Sirna Therapy In Glioblastoma Stem Cells: Identification Of Target Genes And Potential Therapeutic Implications.

Glioblastoma multiforme (GBM), the most common primary brain malignancy, carries a grim prognosis; survival statistics have scarcely improved in decades. Even with the development of temozolomide, the current front-line chemotherapeutic agent for GBM, improvement in long-term survival has been minimal, with recurrence virtually assured. One explanation for the persistence of this disease is the presence of a stem-like cell population within GBM (glioblastoma stem cells, or GSCs). These cells are capable of self-renewal, tumor initiation, and are resistant to chemotherapy. We hypothesized that derangement in the expression of genes critical for the maintenance of GSCs could eliminate these cells outright, or induce sufficient cell differentiation to sensitize them to existing chemotherapeutic agents. To this end we performed a genome-wide small interfering RNA (siRNA) screen in search of genes that, when reduced in expression, cause GSC cell death or induce differentiation as measured by changes in nestin expression or cell morphology. Our screening yielded a number of candidate siRNAs: their efficacy in reducing cell viability was demonstrated across a number of genetically distinct GSC cell lines. We further identified two siRNAs, targeting ubiquitin C (UBC) and disheveled 2 (DVL2), respectively, that significantly sensitize GSCs to the effects of temozolomide (p\u3c0.05). A similar but not significant effect was also observed in combination treatment with siRNA and either paclitaxel or doxorubicin. We conclude from these observations that siRNA-mediated gene knockdown presents a promising avenue in the development of novel treatments for GBM by taking into account the unique biologic attributes of the therapeutically problematic GSC population

Top-degree rational cohomology in the symplectic group of a number ring

Let $K$ be a number field with ring of integers $R = \mathcal{O}_K$. We show that if $R$ is not a principal ideal domain, then the symplectic group $\operatorname{Sp}_{2n}(R)$ has non-trivial rational cohomology in its virtual cohomological dimension. This demonstrates a sharp contrast to the situation where $R$ is Euclidean. To prove our result, we study the symplectic Steinberg module, i.e. the top-dimensional homology group of the spherical building associated to $\operatorname{Sp}_{2n}(K)$. We show that this module is not generated by integral apartment classes.Comment: 19 pages, 1 figur

Cryo-TEM simulations of amorphous radiation-sensitive samples using multislice wave propagation [preprint]

Image simulation plays a central role in the development and practice of high-resolution electron microscopy, including transmission electron microscopy of frozen-hydrated specimens (cryo-EM). Simulating images with contrast that matches the contrast observed in experimental images remains challenging, especially for amorphous samples. Current state-of-the-art simulators apply post hoc scaling to approximate empirical solvent contrast, attenuated image intensity due to specimen thickness, and amplitude contrast. This practice fails for images that require spatially variable scaling, e.g., simulations of a crowded or cellular environment. Modeling both the signal and the noise accurately is necessary to simulate images of biological specimens with contrast that is correct on an absolute scale. To do so, we introduce the “Frozen-Plasmon” method which explicitly models spatially variable inelastic scattering processes in cryo-EM specimens. This approach produces amplitude contrast that depends on the atomic composition of the specimen, reproduces the total inelastic mean free path as observed experimentally and allows for the incorporation of radiation damage in the simulation. Taken in combination with a new mathematical formulation for accurately sampling the tabulated atomic scattering potentials onto a Cartesian grid, we also demonstrate how the matched-filter concept can be used to quantitatively compare model and experiment. The simulator is available as a standalone program, implemented in C++ with multi-threaded parallelism using the computational imaging system for Transmission Electron Microscopy (cisTEM.

STRUCTURE DETERMINATION OF HETEROGENEOUS BIOLOGICAL SPECIMENS IN CROWDED ENVIRONMENTS

The central dogma of molecular biology describes a strictly linear flow of genetic information stored in DNA transferred through RNA and translated into protein products. In the “post-genomic era” however, it is evident that abundant information flows from protein to protein and even protein back to DNA. The field of Structural Biology seeks to understand how the spatial and temporal organization of that information is stored and transmitted via the three-dimensional structure and dynamics of biological macromolecules. X-ray crystallography, nuclear magnetic resonance, and single particle cryo-electron microscopy (cryo-EM) are the primary techniques available to the structural biologist to deduce structure and dynamics at or near atomic resolutions. These tools are generally limited to the study of stable molecules that can be purified biochemically. Other approaches, like super-resolution light microscopy and cryo-electron tomography (cryo-ET), are amenable to the study of more labile macromolecular complexes or those found in situ; however, they are limited to resolutions of tens of nanometers. Improving the resolving capability of cryo-ET with sub-tomogram averaging to routinely reach beyond 10 Å is the primary goal of this work. My unique contribution to the field of structural biology is a suite of software tools called emClarity (enhanced macromolecular classification and alignment for high-resolution in situ tomography) which allows scientists with minimal computational background to probe the structural states of conformationally variable molecules present in complex and crowded environments

Structure and dynamics of the E. coli chemotaxis core signaling complex by cryo-electron tomography and molecular simulations

To enable the processing of chemical gradients, chemotactic bacteria possess large arrays of transmembrane chemoreceptors, the histidine kinase CheA, and the adaptor protein CheW, organized as coupled core-signaling units (CSU). Despite decades of study, important questions surrounding the molecular mechanisms of sensory signal transduction remain unresolved, owing especially to the lack of a high-resolution CSU structure. Here, we use cryo-electron tomography and sub-tomogram averaging to determine a structure of the Escherichia coli CSU at sub-nanometer resolution. Based on our experimental data, we use molecular simulations to construct an atomistic model of the CSU, enabling a detailed characterization of CheA conformational dynamics in its native structural context. We identify multiple, distinct conformations of the critical P4 domain as well as asymmetries in the localization of the P3 bundle, offering several novel insights into the CheA signaling mechanism

Treatment Strategies in Diffuse Midline Gliomas With the H3K27M Mutation: The Role of Convection-Enhanced Delivery in Overcoming Anatomic Challenges

Diffuse midline gliomas harboring the H3 K27M mutation—including the previously named diffuse intrinsic pontine glioma (DIPG)—are lethal high-grade pediatric brain tumors that are inoperable and without cure. Despite numerous clinical trials, the prognosis remains poor, with a median survival of ~1 year from diagnosis. Systemic administration of chemotherapeutic agents is often hindered by the blood brain barrier (BBB), and even drugs that successfully cross the barrier may suffer from unpredictable distributions. The challenge in treating this deadly disease relies on effective delivery of a therapeutic agent to the bulk tumor as well as infiltrating cells. Therefore, methods that can enhance drug delivery to the brain are of great interest. Convection-enhanced delivery (CED) is a strategy that bypasses the BBB entirely and enhances drug distribution by applying hydraulic pressure to deliver agents directly and evenly into a target region. This technique reliably distributes infusate homogenously through the interstitial space of the target region and achieves high local drug concentrations in the brain. Moreover, recent studies have also shown that continuous delivery of drug over an extended period of time is safe, feasible, and more efficacious than standard single session CED. Therefore, CED represents a promising technique for treating midline tumors with the H3K27M mutation

ITGB5 and AGFG1 variants are associated with severity of airway responsiveness

Background: Airway hyperresponsiveness (AHR), a primary characteristic of asthma, involves increased airway smooth muscle contractility in response to certain exposures. We sought to determine whether common genetic variants were associated with AHR severity. Methods: A genome-wide association study (GWAS) of AHR, quantified as the natural log of the dosage of methacholine causing a 20% drop in FEV1, was performed with 994 non-Hispanic white asthmatic subjects from three drug clinical trials: CAMP, CARE, and ACRN. Genotyping was performed on Affymetrix 6.0 arrays, and imputed data based on HapMap Phase 2, was used to measure the association of SNPs with AHR using a linear regression model. Replication of primary findings was attempted in 650 white subjects from DAG, and 3,354 white subjects from LHS. Evidence that the top SNPs were eQTL of their respective genes was sought using expression data available for 419 white CAMP subjects. Results: The top primary GWAS associations were in rs848788 (P-value 7.2E-07) and rs6731443 (P-value 2.5E-06), located within the ITGB5 and AGFG1 genes, respectively. The AGFG1 result replicated at a nominally significant level in one independent population (LHS P-value 0.012), and the SNP had a nominally significant unadjusted P-value (0.0067) for being an eQTL of AGFG1. Conclusions: Based on current knowledge of ITGB5 and AGFG1, our results suggest that variants within these genes may be involved in modulating AHR. Future functional studies are required to confirm that our associations represent true biologically significant findings

Patients' ratings of genetic conditions validate a taxonomy to simplify decisions about preconception carrier screening via genome sequencing

Advances in genome sequencing and gene discovery have created opportunities to efficiently assess more genetic conditions than ever before. Given the large number of conditions that can be screened, the implementation of expanded carrier screening using genome sequencing will require practical methods of simplifying decisions about the conditions for which patients want to be screened. One method to simplify decision making is to generate a taxonomy based on expert judgment. However, expert perceptions of condition attributes used to classify these conditions may differ from those used by patients. To understand whether expert and patient perceptions differ, we asked women who had received preconception genetic carrier screening in the last 3 years to fill out a survey to rate the attributes (predictability, controllability, visibility, and severity) of several autosomal recessive or X-linked genetic conditions. These conditions were classified into one of five taxonomy categories developed by subject experts (significantly shortened lifespan, serious medical problems, mild medical problems, unpredictable medical outcomes, and adult-onset conditions). A total of 193 women provided 739 usable ratings across 20 conditions. The mean ratings and correlations demonstrated that participants made distinctions across both attributes and categories. Aggregated mean attribute ratings across categories demonstrated logical consistency between the key features of each attribute and category, although participants perceived little difference between the mild and serious categories. This study provides empirical evidence for the validity of our proposed taxonomy, which will simplify patient decisions for results they would like to receive from preconception carrier screening via genome sequencing