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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.

Circulating tumor DNA (ctDNA) in blood plasma is present at very low concentrations compared to cell-free DNA (cfDNA) of non-tumor origin. To enhance ctDNA detection, recent studies have been focused on understanding the non-random fragmentation pattern of cfDNA. These studies have investigated fragment sizes, genomic position of fragment end points, and fragment end motifs. Although these features have been described and shown to be aberrant in cancer patients, there is a lack of understanding of how the individual and integrated analysis of these features enrich ctDNA fraction and enhance ctDNA detection. Using whole genome sequencing and copy number analysis of plasma samples from 5 high grade serious ovarian cancer patients, we observed that (1) ctDNA is enriched not only in fragments shorter than mono-nucleosomes (~ 167 bp), but also in those shorter than di-nucleosomes (~ 240-330 bp) (28-159% enrichment). (2) fragments that start and end at the border or within the nucleosome core are enriched in ctDNA (5-46% enrichment). (3) certain DNA motifs conserved in regions 10 bp up- and down- stream of fragment ends (i.e. cleavage sites) could be used to detect tumor-derived fragments (10-44% enrichment). We further show that the integrated analysis of these three features resulted in a higher enrichment of ctDNA when compared to using fragment size alone (additional 7-25% enrichment after fragment size selection). We believe these genome wide features, which are independent of genetic mutational changes, could allow new ways to analyze and interpret cfDNA data, as significant aberrations of these features from a healthy state could improve its utility as a diagnostic biomarker. ; This study was supported by grants from CRUK Cambridge Institute (Core Grant, A29580) and by a funding from the ERC under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement n. 337905

Background: Recent advances in the study and clinical applications of circulating tumor DNA (ctDNA) are limited by practical considerations of sample collection. Whole genome sequencing (WGS) is increasingly used for analysis of ctDNA, identifying copy-number alterations and fragmentation patterns. We hypothesized that low-depth/shallow WGS (sWGS) data may be generated from minute amounts of cell-free DNA, and that fragment-size selection may remove contaminating genomic DNA from small blood volumes. Dried blood spots have practical advantages for sample collection, may facilitate serial sampling, and could support novel study designs in humans and animal models. Methods: We developed a protocol for the isolation and analysis of cell-free DNA from dried blood spots using filter paper cards and bead-based size selection. DNA extracted and size-selected from dried spots was analyzed using sWGS and PCR. Results: Analyzing a 50L dried blood spot from frozen whole blood of a patient with melanoma, we identified ctDNA based on the presence of tumor-specific somatic copy-number alterations, and found a fragment size profile similar to that observed in plasma DNA. We found alterations in different chromosomes in blood-spots from two patients with high-grade serous ovarian carcinoma. Extending this approach to serial dried blood spots from mouse xenograft models, we detect tumor-derived cell-free DNA and identified ctDNA from the originally grafted ascites. Conclusion: Our data suggest that ctDNA can be detected and monitored in dried blood spots from archived and fresh blood samples, enabling new approaches for sample collection and novel study/trial designs for both patients and in vivo models. ; The University of Cambridge and Cancer Research UK (grant numbers A20240 and A29580). 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. Healthy volunteer samples were provided by the Cambridge Blood and Stem Cell Biobank, which is supported by the Cambridge NIHR Biomedical Research Centre, Wellcome Trust - MRC Stem Cell Institute and the Cambridge Experimental Cancer Medicine Centre, UK.

Tumour heterogeneity leads to the development of multiple resistance mechanisms during targeted therapies. Identifying the dominant driver(s) is critical for treatment decision. We studied the relative dynamics of multiple oncogenic drivers in longitudinal plasma of 50 EGFR-mutant non-small-cell lung cancer patients receiving gefitinib and hydroxychloroquine. We performed digital PCR and targeted sequencing on samples from all patients and shallow whole-genome sequencing on samples from three patients who underwent histological transformation to small-cell lung cancer. In 43 patients with known EGFR mutations from tumour, we identified them accurately in plasma of 41 patients (95%, 41/43). We also found additional mutations, including EGFR T790M (31/50, 62%), TP53 (23/50, 46%), PIK3CA (7/50, 14%) and PTEN (4/50, 8%). Patients with both TP53 and EGFR mutations before treatment had worse overall survival than those with only EGFR Patients who progressed without T790M had worse PFS during TKI continuation and developed alternative alterations, including small-cell lung cancer-associated copy number changes and TP53 mutations, that tracked subsequent treatment responses. Longitudinal plasma analysis can help identify dominant resistance mechanisms, including non-druggable genetic information that may guide clinical management. ; We would like to acknowledge the support of The University of Cambridge, Cancer Research UK (grant numbers A11906, A20240) (to N.R.), the European Research Council under the European Union's Seventh Framework Programme (FP/2007- 2013) / ERC Grant Agreement n. 337905 (to N.R.), and Hutchison Whampoa Limited (to N.R.)