CGH, cDNA and tissue microarray analyses implicate FGFR2 amplification in a small subset of breast tumors.

Multiple regions of the genome are often amplified during breast cancer development and progression, as evidenced in a number of published studies by comparative genomic hybridization (CGH). However, only relatively few target genes for such amplifications have been identified. Here, we indicate how small-scale commercially available cDNA and CGH microarray formats combined with the tissue microarray technology enable rapid identification of putative amplification target genes as well as analysis of their clinical significance. According to CGH, the SUM-52 breast cancer cell line harbors several high-level DNA amplification sites, including the 10q26 chromosomal region where the fibroblast growth factor receptor 2 (FGFR2) gene has been localized. High level amplification of FGFR2 in SUM-52 was identified using CGH analysis on a microarray of BAC clones. A cDNA microarray survey of 588 genes showed >40-fold overexpression of FGFR2. Finally, a tissue microarray based FISH analysis of 750 uncultured primary breast cancers demonstrated in vivo amplification of the FGFR2 gene in about 1% of the tumors. In conclusion, three consecutive microarray (CGH, cDNA and tissue) experiments revealed high-level amplification and overexpression of the FGFR2 in a breast cancer cell line, but only a low frequency of involvement in primary breast tumors. Applied to a genomic scale with larger arrays, this strategy should facilitate identification of the most important target genes for cytogenetic rearrangements, such as DNA amplification sites detected by conventional CGH. Figures on http://www.esacp.org/acp/2001/22-4/heiskanen.htm     

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.     

Genome-wide detection of chromosomal imbalances in tumors using BAC microarrays

Chromosomal imbalances such as deletions and amplifications are common rearrangements in most tumors. Specific rearrangements are consistently associated with specific tumor types or stages, implicating the role of the genes in a region of chromosomal imbalance in tumor initiation and progression. The development of comparative genomic hybridization (CGH) has obviated the need to obtain metaphase spreads from tumors, so that the chromosomal imbalances in many solid tumors may be revealed using an extracted genomic DNA sample. However, the resolution of the cytogenetic method remains and the extreme technical difficulty of CGH has restricted its use. Conceptually, DNA microarray-based CGH is an obvious solution to all of the limitations of conventional CGH. Although arrays have been used for CGH studies, their success has been limited by poor specific signal-to-noise ratios. Here we demonstrate a microarray-based CGH method that allows reliable detection of chromosomal deletions and amplifications with high resolution. Our microarray system is fundamentally different from most current microarray technologies in that activated DNA is printed on natural glass surfaces while other systems almost exclusively focus on activating the surfaces, a strategy that invariably introduces hybridization backgrounds. The concept of using pre-modification may be generally applied for making arrays of other biological materials, as modifying the substrates will be more controllable in solution than on surfaces.     

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.     

Genome-wide copy number profiling on high-density bacterial artificial chromosomes, single-nucleotide polymorphisms, and oligonucleotide microarrays: a platform comparison based on statistical power analysis.

Recently, comparative genomic hybridization onto bacterial artificial chromosome (BAC) arrays (array-based comparative genomic hybridization) has proved to be successful for the detection of submicroscopic DNA copy-number variations in health and disease. Technological improvements to achieve a higher resolution have resulted in the generation of additional microarray platforms encompassing larger numbers of shorter DNA targets (oligonucleotides). Here, we present a novel method to estimate the ability of a microarray to detect genomic copy-number variations of different sizes and types (i.e. deletions or duplications). We applied our method, which is based on statistical power analysis, to four widely used high-density genomic microarray platforms. By doing so, we found that the high-density oligonucleotide platforms are superior to the BAC platform for the genome-wide detection of copy-number variations smaller than 1 Mb. The capacity to reliably detect single copy-number variations below 100 kb, however, appeared to be limited for all platforms tested. In addition, our analysis revealed an unexpected platform-dependent difference in sensitivity to detect a single copy-number loss and a single copy-number gain. These analyses provide a first objective insight into the true capacities and limitations of different genomic microarrays to detect and define DNA copy-number variations.     

Current status and future prospects of array-based comparative genomic hybridisation.

The majority of human cancers as well as many developmental abnormalities harbour chromosomal imbalances, many of which result in the gain and/or loss of genomic material. Conventional comparative genomic hybridisation (CGH) has been used extensively to map DNA copy number changes to chromosomal positions. The introduction of microarray CGH provided a powerful tool to precisely detect and quantify genomic aberrations and map these directly onto the sequence of the human genome. In the past several years, a number of different approaches towards array-based CGH have been undertaken. This paper reviews these approaches and presents some of the recently-developed applications of this new technology in both research and clinical settings.     

Nonparametric testing for DNA copy number induced differential mRNA gene expression

Summary .  The central dogma of molecular biology relates DNA with mRNA. Array CGH measures DNA copy number and gene expression microarrays measure the amount of mRNA. Methods that integrate data from these two platforms may uncover meaningful biological relationships that further our understanding of cancer. We develop nonparametric tests for the detection of copy number induced differential gene expression. The tests incorporate the uncertainty of the calling of genomic aberrations. The test is preceded by a "tuning algorithm" that discards certain genes to improve the overall power of the false discovery rate selection procedure. Moreover, the test statistics are "shrunken" to borrow information across neighboring genes that share the same array CGH signature. For each gene we also estimate its effect, its amount of differential expression due to copy number changes, and calculate the coefficient of determination. The method is illustrated on breast cancer data, in which it confirms previously reported findings, now with a more profound statistical underpinning.     

Targeted next generation sequencing identifies clinically actionable mutations in patients with melanoma

Somatic sequencing of cancers has produced new insight into tumorigenesis, tumor heterogeneity, and disease progression, but the vast majority of genetic events identified are of indeterminate clinical significance. Here, we describe a NextGen sequencing approach to fully analyzing 248 genes, including all those of known clinical significance in melanoma. This strategy features solution capture of DNA followed by multiplexed, high‐throughput sequencing and was evaluated in 31 melanoma cell lines and 18 tumor tissues from patients with metastatic melanoma. Mutations in melanoma cell lines correlated with their sensitivity to corresponding small molecule inhibitors, confirming, for example, lapatinib sensitivity in ERBB4 mutant lines and identifying a novel activating mutation of BRAF. The latter event would not have been identified by clinical sequencing and was associated with responsiveness to a BRAF kinase inhibitor. This approach identified focal copy number changes of PTEN not found by standard methods, such as comparative genomic hybridization (CGH). Actionable mutations were found in 89% of the tumor tissues analyzed, 56% of which would not be identified by standard‐of‐care approaches. This work shows that targeted sequencing is an attractive approach for clinical use in melanoma.     

Development of a DNA-labeling system for array-based comparative genomic hybridization.

Chromosomal amplifications and deletions are critical components of tumorigenesis and DNA copy-number variations also correlate with changes in mRNA expression levels. Genome-wide microarray comparative genomic hybridization (CGH) has become an important method for detecting and mapping chromosomal changes in tumors. Thus, the ability to detect twofold differences in fluorescent intensity between samples on microarrays depends on the generation of high-quality labeled probes. To enhance array-based CGH analysis, a random prime genomic DNA labeling method optimized for improved sensitivity, signal-to-noise ratios, and reproducibility has been developed. The labeling system comprises formulated random primers, nucleotide mixtures, and notably a high concentration of the double mutant exo-large fragment of DNA polymerase I (exo-Klenow). Microarray analyses indicate that the genomic DNA-labeled templates yield hybridization signals with higher fluorescent intensities and greater signal-to-noise ratios and detect more positive features than the standard random prime and conventional nick translation methods. Also, templates generated by this system have detected twofold differences in gene copy number between male and female genomic DNA and identified amplification and deletions from the BT474 breast cancer cell line in microarray hybridizations. Moreover, alterations in gene copy number were routinely detected with 0.5 microg of genomic DNA starting sample. The method is flexible and performs efficiently with different fluorescently labeled nucleotides. Application of the optimized CGH labeling system may enhance the resolution and sensitivity of array-based CGH analysis in cancer and medical genetic studies.     

Comprehensive genetic analysis of cancer cells

Human cancer is viewed as a disorder of genes originating from the progeny of a single cell that has accumulated multiple genetic alterations. The genetic alterations include point mutation, chromosomal rearrangements and imbalances. Amplifications primarily involve oncogenes whose overexpression leads to growth deregulation, while deletions commonly target tumor suppressor genes that control cell cycle checkpoints and DNA repair mechanisms. With the advent of molecular cytogenetics procedures for global detection of genomic imbalances and for multicolor visualization of structural chromosome changes, as well as the completion of human genome mapping and the development of microarray technology for serial gene expression analysis of the entire genomes, a significant progress has been made in uncovering the molecular basis of cancer. The major challenge in cancer biology is to decipher the molecular anatomy of various cancers and to identify cancer-related genes that now comprise only a fraction of human genes. The complete genetic anatomy of specific cancers would allow a better understanding of the role of genetic alterations in carcinogenesis, provide diagnostic and prognostic markers and discriminate between cells at different stages of progression toward malignancy. This review highlights current technologies that are available to explore cancer cells and outlines their application to investigations in human hepatocellular carcinoma.     

Analysis of array CGH data: from signal ratio to gain and loss of DNA regions

MOTIVATION: Genomic DNA regions are frequently lost or gained during tumor progression. Array Comparative Genomic Hybridization (array CGH) technology makes it possible to assess these changes in DNA in cancers, by comparison with a normal reference. The identification of systematically deleted or amplified genomic regions in a set of tumors enables biologists to identify genes involved in cancer progression because tumor suppressor genes are thought to be located in lost genomic regions and oncogenes, in gained regions. Array CGH profiles should also improve the classification of tumors. The achievement of these goals requires a methodology for detecting the breakpoints delimiting altered regions in genomic patterns and assigning a status (normal, gained or lost) to each chromosomal region. RESULTS: We have developed a methodology for the automatic detection of breakpoints from array CGH profile, and the assignment of a status to each chromosomal region. The breakpoint detection step is based on the Adaptive Weights Smoothing (AWS) procedure and provides highly convincing results: our algorithm detects 97, 100 and 94% of breakpoints in simulated data, karyotyping results and manually analyzed profiles, respectively. The percentage of correctly assigned statuses ranges from 98.9 to 99.8% for simulated data and is 100% for karyotyping results. Our algorithm also outperforms other solutions on a public reference dataset. AVAILABILITY: The R package GLAD (Gain and Loss Analysis of DNA) is available upon request.     

Optimizing comparative genomic hybridization probes for genotyping and SNP detection in Plasmodium falciparum

Microarray-based comparative genomic hybridizations (CGH) interrogate genomic DNA to identify structural differences such as amplifications and deletions that are easily detected as large signal aberrations. Subtle signal deviations caused by single nucleotide polymorphisms (SNPs) can also be detected but is challenged by a high AT content (81%) in P. falciparum. We compared genome-wide CGH signal to sequence polymorphisms between parasite strains 3D7, HB3, and Dd2 using NimbleGen microarrays. From 23,191 SNPs (excluding var/rif/stevor genes), our CGH probe set detected SNPs with > 99.9% specificity but low (< 10%) sensitivity. Probe length, melting temperature, GC content, SNP location in the probe, mutation type, and hairpin structures affected SNP sensitivity. Previously unrecognized variable number tandem repeats (VNTRs) also were detected by this method. These findings will guide the redesign of a probe set to optimize an openly available CGH microarray platform for high-resolution genotyping suitable for population genomics studies.     

High Resolution Array-CGH Characterization of Human Stem Cells Using a Stem Cell Focused Microarray

Human embryonic and induced pluripotent stem cells (ESCs, iPSCs) that are cultured for an extended period of time are susceptible to genomic instability. Chromosomal aberrations decrease the reliability and reproducibility of experiments and could deem the cells unusable for therapeutic purposes. The genetic stability of human ESCs and iPSCs is commonly monitored by karyotype analysis. However, this low-resolution technique can only identify large aneuploidies. A reliable, high-resolution technique to detect genomic aberrations at a cost comparable to karyotyping is needed to better characterize stem cell lines. We have designed a stem cell focused array-comparative genomic hybridization microarray that covers the entire genome at high resolution with increased probe coverage in over 60 stem cell associated genes and more than 195 cancer related genes. Several iPSC lines were analyzed using the focused microarray and compared with either karyotyping or a standard Agilent 44K microarray. In addition to the abnormalities detected by these platforms, the custom microarray identified several small duplications spanning stem cell and/or cancer related genes. Scientists using a stem cell focused microarray to characterize their stem cells will be aware of the structural variants present in their cells and be more confident in their experimental results.     

Comparison of Comparative Genomic Hybridization Technologies Across Microarray Platforms

In the 2007 Association of Biomolecular Resource Facilities Microarray Research Group project, we analyzed HL-60 DNA with five platforms: Agilent, Affymetrix 500K, Affymetrix U133 Plus 2.0, Illumina, and RPCI 19K BAC arrays. Copy number variation was analyzed using circular binary segmentation (CBS) analysis of log ratio scores from four independently assessed hybridizations of each platform. Data obtained from these platforms were assessed for reproducibility and the ability to detect formerly reported copy number variations in HL-60. In HL-60, all of the tested platforms detected genomic DNA amplification of the 8q24 locus, trisomy 18, and monosomy X; and deletions at loci 5q11.2~q31, 9p21.3~p22, 10p12~p15, 14q22~q31, and 17p12~p13.3. In the HL-60 genome, at least two of the five platforms detected five novel losses and five novel gains. This report provides guidance in the selection of platforms based on this wide-ranging evaluation of available CGH platforms.     

The genomic landscape of cutaneous melanoma

Somatic mutation analysis of melanoma has been performed at the single gene level extensively over the past several decades. This has provided considerable insight into the critical pathways controlling melanoma initiation and progression. During the last 5 yr, next‐generation sequencing (NGS) has enabled even more comprehensive mutational screening at the level of multigene panels, exomes and genomes. These studies have uncovered many new and unexpected players in melanoma development. The recent landmark study from The Cancer Genome Atlas (TCGA) consortium describing the genomic architecture of 333 cutaneous melanomas provides the largest and broadest analysis to date on the somatic aberrations underlying melanoma genesis. It thus seems timely to review the mutational landscape of melanoma and highlight the key genes and cellular pathways that appear to drive this cancer.     

Robust prostate cancer marker genes emerge from direct integration of inter-study microarray data

MOTIVATION: DNA microarray data analysis has been used previously to identify marker genes which discriminate cancer from normal samples. However, due to the limited sample size of each study, there are few common markers among different studies of the same cancer. With the rapid accumulation of microarray data, it is of great interest to integrate inter-study microarray data to increase sample size, which could lead to the discovery of more reliable markers. RESULTS: We present a novel, simple method of integrating different microarray datasets to identify marker genes and apply the method to prostate cancer datasets. In this study, by applying a new statistical method, referred to as the top-scoring pair (TSP) classifier, we have identified a pair of robust marker genes (HPN and STAT6) by integrating microarray datasets from three different prostate cancer studies. Cross-platform validation shows that the TSP classifier built from the marker gene pair, which simply compares relative expression values, achieves high accuracy, sensitivity and specificity on independent datasets generated using various array platforms. Our findings suggest a new model for the discovery of marker genes from accumulated microarray data and demonstrate how the great wealth of microarray data can be exploited to increase the power of statistical analysis. CONTACT: leixu@jhu.edu.     

Comparative genomic hybridisation for the analysis of chromosomal imbalances in solid tumours and haematological malignancies

 Comparative genomic hybridisation (CGH) is based on a two-colour, competitive fluorescence in situ hybridisation of differentially labelled tumour and reference DNA to normal metaphase chromosomes. This new technology has made a great impact in molecular tumour pathology due to its possible application to archival specimens and the ability to create copy number karyotypes throughout the whole genome from very small amounts of DNA. If chromosomal imbalances can be correlated with a etiological and clinical features of tumours, CGH could be able to provide new prognostic and diagnostic criteria. CGH findings further provide starting points for the molecular genetic characterisation of altered chromosomal regions harbouring yet unidentified genes involved in tumorigenesis and tumour progression. An overview of the results of published CGH studies on solid tumours and haematological malignancies is presented. Methodological limitations of the CGH technology are reported, as well as future developments which will improve its use in routine analysis. Accepted: 29 July 1997