A forward genetics approach to identify molecular drivers of liver cancer using Sleeping Beauty mouse models Jesse Daniel Riordan , University of Iowa Follow

[摘要] Each year liver cancer kills more than half a million people, making it the third leading cause of cancer-related death worldwide. Annual incidence continues to rise steadily, both domestically and globally, increasing the burden of this disease. Advancements in the ability to obtain detailed molecular profiles of tumors have led to the successful development of targeted therapies for a number of different cancers. Unfortunately, however, the molecular pathogenesis of liver cancer is poorly understood relative to many other types of malignancies. Thus, the identification of factors contributing to the development and progression of liver tumors is a major goal of current research. In pursuit of this goal, I have utilized the Sleeping Beauty (SB) transposon system as a tool for forward genetic mutagenesis screening in mice. The SB system recapitulates the kinetics of spontaneous tumor development in humans by providing a stepwise accumulation of mutations. Micro-evolutionary processes within a developing tumor lead to the selective expansion of cells harboring mutations that confer some kind of selective advantage. By identifying the most prevalent mutation events within a specific tumor type across a large number of independent samples, a list of genes implicated as being involved in tumorigenesis can be generated. Using this approach, the Dlk1-Dio3 imprinted domain was identified as a site of frequent mutation in SB-induced hepatocellular carcinomas (HCCs). I discovered that the mechanistic basis for recurrent selection of transposon insertion within this domain in liver tumors involved activated expression of Retrotransposon-like 1 (Rtl1) . I also found that RTL1 activation is a common event in human HCC, suggesting that it could potentially be beneficial as a therapeutic target in a subset of patients. Etiological factors related to liver cancer development are varied, but are linked by the fact that each provides a chronic liver injury stimulus that promotes the development of hepatic fibrosis. In fact, ˜ 90% of human HCC occurs in this context, and yet the majority of mouse liver cancer models fail to account for this important environmental component of the disease. I have conducted a screen for genetic drivers of liver cancer in the presence or absence of hepatic fibrosis. Comparison of mutation profiles between fibrotic and non-fibrotic tumors revealed largely non-overlapping sets of candidate genes, indicative of a differential selective pressure for mutations depending on the fibrotic context of the liver. Driver mutations identified preferentially in the presence of liver fibrosis have a high likelihood of relevance to human disease, given the similarities in environmental context and kinetics of mutation acquisition. Consistent with this idea, multiple genes with well-established roles in human HCC were found to be preferentially mutated in SB-induced tumors developed in a fibrotic liver. Before a candidate cancer gene identified in an animal model system can have an impact on human disease, its proposed role in tumorigenesis must be validated. Existing techniques for validation of putative liver cancer genes suffer from significant limitations including high cost, low throughput, and a level of complexity that prohibits widespread utilization. I have contributed to the generation of a novel tool for in vivo validation of candidate genes that is not subject to these limitations. By combining elements of recombinant adenoviral vectors and the piggyBac transposition system, we have generated a highly flexible gene delivery system with significant advantages over existing techniques. The Ad-PB system has broad accessibility and applicability, making it a valuable tool for advancing efforts to improve cancer therapies.