The long-term goal of this proposal is to identify genetic modifiers of lung cancer induction. Although lung cancer is largely induced by smoking, there is strong evidence for genetic susceptibility and gene-environment interactions in the development of lung cancer. However, the identification of genetic factors underlying lung cancer induction in humans is impeded by limited genetic variation in human populations and by limitations in conducting genetic analysis in humans. Inbred mouse models offer an effective means of identifying candidate lung cancer susceptibility loci by using controlled mating as well as controlled tobacco exposure. The effectiveness of the inbred mouse model was demonstrated by genetic linkage studies using various strains of inbred mice by having mapped several pulmonary adenoma susceptibility (Pas) and pulmonary adenoma resistance (Par) loci. With the increasing number of available mouse polymorphic genetic markers, genome- wide association (GWA) analysis has become an important genetic method to identify novel quantitative trait loci (QTL) and to fine-map previously identified QTL. We hypothesize that genetic modifiers for lung tumorigenesis can be identified using large populations of relevant individuals (mice or humans) and genome-wide set of single nucleotide polymorphisms (SNPs) for each subject.
Three aims are proposed to accomplish our goal.
In aim 1, we will conduct GWA analysis to map mouse lung tumor susceptibility QTL in response to tobacco smoke in 44 strains of mice using more than 190,000 SNP markers.
In aim 2, we will examine human homologues of mouse susceptibility loci in high risk lung cancer families and sporadic lung cancer populations. Finally, these candidate genes indentified in Aim 2 will be further examined using funcational analyses in Aim 3. The significance of these studies is that they will identify human lung cancer genetic modifiers which confer increased risk of lung cancer and will help in developing mouse models relevant to these loci. The innovative aspect of this proposal is that we will examine the correlation between human and mouse susceptibility loci.
Lung cancer is the leading cause of cancer death in men and women in the United States. Despite major advances in recent years, most lung cancers are disseminated at the time of presentation and have a mortality rate of about 90%. Studies of familial aggregation of lung cancer suggest that genetic factors are involved in human lung tumor development. This proposal will identify genetic modifiers of lung cancer induction using comparative genomic approaches. We anticipate the identification of human lung cancer genetic modifiers which confer increased risk of lung cancer through the proposed cross-species studies between human and mouse susceptibility loci.
|Ma, Jianzhong; Xiong, Momiao; You, Ming et al. (2014) Genome-wide association tests of inversions with application to psoriasis. Hum Genet 133:967-74|
|Xiao, Feifei; Ma, Jianzhong; Cai, Guoshuai et al. (2014) Natural and orthogonal model for estimating gene-gene interactions applied to cutaneous melanoma. Hum Genet 133:559-74|
|Xiao, Feifei; Ma, Jianzhong; Amos, Christopher I (2013) A unified framework integrating parent-of-origin effects for association study. PLoS One 8:e72208|
|Hua, Xing; Xu, Haiming; Yang, Yaning et al. (2013) DrGaP: a powerful tool for identifying driver genes and pathways in cancer sequencing studies. Am J Hum Genet 93:439-51|
|Liu, Pengyuan; Morrison, Carl; Wang, Liang et al. (2012) Identification of somatic mutations in non-small cell lung carcinomas using whole-exome sequencing. Carcinogenesis 33:1270-6|
|Pan, Jing; Zhang, Qi; Wang, Yian et al. (2010) 26S proteasome activity is down-regulated in lung cancer stem-like cells propagated in vitro. PLoS One 5:e13298|