Objectif
The main scientific questions addressed in this proposal relate to the understanding of molecular mechanisms of growth control and cancer through the combined use of high-throughput technologies and computational biology. We aim to create a systems-level understanding of the cell cycle, and its regulation by physiological growth factors and oncogenes through the use high-throughput biology to identify all or the majority of genes that are essential for cell cycle progression, and by combining this dataset with computationally predicted and experimentally validated target genes of growth factors and oncogenic pathways. In my opinion, such systems biology approach is critical for understanding of growth control, as organ-specific growth control has proven particularly refractory to genetic dissection. Much of what we know about physiological mechanisms controlling cellular growth in mammals has been revealed by human cancer genetics. These studies have revealed that a large number of genes can contribute to aberrant cell growth; there are more than 300 genes that have been linked to cancer, and mutations found in cancer are often cell type specific ( oncogene preference , i.e. PTCH mutations in medulloblastoma, APC in colon cancer, TMPRSS2-ERG in prostate cancer), suggesting that different pathways in different cell lineages are coupled to the cell cycle machinery. We have preliminary evidence that hedgehog (Hh) and Wnt signals are directly coupled to expression of N-myc and c-Myc genes, but only in tissues and cell-types that display a proliferative response to these factors. Both classical molecular and developmental biology as well as high throughput and systems biological methods will be used for dissection of the molecular mechanism of this selectivity. If successful, these experiments would establish a principle explaining why particular mutations are extremely common in some tumor types but not found at all in others.
Champ scientifique
Mots‑clés
Appel à propositions
ERC-2008-AdG
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Régime de financement
ERC-AG - ERC Advanced GrantInstitution d’accueil
17177 Stockholm
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