23 research outputs found

    Genome-wide shRNA screen revealed integrated mitogenic signaling between dopamine receptor D2 (DRD2) and epidermal growth factor receptor (EGFR) in glioblastoma

    Get PDF
    Glioblastoma remains one of the deadliest of human cancers, with most patients succumbing to the disease within two years of diagnosis. The available data suggest that simultaneous inactivation of critical nodes within the glioblastoma molecular circuitry will be required for meaningful clinical efficacy. We conducted parallel genome-wide shRNA screens to identify such nodes and uncovered a number of G-Protein Coupled Receptor (GPCR) neurotransmitter pathways, including the Dopamine Receptor D2 (DRD2) signaling pathway. Supporting the importance of DRD2 in glioblastoma, DRD2 mRNA and protein expression were elevated in clinical glioblastoma specimens relative to matched non-neoplastic cerebrum. Treatment with independent si-/shRNAs against DRD2 or with DRD2 antagonists suppressed the growth of patient-derived glioblastoma lines both in vitro and in vivo. Importantly, glioblastoma lines derived from independent genetically engineered mouse models (GEMMs) were more sensitive to haloperidol, an FDA approved DRD2 antagonist, than the premalignant astrocyte lines by approximately an order of magnitude. The pro-proliferative effect of DRD2 was, in part, mediated through a GNAI2/Rap1/Ras/ERK signaling axis. Combined inhibition of DRD2 and Epidermal Growth Factor Receptor (EGFR) led to synergistic tumoricidal activity as well as ERK suppression in independent in vivo and in vitro glioblastoma models. Our results suggest combined EGFR and DRD2 inhibition as a promising strategy for glioblastoma treatment

    Quantitative Radiographic Measures Derived from Automatic Segmentation of Glioblastoma Medical Imaging Associate with Patient Survival and Tumor Genomics

    No full text
    Glioblastoma, the most common and deadly form of primary brain cancer, is characterized by rapid progression, heterogeneity, and defiance of therapy. The relentless nature of glioblastoma emphasizes the urgency of identifying improved methods to hasten the development of tailored treatments for patients afflicted by this malignancy. Genetic profiling of clinical glioblastoma specimens has revealed that glioblastoma, like other cancers, is composed of many different subtypes that may possess unique sensitivities to therapeutics. To improve the clinical outcome of glioblastoma patients, technologies must be developed to better define and discriminate the subtypes of glioblastomas in an affordable, accurate, and noninvasive manner. The heterogeneity of glioblastoma's genomic and molecular alterations mirror the diversity of its appearance in medical imaging. The emerging field of radiogenomics integrates methods common to neuroimaging, bioinformatics, and molecular biology to identify the radiographic correlates of tumor cellular and molecular processes. Application of radiogenomics to the study of glioblastoma may facilitate its understanding, especially when considering that magnetic resonance (MR) imaging is required for the modern clinical management of this disease. Unfortunately, radiogenomic progress demands accurate and high-throughput methods to reliably segment features from vast and varied imaging archives, and the careful design of metrics which capture biological phenotypes. In this context, we developed a robust algorithm for tumor segmentation and radiophenotype parameterization termed Iterative Probabilitic Voxel Labeling (IPVL). Application of IPVL to glioblastoma tumor images from The Cancer Imaging Archive (TCIA) with associated genomic profiling available via The Cancer Genome Atlas (TCGA) led to the topographic mapping of glioblastoma spatial distributions by molecular subtype, and the discovery of two survival-associated radiographic parameters. These parameters, tumor subventricular distance (SVZd), and lateral ventricle displacement (LVd), correlate with defined physiologic mechanisms, and associated genomic profiles. Together, these results provide proof of principle that quantitative radiographic assessment of glioblastoma is a viable and effective strategy capable of augmenting the power of molecular and genomic research. With further study in the clinical setting, application of these methodologies and novel imaging parameters could impact prognostic evaluation, identify tumor therapeutic subgroups, and hopefully improve the lives of patient

    Quantification of glioblastoma mass effect by lateral ventricle displacement

    No full text
    Abstract Mass effect has demonstrated prognostic significance for glioblastoma, but is poorly quantified. Here we define and characterize a novel neuroimaging parameter, lateral ventricle displacement (LVd), which quantifies mass effect in glioblastoma patients. LVd is defined as the magnitude of displacement from the center of mass of the lateral ventricle volume in glioblastoma patients relative to that a normal reference brain. Pre-operative MR images from 214 glioblastoma patients from The Cancer Imaging Archive (TCIA) were segmented using iterative probabilistic voxel labeling (IPVL). LVd, contrast enhancing volumes (CEV) and FLAIR hyper-intensity volumes (FHV) were determined. Associations with patient survival and tumor genomics were investigated using data from The Cancer Genome Atlas (TCGA). Glioblastoma patients had significantly higher LVd relative to patients without brain tumors. The variance of LVd was not explained by tumor volume, as defined by CEV or FLAIR. LVd was robustly associated with glioblastoma survival in Cox models which accounted for both age and Karnofsky’s Performance Scale (KPS) (p = 0.006). Glioblastomas with higher LVd demonstrated increased expression of genes associated with tumor proliferation and decreased expression of genes associated with tumor invasion. Our results suggest LVd is a quantitative measure of glioblastoma mass effect and a prognostic imaging biomarker

    Molecular physiology of contrast enhancement in glioblastomas: An analysis of The Cancer Imaging Archive (TCIA).

    No full text
    The physiologic processes underlying MRI contrast enhancement in glioblastoma patients remain poorly understood. MRIs of 148 glioblastoma subjects from The Cancer Imaging Archive were segmented using Iterative Probabilistic Voxel Labeling (IPVL). Three aspects of contrast enhancement (CE) were parametrized: the mean intensity of all CE voxels (CEi), the intensity heterogeneity in CE (CEh), and volumetric ratio of CE to necrosis (CEr). Associations between these parameters and patterns of gene expression were analyzed using DAVID functional enrichment analysis. Glioma CpG island methylator phenotype (G-CIMP) glioblastomas were poorly enhancing. Otherwise, no differences in CE parameters were found between proneural, neural, mesenchymal, and classical glioblastomas. High CEi was associated with expression of genes that mediate inflammatory responses. High CEh was associated with increased expression of genes that regulate remodeling of extracellular matrix (ECM) and endothelial permeability. High CEr was associated with increased expression of genes that mediate cellular response to stressful metabolic states, including hypoxia and starvation. Our results indicate that CE in glioblastoma is associated with distinct biological processes involved in inflammatory response and tissue hypoxia. Integrative analysis of these CE parameters may yield meaningful information pertaining to the biologic state of glioblastomas and guide future therapeutic paradigms

    Axinell­amines as Broad-Spectrum Antibacterial Agents: Scalable Synthesis and Biology

    No full text
    Antibiotic-resistant bacteria present an ongoing challenge to both chemists and biologists as they seek novel compounds and modes of action to out-maneuver continually evolving resistance pathways, especially against Gram-negative strains. The dimeric pyrrole–​imidazole alkaloids represent a unique marine natural product class with diverse primary biological activity and chemical architecture. This full account traces the strategy used to develop a second-generation route to key spirocycle <b>9</b>, culminating in a practical synthesis of the axinell­amines and enabling their discovery as broad-spectrum antibacterial agents, with promising activity against both Gram-positive and Gram-negative bacteria. While their detailed mode of antibacterial action remains unclear, the axinell­amines appear to cause secondary membrane destabilization and impart an aberrant cellular morphology consistent with the inhibition of normal septum formation. This study serves as a rare example of a natural product initially reported to be devoid of biological activity surfacing as an active antibacterial agent with an intriguing mode of action

    Differential localization of glioblastoma subtype: implications on glioblastoma pathogenesis.

    No full text
    IntroductionThe subventricular zone (SVZ) has been implicated in the pathogenesis of glioblastoma. Whether molecular subtypes of glioblastoma arise from unique niches of the brain relative to the SVZ remains largely unknown. Here, we tested whether these subtypes of glioblastoma occupy distinct regions of the cerebrum and examined glioblastoma localization in relation to the SVZ.MethodsPre-operative MR images from 217 glioblastoma patients from The Cancer Imaging Archive were segmented automatically into contrast enhancing (CE) tumor volumes using Iterative Probabilistic Voxel Labeling (IPVL). Probabilistic maps of tumor location were generated for each subtype and distances were calculated from the centroid of CE tumor volumes to the SVZ. Glioblastomas that arose in a Genetically Modified Murine Model (GEMM) model were also analyzed with regard to SVZ distance and molecular subtype.ResultsClassical and mesenchymal glioblastomas were more diffusely distributed and located farther from the SVZ. In contrast, proneural and neural glioblastomas were more likely to be located in closer proximity to the SVZ. Moreover, in a GFAP-CreER; PtenloxP/loxP; Trp53loxP/loxP; Rb1loxP/loxP; Rbl1-/- GEMM model of glioblastoma where tumor can spontaneously arise in different regions of the cerebrum, tumors that arose near the SVZ were more likely to be of proneural subtype (p &lt; 0.0001).ConclusionsGlioblastoma subtypes occupy different regions of the brain and vary in proximity to the SVZ. These findings harbor implications pertaining to the pathogenesis of glioblastoma subtypes

    Orthogonal targeting of EGFRvIII expressing glioblastomas through simultaneous EGFR and PLK1 inhibition

    Get PDF
    We identified a synthetic lethality between PLK1 silencing and the expression of an oncogenic Epidermal Growth Factor Receptor, EGFRvIII. PLK1 promoted homologous recombination (HR), mitigating EGFRvIII induced oncogenic stress resulting from DNA damage accumulation. Accordingly, PLK1 inhibition enhanced the cytotoxic effects of the DNA damaging agent, temozolomide (TMZ). This effect was significantly more pronounced in an Ink4a/Arf(-/-) EGFRvIII glioblastoma model relative to an Ink4a/Arf(-/-) PDGF-β model. The tumoricidal and TMZ-sensitizing effects of BI2536 were uniformly observed across Ink4a/Arf(-/-) EGFRvIII glioblastoma clones that acquired independent resistance mechanisms to EGFR inhibitors, suggesting these resistant clones retain oncogenic stress that required PLK1 compensation. Although BI2536 significantly augmented the anti-neoplastic effect of EGFR inhibitors in the Ink4a/Arf(-/-) EGFRvIII model, durable response was not achieved until TMZ was added. Our results suggest that optimal therapeutic effect against glioblastomas requires a "multi-orthogonal" combination tailored to the molecular physiology associated with the target cancer genome
    corecore