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Identification and functional characterization of genetic cancer risk variants

Cel

This Industry-Academia Partnership and Pathways (IAPP) joins three groups which have hitherto focused on different aspects of cancer genetics. deCODE genetics (deCODE) has recently identified several genetic risk variants that are associated with increased risk of cancer, including two distinct genetic prostate cancer risk variants on chromosome 8q24. The University of Torino (UNITO) group has identified a number of germline SNPs in signal transduction genes that are frequently mutated in tumors and the group has developed an innovative technology for knock-in of genetic variants in order to reconstruct genetic events in tumor progression. The Karolinska Institute (OP-KI) group has developed sophisticated tools for cytogenetic studies on tumors. The major objective of this proposal is to perform functional and cytogenetic analysis on several of the cancer risk variants identified by deCODE and UNITO. The major objectives of this proposal are 1) to discover and validate low-medium frequency polymorphisms that predispose to cancer, 2) to functionally validate the newly identified variants in human cells, 3) to identify biological properties associated with the prostate cancer risk alleles located at 8q24. Collaboration between deCODE, UNITO and OP-KI benefits all three partners since the capacities and technical skills are largely complementary. The collaboration is foreseen as an ongoing partnership aimed at elucidating the biological properties of genetic variants conferring risk of cancer.

Zaproszenie do składania wniosków

FP7-PEOPLE-2007-3-1-IAPP
Zobacz inne projekty w ramach tego zaproszenia

Koordynator

ISLENSK ERFDAGREINING EHF
Wkład UE
€ 784 442,00
Adres
STURLUGOTU 8
101 Reykjavik
Islandia

Zobacz na mapie

Region
Ísland Ísland Höfuðborgarsvæði
Rodzaj działalności
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Kontakt administracyjny
Bjorgvin Richardsson (Mr.)
Linki
Koszt całkowity
Brak danych

Uczestnicy (2)