Table of Contents Author Guidelines Submit a Manuscript
BioMed Research International
Volume 2014, Article ID 469103, 9 pages
http://dx.doi.org/10.1155/2014/469103
Research Article

Combined Analysis with Copy Number Variation Identifies Risk Loci in Lung Cancer

1Institute of Health Sciences, Shanghai Jiao Tong University School of Medicine (SJTUSM) and Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai 200025, China
2Chinese National Human Genome Center at Shanghai, Shanghai 201203, China
3Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310029, China
4State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University, 197 Ruijin Road II, Shanghai 200025, China

Received 21 May 2014; Revised 11 June 2014; Accepted 11 June 2014; Published 1 July 2014

Academic Editor: Tao Huang

Copyright © 2014 Xinlei Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background. Lung cancer is the most important cause of cancer mortality worldwide, but the underlying mechanisms of this disease are not fully understood. Copy number variations (CNVs) are promising genetic variations to study because of their potential effects on cancer. Methodology/Principal Findings. Here we conducted a pilot study in which we systematically analyzed the association of CNVs in two lung cancer datasets: the Environment And Genetics in Lung cancer Etiology (EAGLE) and the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial datasets. We used a preestablished association method to test the datasets separately and conducted a combined analysis to test the association accordance between the two datasets. Finally, we identified 167 risk SNP loci and 22 CNVs associated with lung cancer and linked them with recombination hotspots. Functional annotation and biological relevance analyses implied that some of our predicted risk loci were supported by other studies and might be potential candidate loci for lung cancer studies. Conclusions/Significance. Our results further emphasized the importance of copy number variations in cancer and might be a valuable complement to current genome-wide association studies on cancer.