CVE: an R package for interactive variant prioritisation in precision oncology

BACKGROUND: An increasing number of precision oncology programmes are being launched world-wide. To support this development, we present the Cancer Variant Explorer (CVE), an R package with an interactive Shiny web browser interface. RESULTS: Leveraging Oncotator and the Drug Gene Interaction Database, CVE offers exploration of variants within single or multiple tumour exomes to identify drivers, resistance mechanisms and to assess druggability. We present example applications including the analysis of an individual patient and a cohort-wide study, and provide a first extension of CVE by adding a tumour-specific co-expression network. CONCLUSIONS: The CVE package allows interactive variant prioritisation to expedite the analysis of cancer sequencing studies. Our framework also includes the prioritisation of druggable targets, allows exploratory analysis of tissue specific networks and is extendable for specific applications by virtue of its modular design. We encourage the use of CVE within translational research studies and molecular tumour boards. The CVE package is available via Bioconductor ( http://bioconductor.org/packages/CVE/).AM was supported by the National Institute for Health Research, Biomedical Research Centre (NIHR Cambridge BRC) and the German National Academic Foundation (Studienstiftung des deutschen Volkes). We would like also to acknowledge the support of The University of Cambridge, Cancer Research UK Cambridge Centre and Hutchison Whampoa Limited. The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 337905. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Integrating precision cancer medicine into healthcare—policy, practice, and research challenges

Abstract Precision medicine (PM) can be defined as a predictive, preventive, personalized, and participatory healthcare service delivery model. Recent developments in molecular biology and information technology make PM a reality today through the use of massive amounts of genetic, ‘omics’, clinical, environmental, and lifestyle data. With cancer being one of the most prominent public health threats in developed countries, both the research community and governments have been investing significant time, money, and efforts in precision cancer medicine (PCM). Although PCM research is extremely promising, a number of hurdles still remain on the road to an optimal integration of standardized and evidence-based use of PCM in healthcare systems. Indeed, PCM raises a number of technical, organizational, ethical, legal, social, and economic challenges that have to be taken into account in the development of an appropriate health policy framework. Here, we highlight some of the more salient issues regarding the standards needed for integration of PCM into healthcare systems, and we identify fields where more research is needed before policy can be implemented. Key challenges include, but are not limited to, the creation of new standards for the collection, analysis, and sharing of samples and data from cancer patients, and the creation of new clinical trial designs with renewed endpoints. We believe that these issues need to be addressed as a matter of priority by public health policymakers in the coming years for a better integration of PCM into healthcare