A systems biology approach to identification of genetic networks controlling susceptibility to cancer risk


Biological responses to radiation exposure – DNA damage and tumor development – are controlled by a multiplicity of genetic factors, most of which remain unknown. One of the broad and long-term goals of my laboratory is to identify the combinations of genes and their functional polymorphisms that affect the susceptibility of individual human subjects to the effects of ionizing radiation. The detection and characterization of multiple low penetrance genetic variants that control many complex diseases is one of the major challenges of the future, but progress is hampered by formidable technical and conceptual difficulties. Mouse models offer many advantages for the study of the genetic basis of complex traits, including radiation- induced cancers, because of our ability to control both the genetic and environmental components of risk. The goal is the understanding of all stages of multi-step carcinogenesis in the mouse, in particular the relationships between germ line predisposition and somatic genetic changes in tumors. The identification of human homologues of these predisposition genes and discovery of their roles in carcinogenesis will ultimately be important for the development of methods for prediction of risk, diagnosis, prevention and therapy for human cancers. We will exploit the variation in susceptibility to radiation-induced cancers between mouse strains to identify the combinations of quantitative trait loci (QTLs) that control the radiation response. The power of classical mouse genetics will be complemented by new approaches involving haplotyping to refine the genomic locations of QTLs, together with sophisticated genetic analysis of the somatic events in radiation-induced cancers using newly developed high throughput genome wide BAC microarrays. The relationship between somatic events and germline polymorphism that influence risk will be investigated by analysis of allele-specific genetic alterations in tumors that occur within genomic regions containing tumor susceptibility genes. Gene expression microarray technology will be used to identify candidate genes and pathways implicated in radiation-induced acute responses and tumorigenesis in vivo. Expression array analysis will be carried out on normal and tumor tissues from mice that are sensitive or resistant to radiation-induced tumorigenesis, to look for genes that may be differently expressed due to polymorphisms in gene promoter or controlling regions, or in coding regions of upstream regulatory genes. This comprehensive systems biology approach may identify specific genes or pathways that are differentially controlled between mouse strains, and contribute to variation in susceptibility to radiation-induced carcinogenesis.