Asbestos Cancer Update 2008

Department of Neurological Surgery, Memorial Sloan-Kettering Cancer Center, New York, USA.

OBJECT: Brain tumor stem cells (TSCs) hypothetically drive the malignant phenotype of glioblastoma multiforme (GBM), and evidence suggests that a better understanding of these TSCs will have profound implications for treating gliomas. When grown in vitro, putative TSCs grow as a solid sphere, making their subsequent characterization, particularly the cells within the center of the sphere, difficult. Therefore, the purpose of this study was to develop a new method to better understand the proteomic profile of the entire population of cells within a sphere. METHODS: Tumor specimens from patients with confirmed GBM and glioma models in mice were mechanically and enzymatically dissociated and grown in traditional stem cell medium to generate neurospheres. The neurospheres were then embedded in freezing medium, cryosectioned, and analyzed with immunofluorescence. RESULTS: By sectioning neurospheres as thinly as 5 mum, the authors overcame many of the problems associated with immunolabeling whole neurospheres, such as antibody penetration into the core of the sphere and intense background fluorescence that obscures the specificity of immunoreactivity. Moreover, the small quantity of material required and the speed with which this cryosectioning and immunolabeling technique can be performed make it an attractive tool for the rapid assessment of TSC character. CONCLUSIONS: This study is the first to show that cryosectioning of neurospheres derived from glioma models in mice and GBM in humans is a feasible method of better defining the stem cell profile of a glioma.

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From the aEnvironment Division, Electric Power Research Institute, Palo Alto, CA; and bDepartment of Epidemiology, UCLA School of Public Health, Los Angeles, CA.

BACKGROUND:: We conducted a meta-analysis of studies on magnetic field exposure and childhood brain tumors to evaluate homogeneity in the results, to examine reasons for heterogeneity, and to derive a summary effect estimate. Comparison of results from studies of childhood brain cancer and childhood leukemia may also help to assess the potential for selection bias in childhood leukemia studies. METHODS:: We included results from 13 studies. Using an inverse variance-weighted method, summary effect estimates were calculated separately for distance, wire codes, and measured and calculated magnetic fields. Sensitivity analyses were conducted to assess the influence of individual studies, the potential for selection bias, and the possibility of publication bias. RESULTS:: With the exception of wire-code studies, results were compatible with homogeneity across studies. The summary odds ratios (95% confidence intervals) were 0.88 (0.57-1.37) for distance <50 m and 1.14 (0.78-1.67) for calculated or measured magnetic fields above 0.2 muT. For measured or calculated exposures above 0.3 or 0.4 muT, the summary odds ratio was 1.68 (0.83-3.43), with no differences by method of exposure assessment. No single study had a substantial effect on the summary estimates. There was no indication of publication bias. CONCLUSIONS:: With the exception of high cut-point analyses (0.3/0.4 muT), where the possibility of a moderate risk increase cannot be excluded, no increase in childhood brain cancer risk was evident for any of the exposure metrics.

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Department of Geography, GeoVISTA Center, 302 Walker Building, The Pennsylvania State University, University Park, PA 16801, USA.

There is an increasing need for new methods and tools that support knowledge construction from complex geospatial datasets related to public health. This study is part of a larger effort to develop, implement, and test such methods and tools. To be successful, the design of methods and tools must be grounded in a solid understanding of the work practices within the domain of use; the research reported here focuses on developing that understanding. We adopted a user-centered approach to toolset design where we investigated the work of cancer researchers and used the results of that investigation as inputs into the development of design guidelines for new geovisualization and spatial analysis tools. Specifically, we conducted key informant interviews focused on use, or potential use, of geographic information, methods, and tools and complemented this with a systematic analysis of published, peer-reviewed articles on geospatial cancer research. Results were used to characterize the typical process of analysis, to identify fundamental differences between intensive users of geospatial methods and infrequent users, and to outline key stages in analysis and tasks within the stages that methods and tools must support. Our findings inform design and implementation decisions for visual and analytic tools that support cancer prevention and control research and they provide insight into the processes used by cancer researchers for addressing the challenges of geographic factors in public health research and policy.

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