Genome-wide identification of functional polymorphisms modulating individual risk and prognosis of lung cancer

Abstract

Lung cancer is a leading cause of cancer death in Western countries. Although most cases are due to tobacco smoking, complex genetics may modulate this disease, as suggested by epidemiological studies and findings obtained in mouse models. Systematic population-based association studies testing several thousands of genetic markers dispersed genome-wide have recently become a powerful and widely-used approach to identify genetic factors affecting common diseases. In this thesis, the role of genetic polymorphisms and risk of cancer were investigated through a case-control association study in Italian lung adenocarcinoma (ADCA) patients and unrelated controls from general population and through a case-control association family-based study in lung cancer patients and unaffected sibs as controls. I confirmed the relevance of a polygenic model characterized by additive and interchangeable effects of rare alleles in the modulation of individual risk of lung ADCA identifying multiple inherited susceptibility alleles linked to lung cancer. Additionally, I studied the role of genetic polymorphisms modulating individual lung cancer prognosis through a case-only association study in lung ADCA patients with clinical stage I versus higher clinical stage. In particular, I identify two genes (FCN3 and TMEM100) down-regulated up to 1.8-fold in normal lung of stage >I as compared to stage I patients. These results suggest that clinical stage may be genetically determined as reflected in germ-line variations as well as in the transcriptional profile of normal lung tissue. Although clinical application of these results awaits replication in independent and large populations, I found that genetic variants may be involved in the modulation of not only individual risk of lung cancer but also clinical staging. The newly identified individual genetic profiles associated with risk and/or prognosis of lung cancer may thus represent new diagnostic tools and suggest molecular targets for the development of new therapies against lung cancer