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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.

Characterization of ZBTB18 short band by MS.

GSEA analysis in BTSC233.

Proliferation, migration and invasion assays in SNB19 cells.

ZBTB18 promoter methylation analysis.

Glioblastoma (GBM) comprises distinct subtypes characterized by their molecular profile. Mesenchymal identity in GBM has been associated with a comparatively unfavorable prognosis, primarily due to inherent resistance of these tumors to current therapies. The identification of molecular determinants of mesenchymal transformation could potentially allow for the discovery of new therapeutic targets. Zinc Finger and BTB Domain Containing 18 (ZBTB18/ZNF238/RP58) is a zinc finger transcriptional repressor with a crucial role in brain development and neuronal differentiation. Here, ZBTB18 is primarily silenced in the mesenchymal subtype of GBM through aberrant promoter methylation. Loss of ZBTB18 contributes to the aggressive phenotype of glioblastoma through regulation of poor prognosis–associated signatures. Restitution of ZBTB18 expression reverses the phenotype and impairs tumor-forming ability. These results indicate that ZBTB18 functions as a tumor suppressor in GBM through the regulation of genes associated with phenotypically aggressive properties.Implications: This study characterizes the role of the putative tumor suppressor ZBTB18 and its regulation by promoter hypermethylation, which appears to be a common mechanism to silence ZBTB18 in the mesenchymal subtype of GBM and provides a new mechanistic opportunity to specifically target this tumor subclass. Mol Cancer Res; 15(8); 998–1011. ©2017 AACR.

Proliferation, migration and invasion assays in BTSC233 and JX6 cells.

Table S1. Enriched GO terms for commonly upregulated genes in responsive cell lines and U3017MG harboring the control vector upon BMP4 treatment, according to the Database for Annotation, Visualization and Integrated Discovery (DAVID).

GSEA analysis in JX6.

ZBTB18 promoter methylation analysis.

Proteomics and phosphoproteomics data analyses II

Cell death analysis

Background: Glioblastoma multiforme and high-risk neuroblastoma are cancers with poor outcome. Immunotherapy in the form of neurotropic oncolytic viruses is a promising therapeutic approach for these malignancies. Here we evaluate the oncolytic capacity of the neurovirulent and partly IFNβ-resistant Semliki Forest virus (SFV)-4 in glioblastoma multiformes and neuroblastomas. To reduce neurovirulence we constructed SFV4miRT, which is attenuated in normal central nervous system (CNS) cells through insertion of microRNA target sequences for miR124, miR125, miR134.Methods: Oncolytic activity of SFV4miRT was examined in mouse neuroblastoma and glioblastoma multiforme cell lines and in patient-derived human glioblastoma cell cultures (HGCC). In vivo neurovirulence and therapeutic efficacy was evaluated in two syngeneic orthotopic glioma models (CT-2A, GL261) and a syngeneic subcutaneous neuroblastoma model (NXS2). The role of IFNβ in inhibiting therapeutic efficacy was investigated.Results: The introduction of miRNA target sequences reduced neurovirulence of SFV4 in terms of attenuated replication in mouse CNS cells and ability to cause encephalitis when administered intravenously. A single intravenous injection of SFV4miRT prolonged survival and cured four of eight mice (50%) with NXS2 and three of 11 mice (27%) with CT-2A, but not for GL261 tumor-bearing mice. In vivo therapeutic efficacy in different tumor models inversely correlated to secretion of IFNβ by respective cells upon SFV4 infection in vitro. Similarly, killing efficacy of HGCC lines inversely correlated to IFNβ response and interferon-α/β receptor-1 expression.Conclusions: SFV4miRT has reduced neurovirulence, while retaining its oncolytic capacity. SFV4miRT is an excellent candidate for treatment of glioblastoma multiforme and neuroblastoma with low IFN-β secretion. Clin Cancer Res; 23(6); 1519–30. ©2016 AACR.

Supplementary Figure Legends and Materials and Methods

Glioma-initiating cells (GIC) are considered the underlying cause of recurrences of aggressive glioblastomas, replenishing the tumor population and undermining the efficacy of conventional chemotherapy. Here we report the discovery that inhibiting T-type voltage-gated Ca2+ and KCa channels can effectively induce selective cell death of GIC and increase host survival in an orthotopic mouse model of human glioma. At present, the precise cellular pathways affected by the drugs affecting these channels are unknown. However, using cell-based assays and integrated proteomics, phosphoproteomics, and transcriptomics analyses, we identified the downstream signaling events these drugs affect. Changes in plasma membrane depolarization and elevated intracellular Na+, which compromised Na+-dependent nutrient transport, were documented. Deficits in nutrient deficit acted in turn to trigger the unfolded protein response and the amino acid response, leading ultimately to nutrient starvation and GIC cell death. Our results suggest new therapeutic targets to attack aggressive gliomas. Cancer Res; 77(7); 1741–52. ©2017 AACR.

Supplementary material and methods Supplementary Table 1: miR124, miR125 and miR134 expression relative to human or mouse U6 snRNA in normal mouse CNS tissues, mouse neural stem cells, in vitro-differentiated mouse brain cells, mouse neuroblastoma, human neuroblastoma and in human glioblastoma cell culture (HGCC) lines. Supplementary Table 2: Comprehensive information of HGCC lines used in the experiments Supplementary Figure S1. SFV4-GFPmiRT and A7/74-GFPmiRT are inhibited in the presence of exogenous miR124, miR125 or miR134. Supplementary Figure S2. SFV infection induces killing of human neuroblastoma cell lines. Supplementary Figure S3. Oncolytic efficiency of A7/74miRT in murine tumor models in vitro and in vivo. Supplementary Figure S4. SFV4miRT-mediated killing of HGCC lines in vitro in the presence and absence of IFN-β.

Nervous system cancers contain a large spectrum of transcriptional cell states, reflecting processes active during normal development, injury response and growth. However, we lack a good understanding of these states’ regulation and pharmacological importance. Here, we describe the integrated reconstruction of such cellular regulatory programs and their therapeutic targets from extensive collections of single-cell RNA sequencing data (scRNA-seq) from both tumors and developing tissues. Our method, termed single-cell Regulatory-driven Clustering (scRegClust), predicts essential kinases and transcription factors in little computational time thanks to a new efficient optimization strategy. Using this method, we analyze scRNA-seq data from both adult and childhood brain cancers to identify transcription factors and kinases that regulate distinct tumor cell states. In adult glioblastoma, our model predicts that blocking the activity ofPDGFRA,DDR1,ERBB3orSOX6, or increasingYBX1-activity, would potentiate temozolomide treatment. We further perform an integrative study of scRNA-seq data from both cancer and the developing brain to uncover the regulation of emerging meta-modules. We find a meta-module regulated by the transcription factorsSPI1andIRF8and link it to an immune-mediated mesenchymal-like state. Our algorithm is available as an easy-to-use R package and companion visualization tool that help uncover the regulatory programs underlying cell plasticity in cancer and other diseases.

Glioblastomas (GBMs) are malignant brain tumors characterized by uncontrolled, invasive growth along multiple anatomical pathways. GBM is well-studied on a genetic and molecular level, but clinically relevant, experimentally tractable models of invasive growth are largely lacking. We report an integrated study of patient-matched information including clinical and radiological data, patient-derived xenografts, genomics, transcriptomics, epigenomics, and drug response data. Our hypothesis is that joint variation across these levels can expose treatments and biomarkers associated with glioblastoma invasion and recurrence. In total, 64 patient-derived cell lines (PDCLs) were injected into the striatum of n >= 4 mice each, of which 45 PDCLs successfully formed tumors. The tumor-forming PDCLs were each scored with respect to 10 distinct growth characteristics (n= 182 mice). The repertoire of phenotypes was highly divergent and included clear cases of perivascular invasion, white matter invasion, perineuronal satellitosis, and gliosarcoma. We explored if cellular pathways, monitored by RNA sequencing, could account for these differences. DNA repair, Wnt-, and Notch-pathways were predictive of tumor initiation, whereas pathways related to hypoxia, metabolic reprogramming, cellular stress, and inflammation reduced tumor initiation capacity of PDCLs. Transcriptional signatures were also strongly predictive of route-specific invasion. Diffuse invasion was predominantly seen in classical-subtype PDCLs with astrocytic or outer radial glia-like signatures. Proneural PDCLs, in turn, grew as solid tumors with an invasive peripheral region, and mesenchymal tumors were demarcated and invaded around vasculature. To explore the therapeutic implications of our findings, we used our data-driven method TargetTranslator to predict the drug vulnerabilities of different types of invasive glioblastoma. Transcriptional signatures of diffusively growing tumors suggested a vulnerability to neuroactive substrates while perivascular invading tumors would be more susceptible to CDK- and RTK inhibitors. We expect that focusing on drivers of these functional signatures will greatly facilitate the search for effective compounds targeting distinct growth behaviors.

We describe a new molecular subgroup of glioblastoma, the most prevalent malignant adult brain tumour, harbouring a bias towards hypomethylation at defined differentially methylated regions. This epigenetic signature correlates with an enrichment for an astrocytic gene signature, which together with the identification of enriched predicted binding sites of transcription factors known to cause demethylation and to be involved in astrocytic/glial lineage specification, point to a shared ontogeny between this glioblastoma subgroup and astroglial progenitors. At functional level, increased invasiveness, at least in part mediated by SRPX2, and macrophage infiltration characterise this glioblastoma subgroup.

Glioblastoma (GBM) is the most common form of adult brain tumors and patients diagnosed with GBM face a very dismal prognosis with a median survival rate of 15 months. The challenges in treating GBM are many, there is a complex cellular and molecular heterogeneity, both between patients and within individual tumors. In a single tumor, individual cancer cells adopt a variety of stem-like, progenitor-like, and more differentiated phenotypes (a.k.a. cell states). Recent advances in single-cell technology have made it possible to detect this diversity of cellular states, but yet we lack a good explanation for how the states arise and if transitions between states can be exploited to therapeutic ends. We here propose a new computational strategy to measure the differentiation potential of GBM cells, based on the Ising models from statistical mechanics. Originally used to model coupled magnets on a lattice, the Ising models can be generalized to represent the probability of a particular configuration of any system of n variables. We show that the models can be fitted to high-dimensional single cell data in a matter of seconds by solving a convex optimization problem, and that the models help explain cell differentiation in terms of minimization of an energy function of the system. In our on-going work we have fitted the model to single cell data from our previous work on state transitions in GBM (Larsson, Dalmo et al, Molecular Systems Biology 2021) and shown that the predicted differentiation potential of cell states is consistent with the cell state hierarchies derived from lineage tracing experiments. Moving forward, we are now exploring how the Ising models can be used to model state transitions in GBM and to predict the effect of targeted therapy on the cell’s differentiation potential.

Glioblastoma (GBM) is an aggressive nervous system tumor with a mean survival time of 12-14 months. Cells with neural stem cell-like properties can be derived from GBM tumors. These cells seem to escape conventional irradiation treatment, chemotherapy, and surgery, and may play a crucial role for relapse. It is therefore urgent to develop novel approaches for reliable detection of neural stem cell-like cells in GBM. Here we report a luminescent conjugated oligothiophene (LCO), named GlioStem (p-HTMI), for non-invasive and non-amplified real-time detection of live human patient-derived GBM cells and embryonic neural stem/progenitor cells (NSPCs). Within a maximum of 10 minutes after administration of the molecule in vitro, in the existing media, fluorescence emission was observed without any modulation of the cells or additional vehicle, resulting in efficient detection of cytoplasmic luminescent signal in NSPCs or GBM cells from rodents and humans, detectable at Alexa488/GFP wavelength. GlioStem is functionalized with a methylated imidazole moiety resembling the side chain of histidine/histamine, and non-methylated analogues were not functional. In vitro, GlioStem was shown to identify fetal cortical NSPCs from rat (FGF2-expanded), embryonic stem cell-derived NSPCs from mouse (FGF2/EGF-expanded), and FGF2-exposed C6 glioma cell cultures from rat, but not any other cell types investigated. Cell sorting experiments of patient-derived, FGF2/EGF-expanded GBM cells demonstrated that GlioStem in addition to NSPC-markers like Nestin and Sox2 labeled the same population (overlap > 90%) of cells as CD271, a proposed marker for stem cell-like cells and rapidly migrating cells in glioblastoma. Our results suggest that the LCO GlioStem is a versatile tool for immediate and selective detection of subpopulations of neural stem and glioma cells.

Brain tumors are the leading cause of childhood cancer-related death. Medulloblastoma is the most common malignant pediatric brain tumor with about 70% survival. Medulloblastoma comprises four distinct subgroups respective of genomic and molecular drivers influencing tumorigenesis. It has been established that despite being considered a single disease entity, each subgroup arises from a distinct population of cells found within unique compartments of the developing brain. The cell of origin of Group 3 medulloblastoma, the most malignant medulloblastoma subgroups, is currently unknown and remains controversial. Transcriptional profiling has revealed that Group 3 medulloblastomas are characterized by elevated expression of a photoreceptor program, which has not been described in the normal cerebellar development but is well characterized in the developing pineal gland and retinal. By investigating and comparing brain and tumor development between our previously developed medulloblastoma mice model (GMYC), where mice spontaneously develop Group 3 medulloblastoma after 4-6 months of age, and their control counterparts, we found that tumor cells emerged from progenitor cells where MYC overexpression drove the transformation of immature progenitor cells expressing a photoreceptor program. Our data suggest that MYC-driven Group 3 medulloblastoma originates from progenitor cells expressing a photoreceptor program, which has implications for future research and the development of novel treatments targeting this devastating childhood malignancy.