Generating a Lung Cancer Mouse Model through a Sleeping Beauty System

Abstract

Lung cancer is the deadliest type of cancer for men and women alike. Lung cancer alone is one of the leading causes of death worldwide with the five year survival rate of approximately 17%. It is held accountable for 1.38 million deaths, which is 18.2% of the total number of cancer-related deaths1. The statistics on the mortality rates of stomach, colorectal, and lung cancers show that lung cancer mortality rate has always been greater than those of the stomach and colorectal cancers combined since 1975. Previous efforts have been focused on molecular genotyping of lung carcinomas to target possible genes associated with lung cancer. Much of the research conducted on lung cancers has been based on comparing the genotypes of tumors and matched normal tissue from lung cancer patients. Some of this research involved whole-genome sequencing of tumor samples and as a result several candidates for cancer genes and somatic mutations were selected. Even though many mutations and deletions in tumor suppressor genes and oncogenes have been identified in this way, these alterations have been proven to be difficult to exploit therapeutically and their functional consequences unknown to us2. Thus, additional identification of gene alterations associated with lung adenocarcinoma is necessary for finding possible targets to aid in diagnosis and treatment. In this study, we showed that the Sleeping Beauty (SB) system used in our laboratory allowed for random insertional mutations in lung epithelial cells. SB system is a type of transposon-based insertional mutagenesis (TIM) that allows for a novel and unbiased forward genetic screening3. It utilizes mobilized transposon vectors for genome-wide insertional mutagenesis which provide a number of cancer models due to random mutations4. A specific cancer model can be developed with the SB system using Cre recombinase, which limits transposition to one cell type. The transposition system was used to induce lung tumors in the cohorts of triple transgenic mice that harness genetically modified transposons and transposases in their genome. As a result, we have currently generated and analyzed 88 triple transgenic mice, of which 18 had lung tumors. Some mice had multiple lung tumors in multiple lobes, which gave us a total of 21 lung tumor samples. The penetrance, the proportion of transgenic mice that also developed lung tumors, was 0.2. Further analysis needs to be done in order to determine the efficacy of the transposition system to induce lung tumors in a mouse model. This model system may potentially be used to overcome the limitations of having to rely on human case-dependent samples to identify driver mutations over passenger mutations.