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leukocyte cystine concentration to be achieved under therapy is conjectural because it is not known whether cystine accumulation in blood cells is representative of the storage in other tissues. Generally, it is recommended to strive for a ML cystine concentration ⬍0.5 nmol/mg of protein (1 ). This is also the upper limit of cystine seen in heterozygotes, who do not develop nephropathy (4 ). Because we observed a clear difference between cystine content in ML preparations and PMN cells, we suggest that each laboratory produces its own reference values based on the upper cystine values found in heterozygotes. In 1970, Schulman et al. (2 ) showed that cystine accumulation in cystinotic leukocytes is located primarily in phagocytic blood cells rather than in lymphocytes. Cystine measurement in purified PMN preparations improved the sensitivity of the method. Our results were comparable to those of Smolin et al. (5 ), who used a cystine-binding assay for cystine determination. They also found lower cystine in MLs compared with PMNs in heterozygotes, in one untreated patient, and in patients undergoing cysteamine therapy. In our laboratory, the mean intracellular cystine content of healthy controls did not differ between MLs and PMNs, possibly because the low cystine concentrations in healthy persons are close to the detection limit of the HPLC method. To our knowledge, no missed diagnosis of cystinosis as a result of low cystine concentrations in ML preparations has been reported previously. In our laboratory, the diagnosis of cystinosis could have been missed in two patients if cystine had been measured only in MLs. In one patient, treatment with cysteamine was delayed for 6 months because the cystine concentration in the MLs remained within the reference interval. Later the diagnosis of cystinosis in both patients was confirmed by clearly increased cystine in fibroblasts and mutational analysis of the CTNS gene. The possible reasons for falsely low cystine in MLs, especially in young children, could be the overrepresentation of lymphocytes in ML preparations, typical for the first year of life. Furthermore, variations in the differential count of MLs in individual patients can lead to unreliable variations in measured cystine because it is expressed per milligram of protein in the total cell preparation. As described by Kamoun et al. (6 ), for storage experiments, we also used ACD tubes for blood collection. In our laboratory, the storage of blood at room temperature for 24 h led to increases in intracellular cystine content. Thus, the shipping of whole-blood samples for cystine determinations is not advisable. In summary, we recommend measurement of cystine in PMNs and not in ML preparations because the recommended approach increases the sensitivity of cystine detection for the diagnosis of cystinosis and provides a better target concentration during the monitoring of cysteamine treatment.
We acknowledge the Dutch Kidney Foundation for financial support (Grant PC106).
References 1. Gahl W, Thoene JG, Schneider J. Cystinosis: a disorder of lysosomal membrane transport. In: Scriver CR, Beaudet AL, Sly WS, Valle D, eds. The metabolic and molecular bases of inherited disease, 8th ed. New York: McGraw-Hill, 2001:5085–108. 2. Schulman JD, Wong VG, Kuwabara KH, Bradley KH, Seegmiller JE. Intracellular cystine content of leukocyte populations in cystinosis. Arch Intern Med 1970;125:660 – 4. 3. de Graaf-Hess A, Trijbels F, Blom H. New method for determining cystine in leukocytes and fibroblasts. Clin Chem 1999;45:2224 – 8. 4. Middleton R, Bradbury M, Webb N, O’Donoghue D, Van’t Hoff W. Cystinosis. A clinicopathological conference. From toddlers to twenties and beyond. Adult-Paediatric Nephrology Interface Meeting, Manchester 2001. Nephrol Dial Transplant 2003;18:2492–5. 5. Smolin LA, Clark KF, Schneider JA. An improved method for heterozygote detection of cystinosis, using polymorphonuclear leukocytes. Am J Hum Genet 1987;41:266 –75. 6. Kamoun P, Vianey-Saban C, Aupetit J, Boyer S, Chadefaux-Vekemans B. Measurement of cystine in granulocytes and leukocytes: methodological aspects In: Broyer M, ed. Cystinosis. Amsterdam: Elsevier, 1999:86 –92. DOI: 10.1373/clinchem.2004.031872
Oligonucleotide Microarray-Based Mutation Detection of the K-ras Gene in Colorectal Cancers with Use of Competitive DNA Hybridization, Jae-Hyun Park,1† Il-Jin Kim,1† Hio Chung Kang,1 Yong Shin,1 Hye-Won Park,1 SangGeun Jang,1 Ja-Lok Ku,1 Seok-Byung Lim,2 Seung-Yong Jeong,3 and Jae-Gahb Park1,2,3* (1 Korean Hereditary Tumor Registry, Laboratory of Cell Biology, Cancer Research Institute and Cancer Research Center, Seoul National University, Seoul, Korea; 2 Department of Surgery, Seoul National University College of Medicine, Seoul, Korea; 3 Research Institute and Hospital, National Cancer Center, Goyang, Gyeonggi, Korea; † these authors contributed equally to this work; * address correspondence to this author at: National Cancer Center, 809 Madu-dong, Ilsangu, Goyang, Gyeonggi, 411-764, Korea; fax 82-31-9201511, e-mail
[email protected]) In cancer research, gene expression and mutations are increasingly investigated by use of oligonucleotide microarrays, which use immobilized oligonucleotides and sequence-specific DNA probe hybridization to investigate differences between nondiseased and cancer tissues (1 ). In our previous works, we used oligonucleotide microarray-based mutation analysis to detect germline or somatic mutations (2, 3 ). Activating mutations of the K-ras gene occur in ⬃20 – 50% of colorectal cancers, with ⬃85% of the mutations restricted to codons 12 and 13 (4 ). K-ras gene mutations have been widely studied as markers for cancer prognosis, and population-based studies have suggested that mutated K-ras might be associated with some tumor phenotypes (4 – 6 ). Studies of associations between K-ras mutations and specific clinical features generally require the analysis of large numbers of samples (5 ). Thus, researchers need a high-throughput technique for assessing K-ras mutations. Oligonucleotide microarrays may provide a valid option because they allow scientists to accurately and rapidly process large numbers of samples.
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Because the K-ras gene is known to have two mutational hot spots (codons 12 and 13), it has been used as a target gene for testing newly developed techniques for mutation detection, including various applications of the DNA chip (7, 8 ). Here we describe a new method for K-ras oligonucleotide microarray analysis called competitive DNA hybridization (CDH). CDH is a novel, efficient, high-capacity hybridization technique in which various fluorescently labeled samples are mixed to compete with each other in a hybridization reaction. A total of 204 Korean patients with colorectal cancer from Seoul National University Hospital and the National Cancer Center of Korea were screened for somatic K-ras mutations in this study. Written informed consent was obtained from all patients; the cancers included 103 cancers originating from the proximal colon and 101 from the distal colorectum. Genomic DNA was extracted from frozen tumor tissues by use of the TRI reagent (Molecular Research Center) as described previously (3 ). PCR primers spanning codons 12 and 13, designed to amplify a 116-bp region, were as follows: forward, 5⬘-GGCCTGCTGAAAATGACTGAATAT-3⬘; reverse, 5⬘-TGTTGGATCATATTCGTCCACAAAATG-3⬘. PCR reactions (25 L) containing 50 M each of dATP, dTTP, and dGTP (MBI Fermentas) and 10 M each of Cy5-dCTP (Amersham Biosciences) and dCTP were subjected to 35 cycles of amplification (94 °C for 30 s, 56 °C for 30 s, and 72 °C for 1 min, with a final elongation of 7 min at 72 °C) as reported previously (2, 3 ). To evaluate the CDH method, we initially tested addition of six different fluorescently labeled deoxynucleotide triphosphates (dNTPs); from these we selected two additional fluorescently labeled dNTPs: Cy3-dCTP (Amersham Biosciences) and AlexaTM 594-dUTP (Molecular Probes). In the CDH PCR reactions, DNA from each tumor tissue was amplified with one of the fluorescently labeled dNTPs, which were subsequently incorporated into the amplified DNA. Amplified PCR products were purified with the QIAquick PCR Purification Kit (Qiagen) and were subsequently digested with 0.05 U of DNase I (Takara) at 25 °C for 3 min to produce fragments. We then mixed these products together for microarray hybridization. The K-ras oligonucleotide microarray, containing 21bp-long oligonucleotides harboring all possible K-ras mismatch sequences (Table 1), was manufactured as described previously (1 ). Briefly, the synthesized oligonucleotides were spotted with a microarrayer (Cartesian Microsys 5100; Cartesian Technologies); 20 oligonucleotides were arrayed in quadruplicate, including 2 wildtype sequences and 18 containing missense mutations in codons 12 and 13 (total of 80 spots per set). Three complete oligonucleotide sets were spotted separately on each slide, allowing us to hybridize three different samples on each microarray. The PCR-amplified patient samples (above) were dissolved in 5 L of hybridization buffer (HybIt; TeleChem) and hybridized with the K-ras oligonucleotide microarray at 56 °C for 2.5 h in a general hybridization chamber (FINEPCR). The microarray was then rinsed with a buffer solution containing 2 g/L
Table 1. Sequences of the oligonucleotides spotted on the K-ras oligonucleotide microarray. Spot no.
Codon
Namea
Sequence,b 5ⴕ to 3ⴕ
1 2 3 4 5 6 7 8 9 10
12 12 12 12 12 12 12 12 12 12
12W 12M1 12M2 12M3 12M4 12M5 12M6 12M7 12M8 12M9
GTTGGAGCTGGTGGCGTAGGC AGTTGGAGCTTGTGGCGTAGG AGTTGGAGCTAGTGGCGTAGG AGTTGGAGCTCGTGGCGTAGG GTTGGAGCTGATGGCGTAGGC GTTGGAGCTGCTGGCGTAGGC GTTGGAGCTGTTGGCGTAGGC TTGGAGCTGGAGGCGTAGGCA TTGGAGCTGGGGGCGTAGGCA TTGGAGCTGGCGGCGTAGGCA
11 12 13 14 15 16 17 18 19 20
13 13 13 13 13 13 13 13 13 13
13W 13M1 13M2 13M3 13M4 13M5 13M6 13M7 13M8 13M9
GGAGCTGGTGGCGTAGGCAAG TGGAGCTGGTCGCGTAGGCAA TGGAGCTGGTAGCGTAGGCAA TGGAGCTGGTTGCGTAGGCAA GGAGCTGGTGCCGTAGGCAAG GGAGCTGGTGACGTAGGCAAG GGAGCTGGTGTCGTAGGCAAG GAGCTGGTGGTGTAGGCAAGA GAGCTGGTGGAGTAGGCAAGA GAGCTGGTGGGGTAGGCAAGA
a
W, wild-type; M, mutant. The underlined bases indicate the location in the wild-type sequence that has been changed in the mutated sequences. b
sodium dodecyl sulfate in 0.5⫻ standard saline citrate, after which it was scanned with a microarray laser scanner (ScanArray5000; Packard Instruments) set to monitor the wavelengths 632.8, 543.8, and 594 nm, which correspond to Cy5, Cy3, and Alexa 594, respectively (9 ). The intensity of each spot, representing the amount of hybridized tumor DNA, was calculated by the Scanarray and Quantarray (Packard Instrument) image analysis software packages. This procedure allowed the amplified DNA fragments from each patient to compete with each other in a hybridization reaction taking place within the limited space of a spotted oligonucleotide. The overall steps for the mutation detection criteria are as follows (1–3 ): (a) calculate the mean value for the wild-type spots to normalize the wild-type signals; (b) calculate each normalization factor from each wild-type signal; (c) multiply the normalization factors of all oligonucleotides at the same codons or of the same groups; (d) calculate the mean (A) and SD; (e) set a proper cutoff value after considering statistical significance (99% confidence interval); and (f) regard any signal above the cutoff as indicative of a mutation. For confirmation of the microarray results, we amplified all 204 samples with a conventional dNTP mixture and sequenced them bidirectionally as reported previously (10, 11 ). K-ras mutations were identified in 50 of the 204 colorectal cancer samples (24.5%) screened by oligonucleotide microarray. Of these, 28 were from proximal colon cancers (28 of 103; 27.2%), and 22 were from distal colorectal cancers (22 of 101; 21.8%). We detected a total of four
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Fig. 1. Scanned images and signal intensities from the K-ras oligonucleotide microarray. In sample D231 (A and B), Cy5-labeled dCTP was used to detect a missense mutation in codon 13 (GGC3 GAC). In sample D281 (C and D), Cy3-labeled dCTP detected a mutation in codon 12 (GGT3 GAT). The mutations are indicated by arrows; the plotted signal intensities of the spotted oligonucleotides were normalized in relation to the wild-type signal. Some nonspecific binding was also detected (ⴱ). Comparison of the CDH results (B and D) with the control (A and C) revealed that in the CDH experiments, the nonspecific signals were decreased and the ratio of mutated to wild-type (R) signal was increased (D231, from 0.9 to 1.66; D281, from 0.28 to 0.56).
missense mutation types causing amino acid changes in codons 12 or 13. The most common mutation was GGC (Gly)3 GAC (Asp) in codon 13 (21 of 50 samples). We also identified mutations changing GGT (Gly) to GAT (Asp; 16 of 50), GTT (Val; 8 of 50), and TGT (Cys; 5 of 50). The mutations identified by CDH were 100% concordant with our direct sequencing data, with no false positives or false negatives. To investigate possible associations between the mutation profile and phenotype, we performed statistical analyses using the 2 or Fisher exact tests with SPSS software (␣ ⫽ 0.05 was set as the significance level). In agreement with previous reports (4, 6 ), we found that the GGT3 GAT mutation was more prevalent in proximal colon cancer (13 of 28 samples) than in distal colon cancer (3 of 22 samples; P ⫽ 0.014). However, we detected no significant relationship between the K-ras mutation and sex, age, tumor size, differentiation, or TNM stage (data
not shown). We estimated the detection limit of the K-ras oligonucleotide microarray by serial dilution of a positive control mixed with wild-type DNA; the positive control was cancer cell line (SNU-601), which harbors the G12D (GGT3 GAT) K-ras mutation. We could detect the mutated DNA up to a ratio of 1:15, which means that ⬃3% of mutated DNA can be detected by the K-ras oligonucleotide microarray. These results indicated that a K-ras oligonucleotide microarray could be used for samples containing a small fraction of mutated DNA. Although multiple fluorophores have previously been used for genotyping and pooled DNA samples have been used for parallel genotyping (9, 12, 13 ), this is the first report of the use of competitive mixtures of fragments bearing multiple fluorescent dyes. In addition, we sought to reduce the “cross-talk” problem, in which the signal from one fluorophore is detected at more than one wavelength (12 ) because of overlapping excitation and emis-
Clinical Chemistry 50, No. 9, 2004
sion spectra. Thus, we used dNTPs labeled with Cy5, Cy3, and Alexa 594, which have distinct spectra. Accordingly, our CDH results showed improved microarray imaging because there was less nonspecific hybridization (Fig. 1). We also noted that the wild-type (codon 12 and 13) signals were slightly reduced. This can be explained by the fact that the digested wild-type DNA from each sample had to compete with each other for hybridization. In contrast, the mutant DNA, which rarely overlapped in the three mixed samples, did not compete and thus produced a strong signal. As a result, when the sample had a mutation, the signal ratios between mutant and wild-type DNA increased from 0.91 to 1.66 (Fig. 1, A and B) and from 0.28 to 0.56 (Fig. 1, C and D). Thus, our new CDH technique confers several advantages: (a) It reduces the nonspecific signals caused by binding of small DNA fragments that might have homology with the spotted oligonucleotide, because these small DNA fragments compete with each other. (b) Mutational analysis can rely on calculating the signal ratio of mutant to wild type (1, 8 ). Samples can be scored as containing a mutation when the ratio is above the threshold; therefore, the larger ratio can make mutational analysis more correct. (c) Mixing of samples reduces experimental cost and time. In addition, each K-ras microarray contained three separate oligonucleotide sets. This allows researchers to investigate nine samples per microarray, facilitating large-scale analysis. We hybridized three different DNA samples into which the fluorescently labeled dNTPs had been incorporated in one experiment to detect K-ras mutations by the K-ras oligonucleotide microarray. The CDH technology increased the discrimination of mutation signal from nonspecific signals (Fig. 1). In summary, we developed a K-ras oligonucleotide microarray and applied our new CDH method to identify 50 K-ras mutations in samples from 204 Korean colorectal cancer patients. The results of the K-ras microarray analysis agreed perfectly with conventional sequencing data. The new method increases efficiency through pooling of multiple samples, providing a sensitive, rapid, highthroughput system that may be suitable for large-scale studies that require simple, quick, and effective screening of large numbers of samples.
This work was supported by a research grant from the National Cancer Center, Korea, and the BK21 Project for Medicine, Dentistry and Pharmacy. References 1. Kim IJ, Kang HC, Park JH, Shin Y, Ku JL, Yoo BC, et al. Development and application of an oligonucleotide microarray for mutational analysis. In: Hardiman G, ed. Microarrays methods and applications—nuts and bolts. Eagleville, PA: DNA Press, 2003:249 –72. 2. Kim IJ, Kang HC, Park JH, Ku JL, Lee JS, Kwon HJ, et al. RET oligonucleotide microarray for the detection of RET mutations in multiple endocrine neoplasia type 2 syndromes. Clin Cancer Res 2002;8:457– 63. 3. Kim IJ, Kang HC, Park JH, Shin Y, Ku JL, Lim SB, et al. Development and applications of a -catenin oligonucleotide microarray: -catenin mutations are dominantly found in the proximal colon cancers with microsatellite instability. Clin Cancer Res 2003;9:2920 –5. 4. Samowitz WS, Curtin K, Schaffer D, Robertson M, Leppert M, Slattery ML.
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Relationship of Ki-ras mutations in colon cancers to tumor location, stage, and survival: a population-based study. Cancer Epidemiol Biomarkers Prev 2000;9:1193–7. Andreyev HJ, Norman AR, Cunningham D, Oates J, Dix BR, Iacopetta BJ, et al. Kirsten ras mutations in patients with colorectal cancer: the ‘RASCAL II’ study. Br J Cancer 2001;85:692– 6. Brink M, de Goeij AF, Weijenberg MP, Roemen GM, Lentjes MH, Pachen MM, et al. K-ras oncogene mutations in sporadic colorectal cancer in The Netherlands Cohort Study. Carcinogenesis 2003;24:703–10. Lopez-Crapez E, Livache T, Marchand J, Grenier J. K-ras mutation detection by hybridization to a polypyrrole DNA chip. Clin Chem 2001;47:186 –94. Prix L, Uciechowski P, Bockmann B, Giesing M, Schuetz AJ. Diagnostic biochip array for fast and sensitive detection of K-ras mutations in stool. Clin Chem 2002;48:428 –35. Lovmar L, Fredriksson M, Liljedahl U, Sigurdsson S, Syvanen AC. Quantitative evaluation by minisequencing and microarrays reveals accurate multiplexed SNP genotyping of whole genome amplified DNA. Nucleic Acids Res 2003;31:e129. Lagarda H, Catasus L, Arguelles R, Matias-Guiu X, Prat J. K-ras mutations in endometrial carcinomas with microsatellite instability. J Pathol 2001;193: 193–9. Park JH, Kim IJ, Kang HC, Lee SH, Shin Y, Kim KH, et al. Germline mutations of the MEN1 gene in Korean families with multiple endocrine neoplasia type 1 (MEN1) or MEN1-related disorders. Clin Genet 2003;64:48 –53. Hirschhorn JN, Sklar P, Lindblad-Toh K, Lim YM, Ruiz-Gutierrez M, Bolk S, et al. SBE-TAGS: an array-based method for efficient single-nucleotide polymorphism genotyping. Proc Natl Acad Sci U S A 2000;97:12164 –9. Lindroos K, Sigurdsson S, Johansson K, Ronnblom L, Syvanen AC. Multiplex SNP genotyping in pooled DNA samples by a four-colour microarray system. Nucleic Acids Res 2002;30:e70. DOI: 10.1373/clinchem.2004.034017
Paraprotein Interference in Automated Chemistry Analyzers, Agata Smogorzewska, James G. Flood, William H. Long, and Anand S. Dighe* (Department of Pathology, Massachusetts General Hospital, 55 Fruit St., Boston, MA 02114; * author for correspondence: fax 617-726-9206, email
[email protected]) Paraproteins can interfere in chemical measurements when they form precipitates during the testing procedure (1–9 ). Here we describe ways to identify paraproteins that interfere in methods for bilirubin and HDL on an automated analyzer. The approaches appeared to be effective in identifying these rare cases of interference and did not hinder the autovalidation of appropriately high or low values for either assay. Software analysis and reporting programs currently in use that rely on rigid two-point calculations derived from reaction monitors may be susceptible to errors in analysis. We encountered an artifactually increased total bilirubin concentration and an artifactually low HDL in a patient with a monoclonal IgM paraprotein. The tests were initially performed on plasma samples with the Hitachi 917 automated analyzer (Roche Diagnostics) using the Roche total bilirubin assay and the Roche HDL-C Plus assay. For this patient, the reported total bilirubin was 318 mg/L, direct bilirubin was 2 mg/L, total protein was 127 g/L, and HDL was undetectable. Serum protein electrophoresis revealed a monoclonal IgM M component at a concentration of 66 g/L. Similar results were seen on subsequent samples (both in plasma and serum),
