DEVELOPMENT OF ESP: STRUCTURAL & FUNCTIONAL ONCOGENOMICS


Year of Award:
2003
Award Type:
R33
Project Number:
CA103068
RFA Number:
PAR-01-106
Technology Track:
Molecular & Cellular Analysis Technologies
PI/Project Leader:
COLLINS, COLIN C
Other PI or Project Leader:
N/A
Institution:
UNIVERSITY OF CALIFORNIA SAN FRANCISCO
The long-term objective of this proposal is to gain an enhanced understanding of the structural genomics of solid tumors through development of a novel, sequence-based method capable of identifying all types of structural rearrangements that occur in tumor genomes. Genome rearrangements can promote cancer development, progression and/or resistance to therapy by altering gene regulation and/or function, and the involved genes are potential therapeutic targets. This is well established in leukemia and lymphoma, but less so in solid tumors, in part because of the difficulty of identifying the genes involved in complex structural rearrangements. We describe here a powerful and high resolution, sequence-based analytical approach called End Sequence Profiling (ESP). ESP maps copy number aberrations and directly identifies and clones en masse genome breakpoints associated with genome rearrangements such as inversions, translocations, deletions and amplifications. ESP is accomplished by constructing a BAC library of a tumor genome, end sequencing a larger number of BAC clones, and mapping the BAC end sequences (BES) onto the normal genome sequence. Paired BES that map to different parts of the normal genome span structural rearrangements. Sequencing these clones will reveal exact breakpoints and involved genes. In Specific Aim 1 we will: Implement ESP as a cost effective sequence-based technology for determining the structural organization of tumor genomes and clone rearrangement breakpoints en masse. Determine the minimum sequencing depth needed to yield the maximum structural information. Determine if ESP can reproducibly identify recurrent rearrangements between tumors, and if so, whether specific sequence elements are associated with these rearrangements. In Specific Aim 2 we will: Develop robust computational methods for the analysis, visual representation, and integration of ESP data with the human reference sequence, making possible comparison of ESP data from independent tumors. Knowledge of how genome rearrangements such as inversions and translocations impact local gene expression is critical. Thus, we will integrate ESP-based structure data with expression microarray data and co-localize aberrantly expressed genes with genome rearrangement breakpoints. In Specific Aim 3: We will biologically and clinically validate key ESP findings. We believe ESP provides a rational framework for sequencing tumor genomes. In fact, ( 100 tumor genomes can be analyzed at ( 10 kb resolution for less than sequencing a single 3000 Mb genome yielding hundreds of novel biomarkers and therapeutic targets associated with translocations, inversions, and complex rearrangements. This is important because, just as a comprehensive systems-based knowledge of human biology is predicated on the structural organization and sequence of the human genome, a structure-based view of tumor genomes is essential for a comprehensive understanding of tumor biology.