Hepatocellular carcinoma (HCC) remains a menace for human health for the lack of any effective treatment. HCC is usually the end result of chronic liver diseases associated with diverse risk factors. Furthermore, non- alcoholic steatohepatitis (NASH) induced HCC, which is projected to be the leading cause of new cases, remains poorly characterized. Although many mouse models of HCC have been developed, it is unclear how well they represent different subgroups of human HCCs. This research plan proposes to transform HCC animal modeling by establishing a novel in vivo platform to accurately replicate the somatic molecular profiles of human HCC in mice. To do this, three independent HCC mouse models will be exhaustively characterized through exome sequencing and gene expression profiling. Using bioinformatics techniques including machine- learning and network analysis, these datasets will be compared with human HCC datasets from TCGA and the ICGC to identify subgroups of patients with similar somatic molecular profiles to the HCC mouse models as well as refined minimum sets of characteristic genetic aberrations. A derived transposon system will be used to generate mosaic mouse models replicating human HCC genetic subgroups faithfully. These models will enable 1) experimental dissection of the molecular mechanisms underlying distinct etiologies of HCC, 2) systematic assessment of candidate HCC therapies and 3) investigation of therapeutic resistances. This K99/R00 career development award proposal describes a two-year mentored and three-year independent research program essential for the development of Dr. Font-Burgada as an independent investigator. Dr. Font-Burgada received his PhD at University of Barcelona, Spain, for the work he performed to investigate basic chromatin regulatory and epigenetic mechanisms. He then moved to University of California, San Diego where he joined Dr. Michael Karin's laboratory to train in mouse models of cancer and signal transduction. For the accomplishment of this research proposal, Dr. Font-Burgada has designed a strong training and career development plan consisting of: 1- the continued mentorship of Dr. Michael Karin to gain additional expertise in mouse models of HCC and signal transduction, 2- Training in bioinformatics, specifically in methods to identify cancer driver genetic aberrations and network-based approaches for comparative genomic analysis of mouse and human HCCs, to be overseen by co-mentor Dr. Hannah Carter, an Assistant Professor of Medicine, at UCSD. 3- Training in application of emerging transposon vector technologies to generate mosaic mouse models for in vivo analysis of oncogenic pathways. 4- Career development courses and seminars in a supportive academic environment in the Department of Pharmacology at UCSD to complement other aspects of the training program. This training plan will be overseen by an advisory committee comprising 4 members, mentor, co-mentor, and additional experts in mouse models of cancer and bioinformatics, Inder Verma and Trey Ideker, providing key scientific insights and essential guidance in critical steps in Dr. Font-Burgada transition to independence.
Hepatocellular carcinoma (HCC) has a 5-year survival rate of less than 10% and leads to 700000 deaths globally each year. The genetic causes of this disease are poorly understood and the only available targeted therapy extends life expectancy by a mere 3 months. In order to improve these dismal statistics, I am developing a novel class of mouse models capable of reproducing the spectrum of mutations observed in a given human tumor, to enable study of HCC biology as well as systematic testing of therapeutic combinations.
| Marty Pyke, Rachel; Thompson, Wesley Kurt; Salem, Rany M et al. (2018) Evolutionary Pressure against MHC Class II Binding Cancer Mutations. Cell 175:416-428.e13 |
| Dow, Michelle; Pyke, Rachel M; Tsui, Brian Y et al. (2018) Integrative genomic analysis of mouse and human hepatocellular carcinoma. Proc Natl Acad Sci U S A 115:E9879-E9888 |
| Marty, Rachel; Kaabinejadian, Saghar; Rossell, David et al. (2017) MHC-I Genotype Restricts the Oncogenic Mutational Landscape. Cell 171:1272-1283.e15 |
