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      Current Challenges and Opportunities in Treating Glioblastoma

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          Abstract

          Glioblastoma multiforme (GBM), the most common and aggressive primary brain tumor, has a high mortality rate despite extensive efforts to develop new treatments. GBM exhibits both intra- and intertumor heterogeneity, lending to resistance and eventual tumor recurrence. Large-scale genomic and proteomic analysis of GBM tumors has uncovered potential drug targets. Effective and “druggable” targets must be validated to embark on a robust medicinal chemistry campaign culminating in the discovery of clinical candidates. Here, we review recent developments in GBM drug discovery and delivery. To identify GBM drug targets, we performed extensive bioinformatics analysis using data from The Cancer Genome Atlas project. We discovered 20 genes, BOC, CLEC4GP1, ELOVL6, EREG, ESR2, FDCSP, FURIN, FUT8-AS1, GZMB, IRX3, LITAF, NDEL1, NKX3-1, PODNL1, PTPRN, QSOX1, SEMA4F, TH, VEGFC, and C20orf166AS1 that are overexpressed in a subpopulation of GBM patients and correlate with poor survival outcomes. Importantly, nine of these genes exhibit higher expression in GBM versus low-grade glioma and may be involved in disease progression. In this review, we discuss these proteins in the context of GBM disease progression. We also conducted computational multi-parameter optimization to assess the blood-brain barrier (BBB) permeability of small molecules in clinical trials for GBM treatment. Drug delivery in the context of GBM is particularly challenging because the BBB hinders small molecule transport. Therefore, we discuss novel drug delivery methods, including nanoparticles and prodrugs. Given the aggressive nature of GBM and the complexity of targeting the central nervous system, effective treatment options are a major unmet medical need. Identification and validation of biomarkers and drug targets associated with GBM disease progression present an exciting opportunity to improve treatment of this devastating disease.

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          Mutant p53: one name, many proteins.

          There is now strong evidence that mutation not only abrogates p53 tumor-suppressive functions, but in some instances can also endow mutant proteins with novel activities. Such neomorphic p53 proteins are capable of dramatically altering tumor cell behavior, primarily through their interactions with other cellular proteins and regulation of cancer cell transcriptional programs. Different missense mutations in p53 may confer unique activities and thereby offer insight into the mutagenic events that drive tumor progression. Here we review mechanisms by which mutant p53 exerts its cellular effects, with a particular focus on the burgeoning mutant p53 transcriptome, and discuss the biological and clinical consequences of mutant p53 gain of function.
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            Nanoparticle-mediated brain drug delivery: Overcoming blood-brain barrier to treat neurodegenerative diseases.

            The blood-brain barrier (BBB) is a vital boundary between neural tissue and circulating blood. The BBB's unique and protective features control brain homeostasis as well as ion and molecule movement. Failure in maintaining any of these components results in the breakdown of this specialized multicellular structure and consequently promotes neuroinflammation and neurodegeneration. In several high incidence pathologies such as stroke, Alzheimer's (AD) and Parkinson's disease (PD) the BBB is impaired. However, even a damaged and more permeable BBB can pose serious challenges to drug delivery into the brain. The use of nanoparticle (NP) formulations able to encapsulate molecules with therapeutic value, while targeting specific transport processes in the brain vasculature, may enhance drug transport through the BBB in neurodegenerative/ischemic disorders and target relevant regions in the brain for regenerative processes. In this review, we will discuss BBB composition and characteristics and how these features are altered in pathology, namely in stroke, AD and PD. Additionally, factors influencing an efficient intravenous delivery of polymeric and inorganic NPs into the brain as well as NP-related delivery systems with the most promising functional outcomes will also be discussed.
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              Use of proteomic patterns in serum to identify ovarian cancer.

              New technologies for the detection of early-stage ovarian cancer are urgently needed. Pathological changes within an organ might be reflected in proteomic patterns in serum. We developed a bioinformatics tool and used it to identify proteomic patterns in serum that distinguish neoplastic from non-neoplastic disease within the ovary. Proteomic spectra were generated by mass spectroscopy (surface-enhanced laser desorption and ionisation). A preliminary "training" set of spectra derived from analysis of serum from 50 unaffected women and 50 patients with ovarian cancer were analysed by an iterative searching algorithm that identified a proteomic pattern that completely discriminated cancer from non-cancer. The discovered pattern was then used to classify an independent set of 116 masked serum samples: 50 from women with ovarian cancer, and 66 from unaffected women or those with non-malignant disorders. The algorithm identified a cluster pattern that, in the training set, completely segregated cancer from non-cancer. The discriminatory pattern correctly identified all 50 ovarian cancer cases in the masked set, including all 18 stage I cases. Of the 66 cases of non-malignant disease, 63 were recognised as not cancer. This result yielded a sensitivity of 100% (95% CI 93--100), specificity of 95% (87--99), and positive predictive value of 94% (84--99). These findings justify a prospective population-based assessment of proteomic pattern technology as a screening tool for all stages of ovarian cancer in high-risk and general populations.
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                Author and article information

                Contributors
                Role: ASSOCIATE EDITOR
                Journal
                Pharmacol Rev
                Pharmacol. Rev
                pharmrev
                Pharmacol Rev
                PharmRev
                Pharmacological Reviews
                The American Society for Pharmacology and Experimental Therapeutics (Bethesda, MD )
                0031-6997
                1521-0081
                July 2018
                July 2018
                July 2018
                : 70
                : 3
                : 412-445
                Affiliations
                [1]Department of Medicinal Chemistry, College of Pharmacy, North Campus Research Complex, Ann Arbor, Michigan (A.S., U.L., N.N.); Biostatistics Department and School of Public Health, University of Michigan, Ann Arbor, Michigan (A.B.); and Department of Chemistry, Faculty of Science, Chulalongkorn University, Bangkok, Thailand (U.L., N.M.)
                Author notes
                Address correspondence to: Dr. Nouri Neamati, North Campus Research Complex, Bldg. 520, Rm 1363, 1600 Huron Pkwy, Ann Arbor, MI 48109-2800. E-mail: neamati@ 123456umich.edu
                Article
                PHARMREV_014944
                10.1124/pr.117.014944
                5907910
                29669750
                1e9d54a7-8120-41d7-b5c1-cdda7c79e850
                Copyright © 2018 by The Author(s)

                This is an open access article distributed under the CC BY-NC Attribution 4.0 International license.

                History
                Page count
                Figures: 10, Tables: 4, Equations: 0, References: 266, Pages: 34
                Categories
                Review Articles
                Custom metadata
                v1

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