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Purpose: The modern researcher is confronted with hundreds of published methods to interpret genetic variants. There are databases of genes and variants, phenotype-genotype relationships, algorithms that score and rank genes, and in silico variant effect prediction tools. Because variant prioritization is a multifactorial problem, a welcome development in the field has been the emergence of decision support frameworks, which make it easier to integrate multiple resources in an interactive environment. Current decision support frameworks are typically limited by closed proprietary architectures, access to a restricted set of tools, lack of customizability, Web dependencies that expose protected data, or limited scalability., Methods: We present the Open Custom Ranked Analysis of Variants Toolkit 1 (OpenCRAVAT) a new open-source, scalable decision support system for variant and gene prioritization. We have designed the resource catalog to be open and modular to maximize community and developer involvement, and as a result, the catalog is being actively developed and growing every month. Resources made available via the store are well suited for analysis of cancer, as well as Mendelian and complex diseases., Results: OpenCRAVAT offers both command-line utility and dynamic graphical user interface, allowing users to install with a single command, easily download tools from an extensive resource catalog, create customized pipelines, and explore results in a richly detailed viewing environment. We present several case studies to illustrate the design of custom workflows to prioritize genes and variants., Conclusion: OpenCRAVAT is distinguished from similar tools by its capabilities to access and integrate an unprecedented amount of diverse data resources and computational prediction methods, which span germline, somatic, common, rare, coding, and noncoding variants.

Cancer sequencing studies are increasingly comprehensive and well powered, returning long lists of somatic mutations that can be difficult to sort and interpret. Diligent analysis and quality control can require multiple computational tools of distinct utility and producing disparate output, creating additional challenges for the investigator. The Cancer-Related Analysis of Variants Toolkit (CRAVAT) is an evolving suite of informatics tools for mutation interpretation that includes mutation mapping and quality control, impact prediction and extensive annotation, gene- and mutation-level interpretation, including joint prioritization of all nonsilent mutation consequence types, and structural and mechanistic visualization. Results from CRAVAT submissions are explored in an interactive, user-friendly web environment with dynamic filtering and sorting designed to highlight the most informative mutations, even in the context of very large studies. CRAVAT can be run on a public web portal, in the cloud, or downloaded for local use, and is easily integrated with other methods for cancer omics analysis. Cancer Res; 77(21); e35-38. ©2017 AACR ., (©2017 American Association for Cancer Research.)

Background: Treatment with interferon beta reduces clinical exacerbations in multiple sclerosis (MS) through several immunomodulatory mechanisms that involve the augmentation of programmed cell death (apoptosis) of peripheral T lymphocytes. The expression of survivin, a cell cycle-regulated antiapoptosis protein, is up-regulated in mitogen-stimulated T lymphocytes from patients with MS, and this expression correlates with MS disease activity., Objective: To evaluate the effect of interferon beta on the expression of survivin and other apoptosis regulatory molecules in peripheral T lymphocytes from patients with MS., Patients and Methods: In a prospective, combined clinical and immunologic study, we evaluated the expression of survivin, Bcl-2 protein, and the death receptor Fas in mitogen-stimulated T lymphocytes from 26 patients with MS, before and serially after treatment with interferon beta-1a. We also investigated the long-term effects of interferon beta-1a on cellular expression of these proteins and T-lymphocyte apoptosis in a cross-sectional study of 19 patients with MS receiving long-term interferon beta-1a therapy., Results: Treatment with interferon beta-1a reduced the expression of survivin in in vitro stimulated T lymphocytes. This reduced expression correlated with augmented T-cell susceptibility to apoptosis and with clinical response to treatment. In contrast, interferon beta-1a therapy did not significantly alter cellular expression of Bcl-2 protein or Fas. This down-regulatory effect of interferon beta-1a on cellular expression of survivin was maintained after long-term therapy., Conclusions: Our observations suggest that interferon beta exerts a regulatory effect on peripheral T lymphocytes through an antiapoptosis mechanism that involves the down-regulation of cellular survivin expression.