a treatment strategy, either by using targeted molecules to convert the mutant p53 back to its wild type form or by using MDM2 and MDMX (also known as MDM4) inhibitors. MDM2 down regulates p53 activity via ubiquitin-dependent degradation and is amplified or overexpressed in 14% of GB cases. Thus, suppression of MDM2 offers an opportunity for urgently needed new therapeutic interventions for GB. Numerous small molecule MDM2 inhibitors are currently undergoing clinical evaluation, either as monotherapy or in combination with chemotherapy and/or other targeted agents. In addition, considering the major role of both p53 and MDM2 in the downstream signaling response to radiation-induced DNA damage, the combination of MDM2 inhibitors with radiation may offer a valuable therapeutic radiosensitizing approach for GB therapy. This review covers the role of MDM2/X in cancer and more specifically in GB, followed by the rationale for the potential radiosensitizing effect of MDM2 inhibition. Finally, the current status of MDM2/X inhibition and p53 activation for the treatment of GB is given.

Glutamatergic Mechanisms in Glioblastoma and Tumor-Associated Epilepsy

The progression of glioblastomas is associated with a variety of neurological impairments, such as tumor-related epileptic seizures. Seizures are not only a common comorbidity of glioblastoma but often an initial clinical symptom of this cancer entity. Both, glioblastoma and tumor-associated epilepsy are closely linked to one another through several pathophysiological mechanisms, with the neurotransmitter glutamate playing a key role. Glutamate interacts with its ionotropic and metabotropic receptors to promote both tumor progression and excitotoxicity. In this review, based on its physiological functions, our current understanding of glutamate receptors and glutamatergic signaling will be discussed in detail. Furthermore, preclinical models to study glutamatergic interactions between glioma cells and the tumor-surrounding microenvironment will be presented. Finally, current studies addressing glutamate receptors in glioma and tumor-related epilepsy will be highlighted and future approaches to interfere with the glutamatergic network are discussed.

A Drug Screening Pipeline Using 2D and 3D Patient-Derived In Vitro Models for Pre-Clinical Analysis of Therapy Response in Glioblastoma

Glioblastoma is one of the most common and lethal types of primary brain tumor. Despite aggressive treatment with chemotherapy and radiotherapy, tumor recurrence within 6-9 months is common. To overcome this, more effective therapies targeting cancer cell stemness, invasion, metabolism, cell death resistance and the interactions of tumor cells with their surrounding microenvironment are required. In this study, we performed a systematic review of the molecular mechanisms that drive glioblastoma progression, which led to the identification of 65 drugs/inhibitors that we screened for their efficacy to kill patient-derived glioma stem cells in two dimensional (2D) cultures and patient-derived three dimensional (3D) glioblastoma explant organoids (GBOs). From the screening, we found a group of drugs that presented different selectivity on different patient-derived in vitro models. Moreover, we found that Costunolide, a TERT inhibitor, was effective in reducing the cell viability in vitro of both primary tumor models as well as tumor models pre-treated with chemotherapy and radiotherapy. These results present a novel workflow for screening a relatively large groups of drugs, whose results could lead to the identification of more personalized and effective treatment for recurrent glioblastoma.

Re-evaluating Biopsy for Recurrent Glioblastoma: A Position Statement by the Christopher Davidson Forum Investigators

Patients with glioblastoma (GBM) need bold new approaches to their treatment, yet progress has been hindered by a relative inability to dynamically track treatment response, mechanisms of resistance, evolution of targetable mutations, and changes in mutational burden. We are writing on behalf of a multidisciplinary group of academic neuro-oncology professionals who met at the collaborative Christopher Davidson Forum at Washington University in St Louis in the fall of 2019. We propose a dramatic but necessary change to the routine management of patients with GBM to advance the field: to routinely biopsy recurrent GBM at the time of presumed recurrence. Data derived from these samples will identify true recurrence vs treatment effect, avoid treatments with little chance of success, enable clinical trial access, and aid in the scientific advancement of our understanding of GBM.