MT-125 Inhibits Non-Muscle Myosin IIA and IIB, Synergizes with Oncogenic Kinase Inhibitors, and Prolongs Survival in Glioblastoma.

We have identified a NMIIA and IIB-specific small molecule inhibitor, MT-125, and have studied its effects in GBM. MT-125 has high brain penetrance and retention and an excellent safety profile; blocks GBM invasion and cytokinesis, consistent with the known roles of NMII; and prolongs survival as a single agent in murine GBM models. MT-125 increases signaling along both the PDGFR- and MAPK-driven pathways through a mechanism that involves the upregulation of reactive oxygen species, and it synergizes with FDA-approved PDGFR and mTOR inhibitors in vitro . Combining MT-125 with sunitinib, a PDGFR inhibitor, or paxalisib, a combined PI3 Kinase/mTOR inhibitor significantly improves survival in orthotopic GBM models over either drug alone, and in the case of sunitinib, markedly prolongs survival in ∼40% of mice. Our results provide a powerful rationale for developing NMII targeting strategies to treat cancer and demonstrate that MT-125 has strong clinical potential for the treatment of GBM. Highlights: MT-125 is a highly specific small molecule inhibitor of non-muscle myosin IIA and IIB, is well-tolerated, and achieves therapeutic concentrations in the brain with systemic dosing.Treating preclinical models of glioblastoma with MT-125 produces durable improvements in survival.MT-125 stimulates PDGFR- and MAPK-driven signaling in glioblastoma and increases dependency on these pathways.Combining MT-125 with an FDA-approved PDGFR inhibitor in a mouse GBM model synergizes to improve median survival over either drug alone, and produces tumor free, prolonged survival in over 40% of mice.

Osteopontin drives neuroinflammation and cell loss in MAPT-N279K frontotemporal dementia patient neurons.

Frontotemporal dementia (FTD) is an incurable group of early-onset dementias that can be caused by the deposition of hyperphosphorylated tau in patient brains. However, the mechanisms leading to neurodegeneration remain largely unknown. Here, we combined single-cell analyses of FTD patient brains with a stem cell culture and transplantation model of FTD. We identified disease phenotypes in FTD neurons carrying the MAPT-N279K mutation, which were related to oxidative stress, oxidative phosphorylation, and neuroinflammation with an upregulation of the inflammation-associated protein osteopontin (OPN). Human FTD neurons survived less and elicited an increased microglial response after transplantation into the mouse forebrain, which we further characterized by single nucleus RNA sequencing of microdissected grafts. Notably, downregulation of OPN in engrafted FTD neurons resulted in improved engraftment and reduced microglial infiltration, indicating an immune-modulatory role of OPN in patient neurons, which may represent a potential therapeutic target in FTD.

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

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

Multiplexed single-cell lineage tracing of mitotic kinesin inhibitor resistance in glioblastoma.

Glioblastoma (GBM) is a deadly brain tumor, and the kinesin motor KIF11 is an attractive therapeutic target with roles in proliferation and invasion. Resistance to KIF11 inhibitors, which has mainly been studied in animal models, presents significant challenges. We use lineage-tracing barcodes and single-cell RNA sequencing to analyze resistance in patient-derived GBM neurospheres treated with ispinesib, a potent KIF11 inhibitor. Similar to GBM progression in patients, untreated cells lose their neural lineage identity and become mesenchymal, which is associated with poor prognosis. Conversely, cells subjected to long-term ispinesib treatment exhibit a proneural phenotype. We generate patient-derived xenografts and show that ispinesib-resistant cells form less aggressive tumors in vivo, even in the absence of drug. Moreover, treatment of human ex vivo GBM slices with ispinesib demonstrates phenotypic alignment with in vitro responses, underscoring the clinical relevance of our findings. Finally, using retrospective lineage tracing, we identify drugs that are synergistic with ispinesib.

Human stem cell transplantation models of Alzheimer's disease.

Alzheimer's disease (AD) is the most frequent form of dementia. It is characterized by pronounced neuronal degeneration with formation of neurofibrillary tangles and deposition of amyloid ß throughout the central nervous system. Animal models have provided important insights into the pathogenesis of AD and they have shown that different brain cell types including neurons, astrocytes and microglia have important functions in the pathogenesis of AD. However, there are difficulties in translating promising therapeutic observations in mice into clinical application in patients. Alternative models using human cells such as human induced pluripotent stem cells (iPSCs) may provide significant advantages, since they have successfully been used to model disease mechanisms in neurons and in glial cells in neurodegenerative diseases in vitro and in vivo. In this review, we summarize recent studies that describe the transplantation of human iPSC-derived neurons, astrocytes and microglial cells into the forebrain of mice to generate chimeric transplantation models of AD. We also discuss opportunities, challenges and limitations in using differentiated human iPSCs for in vivo disease modeling and their application for biomedical research.

OGDH and Bcl-xL loss causes synthetic lethality in glioblastoma.

Glioblastoma (GBM) remains an incurable disease, requiring more effective therapies. Through interrogation of publicly available CRISPR and RNAi library screens, we identified the α-ketoglutarate dehydrogenase (OGDH) gene, which encodes an enzyme that is part of the tricarboxylic acid (TCA) cycle, as essential for GBM growth. Moreover, by combining transcriptome and metabolite screening analyses, we discovered that loss of function of OGDH by the clinically validated drug compound CPI-613 was synthetically lethal with Bcl-xL inhibition (genetically and through the clinically validated BH3 mimetic, ABT263) in patient-derived xenografts as well neurosphere GBM cultures. CPI-613-mediated energy deprivation drove an integrated stress response with an upregulation of the BH3-only domain protein, Noxa, in an ATF4-dependent manner, as demonstrated by genetic loss-of-function experiments. Consistently, silencing of Noxa attenuated cell death induced by CPI-613 in model systems of GBM. In patient-derived xenograft models of GBM in mice, the combination treatment of ABT263 and CPI-613 suppressed tumor growth and extended animal survival more potently than each compound on its own. Therefore, combined inhibition of Bcl-xL along with disruption of the TCA cycle might be a treatment strategy for GBM.

Immune Response following FLASH and Conventional Radiation in Diffuse Midline Glioma.

PURPOSE: Diffuse midline glioma (DMG) is a fatal tumor traditionally treated with radiation therapy (RT) and previously characterized as having a noninflammatory tumor immune microenvironment (TIME). FLASH is a novel RT technique using ultra-high dose rate that is associated with decreased toxicity and effective tumor control. However, the effect of FLASH and conventional (CONV) RT on the DMG TIME has not yet been explored. METHODS AND MATERIALS: Here, we performed single-cell RNA sequencing (scRNA-seq) and flow cytometry on immune cells isolated from an orthotopic syngeneic murine model of brainstem DMG after the use of FLASH (90 Gy/sec) or CONV (2 Gy/min) dose-rate RT and compared to unirradiated tumor (SHAM). RESULTS: At day 4 post-RT, FLASH exerted similar effects as CONV in the predominant microglial (MG) population, including the presence of two activated subtypes. However, at day 10 post-RT, we observed a significant increase in the type 1 interferon α/ß receptor (IFNAR+) in MG in CONV and SHAM compared to FLASH. In the non-resident myeloid clusters of macrophages (MACs) and dendritic cells (DCs), we found increased type 1 interferon (IFN1) pathway enrichment for CONV compared to FLASH and SHAM by scRNA-seq. We observed this trend by flow cytometry at day 4 post-RT in IFNAR+ MACs and DCs, which equalized by day 10 post-RT. DMG control and murine survival were equivalent between RT dose rates. CONCLUSIONS: Our work is the first to map CONV and FLASH immune alterations of the DMG TIME with single-cell resolution. Although DMG tumor control and survival were similar between CONV and FLASH, we found that changes in immune compartments differed over time. Importantly, although both RT modalities increased IFN1, we found that the timing of this response was cell-type and dose-rate dependent. These temporal differences, particularly in the context of tumor control, warrant further study.

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

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

EZH2 Inhibition Sensitizes IDH1R132H-Mutant Gliomas to Histone Deacetylase Inhibitor.

Isocitrate Dehydrogenase-1 (IDH1) is commonly mutated in lower-grade diffuse gliomas. The IDH1R132H mutation is an important diagnostic tool for tumor diagnosis and prognosis; however, its role in glioma development, and its impact on response to therapy, is not fully understood. We developed a murine model of proneural IDH1R132H-mutated glioma that shows elevated production of 2-hydroxyglutarate (2-HG) and increased trimethylation of lysine residue K27 on histone H3 (H3K27me3) compared to IDH1 wild-type tumors. We found that using Tazemetostat to inhibit the methyltransferase for H3K27, Enhancer of Zeste 2 (EZH2), reduced H3K27me3 levels and increased acetylation on H3K27. We also found that, although the histone deacetylase inhibitor (HDACi) Panobinostat was less cytotoxic in IDH1R132H-mutated cells (either isolated from murine glioma or oligodendrocyte progenitor cells infected in vitro with a retrovirus expressing IDH1R132H) compared to IDH1-wild-type cells, combination treatment with Tazemetostat is synergistic in both mutant and wild-type models. These findings indicate a novel therapeutic strategy for IDH1-mutated gliomas that targets the specific epigenetic alteration in these tumors.

Induced pluripotent stem cell models as a tool to investigate and test fluid biomarkers in Alzheimer's disease and frontotemporal dementia.

Neurodegenerative diseases are increasing in prevalence and comprise a large socioeconomic burden on patients and their caretakers. The need for effective therapies and avenues for disease prevention and monitoring is of paramount importance. Fluid biomarkers for neurodegenerative diseases have gained a variety of uses, including informing participant selection for clinical trials, lending confidence to clinical diagnosis and disease staging, determining prognosis, and monitoring therapeutic response. Their role is expected to grow as disease-modifying therapies start to be available to a broader range of patients and as prevention strategies become established. Many of the underlying molecular mechanisms of currently used biomarkers are incompletely understood. Animal models and in vitro systems using cell lines have been extensively employed but face important translatability limitations. Induced pluripotent stem cell (iPSC) technology, where a theoretically unlimited range of cell types can be reprogrammed from peripheral cells sampled from patients or healthy individuals, has gained prominence over the last decade. It is a promising avenue to study physiological and pathological biomarker function and response to experimental therapeutics. Such systems are amenable to high-throughput drug screening or multiomics readouts such as transcriptomics, lipidomics, and proteomics for biomarker discovery, investigation, and validation. The present review describes the current state of biomarkers in the clinical context of neurodegenerative diseases, with a focus on Alzheimer's disease and frontotemporal dementia. We include a discussion of how iPSC models have been used to investigate and test biomarkers such as amyloid-ß, phosphorylated tau, neurofilament light chain or complement proteins, and even nominate novel biomarkers. We discuss the limitations of current iPSC methods, mentioning alternatives such as coculture systems and three-dimensional organoids which address some of these concerns. Finally, we propose exciting prospects for stem cell transplantation paradigms using animal models as a preclinical tool to study biomarkers in the in vivo context.

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

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

Single-cell analysis of 5-aminolevulinic acid intraoperative labeling specificity for glioblastoma.

OBJECTIVE: Glioblastoma (GBM) is the most common and aggressive malignant primary brain tumor, and resection is a key part of the standard of care. In fluorescence-guided surgery (FGS), fluorophores differentiate tumor tissue from surrounding normal brain. The heme synthesis pathway converts 5-aminolevulinic acid (5-ALA), a fluorogenic substrate used for FGS, to fluorescent protoporphyrin IX (PpIX). The resulting fluorescence is believed to be specific to neoplastic glioma cells, but this specificity has not been examined at a single-cell level. The objective of this study was to determine the specificity with which 5-ALA labels the diversity of cell types in GBM. METHODS: The authors performed single-cell optical phenotyping and expression sequencing-version 2 (SCOPE-seq2), a paired single-cell imaging and RNA sequencing method, of individual cells on human GBM surgical specimens with macroscopically visible PpIX fluorescence from patients who received 5-ALA prior to surgery. SCOPE-seq2 allowed the authors to simultaneously image PpIX fluorescence and unambiguously identify neoplastic cells from single-cell RNA sequencing. Experiments were also conducted in cell culture and co-culture models of glioma and in acute slice cultures from a mouse glioma model to investigate cell- and tissue-specific uptake and secretion of 5-ALA and PpIX. RESULTS: SCOPE-seq2 analysis of human GBM surgical specimens revealed that 5-ALA treatment resulted in labeling that was not specific to neoplastic glioma cells. The cell culture further demonstrated that nonneoplastic cells could be labeled by 5-ALA directly or by PpIX secreted from surrounding neoplastic cells. Acute slice cultures from mouse glioma models showed that 5-ALA preferentially labeled GBM tumor tissue over nonneoplastic brain tissue with significant labeling in the tumor margins, and that this contrast was not due to blood-brain barrier disruption. CONCLUSIONS: Together, these findings support the use of 5-ALA as an indicator of GBM tissue but question the main advantage of 5-ALA for specific intracellular labeling of neoplastic glioma cells in FGS. Further studies are needed to systematically compare the performance of 5-ALA to that of potential alternatives for FGS.

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

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

Multiplexed single-cell lineage tracing of mitotic kinesin inhibitor resistance in glioblastoma.

Glioblastoma (GBM) is a deadly brain tumor, and the kinesin motor KIF11 is an attractive therapeutic target because of its dual roles in proliferation and invasion. The clinical utility of KIF11 inhibitors has been limited by drug resistance, which has mainly been studied in animal models. We used multiplexed lineage tracing barcodes and scRNA-seq to analyze drug resistance time courses for patient-derived GBM neurospheres treated with ispinesib, a potent KIF11 inhibitor. Similar to GBM progression in patients, untreated cells lost their neural lineage identity and transitioned to a mesenchymal phenotype, which is associated with poor prognosis. In contrast, cells subjected to long-term ispinesib treatment exhibited a proneural phenotype. We generated patient-derived xenografts to show that ispinesib-resistant cells form less aggressive tumors in vivo, even in the absence of drug. Finally, we used lineage barcodes to nominate drug combination targets by retrospective analysis of ispinesib-resistant clones in the drug-naïve setting and identified drugs that are synergistic with ispinesib.

MGMT Promoter Methylation Predicts Overall Survival after Chemotherapy for 1p/19q-Codeleted Gliomas.

PURPOSE: While MGMT promoter methylation (mMGMT) is predictive of response to alkylating chemotherapy and guides treatment decisions in glioblastoma, its role in grade 2 and 3 glioma remains unclear. Recent data suggest that mMGMT is prognostic of progression-free survival in 1p/19q-codeleted oligodendrogliomas, but an effect on overall survival (OS) has not been demonstrated. EXPERIMENTAL DESIGN: We identified patients with newly diagnosed 1p/19q-codeleted gliomas and known MGMT promoter status in the National Cancer Database from 2010 to 2019. Multivariable Cox proportional hazards regression modeling was used to assess the effect of mMGMT on OS after adjusting for age, sex, race, comorbidity, grade, extent of resection, chemotherapy, and radiotherapy. RESULTS: We identified 1,297 eligible patients, 938 (72.3%) of whom received chemotherapy in their initial course of treatment. The MGMT promoter was methylated in 1,009 (77.8%) patients. Unmethylated MGMT (uMGMT) was associated with worse survival compared with mMGMT [70% {95% confidence interval (CI), 64%-77%} vs. 81% (95% CI, 78%-85%); P < 0.001; adjusted HR (aHR), 2.35 (95% CI, 1.77-3.14)]. uMGMT was associated with worse survival in patients who received chemotherapy [63% (95% CI, 55-73%) vs. 80% (95% CI, 76%-84%); P < 0.001; aHR, 2.61 (95% CI, 1.89-3.60)] but not in patients who did not receive chemotherapy [P = 0.38; HR, 1.31 (95% CI, 0.71-2.42)]. Similar results were observed regardless of World Health Organization grade and after single- or multiagent chemotherapy. CONCLUSIONS: Our study demonstrates an association between mMGMT and OS in 1p/19q-codeleted gliomas. MGMT promoter status should be considered as a stratification factor in future clinical trials of 1p/19q-codeleted gliomas that use OS as an endpoint.

Clinical utility of whole-genome DNA methylation profiling as a primary molecular diagnostic assay for central nervous system tumors-A prospective study and guidelines for clinical testing.

Background: Central nervous system (CNS) cancer is the 10th leading cause of cancer-associated deaths for adults, but the leading cause in pediatric patients and young adults. The variety and complexity of histologic subtypes can lead to diagnostic errors. DNA methylation is an epigenetic modification that provides a tumor type-specific signature that can be used for diagnosis. Methods: We performed a prospective study using DNA methylation analysis as a primary diagnostic method for 1921 brain tumors. All tumors received a pathology diagnosis and profiling by whole genome DNA methylation, followed by next-generation DNA and RNA sequencing. Results were stratified by concordance between DNA methylation and histopathology, establishing diagnostic utility. Results: Of the 1602 cases with a World Health Organization histologic diagnosis, DNA methylation identified a diagnostic mismatch in 225 cases (14%), 78 cases (5%) did not classify with any class, and in an additional 110 (7%) cases DNA methylation confirmed the diagnosis and provided prognostic information. Of 319 cases carrying 195 different descriptive histologic diagnoses, DNA methylation provided a definitive diagnosis in 273 (86%) cases, separated them into 55 methylation classes, and changed the grading in 58 (18%) cases. Conclusions: DNA methylation analysis is a robust method to diagnose primary CNS tumors, improving diagnostic accuracy, decreasing diagnostic errors and inconclusive diagnoses, and providing prognostic subclassification. This study provides a framework for inclusion of DNA methylation profiling as a primary molecular diagnostic test into professional guidelines for CNS tumors. The benefits include increased diagnostic accuracy, improved patient management, and refinements in clinical trial design.

Association of MGMT Promoter Methylation With Survival in Low-grade and Anaplastic Gliomas After Alkylating Chemotherapy.

Importance: O6-methylguanine-DNA methyltransferase (MGMT [OMIM 156569]) promoter methylation (mMGMT) is predictive of response to alkylating chemotherapy for glioblastomas and is routinely used to guide treatment decisions. However, the utility of MGMT promoter status for low-grade and anaplastic gliomas remains unclear due to molecular heterogeneity and the lack of sufficiently large data sets. Objective: To evaluate the association of mMGMT for low-grade and anaplastic gliomas with chemotherapy response. Design, Setting, and Participants: This cohort study aggregated grade II and III primary glioma data from 3 prospective cohort studies with patient data collected from August 13, 1995, to August 3, 2022, comprising 411 patients: MSK-IMPACT, EORTC (European Organization of Research and Treatment of Cancer) 26951, and Columbia University. Statistical analysis was performed from April 2022 to January 2023. Exposure: MGMT promoter methylation status. Main Outcomes and Measures: Multivariable Cox proportional hazards regression modeling was used to assess the association of mMGMT status with progression-free survival (PFS) and overall survival (OS) after adjusting for age, sex, molecular class, grade, chemotherapy, and radiotherapy. Subgroups were stratified by treatment status and World Health Organization 2016 molecular classification. Results: A total of 411 patients (mean [SD] age, 44.1 [14.5] years; 283 men [58%]) met the inclusion criteria, 288 of whom received alkylating chemotherapy. MGMT promoter methylation was observed in 42% of isocitrate dehydrogenase (IDH)-wild-type gliomas (56 of 135), 53% of IDH-mutant and non-codeleted gliomas (79 of 149), and 74% of IDH-mutant and 1p/19q-codeleted gliomas (94 of 127). Among patients who received chemotherapy, mMGMT was associated with improved PFS (median, 68 months [95% CI, 54-132 months] vs 30 months [95% CI, 15-54 months]; log-rank P < .001; adjusted hazard ratio [aHR] for unmethylated MGMT, 1.95 [95% CI, 1.39-2.75]; P < .001) and OS (median, 137 months [95% CI, 104 months to not reached] vs 61 months [95% CI, 47-97 months]; log-rank P < .001; aHR, 1.65 [95% CI, 1.11-2.46]; P = .01). After adjusting for clinical factors, MGMT promoter status was associated with chemotherapy response in IDH-wild-type gliomas (aHR for PFS, 2.15 [95% CI, 1.26-3.66]; P = .005; aHR for OS, 1.69 [95% CI, 0.98-2.91]; P = .06) and IDH-mutant and codeleted gliomas (aHR for PFS, 2.99 [95% CI, 1.44-6.21]; P = .003; aHR for OS, 4.21 [95% CI, 1.25-14.2]; P = .02), but not IDH-mutant and non-codeleted gliomas (aHR for PFS, 1.19 [95% CI, 0.67-2.12]; P = .56; aHR for OS, 1.07 [95% CI, 0.54-2.12]; P = .85). Among patients who did not receive chemotherapy, mMGMT status was not associated with PFS or OS. Conclusions and Relevance: This study suggests that mMGMT is associated with response to alkylating chemotherapy for low-grade and anaplastic gliomas and may be considered as a stratification factor in future clinical trials of patients with IDH-wild-type and IDH-mutant and codeleted tumors.

Re-convolving the compositional landscape of primary and recurrent glioblastoma reveals prognostic and targetable tissue states.

Glioblastoma (GBM) diffusely infiltrates the brain and intermingles with non-neoplastic brain cells, including astrocytes, neurons and microglia/myeloid cells. This complex mixture of cell types forms the biological context for therapeutic response and tumor recurrence. We used single-nucleus RNA sequencing and spatial transcriptomics to determine the cellular composition and transcriptional states in primary and recurrent glioma and identified three compositional 'tissue-states' defined by cohabitation patterns between specific subpopulations of neoplastic and non-neoplastic brain cells. These tissue-states correlated with radiographic, histopathologic, and prognostic features and were enriched in distinct metabolic pathways. Fatty acid biosynthesis was enriched in the tissue-state defined by the cohabitation of astrocyte-like/mesenchymal glioma cells, reactive astrocytes, and macrophages, and was associated with recurrent GBM and shorter survival. Treating acute slices of GBM with a fatty acid synthesis inhibitor depleted the transcriptional signature of this pernicious tissue-state. These findings point to therapies that target interdependencies in the GBM microenvironment.

Convection-enhanced delivery of immunomodulatory therapy for high-grade glioma.

The prognosis for glioblastoma has remained poor despite multimodal standard of care treatment, including temozolomide, radiation, and surgical resection. Further, the addition of immunotherapies, while promising in a number of other solid tumors, has overwhelmingly failed in the treatment of gliomas, in part due to the immunosuppressive microenvironment and poor drug penetrance to the brain. Local delivery of immunomodulatory therapies circumvents some of these challenges and has led to long-term remission in select patients. Many of these approaches utilize convection-enhanced delivery (CED) for immunological drug delivery, allowing high doses to be delivered directly to the brain parenchyma, avoiding systemic toxicity. Here, we review the literature encompassing immunotherapies delivered via CED-from preclinical model systems to clinical trials-and explore how their unique combination elicits an antitumor response by the immune system, decreases toxicity, and improves survival among select high-grade glioma patients.

A Transcriptome-Based Precision Oncology Platform for Patient-Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies.

Predicting in vivo response to antineoplastics remains an elusive challenge. We performed a first-of-kind evaluation of two transcriptome-based precision cancer medicine methodologies to predict tumor sensitivity to a comprehensive repertoire of clinically relevant oncology drugs, whose mechanism of action we experimentally assessed in cognate cell lines. We enrolled patients with histologically distinct, poor-prognosis malignancies who had progressed on multiple therapies, and developed low-passage, patient-derived xenograft models that were used to validate 35 patient-specific drug predictions. Both OncoTarget, which identifies high-affinity inhibitors of individual master regulator (MR) proteins, and OncoTreat, which identifies drugs that invert the transcriptional activity of hyperconnected MR modules, produced highly significant 30-day disease control rates (68% and 91%, respectively). Moreover, of 18 OncoTreat-predicted drugs, 15 induced the predicted MR-module activity inversion in vivo. Predicted drugs significantly outperformed antineoplastic drugs selected as unpredicted controls, suggesting these methods may substantively complement existing precision cancer medicine approaches, as also illustrated by a case study. SIGNIFICANCE: Complementary precision cancer medicine paradigms are needed to broaden the clinical benefit realized through genetic profiling and immunotherapy. In this first-in-class application, we introduce two transcriptome-based tumor-agnostic systems biology tools to predict drug response in vivo. OncoTarget and OncoTreat are scalable for the design of basket and umbrella clinical trials. This article is highlighted in the In This Issue feature, p. 1275.