banda transcan 2 2016ul

Title: Cancer prevention through improved familial risk assessment and gene discovery.

Project Coordinator:
Kari HEMMINKI (Germany) German Cancer Research Center, Heidelberg

Project Partners:
Jan LUBINSKI (Poland) Pomeranian Medical University, Szczecin
Rolf SIJMONS (Netherlands) University of Groeningen, Groeningen

Project Abstract:
There is clear evidence that clinical genetic counseling for hereditary cancer saves lives and relieves anxiety. However, counseling is rarely extended to common familial cancers for which gene tests are not available. The first aim of the study is to produce authoritative data on familial risks on all cancers and to convert these to simple risk prediction web tools for use in clinical counseling for the prevention of familial cancer. The data will be generated at DKFZ on the world’s largest family dataset, the Swedish Family-Cancer Database. The tools will predict cancer risks in the following 5/10/20 year period based on the counselee’s family cancer constellation. They will also suggest a cancer syndrome if the family history matches a known syndrome. Before public release, the tools are clinically tested in the clinical counseling clinic in Groningen. The second aim is to identify novel genes that predispose to familial cancer. We follow the empirical gene discovery paradigm by identifying high-risk families diagnosed with the same cancer in several family members. Such families and samples are identified from the world’s largest biobank of 16,000 familial cancers in Szczecin. Germline DNA from cases and unaffected family members will be sequenced genome-wide at the DKFZ core facility, one of Europe’s top sequencing centers. The target is to analyze between 20 and 30 informative families for various cancers during the 3 year period. This will be maximally 20 to 30 different cancers but for some cancers several families with unknown genes may be analyzed. Based on our recent proof-of-principle study on melanoma, a single family may allow identification of a high-risk variant when the new genome-wide sequencing technology is applied. In that example, the detected variant targeted a transcription factor binding site which turned out to be the most common gene variant in melanoma yet described, with implications to prognosis. The present project aims at cancer prevention at two levels, in facilitating and improving clinical counseling for reducing or avoiding familial cancer and in identifying novel high-risk variants for which predictive gene testing can be established.

Publishable summary:
The project has 2 work-packages (WPs). WP1 focuses on familial risk and on clinically useful risk prediction tools. In WP2 the aim is to identify novel genes that predispose to familial cancer. We follow the empirical gene discovery paradigm by identifying high-risk families diagnosed with the same cancer in several family members in at least 3 generations. Such families and samples have identified mainly from the world’s largest biobank of familial cancers in Szczecin and some from the medical genetic clinic in Groningen.

(Project funded under JTC 2012)


Launch of the call: JTC 2021
The new TRANSCAN-3 project consortium is launching the first Joint Transnational Call for proposals, co-funded by the European Commission, on:
"Next generation cancer immunotherapy: targeting the tumour microenvironment"

International Networking Event (virtual)
on 22 April 2021 hrs 9:00 CET
will focus on the forthcoming co-funded JTC 2021 on:
"Next generation cancer immunotherapy: targeting the tumour microenvironment" 
the event is organized by TUBITAK under the “Turkey in Horizon 2020 Phase II” Technical Assistance Project
in cooperation with TRANSCAN-3

 Sustained collaboration of national and regional programmes in cancer research
is the new project funded by the European Commission under H2020  which started on 1st March 2021 and will last five years (G. A. no. 964264)

A TRANSCAN-2 brochure, highlighting key achievements, is available for download


eu flagship

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 643638.

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