Genome Wide Copy Number Variation Analysis In Lung Cancer

Lung cancer is one of the most common human cancers and one of the high incidence of malignant neoplasms in China. Worldwide, lung cancer mortality is the highest of all cancers. Since 1985, with the continuous development of human industrial society, the incidence of lung cancer is rising. The number of lung cancer caused death is larger than the sum of breast cancer, prostate cancer and colorectal cancer caused death. China is the world’s largest country of lung cancer patients. Every year, over 400,000 people are diagnosed, and the number is still rising. Lung cancer has become a serious problem of public health in China.Many studies show that the lung carcinogenesis is closely related to smoking. In 1995, a survey by World Health Organization showed that nearly 70% of lung cancer patients smoked, of which 80% of patients smoked more than 10 years. Active or passive smoking has become an important external environmental factors in the pathogenesis of lung cancer. However, the genetic mechanisms for lung cancer is still not very clear.Human Genome Variations include single nucleotide polymorphisms(SNP), copy number variations(CNV), and so on. CNV means the amplification, deletion or more complex variations of DNA regions larger than 1kb. Compared to SNPs which accounted for 0.5% of the human genome variation, CNVs span nearly 12 percent of human genome. CNV has become an important genomic variation and its role in the complex human diseases continues to be disclosed.This study focus on the genetic mechanism of lung cancer and the role of copy number variation in the incidence of lung cancer through genome wide copy number variation analysis of lung cancer patient. We collected a total number of nearly 5,500 whole-genome DNA microarray data for European/American people, including the EAGLE(Environment And Genetics, in Lung cancer Etiology) and PLCO(Prostate, Lung, Colorectal, and by grants from Ovarian) projects. We have designed a new strategy, including SNP-based association analysis, window-based cluster testing and combined analysis of two independent dataset. Finally, we predicted 167 potential SNP risk loci and 22 CNVs associated with lung cancer. Further analysis showed that our results were supported by other studies and provided some potential target sites for the lung cancer research.