The transcriptional regulatory network of proneural glioma determines the genetic alterations selected during tumor progression

Integration of multi-omics data revealed the orphan CpG islands and enhancer-dominated c is-regulatory network in glioma

The complex transcriptional regulatory network leads to the poor prognosis of glioma. The role of orphan CpG islands (oCGIs) in the transcriptional regulatory network has been overlooked. We conducted a comprehensive exploration of the cis-regulatory roles of oCGIs and enhancers by integrating multi-omics data. Direct regulation of target genes by oCGIs or enhancers is of great importance in the cis-regulatory network. Furthermore, based on single-cell multi-omics data, we found that the highly activated cis-regulatory network in cluster 2 (C2) sustains the high proliferative potential of glioma cells. The upregulation of oCGIs and enhancers related genes in C2 results in glioma patients exhibiting resistance to radiotherapy and chemotherapy. These findings were further validated through glioma cell line related experiments. Our study offers insight into the pathogenesis of glioma and provides a strategy to treat this challenging disease.

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.

Identification of a novel gene signature for neuroblastoma differentiation using a Boolean implication network

Although induction of differentiation represents an effective strategy for neuroblastoma treatment, the mechanisms underlying neuroblastoma differentiation are poorly understood. We generated a computational model of neuroblastoma differentiation consisting of interconnected gene clusters identified based on symmetric and asymmetric gene expression relationships. We identified a differentiation signature consisting of series of gene clusters comprised of 1251 independent genes that predicted neuroblastoma differentiation in independent datasets and in neuroblastoma cell lines treated with agents known to induce differentiation. This differentiation signature was associated with patient outcomes in multiple independent patient cohorts and validated the role of MYCN expression as a marker of neuroblastoma differentiation. Our results further identified novel genes associated with MYCN via asymmetric Boolean implication relationships that would not have been identified using symmetric computational approaches and that were associated with both neuroblastoma differentiation and patient outcomes. Our differentiation signature included a cluster of genes involved in intracellular signaling and growth factor receptor trafficking pathways that is strongly associated with neuroblastoma differentiation, and we validated the associations of UBE4B, a gene within this cluster, with neuroblastoma cell and tumor differentiation. Our findings demonstrate that Boolean network analyses of symmetric and asymmetric gene expression relationships can identify novel genes and pathways relevant for neuroblastoma tumor differentiation that could represent potential therapeutic targets.

STING agonist-loaded, CD47/PD-L1-targeting nanoparticles potentiate antitumor immunity and radiotherapy for glioblastoma

As a key component of the standard of care for glioblastoma, radiotherapy induces several immune resistance mechanisms, such as upregulation of CD47 and PD-L1. Here, leveraging these radiotherapy-elicited processes, we generate a bridging-lipid nanoparticle (B-LNP) that engages tumor-associated myeloid cells (TAMCs) to glioblastoma cells via anti-CD47/PD-L1 dual ligation. We show that the engager B-LNPs block CD47 and PD-L1 and promote TAMC phagocytic activity. To enhance subsequent T cell recruitment and antitumor responses after tumor engulfment, the B-LNP was encapsulated with diABZI, a non-nucleotidyl agonist for stimulator of interferon genes. In vivo treatment with diABZI-loaded B-LNPs induced a transcriptomic and metabolic switch in TAMCs, turning these immunosuppressive cells into antitumor effectors, which induced T cell infiltration and activation in brain tumors. In preclinical murine models, B-LNP/diABZI administration synergized with radiotherapy to promote brain tumor regression and induce immunological memory against glioma. In summary, our study describes a nanotechnology-based approach that hijacks irradiation-triggered immune checkpoint molecules to boost potent and long-lasting antitumor immunity against glioblastoma.

Alternative RNA splicing modulates ribosomal composition and determines the spatial phenotype of glioblastoma cells

Glioblastoma (GBM) is characterized by exceptionally high intratumoral heterogeneity. However, the molecular mechanisms underlying the origin of different GBM cell populations remain unclear. Here, we found that the compositions of ribosomes of GBM cells in the tumour core and edge differ due to alternative RNA splicing. The acidic pH in the core switches before messenger RNA splicing of the ribosomal gene RPL22L1 towards the RPL22L1b isoform. This allows cells to survive acidosis, increases stemness and correlates with worse patient outcome. Mechanistically, RPL22L1b promotes RNA splicing by interacting with lncMALAT1 in the nucleus and inducing its degradation. Contrarily, in the tumour edge region, RPL22L1a interacts with ribosomes in the cytoplasm and upregulates the translation of multiple messenger RNAs including TP53. We found that the RPL22L1 isoform switch is regulated by SRSF4 and identified a compound that inhibits this process and decreases tumour growth. These findings demonstrate how distinct GBM cell populations arise during tumour growth. Targeting this mechanism may decrease GBM heterogeneity and facilitate therapy.

Individualized pathway activity algorithm identifies oncogenic pathways in pan-cancer analysis

Background

Accumulative evidences have shown that dysregulation of biological pathways contributed to the initiation and progression of malignant tumours. Several methods for pathway activity measurement have been proposed, but they are restricted to making comparisons between groups or sensitive to experimental batch effects.

Methods

We introduced a novel method for individualized pathway activity measurement (IPAM) that is based on the ranking of gene expression levels in individual sample. Taking advantage of IPAM, we calculated the pathway activity of 318 pathways from KEGG database in the 10528 tumour/normal samples of 33 cancer types from TCGA to identify characteristic dysregulated pathways among different cancer types.

Findings

IPAM precisely quantified the level of activity of each pathway in pan-cancer analysis and exhibited better performance in cancer classification and prognosis prediction over five widely used tools. The average ROC-AUC of cancer diagnostic model using tumour-educated platelets (TEPs) reached 92.84%, suggesting the potential of our algorithm in early diagnosis of cancer. We identified several pathways significantly deregulated and associated with patient survival in a large fraction of cancer types, such as tyrosine metabolism, fatty acid degradation, cell cycle, p53 signalling pathway and DNA replication. We also confirmed the dominant role of metabolic pathways in cancer pathway dysregulation and identified the driving factors of specific pathway dysregulation, such as PPARA for branched-chain amino acid metabolism and NR1I2, NR1I3 for fatty acid metabolism.

Interpretation

Our study will provide novel clues for understanding the pathological mechanisms of cancer, ultimately paving the way for personalized medicine of cancer.

Funding

A full list of funding can be found in the Acknowledgements section.

Mechanism-Centric Approaches for Biomarker Detection and Precision Therapeutics in Cancer

Biomarker discovery is at the heart of personalized treatment planning and cancer precision therapeutics, encompassing disease classification and prognosis, prediction of treatment response, and therapeutic targeting. However, many biomarkers represent passenger rather than driver alterations, limiting their utilization as functional units for therapeutic targeting. We suggest that identification of driver biomarkers through mechanism-centric approaches, which take into account upstream and downstream regulatory mechanisms, is fundamental to the discovery of functionally meaningful markers. Here, we examine computational approaches that identify mechanism-centric biomarkers elucidated from gene co-expression networks, regulatory networks (e.g., transcriptional regulation), protein-protein interaction (PPI) networks, and molecular pathways. We discuss their objectives, advantages over gene-centric approaches, and known limitations. Future directions highlight the importance of input and model interpretability, method and data integration, and the role of recently introduced technological advantages, such as single-cell sequencing, which are central for effective biomarker discovery and time-cautious precision therapeutics.

Androgen Receptor, Although Not a Specific Marker For, Is a Novel Target to Suppress Glioma Stem Cells as a Therapeutic Strategy for Glioblastoma

Targeting androgen receptor (AR) has been shown to be promising in treating glioblastoma (GBM) in cell culture and flank implant models but the mechanisms remain unclear. AR antagonists including enzalutamide are available for treating prostate cancer patients in clinic and can pass the blood-brain barrier, thus are potentially good candidates for GBM treatment but have not been tested in GBM orthotopically. Our current studies confirmed that in patients, a majority of GBM tumors overexpress AR in both genders. Enzalutamide inhibited the proliferation of GBM cells both in vitro and in vivo. Although confocal microscopy demonstrated that AR is expressed but not specifically in glioma cancer stem cells (CSCs) (CD133+), enzalutamide treatment significantly decreased CSC population in cultured monolayer cells and spheroids, suppressed tumor sphere-forming capacity of GBM cells, and downregulated CSC gene expression at mRNA and protein levels in a dose- and time-dependent manner. We have, for the first time, demonstrated that enzalutamide treatment decreased the density of CSCs in vivo and improved survival in an orthotopic GBM mouse model. We conclude that AR antagonists potently target glioma CSCs in addition to suppressing the overall proliferation of GBM cells as a mechanism supporting their repurposing for clinical applications treating GBM.

Convection Enhanced Delivery of Topotecan for Gliomas: A Single-Center Experience

A key limitation to glioma treatment involves the blood brain barrier (BBB). Convection enhanced delivery (CED) is a technique that uses a catheter placed directly into the brain parenchyma to infuse treatments using a pressure gradient. In this manuscript, we describe the physical principles behind CED along with the common pitfalls and methods for optimizing convection. Finally, we highlight our institutional experience using topotecan CED for the treatment of malignant glioma.

Revealing Prognosis-Related Pathways at the Individual Level by a Comprehensive Analysis of Different Cancer Transcription Data

Identifying perturbed pathways at an individual level is important to discover the causes of cancer and develop individualized custom therapeutic strategies. Though prognostic gene lists have had success in prognosis prediction, using single genes that are related to the relevant system or specific network cannot fully reveal the process of tumorigenesis. We hypothesize that in individual samples, the disruption of transcription homeostasis can influence the occurrence, development, and metastasis of tumors and has implications for patient survival outcomes. Here, we introduced the individual-level pathway score, which can measure the correlation perturbation of the pathways in a single sample well. We applied this method to the expression data of 16 different cancer types from The Cancer Genome Atlas (TCGA) database. Our results indicate that different cancer types as well as their tumor-adjacent tissues can be clearly distinguished by the individual-level pathway score. Additionally, we found that there was strong heterogeneity among different cancer types and the percentage of perturbed pathways as well as the perturbation proportions of tumor samples in each pathway were significantly different. Finally, the prognosis-related pathways of different cancer types were obtained by survival analysis. We demonstrated that the individual-level pathway score (iPS) is capable of classifying cancer types and identifying some key prognosis-related pathways.

CD8+ T-cell-Mediated Immunoediting Influences Genomic Evolution and Immune Evasion in Murine Gliomas

PURPOSE

Cancer immunoediting shapes tumor progression by the selection of tumor cell variants that can evade immune recognition. Given the immune evasion and intratumor heterogeneity characteristic of gliomas, we hypothesized that CD8⁺ T cells mediate immunoediting in these tumors.

EXPERIMENTAL DESIGN

We developed retrovirus-induced PDGF⁺ Pten ^-/- murine gliomas and evaluated glioma progression and tumor immunogenicity in the absence of CD8⁺ T cells by depleting this immune cell population. Furthermore, we characterized the genomic alterations present in gliomas that developed in the presence and absence of CD8⁺ T cells.

RESULTS

Upon transplantation, gliomas that developed in the absence of CD8⁺ T cells engrafted poorly in recipients with intact immunity but engrafted well in those with CD8⁺ T-cell depletion. In contrast, gliomas that developed under pressure from CD8⁺ T cells were able to fully engraft in both CD8⁺ T-cell-depleted mice and immunocompetent mice. Remarkably, gliomas developed in the absence of CD8⁺ T cells exhibited increased aneuploidy, MAPK pathway signaling, gene fusions, and macrophage/microglial infiltration, and showed a proinflammatory phenotype. MAPK activation correlated with macrophage/microglia recruitment in this model and in the human disease.

CONCLUSIONS

Our studies indicate that, in these tumor models, CD8⁺ T cells influence glioma oncogenic pathways, tumor genotype, and immunogenicity. This suggests immunoediting of immunogenic tumor clones through their negative selection by CD8⁺ T cells during glioma formation.

Enhancing Brain Retention of a KIF11 Inhibitor Significantly Improves its Efficacy in a Mouse Model of Glioblastoma

Glioblastoma, the most lethal primary brain cancer, is extremely proliferative and invasive. Tumor cells at tumor/brain-interface often exist behind a functionally intact blood-brain barrier (BBB), and so are shielded from exposure to therapeutic drug concentrations. An ideal glioblastoma treatment needs to engage targets that drive proliferation as well as invasion, with brain penetrant therapies. One such target is the mitotic kinesin KIF11, which can be inhibited with ispinesib, a potent molecularly-targeted drug. Although, achieving durable brain exposures of ispinesib is critical for adequate tumor cell engagement during mitosis, when tumor cells are vulnerable, for efficacy. Our results demonstrate that the delivery of ispinesib is restricted by P-gp and Bcrp efflux at BBB. Thereby, ispinesib distribution is heterogeneous with concentrations substantially lower in invasive tumor rim (intact BBB) compared to glioblastoma core (disrupted BBB). We further find that elacridar—a P-gp and Bcrp inhibitor—improves brain accumulation of ispinesib, resulting in remarkably reduced tumor growth and extended survival in a rodent model of glioblastoma. Such observations show the benefits and feasibility of pairing a potentially ideal treatment with a compound that improves its brain accumulation, and supports use of this strategy in clinical exploration of cell cycle-targeting therapies in brain cancers.

Lentiviral Vector Induced Modeling of High-Grade Spinal Cord Glioma in Minipigs

BACKGROUND

Prior studies have applied driver mutations targeting the RTK/RAS/PI3K and p53 pathways to induce the formation of high-grade gliomas in rodent models. In the present study, we report the production of a high-grade spinal cord glioma model in pigs using lentiviral gene transfer.

METHODS

Six Gottingen Minipigs received thoracolumbar (T14-L1) lateral white matter injections of a combination of lentiviral vectors, expressing platelet-derived growth factor beta (PDGF-B), constitutive HRAS, and shRNA-p53 respectively. All animals received injection of control vectors into the contralateral cord. Animals underwent baseline and endpoint magnetic resonance imaging (MRI) and were evaluated daily for clinical deficits. Hematoxylin and eosin (H&E) and immunohistochemical analysis was conducted. Data are presented using descriptive statistics including relative frequencies, mean, standard deviation, and range.

RESULTS

100% of animals (n = 6/6) developed clinical motor deficits ipsilateral to the oncogenic lentiviral injections by a three-week endpoint. MRI scans at endpoint demonstrated contrast enhancing mass lesions at the site of oncogenic lentiviral injection and not at the site of control injections. Immunohistochemistry demonstrated positive staining for GFAP, Olig2, and a high Ki-67 proliferative index. Histopathologic features demonstrate consistent and reproducible growth of a high-grade glioma in all animals.

CONCLUSIONS

Lentiviral gene transfer represents a feasible pathway to glioma modeling in higher order species. The present model is the first lentiviral vector induced pig model of high-grade spinal cord glioma and may potentially be used in preclinical therapeutic development programs.

NExUS: Bayesian simultaneous network estimation across unequal sample sizes

MOTIVATION

Network-based analyses of high-throughput genomics data provide a holistic, systems-level understanding of various biological mechanisms for a common population. However, when estimating multiple networks across heterogeneous sub-populations, varying sample sizes pose a challenge in the estimation and inference, as network differences may be driven by differences in power. We are particularly interested in addressing this challenge in the context of proteomic networks for related cancers, as the number of subjects available for rare cancer (sub-)types is often limited.

RESULTS

We develop NExUS (Network Estimation across Unequal Sample sizes), a Bayesian method that enables joint learning of multiple networks while avoiding artefactual relationship between sample size and network sparsity. We demonstrate through simulations that NExUS outperforms existing network estimation methods in this context, and apply it to learn network similarity and shared pathway activity for groups of cancers with related origins represented in The Cancer Genome Atlas (TCGA) proteomic data.

AVAILABILITY AND IMPLEMENTATION

The NExUS source code is freely available for download at https://github.com/priyamdas2/NExUS.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Ex vivo multi-electrode analysis reveals spatiotemporal dynamics of ictal behavior at the infiltrated margin of glioma

The purpose of this study is to develop a platform in which the cellular and molecular underpinnings of chronic focal neocortical lesional epilepsy can be explored and use it to characterize seizure-like events (SLEs) in an ex vivo model of infiltrating high-grade glioma. Microelectrode arrays were used to study electrophysiologic changes in ex vivo acute brain slices from a PTEN/p53 deleted, PDGF-B driven mouse model of high-grade glioma. Electrode locations were co-registered to the underlying histology to ascertain the influence of the varying histologic landscape on the observed electrophysiologic changes. Peritumoral, infiltrated, and tumor sites were sampled in tumor-bearing slices. Following the addition of zero Mg²⁺ solution, all three histologic regions in tumor-bearing slices showed significantly greater increases in firing rates when compared to the control sites. Tumor-bearing slices demonstrated increased proclivity for SLEs, with 40 events in tumor-bearing slices and 5 events in control slices (p-value = .0105). Observed SLEs were characterized by either low voltage fast (LVF) onset patterns or short bursts of repetitive widespread, high amplitude low frequency discharges. Seizure foci comprised areas from all three histologic regions. The onset electrode was found to be at the infiltrated margin in 50% of cases and in the peritumoral region in 36.9% of cases. These findings reveal a landscape of histopathologic and electrophysiologic alterations associated with ictogenesis and spread of tumor-associated seizures.

Myosin IIA suppresses glioblastoma development in a mechanically sensitive manner

The ability of glioblastoma to disperse through the brain contributes to its lethality, and blocking this behavior has been an appealing therapeutic approach. Although a number of proinvasive signaling pathways are active in glioblastoma, many are redundant, so targeting one can be overcome by activating another. However, these pathways converge on nonredundant components of the cytoskeleton, and we have shown that inhibiting one of these-the myosin II family of cytoskeletal motors-blocks glioblastoma invasion even with simultaneous activation of multiple upstream promigratory pathways. Myosin IIA and IIB are the most prevalent isoforms of myosin II in glioblastoma, and we now show that codeleting these myosins markedly impairs tumorigenesis and significantly prolongs survival in a rodent model of this disease. However, while targeting just myosin IIA also impairs tumor invasion, it surprisingly increases tumor proliferation in a manner that depends on environmental mechanics. On soft surfaces myosin IIA deletion enhances ERK1/2 activity, while on stiff surfaces it enhances the activity of NFκB, not only in glioblastoma but in triple-negative breast carcinoma and normal keratinocytes as well. We conclude myosin IIA suppresses tumorigenesis in at least two ways that are modulated by the mechanics of the tumor and its stroma. Our results also suggest that inhibiting tumor invasion can enhance tumor proliferation and that effective therapy requires targeting cellular components that drive both proliferation and invasion simultaneously.

Predicting stage-specific cancer related genes and their dynamic modules by integrating multiple datasets

BACKGROUND

The mechanism of many complex diseases has not been detected accurately in terms of their stage evolution. Previous studies mainly focus on the identification of associations between genes and individual diseases, but less is known about their associations with specific disease stages. Exploring biological modules through different disease stages could provide valuable knowledge to genomic and clinical research.

RESULTS

In this study, we proposed a powerful and versatile framework to identify stage-specific cancer related genes and their dynamic modules by integrating multiple datasets. The discovered modules and their specific-signature genes were significantly enriched in many relevant known pathways. To further illustrate the dynamic evolution of these clinical-stages, a pathway network was built by taking individual pathways as vertices and the overlapping relationship between their annotated genes as edges.

CONCLUSIONS

The identified pathway network not only help us to understand the functional evolution of complex diseases, but also useful for clinical management to select the optimum treatment regimens and the appropriate drugs for patients.

Newly Diagnosed Glioblastoma: A Review on Clinical Management

Glioblastoma is an aggressive primary tumor of the central nervous system. This review will focus on clinical developments and management of newly diagnosed disease, including a discussion about the incorporation of molecular features into the classification of glioblastoma. Such advances will continue to shape our thinking about the disease and how to best manage it. With regards to treatment, the role of surgical resection, radiotherapy, chemotherapy, and tumor-treating fields will be presented. Pivotal studies defining our current standard of care will be highlighted, as will key ongoing trials that may influence our management of glioblastoma in the near future.

Elucidating synergistic dependencies in lung adenocarcinoma by proteome-wide signaling-network analysis

To understand drug combination effect, it is necessary to decipher the interactions between drug targets-many of which are signaling molecules. Previously, such signaling pathway models are largely based on the compilation of literature data from heterogeneous cellular contexts. Indeed, de novo reconstruction of signaling interactions from large-scale molecular profiling is still lagging, compared to similar efforts in transcriptional and protein-protein interaction networks. To address this challenge, we introduce a novel algorithm for the systematic inference of protein kinase pathways, and applied it to published mass spectrometry-based phosphotyrosine profile data from 250 lung adenocarcinoma (LUAD) samples. The resulting network includes 43 TKs and 415 inferred, LUAD-specific substrates, which were validated at >60% accuracy by SILAC assays, including "novel' substrates of the EGFR and c-MET TKs, which play a critical oncogenic role in lung cancer. This systematic, data-driven model supported drug response prediction on an individual sample basis, including accurate prediction and validation of synergistic EGFR and c-MET inhibitor activity in cells lacking mutations in either gene, thus contributing to current precision oncology efforts.

Pan-cancer analysis of transcriptional metabolic dysregulation using The Cancer Genome Atlas

Understanding metabolic dysregulation in different disease settings is vital for the safe and effective incorporation of metabolism-targeted therapeutics in the clinic. Here, using transcriptomic data for 10,704 tumor and normal samples from The Cancer Genome Atlas, across 26 disease sites, we present a novel bioinformatics pipeline that distinguishes tumor from normal tissues, based on differential gene expression for 114 metabolic pathways. We confirm pathway dysregulation in separate patient populations, demonstrating the robustness of our approach. Bootstrapping simulations were then applied to assess the biological significance of these alterations. We provide distinct examples of the types of analysis that can be accomplished with this tool to understand cancer specific metabolic dysregulation, highlighting novel pathways of interest, and patterns of metabolic flux, in both common and rare disease sites. Further, we show that Master Metabolic Transcriptional Regulators explain why metabolic differences exist, can segregate patient populations, and predict responders to different metabolism-targeted therapeutics.

Alterations in the Brain Microenvironment in Diffusely Infiltrating Low-Grade Glioma

Glioma cells diffusely infiltrate the surrounding brain tissue where they intermingle with nonneoplastic brain cells, including astrocytes, microglia, oligodendrocytes and neurons. The infiltrative margins of glioma represent the structural and functional interface between neoplastic and nonneoplastic brain tissue that underlies neurologic alterations associated with glioma, including epilepsy and neurologic deficits. Technological advancements in molecular analysis, including single cell sequencing, now allow us to assess alterations in specific cell types in the brain tumor microenvironment, which can enhance the development of novel therapies that target glioma growth and glioma-induced neurologic symptoms.

Genetic Abnormalities, Clonal Evolution, and Cancer Stem Cells of Brain Tumors

Brain tumors are highly heterogeneous and have been classified by the World Health Organization in various histological and molecular subtypes. Gliomas have been classified as ranging from low-grade astrocytomas and oligodendrogliomas to high-grade astrocytomas or glioblastomas. These tumors are characterized by a peculiar pattern of genetic alterations. Pediatric high-grade gliomas are histologically indistinguishable from adult glioblastomas, but they are considered distinct from adult glioblastomas because they possess a different spectrum of driver mutations (genes encoding histones H3.3 and H3.1). Medulloblastomas, the most frequent pediatric brain tumors, are considered to be of embryonic derivation and are currently subdivided into distinct subgroups depending on histological features and genetic profiling. There is emerging evidence that brain tumors are maintained by a special neural or glial stem cell-like population that self-renews and gives rise to differentiated progeny. In many instances, the prognosis of the majority of brain tumors remains negative and there is hope that the new acquisition of information on the molecular and cellular bases of these tumors will be translated in the development of new, more active treatments.

PRMT5-mediated regulation of developmental myelination

Oligodendrocytes (OLs) are the myelin-forming cells of the central nervous system. They are derived from differentiation of oligodendrocyte progenitors through a process requiring cell cycle exit and histone modifications. Here we identify the histone arginine methyl-transferase PRMT5, a molecule catalyzing symmetric methylation of histone H4R3, as critical for developmental myelination. PRMT5 pharmacological inhibition, CRISPR/cas9 targeting, or genetic ablation decrease p53-dependent survival and impair differentiation without affecting proliferation. Conditional ablation of Prmt5 in progenitors results in hypomyelination, reduced survival and differentiation. Decreased histone H4R3 symmetric methylation is followed by increased nuclear acetylation of H4K5, and is rescued by pharmacological inhibition of histone acetyltransferases. Data obtained using purified histones further validate the results obtained in mice and in cultured oligodendrocyte progenitors. Together, these results identify PRMT5 as critical for oligodendrocyte differentiation and developmental myelination by modulating the cross-talk between histone arginine methylation and lysine acetylation.

Myelin-forming cells derive from oligodendrocyte progenitors. Here the authors identify histone arginine methyl-transferase PRMT5 as critical for developmental myelination by modulating the cross-talk between histone arginine methylation and lysine acetylation, to favor differentiation.

Genomic profiles of low-grade murine gliomas evolve during progression to glioblastoma

Background

Gliomas are diverse neoplasms with multiple molecular subtypes. How tumor-initiating mutations relate to molecular subtypes as these tumors evolve during malignant progression remains unclear.

Methods

We used genetically engineered mouse models, histopathology, genetic lineage tracing, expression profiling, and copy number analyses to examine how genomic tumor diversity evolves during the course of malignant progression from low- to high-grade disease.

Results

Knockout of all 3 retinoblastoma (Rb) family proteins was required to initiate low-grade tumors in adult mouse astrocytes. Mutations activating mitogen-activated protein kinase signaling, specifically KrasG12D, potentiated Rb-mediated tumorigenesis. Low-grade tumors showed mutant Kras-specific transcriptome profiles but lacked copy number mutations. These tumors stochastically progressed to high-grade, in part through acquisition of copy number mutations. High-grade tumor transcriptomes were heterogeneous and consisted of 3 subtypes that mimicked human mesenchymal, proneural, and neural glioblastomas. Subtypes were confirmed in validation sets of high-grade mouse tumors initiated by different driver mutations as well as human patient-derived xenograft models and glioblastoma tumors.

Conclusion

These results suggest that oncogenic driver mutations influence the genomic profiles of low-grade tumors and that these, as well as progression-acquired mutations, contribute strongly to the genomic heterogeneity across high-grade tumors.

The possibility of cancer immune editing in gliomas. A critical review

The relationship between anti-tumoral immunity and cancer progression is complex. Recently, immune editing has emerged as a model to explain the interplay between the immune system and the selection of genetic alterations in cancer. In this model, the immune system selects cancer cells that grow as these are fit to escape immune surveillance during tumor development. Gliomas and glioblastoma, the most aggressive and most common of all primary malignant brain tumors are genetically heterogeneous, are relatively less antigenic, and are less responsive to immunotherapy than other cancers. In this review, we provide an overview of the relationship between glioma´s immune suppressive features, anti-tumoral immunity and cancer genomics. In this context, we provide a critical discussion of evidence suggestive of immune editing in this disease and discuss possible alternative explanations for these findings.

Integrative molecular network analysis identifies emergent enzalutamide resistance mechanisms in prostate cancer

Recent work demonstrates that castration-resistant prostate cancer (CRPC) tumors harbor countless genomic aberrations that control many hallmarks of cancer. While some specific mutations in CRPC may be actionable, many others are not. We hypothesized that genomic aberrations in cancer may operate in concert to promote drug resistance and tumor progression, and that organization of these genomic aberrations into therapeutically targetable pathways may improve our ability to treat CRPC. To identify the molecular underpinnings of enzalutamide-resistant CRPC, we performed transcriptional and copy number profiling studies using paired enzalutamide-sensitive and resistant LNCaP prostate cancer cell lines. Gene networks associated with enzalutamide resistance were revealed by performing an integrative genomic analysis with the PAthway Representation and Analysis by Direct Reference on Graphical Models (PARADIGM) tool. Amongst the pathways enriched in the enzalutamide-resistant cells were those associated with MEK, EGFR, RAS, and NFKB. Functional validation studies of 64 genes identified 10 candidate genes whose suppression led to greater effects on cell viability in enzalutamide-resistant cells as compared to sensitive parental cells. Examination of a patient cohort demonstrated that several of our functionally-validated gene hits are deregulated in metastatic CRPC tumor samples, suggesting that they may be clinically relevant therapeutic targets for patients with enzalutamide-resistant CRPC. Altogether, our approach demonstrates the potential of integrative genomic analyses to clarify determinants of drug resistance and rational co-targeting strategies to overcome resistance.

The Updated World Health Organization Glioma Classification: Cellular and Molecular Origins of Adult Infiltrating Gliomas

CONTEXT

- In the recently updated World Health Organization (WHO) classification of central nervous system tumors, our concept of infiltrating gliomas as a molecular dichotomy between oligodendroglial and astrocytic tumors has been codified. Advances in animal models of glioma and a wealth of sophisticated molecular analyses of human glioma tissue have led to a greater understanding of some of the biologic underpinnings of gliomagenesis.

OBJECTIVE

- To review our understanding of gliomagenesis in the setting of the recently updated WHO classification of central nervous system tumors. Topics addressed include a summary of an updated diagnostic schema for infiltrating gliomas, the crucial importance of isocitrate dehydrogenase mutations, candidate cells of origin for gliomas, environmental and other posited contributing factors to gliomagenesis, and the possible role of chromatin topology in setting the stage for gliomagenesis.

DATA SOURCES

- We conducted a primary literature search using PubMed.

CONCLUSIONS

- With multidimensional molecular data sets spanning increasingly larger numbers of patients with infiltrating gliomas, our understanding of the disease at the point of surgical resection has improved dramatically and this understanding is reflected in the updated WHO classification. Animal models have demonstrated a diversity of candidates for glioma cells of origin, but crucial questions remain, including the role of neural stem cells, more differentiated progenitor cells, and glioma stem cells. At this stage the increase in data generated from human samples will hopefully inform the creation of newer animal models that will recapitulate more accurately the diversity of gliomas and provide novel insights into the biologic mechanisms underlying tumor initiation and progression.

Harnessing OLIG2 function in tumorigenicity and plasticity to target malignant gliomas

Glioblastoma (GBM) is the most prevalent and malignant brain tumor, displaying notorious resistance to conventional therapy, partially due to molecular and genetic heterogeneity. Understanding the mechanisms for gliomagenesis, tumor stem/progenitor cell propagation and phenotypic diversity is critical for devising effective and targeted therapy for this lethal disease. The basic helix-loop-helix transcription factor OLIG2, which is universally expressed in gliomas, has emerged as an important player in GBM cell reprogramming, genotoxic resistance, and tumor phenotype plasticity. In an animal model of proneural GBM, elimination of mitotic OLIG2⁺ progenitors blocks tumor growth, suggesting that these progenitors are a seeding source for glioma propagation. OLIG2 deletion reduces tumor growth and causes an oligodendrocytic to astrocytic phenotype shift, with PDGFRα downregulation and reciprocal EGFR signaling upregulation, underlying alternative pathways in tumor recurrence. In patient-derived glioma stem cells (GSC), knockdown of OLIG2 leads to downregulation of PDGFRα, while OLIG2 silencing results in a shift from proneural-to-classical gene expression pattern or a proneural-to-mesenchymal transition in distinct GSC cell lines, where OLIG2 appears to regulate EGFR expression in a context-dependent manner. In addition, post-translational modifications such as phosphorylation by a series of protein kinases regulates OLIG2 activity in glioma cell growth and invasive behaviors. In this perspective, we will review the role of OLIG2 in tumor initiation, proliferation and phenotypic plasticity in animal models of gliomas and human GSC cell lines, and discuss the underlying mechanisms in the control of tumor growth and potential therapeutic strategies to target OLIG2 in malignant gliomas.

Quantitative Phosphoproteomics Reveals Wee1 Kinase as a Therapeutic Target in a Model of Proneural Glioblastoma

Glioblastoma (GBM) is the most common malignant primary brain cancer. With a median survival of about a year, new approaches to treating this disease are necessary. To identify signaling molecules regulating GBM progression in a genetically engineered murine model of proneural GBM, we quantified phosphotyrosine-mediated signaling using mass spectrometry. Oncogenic signals, including phosphorylated ERK MAPK, PI3K, and PDGFR, were found to be increased in the murine tumors relative to brain. Phosphorylation of CDK1 pY15, associated with the G2 arrest checkpoint, was identified as the most differentially phosphorylated site, with a 14-fold increase in phosphorylation in the tumors. To assess the role of this checkpoint as a potential therapeutic target, syngeneic primary cell lines derived from these tumors were treated with MK-1775, an inhibitor of Wee1, the kinase responsible for CDK1 Y15 phosphorylation. MK-1775 treatment led to mitotic catastrophe, as defined by increased DNA damage and cell death by apoptosis. To assess the extensibility of targeting Wee1/CDK1 in GBM, patient-derived xenograft (PDX) cell lines were also treated with MK-1775. Although the response was more heterogeneous, on-target Wee1 inhibition led to decreased CDK1 Y15 phosphorylation and increased DNA damage and apoptosis in each line. These results were also validated in vivo, where single-agent MK-1775 demonstrated an antitumor effect on a flank PDX tumor model, increasing mouse survival by 1.74-fold. This study highlights the ability of unbiased quantitative phosphoproteomics to reveal therapeutic targets in tumor models, and the potential for Wee1 inhibition as a treatment approach in preclinical models of GBM. Mol Cancer Ther; 15(6); 1332-43. ©2016 AACR.

Quantitative Phosphoproteomics Reveals Wee1 Kinase as a Therapeutic Target in a Model of Proneural Glioblastoma

Glioblastoma (GBM) is the most common malignant primary brain cancer. With a median survival of about a year, new approaches to treating this disease are necessary. To identify signaling molecules regulating GBM progression in a genetically engineered murine model of proneural GBM, we quantified phosphotyrosine-mediated signaling using mass spectrometry. Oncogenic signals, including phosphorylated ERK MAPK, PI3K, and PDGFR, were found to be increased in the murine tumors relative to brain. Phosphorylation of CDK1 pY15, associated with the G2 arrest checkpoint, was identified as the most differentially phosphorylated site, with a 14-fold increase in phosphorylation in the tumors. To assess the role of this checkpoint as a potential therapeutic target, syngeneic primary cell lines derived from these tumors were treated with MK-1775, an inhibitor of Wee1, the kinase responsible for CDK1 Y15 phosphorylation. MK-1775 treatment led to mitotic catastrophe, as defined by increased DNA damage and cell death by apoptosis. To assess the extensibility of targeting Wee1/CDK1 in GBM, patient-derived xenograft (PDX) cell lines were also treated with MK-1775. Although the response was more heterogeneous, on-target Wee1 inhibition led to decreased CDK1 Y15 phosphorylation and increased DNA damage and apoptosis in each line. These results were also validated in vivo, where single-agent MK-1775 demonstrated an antitumor effect on a flank PDX tumor model, increasing mouse survival by 1.74-fold. This study highlights the ability of unbiased quantitative phosphoproteomics to reveal therapeutic targets in tumor models, and the potential for Wee1 inhibition as a treatment approach in preclinical models of GBM. Mol Cancer Ther; 15(6); 1332-43. ©2016 AACR.

Olig2-Dependent Reciprocal Shift in PDGF and EGF Receptor Signaling Regulates Tumor Phenotype and Mitotic Growth in Malignant Glioma

Malignant gliomas exhibit extensive heterogeneity and poor prognosis. Here we identify mitotic Olig2-expressing cells as tumor-propagating cells in proneural gliomas, elimination of which blocks tumor initiation and progression. Intriguingly, deletion of Olig2 resulted in tumors that grow, albeit at a decelerated rate. Genome occupancy and expression profiling analyses reveal that Olig2 directly activates cell-proliferation machinery to promote tumorigenesis. Olig2 deletion causes a tumor phenotypic shift from an oligodendrocyte precursor-correlated proneural toward an astroglia-associated gene expression pattern, manifest in downregulation of platelet-derived growth factor receptor-α and reciprocal upregulation of epidermal growth factor receptor (EGFR). Olig2 deletion further sensitizes glioma cells to EGFR inhibitors and extends the lifespan of animals. Thus, Olig2-orchestrated receptor signaling drives mitotic growth and regulates glioma phenotypic plasticity. Targeting Olig2 may circumvent resistance to EGFR-targeted drugs.

Network-based methods for identifying critical pathways of complex diseases: a survey

We review seven major network-based pathway analysis methods and enumerate their benefits and limitations from an algorithmic perspective to provide a reference for the next generation of pathway analysis methods.

Construction and analysis of dynamic transcription factor regulatory networks in the progression of glioma

The combinatorial cross-regulation of transcription factors (TFs) plays an important role in cellular identity and function; however, the dynamic regulation of TFs during glioma progression remains largely unknown. Here, we used the genome-wide expression of TFs to construct an extensive human TF network comprising interactions among 513 TFs and to analyse the dynamics of the TF-TF network during glioma progression. We found that the TF regulatory networks share a common architecture and that the topological structures are conserved. Strikingly, despite the conservation of the network architecture, TF regulatory networks are highly grade specific, and TF circuitry motifs are dynamically rewired during glioma progression. In addition, the most frequently observed structure in the grade-specific TF networks was the feedforward loop (FFL). We described applications that show how investigating the behaviour of FFLs in glioblastoma can reveal FFLs (such as RARG-NR1I2-CDX2) that are associated with prognosis. We constructed comprehensive TF-TF networks and systematically analysed the circuitry, dynamics, and topological principles of the networks during glioma progression, which will further enhance our understanding of the functions of TFs in glioma.

Pathway and network analysis of cancer genomes

Genomic information on tumors from 50 cancer types cataloged by the International Cancer Genome Consortium (ICGC) shows that only a few well-studied driver genes are frequently mutated, in contrast to many infrequently mutated genes that may also contribute to tumor biology. Hence there has been large interest in developing pathway and network analysis methods that group genes and illuminate the processes involved. We provide an overview of these analysis techniques and show where they guide mechanistic and translational investigations.

Biomarkers for glioma immunotherapy: the next generation

The term "biomarker" historically refers to a single parameter, such as the expression level of a gene or a radiographic pattern, used to indicate a broader biological state. Molecular indicators have been applied to several aspects of cancer therapy: to describe the genotypic and phenotypic state of neoplastic tissue for prognosis, to predict susceptibility to anti-proliferative agents, to validate the presence of specific drug targets, and to evaluate responsiveness to therapy. For glioblastoma (GBM), immunohistochemical and radiographic biomarkers accessible to the clinical lab have informed traditional regimens, but while immunotherapies have emerged as potentially disruptive weapons against this diffusely infiltrating, heterogeneous tumor, biomarkers with strong predictive power have not been fully established. The cancer immunotherapy field, through the recently accelerated expansion of trials, is currently leveraging this wealth of clinical and biological data to define and revise the use of biomarkers for improving prognostic accuracy, personalization of therapy, and evaluation of responses across the wide variety of tumors. Technological advancements in DNA sequencing, cytometry, and microscopy have facilitated the exploration of more integrated, high-dimensional profiling of the disease system-incorporating both immune and tumor parameters-rather than single metrics, as biomarkers for therapeutic sensitivity. Here we discuss the utility of traditional GBM biomarkers in immunotherapy and how the impending transformation of the biomarker paradigm-from single markers to integrated profiles-may offer the key to bringing predictive, personalized immunotherapy to GBM patients.

Ribosome profiling reveals a cell-type-specific translational landscape in brain tumors

Glioma growth is driven by signaling that ultimately regulates protein synthesis. Gliomas are also complex at the cellular level and involve multiple cell types, including transformed and reactive cells in the brain tumor microenvironment. The distinct functions of the various cell types likely lead to different requirements and regulatory paradigms for protein synthesis. Proneural gliomas can arise from transformation of glial progenitors that are driven to proliferate via mitogenic signaling that affects translation. To investigate translational regulation in this system, we developed a RiboTag glioma mouse model that enables cell-type-specific, genome-wide ribosome profiling of tumor tissue. Infecting glial progenitors with Cre-recombinant retrovirus simultaneously activates expression of tagged ribosomes and delivers a tumor-initiating mutation. Remarkably, we find that although genes specific to transformed cells are highly translated, their translation efficiencies are low compared with normal brain. Ribosome positioning reveals sequence-dependent regulation of ribosomal activity in 5'-leaders upstream of annotated start codons, leading to differential translation in glioma compared with normal brain. Additionally, although transformed cells express a proneural signature, untransformed tumor-associated cells, including reactive astrocytes and microglia, express a mesenchymal signature. Finally, we observe the same phenomena in human disease by combining ribosome profiling of human proneural tumor and non-neoplastic brain tissue with computational deconvolution to assess cell-type-specific translational regulation.

MRI-localized biopsies reveal subtype-specific differences in molecular and cellular composition at the margins of glioblastoma

Glioblastomas (GBMs) diffusely infiltrate the brain, making complete removal by surgical resection impossible. The mixture of neoplastic and nonneoplastic cells that remain after surgery form the biological context for adjuvant therapeutic intervention and recurrence. We performed RNA-sequencing (RNA-seq) and histological analysis on radiographically guided biopsies taken from different regions of GBM and showed that the tissue contained within the contrast-enhancing (CE) core of tumors have different cellular and molecular compositions compared with tissue from the nonenhancing (NE) margins of tumors. Comparisons with the The Cancer Genome Atlas dataset showed that the samples from CE regions resembled the proneural, classical, or mesenchymal subtypes of GBM, whereas the samples from the NE regions predominantly resembled the neural subtype. Computational deconvolution of the RNA-seq data revealed that contributions from nonneoplastic brain cells significantly influence the expression pattern in the NE samples. Gene ontology analysis showed that the cell type-specific expression patterns were functionally distinct and highly enriched in genes associated with the corresponding cell phenotypes. Comparing the RNA-seq data from the GBM samples to that of nonneoplastic brain revealed that the differentially expressed genes are distributed across multiple cell types. Notably, the patterns of cell type-specific alterations varied between the different GBM subtypes: the NE regions of proneural tumors were enriched in oligodendrocyte progenitor genes, whereas the NE regions of mesenchymal GBM were enriched in astrocytic and microglial genes. These subtype-specific patterns provide new insights into molecular and cellular composition of the infiltrative margins of GBM.

Convection-enhanced delivery of etoposide is effective against murine proneural glioblastoma

BACKGROUND

Glioblastoma subtypes have been defined based on transcriptional profiling, yet personalized care based on molecular classification remains unexploited. Topoisomerase II (TOP2) contributes to the transcriptional signature of the proneural glioma subtype. Thus, we targeted TOP2 pharmacologically with etoposide in proneural glioma models.

METHODS

TOP2 gene expression was evaluated in mouse platelet derived growth factor (PDGF)(+)phosphatase and tensin homolog (PTEN)(-/-)p53(-/-) and PDGF(+)PTEN(-/-) proneural gliomas and cell lines, as well as human glioblastoma from The Cancer Genome Atlas. Correlation between TOP2 transcript levels and etoposide susceptibility was investigated in 139 human cancer cell lines from the Cancer Cell Line Encyclopedia public dataset and in mouse proneural glioma cell lines. Convection-enhanced delivery (CED) of etoposide was tested on cell-based PDGF(+)PTEN(-/-)p53(-/-) and retroviral-based PDGF(+)PTEN(-/-) mouse proneural glioma models.

RESULTS

TOP2 expression was significantly higher in human proneural glioblastoma and in mouse proneural tumors at early as well as late stages of development compared with normal brain. TOP2B transcript correlated with susceptibility to etoposide in mouse proneural cell lines and in 139 human cancer cell lines from the Cancer Cell Line Encyclopedia. Intracranial etoposide CED treatment (680 μM) was well tolerated by mice and led to a significant survival benefit in the PDGF(+)PTEN(-/-)p53(-/-) glioma model. Moreover, etoposide CED treatment at 80 μM but not 4 μM led to a significant survival advantage in the PDGF(+)PTEN(-/-) glioma model.

CONCLUSIONS

TOP2 is highly expressed in proneural gliomas, rendering its pharmacological targeting by intratumoral administration of etoposide by CED effective on murine proneural gliomas. We provide evidence supporting clinical testing of CED of etoposide with a molecular-based patient selection approach.