| Project Detail |
Genome engineering to model cancer onset
Despite the cell of origin, cancers follow the same principles in terms of their development. They accumulate genetic changes including mutations, amplifications, or deletions of parts of the DNA known as copy number alterations (CNAs). Funded by the European Research Council, the MACHETE project aims to investigate the functional impact of CNAs. Researchers will utilise a novel genome engineering toolkit to introduce CNAs in the genome of pancreatic cells to model the development of pancreatic cancer. Moreover, the work will unveil important information on the role of genetic aberrations in metastasis and response to therapy and may unveil novel targets of therapeutic value.
Cancers arise through genetic and epigenetic alterations that drive the transformation of single cells into malignant tumors. Among genetic changes, copy number alterations (CNAs) are recurrent chromosomal events that increase or decrease the dosage of specific regions of DNA, can affect up to 30% of a cancer cell genome, and are associated with poor clinical outcomes. Despite their pervasiveness, the functional effects of specific CNAs on cancer phenotypes remain largely unknown, as current approaches cannot faithfully recapitulate the unique properties of these chromosomal alterations. Indeed, CNAs can uniquely affect the expression of hundreds of linked genes and change DNA topology, which in turn can promote intra-tumor heterogeneity as illustrated by random segregation of oncogenes in extra chromosomal DNA (ecDNA). In order to study the functional role of CNAs in cancer, this proposal employs MACHETE, a novel genome engineering toolkit that enables the generation of megabase-sized deletions, gains, and oncogene amplification in ecDNA. Using pancreatic ductal adenocarcinoma (PDAC) as a disease model, we will engineer the major CNAs in this lethal tumor to dissect their role in immune evasion, metastasis, and response to therapy. Additionally, through sequential engineering we will study whether the order of CNA acquisition leads to divergent or convergent phenotypes, a highly relevant yet unexplored aspect of cancer biology. Overall, by combining the MACHETE genome engineering platform with in vivo cancer models and molecular approaches, this proposal will begin to systematically dissect the function of recurrent CNAs in PDAC, with direct implications for therapy. Importantly, the methods and conceptual framework of this proposal are broadly applicable to other cancers and diseases characterized by similar chromosomal alterations, where understanding their underlying biology may lead to a new class of CNA-based clinical targets. |
