Genomic rearrangements give rise to a variety of diseases classified as 'genomic disorders' 9. Because they involve large regions, it is common for genomic disorders to include many deleted or duplicated genes, unlike traditional mutations that affect a single coding-region change of one gene. These genes can be either fully encompassed or partially overlapped by the pathogenic CNV. Deletions of 22q11.2 are associated with DiGeorge/velocardiofacial syndrome and include the catechol-O-methyltransferase gene, the T box transcription factor 1 gene and others 10. Similarly, the autosomal dominant Prader-Willi syndrome (15q11-q13 deletion) involves many genes 11, and the Williams-Beuren syndrome (7q11.23 deletion) involves 28 genes 12. As microarray resolution increases, genomic disorders will certainly be found that are caused by small CNVs involving only a single gene, or even a portion of one gene.

Usually, the genes contained in the pathogenic CNV are candidates for association with the clinical phenotype under study. However, research on genomic disorders has shown that some genes within a CNV may not be necessary, or may not be sufficient, to cause the observed disease. For example, a recurrent 3.7 Mb microdeletion is responsible for 70% of cases of Smith-Magenis syndrome (SMS) 13, a neurobehavioral disorder involving sleep disturbance, craniofacial and skeletal anomalies, intellectual disability and distinctive behavioral traits. Although the size of the deletions observed varies, the identification of a common 'critical region' (1.5 Mb) in SMS patients led to the conclusion that the retinoic acid induced 1 (RAI1) gene alone is responsible for most SMS features. Indeed, RAI1 point mutations have been seen in patients without deletions with similar phenotypes, thus confirming that this gene (of the 13 in the critical region) is necessary to cause SMS. Patients with additional genes deleted have a variable and more severe phenotype. In contrast, in Williams-Beuren syndrome, not only the aneuploid genes but also genes far outside the deleted region have reduced expression and are thought to contribute to the phenotype 14. Such long-range influence of CNVs on distant gene expression is proposed to be caused by positional effects 15.

Recombination between highly homologous sequences (non-allelic homologous recombination) can generate deletions, duplications, inversions and translocations. The sequence architecture that allows one copy number change can also allow its reciprocal at the same locus. The reciprocal events usually cause different phenotypes and occur at different frequencies in the population and at different rates during meiosis 16.

As with SNPs, CNVs that are found frequently in the healthy population (common CNVs) are very likely to have a role in cancer etiology. In the only study published so far that begins to test the hypothesis that common CNVs are associated with malignancy, we 18 created a map of every known CNV whose locus coincides with that of bona fide cancer-related genes (as catalogued by 19); we called these cancer CNVs. In an initial analysis 18, we examined 770 healthy genomes using the Affymetrix 500 K array set, which has an average inter-probe distance of 5.8 kb. As CNVs are generally thought to be depleted in gene regions 20, it was surprising to find 49 cancer genes that were directly encompassed or overlapped by a CNV in more than one person in a large reference population (Figure 1). In the top ten genes, cancer CNVs could be found in four or more people. In this analysis only CNVs directly overlapping a cancer gene were selected (either both breakpoints were inside the genomic interval containing the gene, both were outside the interval, or one breakpoint was inside while the other was outside). However, this is probably an underestimate of the actual number of common cancer CNVs, for two reasons. First, many smaller variants are missed at the resolution of this array: the mean size of CNVs found using the Affymetrix 500 K array is 206 kb 20, whereas the CNVs found using the newer Affymetrix 6.0 platform with a median inter-marker distance of less than 700 bp are 5-15 times smaller 21. Second, as discussed above, there are unquestionably additional, more distal CNVs that have a long-range effect on cancer gene transcription levels.

Validating the initial observation 18, many of these genes are also found in the DGV, a curated list of CNVs compiled from numerous publications 4. Analysis of the DGV 22 shows that nearly 40% of cancer-related genes are interrupted by a CNV. This trend continues: even among the ten most recent CNV publications in the DGV (those published after February 2008), many important tumor suppressor genes and oncogenes can be found with diverse functions, including apoptosis, control of cell cycle checkpoints and DNA repair, and numerous translocation and fusion gene partners. An example of this is Rad51L1, a gene that is a member of the RAD51 family; this is essential for DNA repair by homologous recombination and has been shown by a GWA study to contain a SNP that is strongly associated with breast cancer 23.

The challenge will be to determine which of these genes are dosage-sensitive and which tissues containing these common cancer CNVs will be susceptible to malignant transformation and growth. One approach is to characterize specific cancer CNVs in great detail, in terms of both population frequency and breakpoint sequence 24. For example, in a pilot candidate-gene association study, we found a cancer CNV at the gene MLLT4 (a Ras target encoding a protein that regulates cell-cell adhesion) that seems to be associated with the Li-Fraumeni cancer predisposition disorder (LFS); individuals affected with LFS harbor a germline heterozygous mutation of the Tp53 tumor suppressor gene 18. The frequency of this CNV is significantly increased in LFS (P = 0.006, Fisher's exact test): 3 of the 19 LFS probands (15.8%; observed/expected = 3/0.4 = 7.5) harbored the CNV duplication, whereas only 12 of 710 healthy individuals from the reference population (1.69%; observed/expected = 12/14.6 = 0.82) harbored the CNV.

A nice illustration of a focal CNV with phenotypic effect is given by the mitochondrial tumor suppressor gene (Mtus1); Frank et al. 25 found that a small deletion in Mtus1 is associated with a decreased risk of familial and high-risk breast cancer. Using long-range PCR, we independently fine-mapped this common cancer CNV and genotyped it in a panel of healthy controls. Although it is only 1.1 kb in size, the deletion removes an entire exon of Mtus1. Direct sequencing reveals a 41 bp stretch of homology flanking the exon, which leads to this deletion by non-allelic homologous recombination (Figure 2).

These examples demonstrate hypothesis-driven approaches, which are restricted to genes for which there is an a priori association with cancer. Ultimately, it will be important to be able to discover and test every CNV in a genome for cancer susceptibility, but although this hypothesis-free approach is becoming technically tractable and more economical, such studies do have unique analytical challenges. As elaborated upon elsewhere 2627 these challenges include: the unknown allele frequency and integer copy number of most CNVs, both within and among populations; the absence of sequence-level breakpoint information for most CNVs and the architectural complexity of some CNV regions, including smaller CNVs within larger ones 24.

Common cancer SNPs - and by analogy common cancer CNVs - each confer only a minor increase in disease risk, but collectively they may cause a substantially elevated risk. In contrast, the mutations associated with hereditary cancer syndromes are frequently highly penetrant on their own and are usually inherited in an autosomal dominant manner. Unlike low-penetrance alleles, rare high-penetrance mutations will almost always co-segregate with the disease in families.

There are over 200 cancer syndromes and although most arise infrequently, they account for 5-10% of all cancer cases 28. These are caused by base-pair-sized germline mutations in many central tumor suppressor genes - such as TP53, APC, BRCA1, BRCA2, PTEN, and RB1 - and (fewer) oncogenes, including HRAS and RET.

The role of large structural mutations in cancer syndromes has been less appreciated, probably because genomic deletions or duplications are not readily detected by PCR-based sequencing. New multiplexing methods, especially multiplex ligation-dependent probe amplification (MLPA) 29, allow targeted copy number assessment of single gene or exon changes. This has led to a recent upsurge in discoveries of patients and families with rare pathogenic CNVs that strongly predispose to cancer. Of the 70 germline cancer genes in the Cancer Genes Census 30, 28 have been reported to be mutated by genomic deletion or duplication (the genes and citations are shown in Table 1). We hypothesize that many of the remaining gene mutations will be found to have a genomic equivalent and, perhaps more importantly, that predisposing CNVs will be found in other regions not usually associated with hereditary cancer. A recent report by Jackson et al. 31 describing five patients with rhabdoid predisposition syndrome and deletions at SMARCB1 (22q11.2) highlights the benefits of a global approach to CNV detection: using SNP arrays to gain a broad perspective on the SMARCB1 deletion and surrounding chromosomal landscape, it was found that the extent of two patients' deletions in fact extended past SMARCB1, impinging on neighboring genes, and explaining their clinical phenotype.

The presence of rare cancer CNVs leads to many questions: do they differ from base-pair changes at the same locus? What is their penetrance? What are the mutational processes that give rise to them? Do they have reciprocal deletions/duplications? Do they have long-range effects on gene expression? These questions provide fertile ground for future research. These studies may involve identifying novel CNVs in unexplained familial clusterings of cancer, or the use of in vitro models in which cancer CNVs are created to measure their effect on cellular proliferation, genomic instability and the other hallmarks of cancer 32.

One potential model to explain the contribution of common and rare CNVs to cancer predisposition is shown in Figure 3. We propose that the number of copy-number-variable regions in healthy persons is maintained by efficient DNA repair, while CNVs are more abundant in cancer-prone individuals because of germline defects in these processes. Although tumors are known to have increased somatic CNV and instability, our model suggests these alterations arise much earlier in cancer-predisposed individuals.

Genome-scale analyses have found many formerly invisible CNAs. In an analysis of 371 lung adenocarcinoma samples using a 250,000 probe array, Weir et al. 33 identified seven recurrent homozygous deletions and 24 recurrent amplifications. The most significant amplification, at 14q13.3 and containing the novel oncogene NKX2-1, had not been found in previous studies; because of insufficient resolution and sample size, the target gene it contained had not been identified. Using an even denser array, Mullighan et al. 34 profiled the DNA copy number changes of 242 pediatric acute lymphoblastic leukemia (ALL) patients, including 192 with B-progenitor leukemia (B-ALL) and 50 with T-lineage leukemia (T-ALL). Global differences between the subtypes' genomes and recurrent abnormalities at specific loci were identified. An average of six CNAs were found per leukemia genome, but significant differences in the number of CNAs were found within the B-ALL group and between the B-ALL and T-ALL subtypes. Intriguingly, in 30% of B-ALL patients, the authors 34 detected deletions of PAX5, a transcription factor that is expressed during early stages of B-cell development. Using CNA analysis to pinpoint critical genes can also help to plan subsequent sequencing efforts. For example, having identified deletions at PAX5, the authors 34 found that an additional 14 patients had point mutations in the same gene.

In glioblastoma, CNA information, mRNA expression levels and methylation changes have been measured and nucleotide mutational analyses have been carried out 35. Integrative analysis has shown that over 70% of tumors carry alterations in the retinoblastoma, p53 and receptor tyrosine kinase pathways. Although cancer is driven primarily by alterations of the genome, this study 35 and others have shown that CNA profiles can be combined with other high-throughput data to create insights that are 'greater than the sum of their parts'.