IWP1 developed a distributed NGS diagnostics platform facilitating analysis of large-scale cancer cohorts as well as diagnostics for single cases in the clinics (eDiVApipeline). We developed novel methods for copy number variant detection (ClinCNV), identification of false positive variant calls (ABB), prioritization of causal risk variants (eDiVA modules Score and Prioritize) as well as a comprehensive disease knowledge database. eDiVA and all integrated methods support the analysis of germline risk variants as well as somatic cancer driver mutations and has been used to analyse and annotate cancer datasets used in WP2 to 5.
WP2 developed a novel rare variant association study (RVAS) test, called BATI, and a comprehensive platform for RVAS analysis (REWAS). We used REWAS and BATI to perform RVAS tests on germline data from multiple cancer types included in the ICGC and TCGA cohorts. Two novel risk genes for breast and colon cancer identified by REWAS could be replicated in work package 4.
WP3 developed and applied computational methods for the identification of regulatory variants, with a specific focus on identification of germline variants associated to cancer risk. We developed methods for i) identification and functional annotation of regulatory variants, ii) detecting effects of regulatory variants as e.g. gene expression changes, and iii) the integration of epigenetic and genetic features to identify regulatory links in the context of cancer. We applied our methods to data from the PCAWG consortium, providing WGS data for a cohort of 2834 cancer cases. We were a major contributor to the analysis of the gene expression data in this international effort, identifying new regulatory variants through expression quantitative trait loci mapping of both germline and somatic variants.
In WP4, we have gathered ~6,000 cancer cases and controls for the evaluation of cancer risk variant candidates identified in WP2-3. We analysed an evaluation cohort of 1000 bc and 1000 cc cases, (compared to 1000 controls). We could replicate 2 candidate risk genes for colon and breast cancer identified in WP2.
In WP5 we have implemented a CRISPR-Cas based protocol for generating knock-in clones in MCF-10A cells, which allows us to generate clones with candidate risk mutations of interest within 3 weeks without the need for pre-screening. We have generated knock-in clones for 2 candidate cancer risk variants, specifically one coding and one regulatory variant with possible association to bc.
WP6 developed and evaluated a panel of diagnostic markers, inclusive of sCDs, against both bc and cc, and developed IVD-grade immunoassays for these markers suitable for samples screening. We developed predictive models for the diagnosis by screening retrospective samples of both diseases. The diagnostic capacity of the panel was enhanced via the combination with genomic data. Significant diagnostic capability in cc cases has been achieved, which could potentially be developed into a diagnostic product for the early detection of this disease after a larger study is followed.
WP7 has been dedicated to management and coordination. We have developed audio-visual media, communicated results, organized meetings, TC and one symposium on ethical issues of clinical genome sequencing, We ensured that the development of the PanCanRisk project has at all times complied with the tenets of the national and EU regulations regarding ethical issues and privacy of data.
