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Clinical Chemistry 50: 1322-1327, 2004. First published June 3, 2004; 10.1373/clinchem.2004.032060
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(Clinical Chemistry. 2004;50:1322-1327.)
© 2004 American Association for Clinical Chemistry, Inc.

Molecular Diagnostics and Genetics

Three-Dimensional Microarray Compared with PCR–Single-Strand Conformation Polymorphism Analysis/DNA Sequencing for Mutation Analysis of K-ras Codons 12 and 13

Masato Maekawa1,a, Tomonori Nagaoka1,3, Terumi Taniguchi1, Hitomi Higashi1, Haruhiko Sugimura2, Kokichi Sugano4, Hiroyuki Yonekawa5, Takatomo Satoh3, Toshinobu Horii1, Naohito Shirai1, Akihiro Takeshita1 and Takashi Kanno1

1 Department of Laboratory Medicine and 2 1st Department of Pathology, Hamamatsu University School of Medicine, Hamamatsu, Japan. 3 Genome Medical Business Division, OLYMPUS Corporation, Hachioji, Japan., 4 Oncogene Research Unit/Cancer Prevention Unit, Tochigi Cancer Center Research Institute, Utsunomiya, Japan. 5 Scientific Equipment Group, OLYMPUS America, Inc., New York, NY.

aAddress correspondence to this author at: Department of Laboratory Medicine, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan. Fax 81-53-435-2794; e-mail mmaekawa{at}hama-med.ac.jp.


   Abstract
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 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Background: We developed a rapid, precise, and accurate microarray-based method that uses a three-dimensional platform for detection of mutations.

Methods: We used the PamChip® microarray to detect mutations in codons 12 and 13 of K-ras in 15 cell lines and 81 gastric or colorectal cancer tissues. Fluorescein isothiocyanate-labeled PCR products were analyzed with the microarray. We confirmed the microarray results with PCR–single-strand conformation polymorphism (SSCP) analysis and DNA sequencing.

Results: We could correctly identify wild-type, heterozygous, and homozygous mutant genotypes with the PamChip microarray in <3.5 h. The array data were consistent with those of PCR-SSCP analysis and DNA sequencing. All 15 cell lines and 80 of 81 clinical cancer specimens (98.8%; 95% confidence interval, 96.4–100%) were genotyped accurately with the microarray, a rate better than that of direct DNA sequencing (38.9%) or SSCP (93.8%). Only one clinical specimen was misdiagnosed as homozygous for the wild-type allele. Densitometric analysis of SSCP bands indicated that the content of the mutant allele in the specimen was ~16%. The PamChip microarray could detect mutant alleles representing more than 25% of the SSCP band proportions. Therefore, the limit for detection of mutant alleles by the PamChip microarray was estimated to be 16–25% of the total DNA.

Conclusions: The PamChip microarray is a novel three-dimensional microarray system and can be used to analyze K-ras mutations quickly and accurately. The mutation detection rate was nearly 100% and was similar to that of PCR-SSCP together with sequencing analysis, but the microarray analysis was faster and easier.


   Introduction
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 Introduction
Materials and Methods
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Microarray technologies were initially developed to study differential gene expression in complex populations of RNA in tissues. Microarrays used for such purposes have a high density of spots (1)(2). Detection of single-nucleotide polymorphisms (SNPs) by microarrays is a versatile methodology that is suitable for high-throughput diagnostic procedures (3)(4). SNP detection and genotyping have also been done by PCR–single-strand conformation polymorphism (PCR-SSCP) analysis, degenerate HPLC, PCR–restriction fragment length polymorphism analysis, DNA sequencing, TaqMan PCR, and the Invader assay (5). DNA microarrays have also been used for genotyping applications, including SNP typing, detection of genomic and somatic mutations, identification of microbes, and detection of allelic imbalances (6)(7)(8)(9)(10)(11). Commercially available microarrays have features beyond simple passive hybridization, including microfabricated fluidic channels, electronic hybridization, novel posthybridization signaling steps, and flow-through dynamics (12)(13).

Recently, PamGene International B.V. developed a novel three-dimensional flow-through platform that uses a porous aluminum oxide substrate as a solid support (14). Because the substrate has long branched capillaries, the reactive surface of this material is several-hundred-fold greater than that of a two-dimensional surface. Therefore, the flow-through microarray reduces hybridization times and increases signal and signal-to-noise ratios. This unique platform technology has been used by PamGene International B.V. and OLYMPUS Corporation to develop the PamChip® microarray and FD10 microarray system. The PamChip microarray has a disposable housing optimized for flow-through hybridization of samples. The hybridization is performed by repeated pumping of the sample solution up and down through the substrate. FD10 is an integrated PamChip microarray system that has solution-driven incubation and image acquisition functions with the ability to analyze and process four arrays simultaneously as well as optimized software for analysis. This system has already been used for gene expression profiling (15).

K-ras is an oncogene in which various point mutations are frequently detected in cancers of the digestive organs. The mutations are clustered in a very narrow region, codons 12 and 13 (16). The mutation sites in codon 12 are considered a mutational hot spot in carcinogenesis, which makes K-ras a promising candidate for mutation screening with microarray technologies.

Here we describe a rapid, precise, and accurate microarray system that uses the three-dimensional platform technology for mutation detection. Retrospective and/or comparative analyses were performed for mutations in codons 12 and 13 of K-ras.


   Materials and Methods
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 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
samples and dna isolation
Cancer cell lines were obtained from the Japanese Cell Resource Bank (COLO320, MKN1, MKN7, MKN28, MKN45, MKN74, KATOIII, A431, and LU65) and from the American Type Culture Collection (SW1116). The NEDATE cell line was established at the National Cancer Center Hospital. The C-1 and PSN1 cell lines were kindly supplied by the Pathology Division of the National Cancer Center Research Institute. Lymphoblastoid cell lines (TK6 and WTK-1) were obtained from the National Institute of Health Science. Genomic DNA was extracted from 15 cell lines as described previously (17)(18).

DNA samples extracted from gastric or colorectal cancer tissues and corresponding healthy mucosae were selected from DNA stocks at Hamamatsu University School of Medicine, National Cancer Center Hospital, and Tochigi Cancer Center Hospital by K-ras mutation typing based on previously performed PCR-SSCP analysis. The experimental design was approved by the Committee for Genetic Analysis at Hamamatsu University School of Medicine.

pcr-sscp analysis and direct sequencing
The PCR primers used have been described previously (19). These primers amplify a 108-bp fragment containing codons 12 and 13. PCR was performed with ExTaq (TaKaRa), and the amplified products were sequenced directly or subjected to SSCP analysis on 10% nondenaturing polyacrylamide gels (Daiichi Pure Chemicals) (20). Occasionally, extra bands (possibly mutated) detected by SSCP were excised from gels, reamplified, and sequenced. PCR products showing mobility shifts were then sequenced directly with the BigDye Terminator Cycle Sequencing FS Ready Reaction Kit and ABI PRISM 310 Genetic Analyzer (Applied Biosystems).

microarray analysis
Oligonucleotide probes (17mers) were designed to detect K-ras mutations (see Table 1 in the Data Supplement that accompanies the online version of this article at http://www.clinchem.org/content/vol50/issue8/) and spotted on PamChip microarrays. The layout of the PamChip microarrays is shown in Fig. 1 . Wild-type probes for codons 12 and 13 (GGTGGC; shaded circles in Fig. 1 ) and eight mutations (CGTGGC, TGTGGC, AGTGGC, GCTGGC, GATGGC, GTTGGC, GGTGAC, and GGTTGC, where the underlined bases are the sites of the mutations; open and hatched circles in Fig. 1 ) were used for hybridization.



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  		Figure 1. PamChip microarray layout.

Wild-type (shaded circles) and/or mutant (open and hatched circles) probes were used for hybridization. Numbers correspond to those in Table 1 of the online Data Supplement (available at http://www.clinchem.org/content/vol50/issue8/).

A mixture of 5'-fluorescein isothiocyanate-labeled oligonucleotides complementary to the wild-type (GGTGGC) and mutant (GATGGC, CGTGGC, and AGTGGC) sequences were used as hybridization probes in a standard dilution mixture series. The ratios of wild type to mutant (in µmol/L) in the mixtures were 0:10, 2:8, 4:6, 6:4, 8:2, and 10:0. In addition, mixtures of genomic DNA prepared from cell lines were amplified and then subjected to the microarray analysis.

Before hybridization, the test site of each array was washed with 1 mL/L Tween 20 for one pumping cycle. Amplification products (108 bp) were generated with 5'-fluorescein isothiocyanate-labeled primers, denatured for 3 min at 94 °C, and cooled to 4 °C on ice. The target DNA, which was 10 µL of either denatured PCR product or oligonucleotide mixture, was mixed with 40 µL of 1.25x standard saline phosphate–EDTA in the well of a PamChip microarray preheated to 55 °C, and the hybridization was started immediately in the FD10 system. In this flow-through hybridization analysis, the liquid flow rate was 10 µL/s. After 30 cycles (~10 min) of flow-through hybridization at 55 °C, each array was washed once with 1x standard saline phosphate–EDTA with pumping. Array images were captured automatically on the FD10 system and then analyzed with the integrated image acquisition and analysis software.


   Results
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 Abstract
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 Materials and Methods
 Results
Discussion
 References
 
To examine assay reproducibility and accuracy, we used three PamChip microarrays, each of which contained four test channels. Mixtures of oligonucleotides complementary to wild-type and mutant-type probes were hybridized to the PamChip microarray in duplicate. Signal intensities were not always consistent with the theoretical mixture ratio, however, because there were dose–response effects in each mixture. Representative results obtained with the different ratios of the mixture of GGTGGC (wild type) and GATGGC (mutant) are shown in Fig. 2A . In addition, we used mixtures of genomic DNA prepared from cell lines in the different ratios. Representative results obtained with the mixture of MKN45 (wild-type; GGTGGC) and Lu65 (mutant; TGTGGC) are shown in Fig. 2B .



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  		Figure 2. Fluorescence intensities obtained with complementary oligonucleotides (A) and genomic DNA (B).

(A), relationship between hybridization signal intensity and oligonucleotide population ratio. The fluorescence intensities of hybridization signals were examined with use of the complementary oligonucleotides GGTGGC and GATGGC. The relative fluorescence intensities in mixtures consisting of GGTGGC ({square}) and GATGGC ({circ}) were calculated by the following formulas: GGTGGC (%) = GGTGGC signal intensity/(GGTGGC signal intensity + GATGGC signal intensity) x 100; and GATGGC (%) = GATGGC signal intensity/(GGTGGC signal intensity + GATGGC signal intensity) x 100. (B), representative results obtained with the mixture of genomic DNA prepared from two cell lines, MKN45 (wild-type; GGTGGC) and Lu65 (mutant; TGTGGC). The fluorescence intensities were calculated as described above. {square}, wild-type intensities; {circ} mutant intensities. Each symbol represents the mean of four independent microarray results (error bars, SD).

We tested both sense and antisense strands as hybridization probes. In general, the sense strand identified genotypes more accurately. Results of the PamChip microarray analysis of a homozygous wild-type specimen (GGTGGC) with sense and antisense oligonucleotides as hybridization probes are shown in Fig. 3 . A single strong signal for GGTGGC was observed when the sense strand was used as a probe, whereas weak, noisy signals were observed with the antisense probes. We therefore used the sense strand probe in further analyses.



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  		Figure 3. Comparison of sense and antisense strands as hybridization probes.

Hybridization images in the top and bottom rows in the array (top) represent the results obtained with the sense and antisense strands, respectively, used as hybridization probes. The subsequent data analyses (middle and bottom) show the comparison quantitatively.

Wild-type, heterozygous, and homozygous mutant genotypes were detected accurately and reliably in 15 cell lines with the PamChip microarray in a relatively short time. All results correlated with those of PCR-SSCP analysis and DNA sequencing. DNAs from clinical specimens were also analyzed with the PamChip microarray for comparison with PCR-SSCP analysis and/or DNA sequencing. Fig. 4 shows examples of images captured on the FD10 system and results of subsequent data analyses. Essentially, the results obtained with the PamChip microarray were consistent with those of PCR-SSCP analysis and DNA sequencing. Eighty-one clinical cancer specimens were analyzed with the PamChip microarrays, and the genotypes of 80 of these specimens (98.8%) were identified accurately. PCR-SSCP analysis detected all 64 samples homozygous or heterozygous for mutant genotypes in codon 12. The remaining 17 (of 81) specimens were homozygous or heterozygous for mutant alleles in codon 13, but they could not be identified by SSCP analysis because mutant alleles in codon 13 were not used as a reference for SSCP. Although SSCP bands in 12 of the 17 samples were clearly different from those of the wild-type alleles, the remaining 5 samples were misclassified into the mutant genotype, GATGGC, because of the similar electrophoretic pattern. Therefore, the distinct misidentification was 5, and genotyping succeeded in 76 of 81 samples (93.8%). Thirty-six samples (10 homozygous and 26 heterozygous mutant genotypes) were analyzed by direct DNA sequencing. The 10 samples homozygous for mutant genotypes were identified properly. Twenty-two of the 26 heterozygous mutant samples were misclassified into homozygous wild type, and only the remaining 4 samples were correctly identified. In total, 14 of 36 samples (38.9%) were diagnosed accurately.



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  		Figure 4. Representative hybridization images and data.

The representative images and data for heterozygous mutants samples 19 (A), 27 (B), and 7 (C) are shown. The sample numbers are referred to in Table 2 of the online Data Supplement (available at http://www.clinchem.org/content/vol50/issue8/).

Only one sample, a clinical specimen from a patient with colorectal cancer, was classified incorrectly by the PamChip microarray. PamChip analysis yielded a homozygous wild-type genotype, whereas SSCP analysis and DNA sequencing indicated that the genotype was GGTGGC/GATGGC. The semiquantitative proportions obtained by densitometric analysis of SSCP bands were then compared with PamChip microarray and direct DNA sequencing data. The results for clinical specimens are shown in Table 2 of the online Data Supplement. The samples were heterozygous for wild-type and mutant alleles in various proportions. In the single misdiagnosed clinical specimen, the content of the mutant allele was estimated to be ~16% by SSCP analysis. The PamChip microarray could detect mutant alleles proportions >25% by SSCP analysis. The limit for detection of mutant alleles by the PamChip microarray was therefore estimated to be 16–25% of the total DNA. The detection limit of direct sequencing was estimated to be 46–50%.


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
In this study, we analyzed several mixtures containing two oligonucleotides (wild-type plus mutant) with the PamChip microarray. We also analyzed mixtures of genomic DNA (wild-type and mutant) prepared from two cell lines with the PamChip microarray. The fluorescence intensities of each sequence showed dose-dependent relationships and were somewhat consistent with the theoretical proportions in the mixtures of genomic DNA as well as oligonucleotides. Such results for microarray analysis have not been described previously. The accuracy of the fluorescence intensity and the degree of fluorescence were satisfactory and are suitable for microarray analysis.

Clinical DNA samples were analyzed with the PamChip microarray for comparison with PCR-SSCP analysis and/or DNA sequencing data. When somatic mutations in cancer tissues are assessed, it is not possible to avoid contamination by the wild-type allele derived from noncancer cells. We therefore investigated the limit at which each technique could detect the mutant allele. The ability to detect small amounts of mutant DNA within a large amount of wild-type DNA is absolutely necessary for analyzing clinical DNA samples. The combination of PCR-SSCP analysis and DNA sequencing provided the greatest sensitivity. Direct sequencing of PCR products occasionally misdiagnosed samples containing low amounts of the mutant allele (46–50%), and PCR-SSCP analysis could not distinguish genotypes with similar electrophoretic patterns. The PamChip microarray detected DNA mutations when the mutation comprised at least 25% of the tested population of DNA; thus, we believe that samples from patients heterozygous for a particular mutation, i.e., cancer specimens contaminated with noncancerous tissue, would be detectable with this array system. Mutations in mitochondrial DNAs that cause disease typically occur as mixtures of mutant and wild-type mitochondrial DNAs (heteroplasmy), and disease severity is correlated with the proportion of mutant DNA (21). Genotyping of mitochondrial DNA mutations in such diseases can also be performed with this array system.

The entire PamChip process was completed in ~3.25 h, including 1 h for DNA preparation, 2 h for PCR, and 15 min for microarray (hybridization, washing, and signal detection). The PamChip microarray thus substantially reduces the time necessary for microarray analysis. However, at present the PamChip microarray requires PCR amplification of the targeted region, which adds 2–3 h to the total analysis time. To reduce the time for DNA amplification, shuttle PCR or another amplification method may be useful. Multiplex PCR can be used to amplify multiple SNPs simultaneously. A novel microarray analysis that does not require DNA amplification or preparation would be superior for mutation and/or SNP analysis. Such a technique could be easily applied to the selection of medications best suited for each individual and to molecular diagnosis during surgery.

K-ras mutations are typically localized in codons 12, 13, and 61, and ~60% of somatic mutations in cancers occur in codon 12. Amino acid substitutions may affect the physiologic function of a protein and the clinical prognosis. A close association has been reported between a somatic mutation, GAT (Asp), in codon 12 and distant hematogenous metastasis (22). Two specific mutations, TGT (Cys) in codon 12 and GAC (Asp) in codon 13, have been associated with a significantly increased risk of cancer recurrence (23). Etiologic data revealed that GTT (Val) in codon 12 is associated with cancer progression and more aggressive biological behavior (24)(25). Consequently, genotyping of colorectal adenocarcinomas for K-ras status is feasible for use in diagnostic pathology to provide information that could be used to individualize and optimize treatments and prognoses.

In conclusion, the unique features of the PamChip microarray technology, including real-time imaging and temperature control combined with short assay time, make it suitable for clinical screening of mutations. This microarray is potentially useful for limited and targeted purposes, and detection of K-ras mutations is one example of such focused use of this microarray.


   Acknowledgments
 
This research was supported in part by a Grant-in-Aid for Labour Sciences Research (H15-Cancer Prevention-9) for research on cancer prevention and health services; by a Grant-in-Aid from the Second Term Comprehensive 10-Year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare, Japan; by a Grant-in-Aid for Scientific Research (B), for COE (Hamamatsu University School of Medicine); by a Grant-in-Aid from the Ministry of Education, Science, Sports, Culture and Technology, Japan; and by the Smoking Research Foundation.


   References
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 Introduction
 Materials and Methods
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 References
 

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