High-resolution copy number arrays in cancer and the problem of normal genome copy number variation

High-resolution techniques for analysis of genome copy number (CN) enable the analysis of complex cancer somatic genetics. However, the analysis of these data is difficult, and failure to consider a number of issues in depth may result in false leads or unnecessary rejection of true positives. First, segmental duplications may falsely generate CN breakpoints in aneuploid samples. Second, even when tumor data were each normalized to matching lymphocyte DNA, we still observed copy number polymorphisms masquerading as somatic alterations due to allelic imbalance. We investigated a number of different solutions and determined that evaluating matching normal DNA, or at least using locally derived normal baseline data, were preferable to relying on current online databases because of poor cross-platform compatibility and the likelihood of excluding genuine small somatic alterations.     

Structural variation in the human genome: the impact of copy number variants on clinical diagnosis

Over the past few years, the application of whole-genome scanning array technologies has catalyzed the appreciation of a new form of submicroscopic genomic imbalances, referred to as copy number variants. Copy number variants contribute substantially to genetic diversity and result from gains and losses of genomic regions that are 1000 base pairs in size or larger, sometimes encompassing millions of bases of contiguous DNA sequences. As genome-wide scanning techniques become more widely used in diagnostic laboratories, a major challenge is how to accurately interpret which submicroscopic genomic imbalances are pathogenic in nature and which are benign. Herein, we review the literature from the past 3 years on this new source of genomic variability and comment on factors that should be considered when trying to differentiate between a pathogenic and a benign copy number variant.     

CPAS: A trans-omics pathway analysis tool for jointly analyzing DNA copy number variations and mRNA expression profiles data

Pathway-based analysis approaches provide additional insights into the pathogenesis of complex diseases. Copy number variations (CNVs) play an important role in gene expression regulation. Joint pathway analysis of CNVs and gene expression data should provide more useful information for revealing the molecular mechanism of complex diseases. To implement trans-omics pathway analysis of genome-wide CNVs and mRNA expression profiles data, we extended the gene set enrichment analysis algorithm and developed a flexible trans-omics pathway analysis tool CPAS. CPAS was developed by C to interface with R for efficient data analysis. CNV-gene and pathway-gene annotation files derived from public database were included in CPAS. We hope that CPAS could help to identify disease-relevant biological pathways that were undetectable using traditional single-omic analysis approaches.     

Accurate and reliable high-throughput detection of copy number variation in the human genome

This study describes a new tool for accurate and reliable high-throughput detection of copy number variation in the human genome. We have constructed a large-insert clone DNA microarray covering the entire human genome in tiling path resolution that we have used to identify copy number variation in human populations. Crucial to this study has been the development of a robust array platform and analytic process for the automated identification of copy number variants (CNVs). The array consists of 26,574 clones covering 93.7% of euchromatic regions. Clones were selected primarily from the published "Golden Path," and mapping was confirmed by fingerprinting and BAC-end sequencing. Array performance was extensively tested by a series of validation assays. These included determining the hybridization characteristics of each individual clone on the array by chromosome-specific add-in experiments. Estimation of data reproducibility and false-positive/negative rates was carried out using self-self hybridizations, replicate experiments, and independent validations of CNVs. Based on these studies, we developed a variance-based automatic copy number detection analysis process (CNVfinder) and have demonstrated its robustness by comparison with the SW-ARRAY method.     

High-resolution gene copy number and expression profiling of human chromosome 22 in ovarian carcinomas

Previous low-resolution studies of chromosome 22 in ovarian carcinoma have suggested its involvement in the development of the disease. We report a high-resolution analysis of DNA copy number and gene expression of 22q in 18 ovarian carcinomas using a 22q-specific genomic microarray. We identified aberrations in 67% of the studied tumors, which displayed 3 distinct gene copy number profiles. The majority of the cases (11 of 18) demonstrated heterozygous terminal deletions of various sizes, the smallest of which was 3.5 Mb. The second profile, detected in 3 tumors, revealed the coexistence of heterozygous deletions and different patterns of low-copy-number gain that involved the proximal half of 22q. The latter finding has not been reported previously in ovarian carcinoma. One case displayed a continuous deletion encompassing the entire 22q, consistent with monosomy 22. Furthermore, we compared the results with the available data on these tumors by using cDNA microarrays to define the degree of correlation between abnormalities at the DNA level and variation in mRNA expression. By a comparison with the expression data, we were able to identify 21 deleted genes showing low mRNA levels and 12 amplified genes displaying elevated gene expression, several of which play roles in cell cycle control and the induction of apoptosis. Our results indicated significant correlation between DNA copy number aberrations and variation in mRNA expression. We also identified several regions and candidate genes on 22q that should be studied further to determine their role in the development of ovarian cancer.     

High-resolution analysis of DNA copy number alterations and gene expression in renal clear cell carcinoma

We analysed chromosomal copy number aberrations (CNAs) in renal cell carcinomas by array-based comparative genomic hybridization, using a genome-wide scanning array with 2304 BAC and PAC clones covering the whole human genome at a resolution of roughly 1.3 Mb. A total of 30 samples of renal cell carcinoma were analysed, including 26 cases of clear cell carcinoma (CCC) and four cases of chromophobe renal cell carcinoma (ChCC). In CCCs, gains of chromosomes 5q33.1-qter (58%), 7q11.22-q35 (35%) and 16p12.3-p13.12 (19%), and losses of chromosomes 3p25.1-p25.3 (77%), 3p21.31-p22.3 (81%), 3p14.1-p14.2 (77%), 8p23.3 (31%), 9q21.13-qter (19%) and 14q32.32-qter (38%) were detected. On the other hand, the patterns of CNAs differed markedly between CCCs and ChCCs. Next, we examined the correlation of CNAs with expression profiles in the same tumour samples in 22/26 cases of CCC, using oligonucleotide microarray. We extracted genes that were differentially expressed between cases with and without CNAs, and found that significantly more up-regulated genes were localized on chromosomes 5 and 7, where recurrent genomic gains have been detected. Conversely, significantly more down-regulated genes were localized on chromosomes 14 and 3, where recurrent genomic losses have been detected. These results revealed that CNAs were correlated with deregulation of gene expression in CCCs. Furthermore, we compared the patterns of genomic imbalance with histopathological features, and found that loss of 14q appeared to be a specific and additional genetic abnormality in high-grade CCC. When we compared the expression profiles of low-grade CCCs with those of high-grade CCCs, differentially down-regulated genes tended to be localized on chromosomes 14 and 9. Thus, it is suggested that copy number loss at 14q in high-grade CCC may be involved in the down-regulation of genes located in this region.     

High-resolution mapping of the 8p23.1 beta-defensin cluster reveals strictly concordant copy number variation of all genes

One unexpected feature of the human genome is the high structural variability across individuals. Frequently, large regions of the genome show structural polymorphisms and many vary in their abundance. However, accurate methods for the characterization and typing of such copy number variations (CNV) are needed. The defensin cluster at the human region 8p23.1 is one of the best studied CNV regions due to its potential clinical relevance for innate immunity, inflammation, and cancer. The region can be divided into two subclusters, which harbor predominantly either alpha- or beta-defensin genes. Previous studies assessing individual copy numbers gave different results regarding whether the complete beta-defensin cluster varies or only particular genes therein. We applied multiplex ligation-dependent probe amplification (MLPA) to measure defensin locus copy numbers in 42 samples. The data show strict copy number concordance of all 10 loci typed within the beta-defensin cluster in each individual, while seven loci within the alpha-defensin cluster are consistently found as single copies per chromosome. The exception is DEFA3, which is located within the alpha-defensin cluster and was found to also differ in copy number interindividually. Absolute copy numbers ranged from two to nine for the beta-defensin cluster and zero to four for DEFA3. The CNV-typed individuals, including HapMap samples, are publicly available and may serve as a universal reference for absolute copy number determination. On this basis, MLPA represents a reliable technique for medium- to high-throughput typing of 8p23.1 defensin CNV in association studies for diverse clinical phenotypes.     

High-resolution genomic and expression analyses of copy number alterations in breast tumors

Analysis of recurrent DNA amplification can lead to the identification of cancer driver genes, but this process is often hampered by the low resolution of existing copy number analysis platforms. Fifty-one breast tumors were profiled for copy number alterations (CNAs) with the high-resolution Affymetrix 500K SNP array. These tumors were also expression-profiled and surveyed for mutations in selected genes commonly mutated in breast cancer (TP53, CDKN2A, ERBB2, KRAS, PIK3CA, PTEN). Combined analysis of common CNAs and mutations revealed putative associations between features. Analysis of both the prevalence and amplitude of CNAs defined regions of recurrent alteration. Compared with previous array comparative genomic hybridization studies, our analysis provided boundaries for frequently altered regions that were approximately one-fourth the size, greatly reducing the number of potential alteration-driving genes. Expression data from matched tumor samples were used to further interrogate the functional relevance of genes located in recurrent amplicons. Although our data support the importance of some known driver genes such as ERBB2, refined amplicon boundaries at other locations, such as 8p11-12 and 11q13.5-q14.2, greatly reduce the number of potential driver genes and indicate alternatives to commonly suggested driver genes in some cases. For example, the previously reported recurrent amplification at 17q23.2 is reduced to a 249 kb minimal region containing the putative driver RPS6KB1 as well as the putative oncogenic microRNA mir-21. High-resolution copy number analysis provides refined insight into many breast cancer amplicons and their relationships to gene expression, point mutations and breast cancer subtype classifications. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat.     

A new strategy for mapping the human genome.

Recent advances in agarose gel electrophoresis of large DNA fragments raise the possibility of an entirely new approach to mapping mammalian genomes. In this article is discussed the potential of this technology for tackling problems such as construction of linkage maps, identifying chromosome translocation breakpoints, and moving from linked markers to genes causing diseases such as the muscular dystrophies and Huntington's chorea.     

Analysis of copy number variation in the rhesus macaque genome identifies candidate loci for evolutionary and human disease studies

Copy number variants (CNVs) are heritable gains and losses of genomic DNA in normal individuals. While copy number variation is widely studied in humans, our knowledge of CNVs in other mammalian species is more limited. We have designed a custom array-based comparative genomic hybridization (aCGH) platform with 385 000 oligonucleotide probes based on the reference genome sequence of the rhesus macaque (Macaca mulatta), the most widely studied non-human primate in biomedical research. We used this platform to identify 123 CNVs among 10 unrelated macaque individuals, with 24% of the CNVs observed in multiple individuals. We found that segmental duplications were significantly enriched at macaque CNV loci. We also observed significant overlap between rhesus macaque and human CNVs, suggesting that certain genomic regions are prone to recurrent CNV formation and instability, even across a total of approximately 50 million years of primate evolution ( approximately 25 million years in each lineage). Furthermore, for eight of the CNVs that were observed in both humans and macaques, previous human studies have reported a relationship between copy number and gene expression or disease susceptibility. Therefore, the rhesus macaque offers an intriguing, non-human primate outbred model organism with which hypotheses concerning the specific functions of phenotypically relevant human CNVs can be tested.     

Profiling of copy number variations (CNVs) in healthy individuals from three ethnic groups using a human genome 32 K BAC-clone-based array

To further explore the extent of structural large-scale variation in the human genome, we assessed copy number variations (CNVs) in a series of 71 healthy subjects from three ethnic groups. CNVs were analyzed using comparative genomic hybridization (CGH) to a BAC array covering the human genome, using DNA extracted from peripheral blood, thus avoiding any culture-induced rearrangements. By applying a newly developed computational algorithm based on Hidden Markov modeling, we identified 1,078 autosomal CNVs, including at least two neighboring/overlapping BACs, which represent 315 distinct regions. The average size of the sequence polymorphisms was approximately 350 kb and involved in total approximately 117 Mb or approximately 3.5% of the genome. Gains were about four times more common than deletions, and segmental duplications (SDs) were overrepresented, especially in larger deletion variants. This strengthens the notion that SDs often define hotspots of chromosomal rearrangements. Over 60% of the identified autosomal rearrangements match previously reported CNVs, recognized with various platforms. However, results from chromosome X do not agree well with the previously annotated CNVs. Furthermore, data from single BACs deviating in copy number suggest that our above estimate of total variation is conservative. This report contributes to the establishment of the common baseline for CNV, which is an important resource in human genetics.     

Characterization of copy number-stable regions in the human genome

In the past few years the number of copy number variants (CNVs) identified in the human genome has increased significantly, but our understanding of the functional impact of CNVs is still limited. Clinically significant variations cannot easily be distinguished from benign, complicating interpretation of patient data. Multiple studies have focused on analysis of regions that vary in copy number in specific disorders. Here we use the opposite strategy and focus our analysis on regions that never seem to vary in the general population, hypothesizing that these are copy number stable because variations within them are deleterious. Our results show that copy number stable regions are characterized by correlation with a number of genomic features, allowing us to define a list of genomic regions that are dosage sensitive in humans. We find that these dosage-sensitive regions show significant overlap with de novo CNVs identified in patients with intellectual disability or autism. There is also a significant association between copy number stable regions and rare inherited variants in autism patients, but not in controls. Based on this predictive power, we propose that copy number stable regions can be used to complement maps of known CNVs to facilitate interpretation of patient data.     

无创产前检测对于胎儿染色体拷贝数变异的检测价值

目的:探讨无创产前检测(non-invasive prenatal testing,NIPT)对于胎儿染色体拷贝数变异(copy number variations, CNVs)的检测价值。方法:收集18 661例接受NIPT检测的孕妇的临床资料,为提示胎儿携带CNVs的孕妇提供羊水染色体核型或/及染色体微阵列分析,并...     

Analysis of copy number variants and segmental duplications in the human genome: Evidence for a change in the process of formation in recent evolutionary history

Segmental duplications (SDs) are operationally defined as >1 kb stretches of duplicated DNA with high sequence identity. They arise from copy number variants (CNVs) fixed in the population. To investigate the formation of SDs and CNVs, we examine their large-scale patterns of co-occurrence with different repeats. Alu elements, a major class of genomic repeats, had previously been identified as prime drivers of SD formation. We also observe this association; however, we find that it sharply decreases for younger SDs. Continuing this trend, we find only weak associations of CNVs with Alus. Similarly, we find an association of SDs with processed pseudogenes, which is decreasing for younger SDs and absent entirely for CNVs. Next, we find that SDs are significantly co-localized with each other, resulting in a highly skewed "power-law" distribution and chromosomal hotspots. We also observe a significant association of CNVs with SDs, but find that an SD-mediated mechanism only accounts for some CNVs (<28%). Overall, our results imply that a shift in predominant formation mechanism occurred in recent history: approximately 40 million years ago, during the "Alu burst" in retrotransposition activity, non-allelic homologous recombination, first mediated by Alus and then the by newly formed CNVs themselves, was the main driver of genome rearrangements; however, its relative importance has decreased markedly since then, with proportionally more events now stemming from other repeats and from non-homologous end-joining. In addition to a coarse-grained analysis, we performed targeted sequencing of 67 CNVs and then analyzed a combined set of 270 CNVs (540 breakpoints) to verify our conclusions.     

Flow cytometry of human solid tumours: clinical and research applications

The measurement of DNA content of nuclei isolated from solid human neoplasms was one of the first large-scale applications of flow cytometry. Due to the development of directly labelled monoclonal antibodies mainly directed against cell-surface-associated proteins expressed by haematopoetic or lymphoid cells, flow cytometry rapidly evolved to an indispensable clinical technique. However, progress in multiparameter flow cytometry of solid tumours lagged behind.Recent technical improvements in preparing and staining cell suspensions obtained from solid tumours allows the simultaneous measurement of high-resolution DNA content and tumour-associated protein expression of fresh, frozen and even paraffin-embedded clinical samples. These new developments might give an impulse to clinical multiparameter flow cytometry of human solid neoplasms.     

Towards an evidence-based process for the clinical interpretation of copy number variation

The evidence-based review (EBR) process has been widely used to develop standards for medical decision-making and to explore complex clinical questions. This approach can be applied to genetic tests, such as chromosomal microarrays, in order to assist in the clinical interpretation of certain copy number variants (CNVs), particularly those that are rare, and guide array design for optimal clinical utility. To address these issues, the International Standards for Cytogenomic Arrays Consortium has established an EBR Work Group charged with building a framework to systematically assess the potential clinical relevance of CNVs throughout the genome. This group has developed a rating system enumerating the evidence supporting or refuting dosage sensitivity for individual genes and regions that considers the following criteria: number of causative mutations reported; patterns of inheritance; consistency of phenotype; evidence from large-scale case-control studies; mutational mechanisms; data from public genome variation databases; and expert consensus opinion. The system is designed to be dynamic in nature, with regions being reevaluated periodically to incorporate emerging evidence. The evidence collected will be displayed within a publically available database, and can be used in part to inform clinical laboratory CNV interpretations as well as to guide array design.     

A full-coverage,high-resolution human chromosome 22 genomic microarray for clinical and research applications

We have constructed the first comprehensive microarray representinga human chromosome for analysis of DNA copy number variation.This chromosome 22 array covers 34.7 Mb, representing 1.1%of the genome, with an average resolution of 75 kb. Todemonstrate the utility of the array, we have applied it toprofile acral melanoma, dermatofibrosarcoma, DiGeorge syndromeand neurofibromatosis 2. We accurately diagnosed homozygous/heterozygousdeletions, amplifications/gains, IGLV/IGLC locus instability,and breakpoints of an imbalanced translocation. We further identifiedthe 14-3-3 eta isoform as a candidate tumor suppressor in glioblastoma.Two significant methodological advances in array constructionwere also developed and validated. These include a strictlysequence defined, repeat-free, and non-redundant strategy forarray preparation. This approach allows an increase in arrayresolution and analysis of any locus; disregarding common repeats,genomic clone availability and sequence redundancy. In addition,we report that the application of phi29 DNA polymerase is advantageousin microarray preparation. A broad spectrum of issues in medicalresearch and diagnostics can be approached using the array.This well annotated and gene-rich autosome contains numerousuncharacterized disease genes. It is therefore crucial to associatethese genes to specific 22q-related conditions and this arraywill be instrumental towards this goal. Furthermore, comprehensiveepigenetic profiling of 22q-located genes and high-resolutionanalysis of replication timing across the entire chromosomecan be studied using our array. ^* To whom correspondence should be addressed at: Department ofGenetics and Pathology, Rudbeck laboratory 3rd floor, UppsalaUniversity, Dag Hammarskjölds väg 20, 751 85 Uppsala,Sweden. Fax: +46 18558931; Email: jan.dumanski{at}genpat.uu.se      

Identification of osteosarcoma driver genes by integrative analysis of copy number and gene expression data

High-grade osteosarcoma is a tumor with a complex genomic profile, occurring primarily in adolescents with a second peak at middle age. The extensive genomic alterations obscure the identification of genes driving tumorigenesis during osteosarcoma development. To identify such driver genes, we integrated DNA copy number profiles (Affymetrix SNP 6.0) of 32 diagnostic biopsies with 84 expression profiles (Illumina Human-6 v2.0) of high-grade osteosarcoma as compared with its putative progenitor cells, i.e., mesenchymal stem cells (n = 12) or osteoblasts (n = 3). In addition, we performed paired analyses between copy number and expression profiles of a subset of 29 patients for which both DNA and mRNA profiles were available. Integrative analyses were performed in Nexus Copy Number software and statistical language R. Paired analyses were performed on all probes detecting significantly differentially expressed genes in corresponding LIMMA analyses. For both nonpaired and paired analyses, copy number aberration frequency was set to >35%. Nonpaired and paired integrative analyses resulted in 45 and 101 genes, respectively, which were present in both analyses using different control sets. Paired analyses detected >90% of all genes found with the corresponding nonpaired analyses. Remarkably, approximately twice as many genes as found in the corresponding nonpaired analyses were detected. Affected genes were intersected with differentially expressed genes in osteosarcoma cell lines, resulting in 31 new osteosarcoma driver genes. Cell division related genes, such as MCM4 and LATS2, were overrepresented and genomic instability was predictive for metastasis-free survival, suggesting that deregulation of the cell cycle is a driver of osteosarcomagenesis.