title: Identification of rare germline copy number variations over-represented in five human cancer types.
abstract: BACKGROUND
  Copy number variations (CNVs) are increasingly recognized as significant disease susceptibility markers in many complex disorders including cancer. The availability of a large number of chromosomal copy number profiles in both malignant and normal tissues in cancer patients presents an opportunity to characterize not only somatic alterations but also germline CNVs, which may confer increased risk for cancer.
  
  
  RESULTS
  We explored the germline CNVs in five cancer cohorts from the Cancer Genome Atlas (TCGA) consisting of 351 brain, 336 breast, 342 colorectal, 370 renal, and 314 ovarian cancers, genotyped on Affymetrix SNP6.0 arrays. Comparing these to ~3000 normal controls from another study, our case-control association study revealed 39 genomic loci (9 brain, 3 breast, 4 colorectal, 11 renal, and 12 ovarian cancers) as potential candidates of tumor susceptibility loci. Many of these loci are new and in some cases are associated with a substantial increase in disease risk. The majority of the observed loci do not overlap with coding sequences; however, several observed genomic loci overlap with known cancer genes including RET in brain cancers, ERBB2 in renal cell carcinomas, and DCC in ovarian cancers, all of which have not been previously associated with germline changes in cancer.
  
  
  CONCLUSIONS
  This large-scale genome-wide association study for CNVs across multiple cancer types identified several novel rare germline CNVs as cancer predisposing genomic loci. These loci can potentially serve as clinically useful markers conferring increased cancer risk.
authors: Bioinformatics Program, Boston University, Boston, MA, USA. rpark@bu.edu.|Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck St, Boston, MA, 02115, USA. rpark@bu.edu.
authors: Richard W
authors: RW
authors: Park
authors: Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck St, Boston, MA, 02115, USA. tmkim@catholic.ac.kr.|Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, 137-701, South Korea. tmkim@catholic.ac.kr.
authors: Tae-Min
authors: TM
authors: Kim
authors: Bioinformatics Program, Boston University, Boston, MA, USA. kasif@bu.edu.|Department of Biomedical Engineering, Boston University, Boston, MA, USA. kasif@bu.edu.|Children's Hospital Informatics Program, Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA. kasif@bu.edu.
authors: Simon
authors: S
authors: Kasif
authors: Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck St, Boston, MA, 02115, USA. peter_park@harvard.edu.|Children's Hospital Informatics Program, Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA. peter_park@harvard.edu.
authors: Peter J
authors: PJ
authors: Park
mesh_terms: D016022:Case-Control Studies; D056915:DNA Copy Number Variations / Q000235:genetics*; D005260:Female; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D055106:Genome-Wide Association Study / Q000379:methods; D005838:Genotype; D006801:Humans; D008297:Male; D009369:Neoplasms / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D012306:Risk
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