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1 Department of Medical Oncology, Dana Farber Cancer Institute, and 2 Department of Dermatology, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
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ABSTRACT |
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 Top ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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INTRODUCTION |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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3000 BACs), translating into a resolution limit of 2 Mb (6, 7, 8)
. Using this platform, the additional delimitation of regional alterations is made possible by custom microarrays containing BAC contigs that tile across the locus of interest in an iterative locus-specific manner. Prior work has clearly documented the effectiveness of iterative BAC array-CGH profiles to identify candidate cancer genes residing in a focal amplicon (9
, 10)
. Several studies have documented the utility of cDNA-based microarrays for CGH profiling of human cancers (11 , 12) . We have gained considerable experience in the use of cDNA platforms in the analysis of more than 300 human tumors. These studies have demonstrated that commercially available cDNA array-CGH platforms are sufficiently robust to detect regional single-copy changes (13) , providing that high background probes are eliminated by empirical and bioinformatic means.3 Although highly effective, the full potential of cDNA microarrays has been constrained by currently available validated cDNA repositories.
Against the backdrop of this past experience, oligo-based microarrays hold the potential of enhanced design flexibility and eventual full-genome representation of probes capable of accurately reporting single-copy number changes. One long-standing concern has been whether the high complexity of the full genome would undermine the accurate reporting potential of short DNA substrates on a microarray. To date, two types of oligonucleotide microarrays have shown the potential to detect genomic alterations (14, 15, 16)
. One platform uses short oligonucleotides shown previously to be effective in the detection of single-nucleotide polymorphisms, whereas another is a photoprint array of custom-designed 70-mers. In both cases, a PCR-based genomic representation is required to reduce the complexity of the input genomic DNA by 98% as a means to improve hybridization kinetics (14, 15, 16, 17)
. Left unanswered is the extent to which PCR-based amplification biases impact the result.
In this study, we describe assay conditions and bioinformatic tools that enhance the utility of oligo-based microarray platforms in genome-wide DNA copy number analyses of human and mouse cancers. Using a commercially available 60-mer platform, we provide evidence of reliable detection of single copy number alterations in full-complexity genomic DNA. In the analyses of human and mouse cancer genomes, this high-resolution approach readily detects regional and focal CNAs that can be verified by quantitative PCR and are consistent with spectral karyotyping (SKY) data. We suggest that the methodology and analytical tools described in this report should provide investigators with an immediate opportunity to make use of available platforms to gain a detailed and global view of normal and diseased genomes in different species.
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MATERIALS AND METHODS |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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In brief, genomic DNA was fragmented by DpnII restriction digest before labeling. After purification with the QIAquick PCR Purification kit (Qiagen), digested DNA was visualized using the Agilent 2100 BioAnalyzer. For each labeling reaction, 2 µg of digested DNA were used. Each sample is dye-swap labeled for hybridization against normal pooled-human male reference (Promega). DNA samples (2 µg) were denatured in the presence of 740 ng/µl Cy dye-labeled Random Primer (Trilink) and Reaction Buffer (Invitrogen BioPrime Labeling kit) at 98°C for 5 min and then cooled to 2°C for 5 min. The denatured sample was incubated with Klenow fragment, dNTP mix [2.0 mM dATP dGTP dTTP, 1.0 mM dCTP in 10 mM Tris (pH 8.0), 1 mM EDTA], and Cy3 or Cy5 dCTP nucleotides (1 mM; Perkin-Elmer) for 2 h at 37°C. Reactions were terminated using 0.5 M EDTA (pH 8.0). Cy3 and Cy5 reaction pairs (labeled pair, Cy5-sample:Cy3-reference; reversed labeled pair, Cy3-sample:Cy5-reference) were pooled, precipitated, and resuspended in 18.5 µl of SDS (0.514%). After a quality assurance check with NanoDrop determination of Cy3 and Cy5 incorporation, samples were mixed with blocking solution concentrated from 50 µl of human Cot-1 DNA (1 mg/ml; Life Technologies), 20 µl of yeast tRNA (5 mg/ml; Gibco), and 4 µl of (dA)-poly(dT) (5 mg/ml; Sigma). SSC and SDS were added to final concentrations of 3.9x and 0.25%, respectively, in a final volume of 60 µl. For hybridization, samples are denatured at 98°C for 2 min and then cooled at 37°C for 30 min under light protection with foil. Labeled reactions in a volume of 45 µl were pipetted onto Agilent Human 1A oligonucleotide arrays. Hybridization was carried out for 18–20 h at 65°C using the MAUI Hybridization System (BioMicro Systems, Salt Lake City, UT). After hybridization was complete, arrays were washed in 2x SSC and 0.03% SDS at 65°C for 5 min, followed by additional 5-min wash steps in 1x SSC and then 0.2x SSC, each at room temperature. Detailed labeling and hybridization protocols are available for download.4
Image Acquisition and Raw Data Processing.
After drying, hybridized arrays were scanned on an Axon 4000B scanner, and spot finding and flagging were accomplished using GenePix Pro software, version 3.0.5
Alternatively, images were scanned at 10 µm resolution using Agilent scanner equipped with automatic spot finding and flagging ability in addition to reporting of Cy3 and Cy5 signal and background for each spot. Data extraction was performed using Agilent Feature Extraction Software, version 7.1. Custom tools including probe-to-chromosome mapping, ratio calculation, normalization, and visualization were used to compile the CGH profiles from these array data points. These tools are available for download.4
Segmented profiles are also generated as described before (13)
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Custom Analytical Tools.
A package of analysis tools has been designed specifically for oligo array-CGH.4
These consist of an annotation file for human and mouse arrays (which can be adapted to catalogue or custom arrays) and an analysis program. The annotation is generated for all oligo probes, including assembly alignment with BLAST-like alignment tool (BLAT) (18)
, GC-content, Tm (19)
, and minimum free energy for secondary structure with MFOLD (20)
.
To determine whether a specific sample has been successfully profiled, the program measures the percentage of acceptable (good) spots and distribution (mean, median, and SD) of the average deviation of the Log2 ratio of paired hybridizations (dye swap). To estimate noise level of the hybridization, a vector is created from the difference between Log2 ratios of consecutive probes along the physical distance of the chromosome. Noise is estimated by taking the SD of this vector scaled by 1 over the square root of 2 (so-called "derivative SD"). The rationale for this method instead of SD of raw Log2 ratio is based on the fact that derivative SD does not penalize profiles with chromosome changes spanning a large region. Another important quality assurance parameter is the consistency of the paired hybridizations, which is measured by linear correlation based on raw Log2 ratios between the pairs. Unlike expression profiles, most of the probes are expected to report no significant changes in a CGH profile, because regions containing CNAs typically comprise only a small proportion of the entire genome. Thus, probes reporting no copy number alterations (defined as absolute Log2 ratio is less than 0.2 from median filtered profiles with window size 9) are excluded from calculation of correlation. In this way, we measure the concordance of changes that are detected in a pair of dye-swap hybridizations or on multiple-day replicate hybridizations based on correlation of changed regions only.
Real-Time Quantitative PCR.
Relative gene copy numbers were determined by real-time PCR (qPCR) using SYBR Green I detection chemistry and the ABI Prism 7700 Sequence Detection System (Applied Biosystems). Amplification reactions contained 1x QuantiTect SYBR Green PCR buffer (Qiagen), 5 ng of genomic DNA template, 0.25 unit of uracil-N-glycosylase (Applied Biosystems), and 300 nM of each primer in a final volume of 25 µl. The comparative threshold cycle (CT) method was used to quantify target gene copy number in the tumor DNA sample relative to that of an endogenous control gene (Assay-Z) and a reference DNA sample (normal pooled-human male reference; Promega). For primer sequences used in this study, see Supplemental Table 1.
Calculation of Gene Dosage for Array-CGH and Real-Time PCR Data.
Real-time PCR determines gene dosage at a region of interest relative to a control assay designed to interrogate a specific unchanged region in the genome (so-called Assay-Z). This reference region is selected based on array-CGH profiles as a region without copy number alterations. We further verify the actual copy number of the Assay-Z location for each sample by SKY (Supplemental Table 2). The Assay-Z used in this study for human cell lines is located on ATP2B4 gene (1q32, locus 200.77200.89 Mb on UCSC hg 16 map). The gene dosage for real-time PCR is thus calculated by multiplying relative gene copy number by Assay-Z base copy. It is typical for any array-CGH platform to quantitatively underestimate copy number change in Log2 ratio (12)
. To compare estimates of gene dosage between CGH and PCR directly, we built a linear regression model based on Log2 ratio of real-time PCR to adjust segmented Log2 ratio (Supplemental Fig. 1). Given an R2 of 0.9527, the model showed that these two types of measurements are highly correlated and demonstrate the same trend in gene dosage change. We used this model to calculate an estimated array-CGH Log2 ratio, and the array-CGH gene dosage is finally obtained as (Assay-Z base copy)*2(estimated log2 ratio).
SKY.
SKY was performed according to manufacturer’s protocol (Applied Spectral Imaging, Carlsbad, CA).
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RESULTS |
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, these criteria selected 13,502 and 15,729 informative gene-specific probes for the human and mouse arrays, respectively. All subsequent analyses make sole use of these selected informative probes, which together translate into a median resolution of 69.2 kb for human and 48.6 kb for mouse genomes (Table 1)
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, the CGH profile clearly detected a single-copy increase in X chromosome in the female compared with the male reference. Similarly, loss of Y is readily evident, even in the face of sparse probe density along the Y chromosome.
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Verification of CNAs Detected by Oligo Array-CGH.
To further validate our CGH data sets and the robustness of our assay conditions and analytical tools, we used two independent and highly reliable methods to ascertain gene dosage alterations in complex cancer genomes: SKY analysis and qPCR for human cell lines (Supplemental table 3). For SKY studies, we used both published SKY data (e.g., ASPC1; Ref. 21
) as well as newly generated SKY profiles (e.g., DanG, HUP-T4, HPAC, PANC1, and TU8902). SKY ideograms were created for visualization using the National Center for Biotechnology Information Automatic Karyotype to SKYGRAM Converter tool7
and compared with pseudo-karyotype representations of the segmented array-CGH profiles obtained in this study. Fig. 2
illustrates two representative comparisons of the array-CGH and SKY data sets. Noteworthy in the SKY analysis of HPAC is the detection of a one-copy gain of part of chromosome 10q (Fig. 2A
, green chromosome), which is translocated to chromosome 12, and the presence of four copies of chromosome 12p (Fig. 2A
, magenta chromosome). These SKY features mirror those obtained in the segmented array-CGH profile of HPAC cells. Another example is cell line PANC1, which readily shows three copies of 8q (Fig. 2B
, orange chromosome) by SKY and array-CGH assays, underscoring that large regional alterations revealed by SKY are readily detected by array-CGH method used here.
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, the qPCR results were completely concordant with the array-CGH data. For example, real-time qPCR quantitation confirmed the presence of a Chr7 amplicon detected by array-CGH profile of ASPC1 tumor cell line (Fig. 3A)
. Of particular significance, real-time qPCR also confirmed the capacity of oligo array-CGH to detect homozygous deletion of CDKN2A in the 9p region of ASPC1 (Fig. 3B)
. Moreover, the fine structural complexity of this CNA as revealed by the array-CGH profile is mirrored by the real-time qPCR data points. Specifically, three consecutive features within a 20 Mb genomic distance are observed: a two-copy deletion of CDKN2A region at 21 Mb from 9p tip; followed by a focal gain spanning only 1 Mb verified by NGX6 at 35.8 Mb; and single-copy loss from 36.7 Mb. Together, these data provide strong evidence that the oligo array-CGH approach described here provides accurate and reliable representation of complex regional copy number changes in cancer genomes.
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100 kb, whereas the oligo platform is 50 kb (Table 1)
. As shown in Fig. 4
, the oligo array-CGH profile of MK1 (Fig. 4A
, blue) revealed 4 distinct focal amplicons on chromosome 10 measuring 1.4, 0.13, 0.8, and 0.7 Mb, respectively. All four amplifications were confirmed by real-time qPCR (Fig. 4C)
. In contrast, the cDNA-based profile (Fig. 4A
, orange) of the same sample captured only two of the four amplicons (amplicons C and D). In the case of amplicon B, the region in question is interrogated by a single probe on the oligo microarray, located physically at 102.99 Mb on chromosome 10 and flanked by a left neighbor 30 kb away (102.96 Mb) and a right neighbor 100 kb away (103.09 Mb). Within this 130-kb region, there was no probe represented on the cDNA microarray, providing a basis for the lack of detection of this high-amplitude event on that platform (Fig. 4B)
. An observation such as this should provide impetus for the design of higher density oligo microarrays for full-genome interrogation.
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DISCUSSION |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Although previous proof-of-principal studies established the utility of oligonucleotide microarrays in copy number analyses (14, 15, 16) , an important finding of this study is that a PCR enrichment step is not necessary to reduce the genome complexity before hybridization to the microarray. Direct genome labeling and hybridization should serve to eliminate prevailing concerns of PCR amplification bias that may not capture highly focal CNAs or provide fine structural complexity within a given CNA to facilitate mechanistic studies of amplification or deletion. There exists a need to determine the extent to which PCR-based procedure may influence copy number profiles, because amplification may be needed in cases in which clinical materials are limiting. The approach described in this study now makes this possible.
Although current available BAC-based array-CGH platforms typically provide genome-wide coverage at 1-Mb resolution, a recent report has described the construction of tiling BAC microarrays possessing 32,433 BACs spotted in triplicate on two separate glass slides (22)
. These BAC microarrays offer an approximate resolution of 80 kb across the human genome, comparable with the resolution provided by the commercially available expression oligo arrays used in this study. Furthermore, it is reassuring that the array-CGH performance characteristics of the reported tiling BAC arrays and the oligo arrays are comparable with respect to magnitude of signal in changed regions and noise in unchanged regions (22
; this study). On the practical level, it is worth noting that the resolution of oligo array-CGH is not limited by the currently available oligo-arrays designed for expression profiling, rather by availability of genome sequences of any species. Furthermore, such genomic arrays can provide not only complete gene-specific representation with oligos targeted to gene-coding regions, but also representation of unique intragenic sequences, with oligos targeted to noncoding DNAs that may represent important and critical regulatory regions including cis-regulatory elements and microRNAs or mammalian interspersed repeats (MIR) sequences.
In summary, the experimental merits of oligonucleotide-based microarrays include (a) flexibility to design genome-wide or locus-specific custom microarrays with probes targeting coding and noncoding regulatory regions; (b) capacity to provide full genome coverage of known and predicted genes present on the latest draft of genome sequences for virtually any species; and (c) ease of quality control with respect to probe annotation. Availability of a commercial source obviates the need for in-house microarray printing infrastructure and provides increased access across the research community. Finally, the superior performance of this higher-resolution platform is clearly documented over antecedent cDNA platforms. These data raise the possibility that cancer genomes may harbor many focal CNAs that have eluded detection and justify continued efforts to build high-density genomic arrays that permit detailed interrogation of the entire genome.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Note: Supplementary data for this article can be found at Cancer Research Online (http://cancerres.aacrjournals.org).
Requests for reprints: Lynda Chin, Department of Medical Oncology, Dana Farber Cancer Institute, Boston, MA 02115; E-mail: Lynda_Chin{at}dfci.harvard.edu
3 C. Brennan and L. Chin, unpublished observations. 
4 Internet address: http://genomic.dfci.harvard.edu.
5 Internet address: http://www.axon.com/gn_GenePixSoftware.html.
6 Internet address: http://genome.ucsc.edu/.
7 Internet address: http://www.ncbi.nlm.nih.gov/sky/.
Received 4/ 7/04. Revised 5/12/04. Accepted 5/21/04.
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