Cytogenetic analysis from DNA by comparative genomic hybridization

Comparative genomic hybridization (CGH) is a modified in situ hybridization technique which allows detection and mapping of DNA sequence copy differences between two genomes in a single experiment. In CGH analysis, two differentially labelled genomic DNA (study and reference) are co-hybridized to normal metaphase spreads. Chromosomal locations of copy number changes in the DNA segments of the study genome are revealed by a variable fluorescence intensity ratio along each target chromosome. Since its development, CGH has been applied mostly as a research tool in the field of cancer cytogenetics to identify genetic changes in many previously unknown regions. CGH may also have a role in clinical cytogenetics for detection and identification of unbalanced chromosomal abnormalities.     

Digital karyotyping: an update of its applications in cancer

DNA copy number alterations, including entire chromosomal changes and small interstitial DNA amplifications and deletions, characterize the development of cancer. These changes usually affect the expression of target genes and subsequently the function of the target proteins. Since the completion of the human genome project, the capacity to comprehensively analyze the human cancer genome has expanded significantly. Techniques such as digital karyotyping have been developed to allow for the detection of DNA copy number alterations in cancer at the whole-genome scale. When compared with conventional methods such as spectral karyotyping, representational difference analysis, comparative genomic hybridization (CGH), or the more recent array CGH; digital karyotyping provides an evaluation of copy number of genetic material at higher resolution. Digital karyotyping has therefore promised to enhance our understanding of the cancer genome. This article provides an overview of digital karyotyping including the principle of the technology and its applications in identifying potential oncogenes and tumor suppressor genes.     

Detection of DNA copy number abnormality by microarray expression analysis

Gene copy-number abnormalities (CNAs) are characteristic of solid tumors and are found in association with developmental abnormalities and/or mental retardation. The ultimate impact of CNAs is exerted by the altered expression of encoded genes. We have utilized high-density oligonucleotide arrays from Affymetrix to identify DNA CNAs via their impact on mRNA expression levels. In these studies, we have used three different trisomic cell lines (trisomy 9, trisomy 18, trisomy 21) as models of CNAs and have compared mRNA expression in those trisomic cells with that observed in diploid cell lines of matched tissue origin. Our data clearly show that genes from CNA chromosome regions are substantially over-represented (P<0.000001 by chi-square analysis) in the differentially expressed subset from comparisons of all three trisomic cell lines with normal matching cells. In addition, we have been able to detect the origin of the duplication by a statistical scan for over-expressed genes. These data show that microarray detection of differential mRNA expression can be used to identify significant DNA CNAs.     

Genetic Instability of Clathrin-Deficient Strains of Saccharomyces Cerevisiae

Saccharomyces cerevisiae strains carrying a mutation in the clathrin heavy chain gene (CHC1) are genetically unstable and give rise to heterogeneous populations of cells. Manifestations of the instability include increases in genome copy number as well as compensatory genetic changes that allow better growing clathrin-deficient cells to take over the population. Increases in genome copy number appear to result from changes in ploidy as well as alterations in normal nuclear number. Genetic background influences the frequency at which cells with increased genome content are observed in different Chc(-) strains. We cannot distinguish whether genetic background affects the rate at which aberrant nuclear division events occur or a growth advantage of cells with increased nuclear and/or genome content. However, survival of chc1-Δ cells does not require an increase in genome copy number. The clathrin heavy chain gene was mapped 1-2 cM distal to KEX1 on the left arm of chromosome VII by making use of integrated 2μ plasmid sequences to destabilize distal chromosome segments and allow ordering of the genes.     

Comparative genomic hybridization-array analysis enhances the detection of aneuploidies and submicroscopic imbalances in spontaneous miscarriages

Miscarriage is a condition that affects 10%-15% of all clinically recognized pregnancies, most of which occur in the first trimester. Approximately 50% of first-trimester miscarriages result from fetal chromosome abnormalities. Currently, G-banded chromosome analysis is used to determine if large-scale genetic imbalances are the cause of these pregnancy losses. This technique relies on the culture of cells derived from the fetus, a technique that has many limitations, including a high rate of culture failure, maternal overgrowth of fetal cells, and poor chromosome morphology. Comparative genomic hybridization (CGH)-array analysis is a powerful new molecular cytogenetic technique that allows genomewide analysis of DNA copy number. By hybridizing patient DNA and normal reference DNA to arrays of genomic clones, unbalanced gains or losses of genetic material across the genome can be detected. In this study, 41 product-of-conception (POC) samples, which were previously analyzed by G-banding, were tested using CGH arrays to determine not only if the array could identify all reported abnormalities, but also whether any previously undetected genomic imbalances would be discovered. The array methodology detected all abnormalities as reported by G-banding analysis and revealed new abnormalities in 4/41 (9.8%) cases. Of those, one trisomy 21 POC was also mosaic for trisomy 20, one had a duplication of the 10q telomere region, one had an interstitial deletion of chromosome 9p, and the fourth had an interstitial duplication of the Prader-Willi/Angelman syndrome region on chromosome 15q, which, if maternally inherited, has been implicated in autism. This retrospective study demonstrates that the DNA-based CGH-array technology overcomes many of the limitations of routine cytogenetic analysis of POC samples while enhancing the detection of fetal chromosome aberrations.     

Micro-Scale Genomic DNA Copy Number Aberrations as Another Means of Mutagenesis in Breast Cancer

Introduction

In breast cancer, the basal-like subtype has high levels of genomic instability relative to other breast cancer subtypes with many basal-like-specific regions of aberration. There is evidence that this genomic instability extends to smaller scale genomic aberrations, as shown by a previously described micro-deletion event in the PTEN gene in the Basal-like SUM149 breast cancer cell line.

Methods

We sought to identify if small regions of genomic DNA copy number changes exist by using a high density, gene-centric Comparative Genomic Hybridizations (CGH) array on cell lines and primary tumors. A custom tiling array for CGH (244,000 probes, 200 bp tiling resolution) was created to identify small regions of genomic change, which was focused on previously identified basal-like-specific, and general cancer genes. Tumor genomic DNA from 94 patients and 2 breast cancer cell lines was labeled and hybridized to these arrays. Aberrations were called using SWITCHdna and the smallest 25% of SWITCHdna-defined genomic segments were called micro-aberrations (<64 contiguous probes, ∼ 15 kb).

Results

Our data showed that primary tumor breast cancer genomes frequently contained many small-scale copy number gains and losses, termed micro-aberrations, most of which are undetectable using typical-density genome-wide aCGH arrays. The basal-like subtype exhibited the highest incidence of these events. These micro-aberrations sometimes altered expression of the involved gene. We confirmed the presence of the PTEN micro-amplification in SUM149 and by mRNA-seq showed that this resulted in loss of expression of all exons downstream of this event. Micro-aberrations disproportionately affected the 5′ regions of the affected genes, including the promoter region, and high frequency of micro-aberrations was associated with poor survival.

Conclusion

Using a high-probe-density, gene-centric aCGH microarray, we present evidence of small-scale genomic aberrations that can contribute to gene inactivation. These events may contribute to tumor formation through mechanisms not detected using conventional DNA copy number analyses.     

Long Span DNA Paired-End-Tag (DNA-PET) Sequencing Strategy for the Interrogation of Genomic Structural Mutations and Fusion-Point-Guided Reconstruction of Amplicons

Structural variations (SVs) contribute significantly to the variability of the human genome and extensive genomic rearrangements are a hallmark of cancer. While genomic DNA paired-end-tag (DNA-PET) sequencing is an attractive approach to identify genomic SVs, the current application of PET sequencing with short insert size DNA can be insufficient for the comprehensive mapping of SVs in low complexity and repeat-rich genomic regions. We employed a recently developed procedure to generate PET sequencing data using large DNA inserts of 10–20 kb and compared their characteristics with short insert (1 kb) libraries for their ability to identify SVs. Our results suggest that although short insert libraries bear an advantage in identifying small deletions, they do not provide significantly better breakpoint resolution. In contrast, large inserts are superior to short inserts in providing higher physical genome coverage for the same sequencing cost and achieve greater sensitivity, in practice, for the identification of several classes of SVs, such as copy number neutral and complex events. Furthermore, our results confirm that large insert libraries allow for the identification of SVs within repetitive sequences, which cannot be spanned by short inserts. This provides a key advantage in studying rearrangements in cancer, and we show how it can be used in a fusion-point-guided-concatenation algorithm to study focally amplified regions in cancer.     

A high-resolution map of segmental DNA copy number variation in the mouse genome

Submicroscopic (less than 2 Mb) segmental DNA copy number changes are a recently recognized source of genetic variability between individuals. The biological consequences of copy number variants (CNVs) are largely undefined. In some cases, CNVs that cause gene dosage effects have been implicated in phenotypic variation. CNVs have been detected in diverse species, including mice and humans. Published studies in mice have been limited by resolution and strain selection. We chose to study 21 well-characterized inbred mouse strains that are the focus of an international effort to measure, catalog, and disseminate phenotype data. We performed comparative genomic hybridization using long oligomer arrays to characterize CNVs in these strains. This technique increased the resolution of CNV detection by more than an order of magnitude over previous methodologies. The CNVs range in size from 21 to 2,002 kb. Clustering strains by CNV profile recapitulates aspects of the known ancestry of these strains. Most of the CNVs (77.5%) contain annotated genes, and many (47.5%) colocalize with previously mapped segmental duplications in the mouse genome. We demonstrate that this technique can identify copy number differences associated with known polymorphic traits. The phenotype of previously uncharacterized strains can be predicted based on their copy number at these loci. Annotation of CNVs in the mouse genome combined with sequence-based analysis provides an important resource that will help define the genetic basis of complex traits.     

Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer

The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We seek to identify those genetic and epigenetic aberrations that have the most impact on gene function within the tumor. First, we perform a bioinformatic analysis of copy number variation (CNV) and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We separately examined CNV and DNA methylation for 42 primary serous ovarian cancer samples using MOMA-ROMA assays and 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with altered copy number and correlated changes in expression. Among these genes CCNE1, POP4, UQCRB, PHF20L1 and C19orf2 were identified within both data sets. We were specifically interested in copy number variation as our base genomic property in the prediction of tumor suppressors and oncogenes in the altered ovarian tumor. We therefore identify changes in DNA methylation and expression for all amplified and deleted genes. We statistically define tumor suppressor and oncogenic features for these modalities and perform a correlation analysis with expression. We predicted 611 potential oncogenes and tumor suppressors candidates by integrating these data types. Genes with a strong correlation for methylation dependent expression changes exhibited at varying copy number aberrations include CDCA8, ATAD2, CDKN2A, RAB25, AURKA, BOP1 and EIF2C3. We provide copy number variation and DNA methylation analysis for over 11,500 individual genes covering the genetic landscape of ovarian cancer tumors. We show the extent of genomic and epigenetic alterations for known tumor suppressors and oncogenes and also use these defined features to identify potential ovarian cancer gene candidates.     

Genome-wide profiling of gene amplification and deletion in cancer

Accumulations of genetic changes in somatic cells induce phenotypic transformations leading to cancer. Among these genetic changes, gene amplification and deletion are most frequently observed in several kinds of cancers. Amplification of oncogene and/or deletion of tumor suppressor gene, together with dysfunction of the gene by point mutation, are the main causes of cancer. Genome-wide analysis of amplification and deletion of genes in cancers is basic to resolving the mechanisms of carcinogenesis. Comparative genomic hybridization (CGH) developed in 1992 has been utilized to identify DNA copy number abnormalities in various kind of cancers and several reports have shown its usefulness in screening of the genes involved in carcinogenesis, and also in the identification of prognostic factors in cancer. We have shown that 1q23 gain is associated with neuroblastomas that are resistant to aggressive treatment, and have poor prognosis, and 1q and 13q gains are possibly related to drug resistance in ovarian cancers. Recently, the "rough draft" of the human genome was reported and we are ready to utilize the vast information on genomic sequences in cancer research. Moreover, microarray technology enables us to analyze more than ten thousand genes at a time and revealed genetic abnormalities in cancers at a genome-wide level. By combination of microarray and CGH, a powerful screening method for oncogenes and tumor suppressor genes in cancers, called array-CGH, has been developed by several groups. In this article, we overview these genome-wide analytical methods, CGH and array-CGH, and discuss their potential in molecular characterization of cancers.     

Design considerations for array CGH to oligonucleotide arrays.

BACKGROUND: Representational oligonucleotide microarray analysis has been developed for detection of single nucleotide polymorphisms and/or for genome copy number changes. In this process, the intensity of hybridization to oligonucleotides arrays is increased by hybridizing a polymerase chain reaction (PCR)-amplified representation of reduced genomic complexity. However, hybridization to some oligonucleotides is not sufficiently high to allow precise analysis of that portion of the genome. METHODS: In an effort to identify aspects of oligonucleotide hybridization affecting signal intensity, we explored the importance of the PCR product strand to which each oligonucleotide is homologous and the sequence of the array oligonucleotides. We accomplished this by hybridizing multiple PCR-amplified products to oligonucleotide arrays carrying two sense and two antisense 50-mer oligonucleotides for each PCR amplicon. RESULTS: In some cases, hybridization intensity depended more strongly on the PCR amplicon strand (i.e., sense vs. antisense) than on the detection oligonucleotide sequence. In other cases, the oligonucleotide sequence seemed to dominate. CONCLUSION: Oligonucleotide arrays for analysis of DNA copy number or for single nucleotide polymorphism content should be designed to carry probes to sense and antisense strands of each PCR amplicon to ensure sufficient hybridization and signal intensity.     

A comparison study reveals important features of agreement and disagreement between summarized DNA and RNA data obtained from renal cell carcinoma

Cytogenetic abnormalities, such as DNA amplifications and deletions, often lead to significant changes in gene expression levels within a chromosomal region. Instead of generating additional DNA copy number data, one method to identify DNA copy number abnormalities has been to search existing gene expression data for regional perturbations in gene expression. However, it is not clear how well this surrogate method performs in the examination of individual tumors and how we can use both DNA and RNA data to identify candidate genes that may be mutated. Here we report a comparison study using summarized DNA and RNA data to identify chromosomal abnormalities in human samples. Forty-four tissue samples from patients diagnosed as having renal cell carcinoma (RCC) were collected, together with 15 normal kidney samples as controls, and for each sample the genome-wide DNA and RNA data were obtained for comparison using Affymetrix 100K SNP and HGU133plus2 gene expression chips, respectively. The DNA and RNA data was summarized by both chromosome arm and cytogenetic banding patterns and compared. The result of this analysis revealed that the two summarized data sets used to identify cytogenetic changes agreed well. However, some differences between the two were also identified. These differences of large-scale gene expression deregulation without evidence of the comparable DNA copy number alterations may be the result of known mechanisms, such as large-scale methylation or chromosome inactivation, or may be the result of some new mechanism of DNA-RNA translation. The usefulness of the combined data set for identifying regions of mutated genes is also discussed.     

Expression Profiling of Primary and Metastatic Ovarian Tumors Reveals Differences Indicative of Aggressive Disease

The behavior and genetics of serous epithelial ovarian cancer (EOC) metastasis, the form of the disease lethal to patients, is poorly understood. The unique properties of metastases are critical to understand to improve treatments of the disease that remains in patients after debulking surgery. We sought to identify the genetic and phenotypic landscape of metastatic progression of EOC to understand how metastases compare to primary tumors. DNA copy number and mRNA expression differences between matched primary human tumors and omental metastases, collected at the same time during debulking surgery before chemotherapy, were measured using microarrays. qPCR and immunohistochemistry validated findings. Pathway analysis of mRNA expression revealed metastatic cancer cells are more proliferative and less apoptotic than primary tumors, perhaps explaining the aggressive nature of these lesions. Most cases had copy number aberrations (CNAs) that differed between primary and metastatic tumors, but we did not detect CNAs that are recurrent across cases. A six gene expression signature distinguishes primary from metastatic tumors and predicts overall survival in independent datasets. The genetic differences between primary and metastatic tumors, yet common expression changes, suggest that the major clone in metastases is not the same as in primary tumors, but the cancer cells adapt to the omentum similarly. Together, these data highlight how ovarian tumors develop into a distinct, more aggressive metastatic state that should be considered for therapy development.     

Copy Number Gains at 8q24 and 20q11-q13 in Gastric Cancer Are More Common in Intestinal-Type than Diffuse-Type

The present study was aimed at discovering DNA copy number alterations (CNAs) involved in the carcinogenesis of stomach and at understanding their clinicopathological significances in the Korean population. DNA copy numbers were analyzed using Agilent 244K or 400K array comparative genomic hybridization (aCGH) in fresh-frozen tumor and matched normal tissues from 40 gastric cancer patients. Some of the detected CNA regions were validated using multiplex ligation-dependent probe amplification (MLPA) in six of the 40 patients and customized Agilent 60K aCGH in an independent set of 48 gastric cancers. The mRNA levels of genes at common CNA regions were analyzed using quantitative real-time PCR. Copy number gains were more common than losses across the entire genome in tumor tissues compared to matched normal tissues. The mean number of alterations per case was 64 for gains and 40 for losses, and the median aberration length was 44016 bp for gains and 4732 bp for losses. Copy number gains were frequently detected at 7p22.1 (20%), 8q24.21 (27%–30%), 8q24.3 (22%–48%), 13q34 (20%–31%), and 20q11-q13 (25%–30%), and losses at 3p14.2 (43%), 4q35.2 (27%), 6q26 (23%), and 17p13.3 (20%–23%). CNAs at 7p22.1, 13q34, and 17p13.3 have not been reported in other populations. Most of the copy number losses were associated with down-regulation of mRNA levels, but the correlation between copy number gains and mRNA expression levels varied in a gene-dependent manner. In addition, copy number gains tended to occur more commonly in intestinal-type cancers than in diffuse-type cancers. In conclusion, the present study suggests that copy number gains at 8q24 and 20q11-q13 and losses at 3p14.2 may be common events in gastric cancer but CNAs at 7p22.1, 13q34, and 17p13.3 may be Korean-specific.     

Allele-specific disparity in breast cancer

Background

Molecular alterations critical to development of cancer include mutations, copy number alterations (amplifications and deletions) as well as genomic rearrangements resulting in gene fusions. Massively parallel next generation sequencing, which enables the discovery of such changes, uses considerable quantities of genomic DNA (> 5 ug), a serious limitation in ever smaller clinical samples. However, a commonly available microarray platforms such as array comparative genomic hybridization (array CGH) allows the characterization of gene copy number at a single gene resolution using much smaller amounts of genomic DNA. In this study we evaluate the sensitivity of ultra-dense array CGH platforms developed by Agilent, especially that of the 1 million probe array (1 M array), and their application when whole genome amplification is required because of limited sample quantities.

Methods

We performed array CGH on whole genome amplified and not amplified genomic DNA from MCF-7 breast cancer cells, using 244 K and 1 M Agilent arrays. The ADM-2 algorithm was used to identify micro-copy number alterations that measured less than 1 Mb in genomic length.

Results

DNA from MCF-7 breast cancer cells was analyzed for micro-copy number alterations, defined as measuring less than 1 Mb in genomic length. The 4-fold extra resolution of the 1 M array platform relative to the less dense 244 K array platform, led to the improved detection of copy number variations (CNVs) and micro-CNAs. The identification of intra-genic breakpoints in areas of DNA copy number gain signaled the possible presence of gene fusion events. However, the ultra-dense platforms, especially the densest 1 M array, detect artifacts inherent to whole genome amplification and should be used only with non-amplified DNA samples.

Conclusions

This is a first report using 1 M array CGH for the discovery of cancer genes and biomarkers. We show the remarkable capacity of this technology to discover CNVs, micro-copy number alterations and even gene fusions. However, these platforms require excellent genomic DNA quality and do not tolerate relatively small imperfections related to the whole genome amplification.     

Assessing Population Level Genetic Instability via Moving Average

Tumoral tissues tend to generally exhibit aberrations in DNA copy number that are associated with the development and progression of cancer. Genotyping methods such as array-based comparative genomic hybridization (aCGH) provide means to identify copy number variation across the entire genome. To address some of the shortfalls of existing methods of DNA copy number data analysis, including strong model assumptions, lack of accounting for sampling variability of estimators, and the assumption that clones are independent, we propose a simple graphical approach to assess population-level genetic alterations over the entire genome based on moving average. Furthermore, existing methods primarily focus on segmentation and do not examine the association of covariates with genetic instability. In our methods, covariates are incorporated through a possibly mis-specified working model and sampling variabilities of estimators are approximated using a resampling method that is based on perturbing observed processes. Our proposal, which is applicable to partial, entire or multiple chromosomes, is illustrated through application to aCGH studies of two brain tumor types, meningioma and glioma.