Colorectal carcinoma (CRC) arises from multiple mutations and genomic aberrations in distinct driver cancer genes that that in concert to spur neoplastic development and phenotype. This inherent genetic complexity greatly complicates both personalized diagnosis and treatment. Previously published studies have confined that large numbers of genes will be mutated or subject to genomic aberrations in CRC. A significant and emerging challenge for the post-genomic era is to identify which of these mutated genes are """"""""driver"""""""" loci that functionally drive colon cancer development, versus """"""""passenger"""""""" loci without functional relevance. Finally, it is of the highest priority that one forges these genetic observations with correlations of prognosis and clinical outcome. This can only be done if we better understand the unified biological ramifications of the combined and diverse multigenic driver background which act synergistically to promote CRC tumorigenesis. This proposal details an integrated analysis that will rely on the CRC genomic data generated by the Cancer Genome Atlas Project (TCGA) to discover novel candidate CRC genes and study multigenic CRC driver gene co-mutated / dysregulated modules within the genetic context of other drivers and provide biological validation in a powerful in vitro primary culture CRC model which can be engineered for multiple genetic events. To accomplish these goals, we will develop and implement novel statistical methodologies for the integrative analysis of multiple TCGA genomic and clinical data sets. The goal is to identify and prioritize novel CRC genes either singly or as co-mutated modules in combination with other known """"""""driver"""""""" CRC genes. We will use the rich TCGA data set to conduct an integrated CRC genomic analysis of point mutations, gene expression, copy number aberrations and methylation data. We will prioritize the discovery of mutations and other genomic aberrations of these novel CRC genes that are associated with specific clinical stages of disease and other clinical parameters. These statistical and computational studies will then be directly coupled to rapid and robust functional target validation of candidate loci using our rigorously characterized in vitro primary intestinal culture methodology (Gotani et al, Nature Medicine, 2009), in which we have recently established the transforming activity of established CRC loci such as APC, KRAS and TP53. Genetic deletion and retroviral expression of shRNA, cDNA or mutants thereof will be utilized to evaluate putative individual driver loci, as well as combinatorial oncogene modules. This proposal directly addresses fundamental problems in the exploration and translation of novel colorectal cancer gene discovery in the context of clinical data which is available from TCGA.
Colorectal cancer (CRC) represents the third most commonly diagnosed cancer in the United States. This proposal utilizes a fusion of genomic analysis of a large population of patients, mathematical modeling and culture of intestinal fragments to functionally identify genes that are critical for colon cancer development. These studies have implications for generation of novel diagnostic and therapeutic strategies for colon cancer.
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