Assay Validation for Identification of Hereditary Nonpolyposis Colon Cancer-Causing Mutations in Mismatch Repair Genes MLH1, MSH2, and MSH6
2005; Elsevier BV; Volume: 7; Issue: 4 Linguagem: Inglês
10.1016/s1525-1578(10)60584-3
ISSN1943-7811
AutoresMadhuri Hegde, Maria E. Blazo, Belinda Chong, T. Prior, Carolyn Richards,
Tópico(s)DNA Repair Mechanisms
ResumoHereditary nonpolyposis colon cancer (HNPCC, Online Mendelian Inheritance in Man (OMIM) 114500) is an autosomal dominant disorder that is genetically heterogeneous because of underlying mutations in mismatch repair genes, primarily MLH1, MSH2, and MSH6. One challenge to correctly diagnosing HNPCC is that the large size of the causative genes makes identification of mutations both labor intensive and expensive. We evaluated the usefulness of denaturing high performance liquid chromatography (DHPLC) for scanning mismatch repair genes (MLH1, MSH2, and MSH6) for point mutations, small deletions, and insertions. Our assay consisted of 51 sets of primers designed to amplify all exons of these genes. All polymerase chain reaction reactions were amplified simultaneously using the same reaction conditions in a 96-well format. The amplified products were analyzed by DHPLC across a range of optimum temperatures for partial fragment denaturation based on the melting profile of each specific fragment. DNA specimens from 23 previously studied HNPCC patients were analyzed by DHPLC, and all mutations were correctly identified and confirmed by sequence analysis. Here, we present our validation studies of the DHPLC platform for HNPCC mutation analysis and compare its merits with other scanning technologies. This approach provides greater sensitivity and more directed molecular analysis for clinical testing in HNPCC. Hereditary nonpolyposis colon cancer (HNPCC, Online Mendelian Inheritance in Man (OMIM) 114500) is an autosomal dominant disorder that is genetically heterogeneous because of underlying mutations in mismatch repair genes, primarily MLH1, MSH2, and MSH6. One challenge to correctly diagnosing HNPCC is that the large size of the causative genes makes identification of mutations both labor intensive and expensive. We evaluated the usefulness of denaturing high performance liquid chromatography (DHPLC) for scanning mismatch repair genes (MLH1, MSH2, and MSH6) for point mutations, small deletions, and insertions. Our assay consisted of 51 sets of primers designed to amplify all exons of these genes. All polymerase chain reaction reactions were amplified simultaneously using the same reaction conditions in a 96-well format. The amplified products were analyzed by DHPLC across a range of optimum temperatures for partial fragment denaturation based on the melting profile of each specific fragment. DNA specimens from 23 previously studied HNPCC patients were analyzed by DHPLC, and all mutations were correctly identified and confirmed by sequence analysis. Here, we present our validation studies of the DHPLC platform for HNPCC mutation analysis and compare its merits with other scanning technologies. This approach provides greater sensitivity and more directed molecular analysis for clinical testing in HNPCC. Colorectal cancer (CRC) is the second leading cause of cancer-related death in the United States, accounting for more than 57,000 deaths per year (in 2002; Cancer Facts and Figures. American Cancer Society. Available at www.cancer.org). Although the majority of colorectal cancer is not inherited, inherited CRC accounts for up to 10% of total cases and primarily consists of familial adenomatous polyposis (OMIM 175100), or hereditary nonpolyposis colon cancer (HNPCC; OMIM 114500). HNPCC is an autosomal dominant syndrome characterized by increased lifetime risk of early-onset colorectal cancer as well as other cancers of the endometrium, stomach, small intestine, hepatobiliary system, kidney, ureter, and ovary.1Burt RW Familial risk and colorectal cancer.Gastroenterol Clin North Am. 1996; 25: 793-803Abstract Full Text Full Text PDF PubMed Scopus (45) Google Scholar, 2Burt RW Familial association.Adv Exp Med Biol. 1999; 470: 99-104Crossref PubMed Google Scholar Although exact data about its prevalence are unknown, it is estimated that HNPCC or Lynch Syndrome accounts for about 5 to 13% of all CRC, making it the most common hereditary colon cancer syndrome.3Coughlin SS Miller DS Public health perspectives on testing for colorectal cancer susceptibility genes.Am J Prev Med. 1999; 16: 99-104Abstract Full Text Full Text PDF PubMed Scopus (20) Google Scholar, 4de Leon MP Pedroni M Benatti P Percesepe A Di Gregorio C Foroni M Rossi G Genuardi M Neri G Leonardi F Viel A Capozzi E Boiocchi M Roncucci L Hereditary colorectal cancer in the general population: from cancer registration to molecular diagnosis.Gut. 1999; 45: 32-38Crossref PubMed Scopus (57) Google Scholar, 5Cederquist K Golovleva I Emanuelsson M Stenling R Gronberg H A population based cohort study of patients with multiple colon and endometrial cancer: correlation of microsatellite instability (MSI) status, age at diagnosis and cancer risk.Int J Cancer. 2001; 91: 486-491Crossref PubMed Scopus (20) Google Scholar The penetrance of HNPCC mutations has been estimated at approximately 80%, the lifetime risk for a mutation carrier to develop colorectal cancer.6Bocker T Ruschoff J Fishel R Molecular diagnostics of cancer predisposition: hereditary non-polyposis colorectal carcinoma and mismatch repair defects.Biochim Biophys Acta. 1999; 1423: 1-10Google Scholar Identification of HNPCC mutations is important for clinical surveillance in carriers and genetic testing for at-risk relatives. Germline mutations in mismatch repair (MMR) genes, most commonly human mutL homolog 1 (MLH1) on chromosome 3p22.3, human mutS homolog 2 (MSH2) on chromosome 2p21, and human mutS homolog 6 (MSH6) on chromosome 2p16.3, are causative of HNPCC7Fishel R Lescoe MK Rao MR Copeland NG Jenkins NA Garber J Kane M Kolodner R The human mutator gene homolog MSH2 and its association with hereditary nonpolyposis colon cancer.Cell. 1993; 75: 1027-1038Abstract Full Text PDF PubMed Scopus (2578) Google Scholar, 8Aaltonen LA Peltomaki P Genes involved in hereditary nonpolyposis colorectal carcinoma.Anticancer Res. 1994; 14: 1657-1660PubMed Google Scholar, 9Bronner CE Baker SM Morrison PT Warren G Smith LG Lescoe MK Kane M Earabino C Lipford J Lindblom A Tannergård P Bollag RJ Godwin AR Ward DC Nordenskjld M Fishel R Kolodner R Liskay RM Mutation in the DNA mismatch repair gene homologue hMLH1 is associated with hereditary non-polyposis colon cancer.Nature. 1994; 368: 258-261Crossref PubMed Scopus (1913) Google Scholar, 10Papadopoulos N Nicolaides NC Wei Y-F Ruben SM Carter KC Rosen CA Haseltine WA Fleischmann RD Fraser CM Adams MD Venter JC Hamilton SR Petersen GM Watson P Lynch HT Peltomaki P Mecklin J-P de la Chapelle A Kinzler KW Vogelstein B Mutation of a mutL homolog in hereditary colon cancer.Science. 1994; 263: 1625-1629Crossref PubMed Scopus (1761) Google Scholar, 11Wu G Wu W Hegde M Fawkner M Chong B Love D Su LK Lynch P Snow K Richards CS Detection of sequence variations in the adenomatous polyposis coli (APC) gene using denaturing high-performance liquid chromatography.Genet Test. 2001; 5: 281-290Crossref PubMed Scopus (30) Google Scholar. 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The DHPLC platform meets the needs of the clinical molecular laboratories because of its sensitivity, semiautomated operation and cost effectiveness. The principle behind DHPLC is that negatively charged DNA is linked to a neutral column by a positively charged triethylammonium acetate (TEAA). Variants are detected by differential binding of the homo- and heteroduplexes to the column. Detection of sequence variations using DHPLC in numerous disease-related genes has been reported including CFTR, F9, MECP2, RET, and PTEN.19O'Donovan MC Oefner PJ Roberts SC Austin J Hoogendoorn B Guy C Speight G Upadhyaya M Sommer SS McGuffin P Blind analysis of denaturing high-performance liquid chromatography as a tool for mutation detection.Genomics. 1998; 52: 44-49Crossref PubMed Scopus (288) Google Scholar, 20Liu W Smith DI Rechtzigel KJ Thibodeau SN James CD Denaturing high performance liquid chromatography (DHPLC) used in the detection of germline and somatic mutations.Nucleic Acids Res. 1998; 26: 1396-1400Crossref PubMed Scopus (228) Google Scholar, 21Jones AC Austin J Hansen N Hoogendoorn B Oefner PJ Cheadle JP O'Donovan MC Optimal temperature selection for mutation detection by denaturing HPLC and comparison to single-stranded conformation polymorphism and heteroduplex analysis.Clin Chem. 1999; 45: 1133-1140PubMed Google Scholar In genes such as BRCA1/2, TSC1/2, NF-1, and APC, the large size and presence of few hot spots makes DHPLC a preferred method for rapid mutation screening and directed molecular analysis.22Arnold N Gross E Schwarz-Boeger U Pfisterer J Jonat W Kiechle M A highly sensitive, fast, and economical technique for mutation analysis in hereditary breast and ovarian cancers.Hum Mutat. 1999; 14: 333-339Crossref PubMed Scopus (115) Google Scholar, 23Choy YS Dabora SL Hall F Ramesh V Niida Y Franz D Kasprzyk-Obara J Reeve MP Kwiatkowski DJ Superiority of denaturing high performance liquid chromatography over single-stranded conformation and conformation-sensitive gel electrophoresis for mutation detection in TSC2.Ann Hum Genet. 1999; 63: 383-391Crossref PubMed Google Scholar, 24Gross E Arnold N Goette J Schwarz-Boeger U Kiechle M A comparison of BRCA1 mutation analysis by direct sequencing, SSCP and DHPLC.Hum Genet. 1999; 105: 72-78Crossref PubMed Scopus (179) Google Scholar, 25Wagner T Stoppa-Lyonnet D Fleischmann E Muhr D Pages S Sandberg T Caux V Moeslinger R Langbauer G Borg A Oefner P Denaturing high-performance liquid chromatography detects reliably BRCA1 and BRCA2 mutations.Genomics. 1999; 62: 369-376Crossref PubMed Scopus (193) Google Scholar, 26Gross E Arnold N Pfeifer K Bandick K Kiechle M Identification of specific BRCA1 and BRCA2 variants by DHPLC.Hum Mutat. 2000; 16: 345-353Crossref PubMed Scopus (83) Google Scholar, 27Jones AC Sampson JR Hoogendoorn B Cohen D Cheadle JP Application and evaluation of denaturing HPLC for molecular genetic analysis in tuberous sclerosis.Hum Genet. 2000; 106: 663-668Crossref PubMed Scopus (52) Google Scholar, 28Benit P Bonnefont JP Kara Mostefa A Francannet C Munnich A Ray PF Denaturing high-performance liquid chromatography (DHPLC)-based prenatal diagnosis for tuberous sclerosis.Prenat Diagn. 2001; 21: 279-283Crossref PubMed Scopus (11) Google Scholar, 29Roberts PS Jozwiak S Kwiatkowski DJ Dabora SL Denaturing high-performance liquid chromatography (DHPLC) is a highly sensitive, semi-automated method for identifying mutations in the TSC1 gene.J Biochem Biophys Methods. 2001; 47: 33-37Crossref PubMed Scopus (25) Google Scholar In HNPCC, one report describing the use of DHPLC for mutation analysis in MLH1 and MSH2 yielded a sensitivity of 97% compared with sequence analysis.15Holinski-Feder E Muller-Koch Y Friedl W Moeslein G Keller G Plaschke J Ballhausen W Gross M Baldwin-Jedele K Jungck M Mangold E Vogelsang H Schackert HK Lohsea P Murken J Meitinger T DHPLC mutation analysis of the hereditary nonpolyposis colon cancer (HNPCC) genes hMLH1 and hMSH2.J Biochem Biophys Methods. 2001; 47: 21-32Crossref PubMed Scopus (80) Google Scholar Later studies by Kurzawski et al30Kurzawski G Safranow K Suchy J Chlubek D Scott RJ Lubinski J Mutation analysis of MLH1 and MSH2 genes performed by denaturing high-performance liquid chromatography.J Biochem Biophys Methods. 2002; 51: 89-100Crossref PubMed Scopus (43) Google Scholar confirmed the analytical sensitivity of this method (>98%) in a series of 46 patients from HNPCC families by similar DHPLC approach. Several different approaches have previously been described to identify mutations in HNPCC.31Panariello L Scarano MI de Rosa M Capasso L Renda A Riegler G Rossi GB Salvatore F Izzo P hMLH1 mutations in hereditary nonpolyposis colorectal cancer kindreds: mutations in brief no. 182: online.Hum Mutat. 1998; 12: 216-217PubMed Google Scholar, 32Fidalgo P Almeida MR West S Gaspar C Maia L Wijnen J Albuquerque C Curtis A Cravo M Fodde R Leitao CN Burn J Detection of mutations in mismatch repair genes in Portuguese families with hereditary non-polyposis colorectal cancer (HNPCC) by a multi-method approach.Eur J Hum Genet. 2000; 8: 49-53Crossref PubMed Scopus (32) Google Scholar, 33Parc YR Halling KC Burgart LJ McDonnell SK Schaid DJ Thibodeau SN Halling AC Microsatellite instability and hMLH1/hMSH2 expression in young endometrial carcinoma patients: associations with family history and histopathology.Int J Cancer. 2000; 86: 60-66Crossref PubMed Scopus (77) Google Scholar, 34Godino J de La Hoya M Diaz-Rubio E Benito M Caldes T Eight novel germline MLH1 and MSH2 mutations in hereditary non-polyposis colorectal cancer families from Spain.Hum Mutat. 2001; 18: 549Crossref PubMed Scopus (7) Google Scholar Scan-ning methods including single-strand conformation an-alysis (SSCP), conformation-sensitive gel electropho-resis (CSGE), denaturing gradient gel electrophoresis (DGGE), as well as sequencing the entire coding region of the MLH1 and MSH2 genes are well established techniques for clinical diagnostic purposes. However, SSCP, CSGE, and DGGE lack sensitivity, and SSCP has inherent size limitations of 250 bp for fragment analysis with a sensitivity of 70 to 80%. DGGE offers increased sensitivity yet is also very time consuming and requires GC-clamp primers, and mutation in GC-rich regions may not be detected. In view of the many deficiencies of these scanning approaches in terms of sensitivity and specificity, we analyzed the efficacy of a DHPLC approach to satisfy the following criteria: high test sensitivity and specificity, reliable and reproducible results, assay robustness, cost effective, and high-throughput capability. In this communication, we report identification of sequence variations in the MLH1, MSH2, and MSH6 genes using a DHPLC platform under optimized conditions, and we discuss the implementation and validation of this approach in a clinical laboratory setting. Anonymous DNAs from 23 HNPCC patients were obtained from clinical and research laboratories (a+ LabPLUS, Auckland, New Zealand; Mayo Clinic, Rochester, MN; Ohio State University, Columbus, OH). These patients have been previously analyzed using CSGE and SSCP, followed by targeted sequence analysis, or by full gene sequence analysis. DNA was extracted from peripheral blood lymphocytes of noncolorectal cancer individuals for 40 negative con-trols using the Puregene DNA Isolation kit (Gentra Systems, Minneapolis, MN). The transcript and genomic sequence data were accessed from multiple databases (principally through http://genome.ucsc.edu) that carried the reference sequences for the MLH1, MSH2, and MSH6 genes (GenBank Accession nos. NM000249, NM000251, and NM000179 for MLH1, MSH2, and MSH6, respectively). Using this information, primers were designed to contain at least 50 bp of intron. The sequence of the primer pairs, their corresponding amplicon sizes, and optimized conditions for DHPLC analysis are shown in Table 1. All primers were checked against the National Center for Biotechnology Information SNP database (http://www.ncbi.nlm.nih.gov/SNP/) and the HGVbase (http://hgvbase.cgb.ki.se/) to avoid overlapping with single nucleotide polymorphisms (SNP).Table 1Primer Sequences and DHPLC ConditionsNamePrimer sequence (5′ to 3′)PCR sizeTm*Tm for the fragment. PCR (°C)DHPLC gradient %BDHPLC†Optimum temperatures for DHPLC analysis were empirically determined using the predicted fragment melting profile generated by WAVEMAKER software. (table continued) temperatures (°C)MLH1 primer list MLH1-1Faggtgattggctgaaggcac2316247–6162, 63 MLH1-1Rgcccgttaagtcgtagccct MLH1-2Fatgtacattagagtagttgcagactgataaatt2215746–6056, 57 MLH1-2Ragtttccagaacagagaaaggtcc MLH1-3Fcaagaaaatgggaattcaaagagat2415547–6155, 56 MLH1-3Rctaacaaatgacagacaatgtcatcac MLH1-4Fcctttggtgaggtgacagtgg2215646–6057, 58, 59 MLH1-4Rcaggattactctgagacctaggcaa MLH1-5Fttttccccttgggattagtatctatc2275347–6155, 57 MLH1-5Rccctgaaaacttagaagcaattttattt MLH1-6Fggacatcttgggttttattttcaag2355647–6157, 58 MLH1-6Rtgttcaatgtatgagcactagaacaca MLH1-78Fgggctctgacatctagtgtgtgtt4175652–6656, 57, 58 MLH1-78Raaaataatgtgatggaatgataaacca MLH1-9Ftctgattcttttgtaatgtttgagttttg2415547–6156, 57 MLH1-9Rcataaaattccctgtgggtgtttc MLH1-10Fctgaggtgatttcatgactttgtgt2515948–6258, 59, 60 MLH1-10Rgaggagagcctgatagaacatctgt MLH1-11Fgtgggctttttctccccct2815849–6358, 60, 62 MLH1-11Rctctcacgtctggccgg MLH1-12 new Fttttttaatacagactttgctaccaggac4365554–6859, 60, 61 MLH1-12 new Rgttttattacagaataaaggaggtaggctg MLH1-13Fccaaaatgcaacccacaaaatt2825849–6358, 59, 60 MLH1-13Raaccttggcagttgaggcc MLH1-14Fggtgtctctagttctggtgcctg2715848–6259, 60 MLH1-14Rtgcctgtgctccctgga MLH1-15Fcccattttgtcccaactggtt2035745–5956, 57, 58 MLH1-15Rgagagctactattttcagaaacgatcag MLH1-16Ftgggaattcaggcttcatttg2925849–6358, 59, 60 MLH1-16Rgcacccggctggaaatt MLH1-17Fgcactggagaaatgggatttg2215946–6058, 59, 60 MLH1-17Rcctccagcacacatgcatg MLH1-18Fagtctgtgatctccgtttagaatgag2425747–6156, 58, 59 MLH1-18Rttgtatgaggtcctgtcctagtcct MLH1-19Fcatcagccaggacaccagtg2885849–6358, 59, 60 MLH1-19RcggaatacagagaaagaagaacacaMSH2 primer list MSH2-1-diag Fttcgacatggcggtgc2856748–6266, 67 MSH2-1 new Rgtccctccccagcacg MSH2-2Fgaagtccagctaatacagtgcttga3015349–6352, 54, 55 MSH2-2Raaacacaattaaattcttcacatttttatttt MSH2-3Fagagtttggatttttcctttttgc4325752–6656, 57, 58 MSH2-3Rtcatgtcaattaaagagcctttcc MSH2-4Fttcatttttgcttttcttattcctttt3165050–6452, 55, 57 MSH2-4Ratatgacagaaatatccttctaaaaagtcactat MSH2-5Factggatccagtggtatagaaatcttc2855349–6352, 54, 56 MSH2-5Rgcttcttcagtatatgtcaatgaaaaca MSH2-6Fgcgtagtaaggttttcactaatgagc2515648–6256, 57, 58 MSH2-6Rcatgtgggtaactgcaggttaca MSH2-7Ftgagacttacgtgcttagttgataaattt3415350–6452, 55, 56 MSH2-7Rgcacattgccaagtatatattgtatgag MSH2-8Ftgatgcttgtttatctcagtcaaaatt2755348–6253, 54, 55 MSH2-8Raatctacaaactttcttaaagtggcctt MSH2-9 new Fgtctttacccattatttataggattttgtca2175646–6056, 57, 58 MSH2-9 new Rgtatagacaaaagaattattccaacctcc MSH2-10Fattgaaaaatggtagtaggtatttatggaa2745448–6254, 55, 56 MSH2-10Rcacatcatgttagagcatttaggga MSH2-11Fatatgtttcacgtagtacacattgcttcta2495447–6154, 55 MSH2-11Rtcaaatatcatgatttttcttctgttacc MSH2-13Rtcacaggacagagacatacatttctatct MSH2-14Ftgtggcatatccttcccaatg4525552–6655, 56, 57 MSH2-14Raataatttatactaacttagaataaggcaattactgat MSH2-15Ftacataaattgctgtctcttctcatgc3115750–6457, 58 MSH2-15Raaaaaccttcatcttagtgtcctgttt MSH2-16 new Ftaattactaatgggacattcacatgtgt2305547–6155, 56 MSH2-16 new RtaccttcattccattactgggatttMSH6 primer list MSH6Exon 1Ftgttgattggccactggg4636653–5866, 67, 68 MSH6Exon 1Rcaaccccctgtgcgagcctc MSH6Exon 2Ftaactgcctttaaggaaacttgacca3306050–5559, 60, 61 MSH6Exon 2Rtcatatagaaaaaagtctgcctgtctg MSH6Exon 3Fctggtcttgaactgctgggat2895849–5458, 59, 60 MSH6Exon 3Rcccctttcttcccccatc MSH6Exon 4-1Ftgcacgggtaccattataaagtca4505852–5758, 59, 60 MSH6Exon 4-1Rgtattcttggtttctgatgaaatgctag MSH6Exon 4-2Fgaaggaaacgccctcagc4205852–5758, 59, 60 MSH6Exon 4-2Rcagttgcctttcatgaataccag MSH6Exon 4-3Fccacatggatgctcttattgga4205852–5758, 59, 60 MSH6Exon 4-3Rtcatctgaaaactgacctatgaaaaact MSH6Exon 4-4Ftttgttgatacttcactgggaaagtt4205752–5757, 58, 59 MSH6Exon 4-4Rctcctgatcaataaggcattttttg MSH6Exon 4-5Fctctaggtggttgtgtcttctacctc4205752–5757, 58, 59 MSH6Exon 4-5Rtgagtagcctctcaagatctggaa MSH6Exon 4-6Fcgaagttgtagagcttctaaagaagct4805753–5856, 57, 58 MSH6Exon 4-6Rgtcctacagccaattctgttgc MSH6Exon 4-7Fagcctcctggaatacctagagaaac4205852–5758, 59, 60 MSH6Exon 4-7Racttatttttagggataatatacagctggc MSH6Exon 5Fcacttaggctgataaaaccccc3865751–5657, 58, 59 MSH6Exon 5Rgtatgttattcctaatgtcacaaatgacttt MSH6Exon 6Faagacaaaagtttatgaaactgttactacca2505648–5356, 57, 59 MSH6Exon 6Ragaagcaaatatcttttatcacatctaaatg MSH6Exon 7Ftaacctagaagatgaatttatgtaatatgattt2245346–5153, 54, 55 MSH6Exon 7Rttcagataatcttctataaaaatagttatttgt MSH6Exon 8Ftgagttacttccttatgcatattttact2755748–5356, 57, 58 MSH6Exon 8Raatattagcgatacatgtgctagca MSH6Exon 9Ftgctagcacatgtatcgctaatatt3205650–5556, 57, 58 MSH6Exon 9Rgcatcatcccttcccctttta MSH6Exon 10Fgaagggatgatgcactatgaaaaa2965249–5452, 56, 57 MSH6Exon 10Rgtagaaggtagataagaattaaaagggtttaattt* Tm for the fragment.† Optimum temperatures for DHPLC analysis were empirically determined using the predicted fragment melting profile generated by WAVEMAKER software. (table continued) Open table in a new tab The complete coding regions of the MLH1, MSH2, and MSH6 genes, including all splice junctions, were amplified in a total of 51 fragments using primers designed in our laboratory. All exonic fragments of each gene, including intron junctions, were amplified individually using primers designed with Primer Express 1.0 (PE Applied Biosystems, Foster City, CA) with a Tm of approximately 60°C (19 fragments for MLH1 and 16 fragments each for MSH2) and 58°C (16 fragments for MSH6). PCR analysis was performed using standard reaction conditions of 50 ng DNA, 200 μmol/L primers, 200 μmol/L dNTPs, 1× PCR buffer with 1.5 μmol/L MgCl2, and 1.25 units/reaction Faststart TaqDNA polymerase (Roche) in a 96-well plate format. Amplification was performed in the Eppendorf Mastercycler using the following conditions: 95°C for 30 seconds, annealing at X°C (MLH1-58, MSH2-58.8, MSH6-57.8) for 30 seconds, and extension at 72°C for 1 minute, for a total of 35 cycles, and with a final extension at 72°C for 7 minutes, and then held at 4°C. All PCR products were examined by gel electrophoresis before analysis on DHPLC. A Transgenomic WAVE DNA Fragment Analysis System (Transgenomic, Inc., Omaha, NE) and associated WAVEMAKER software were used. An aliquot (5 μl) of the PCR product was directly injected into a DNASep column. Each fragment was analyzed using two to three partially denaturing temperatures (Table 1) to maximize detection of unknown mutations located in various positions throughout the fragment. The optimum conditions were determined empirically, based on fragment melting profile at each selected temperature. The column mobile phase for sample elution consisted of a mixture of the following: buffer A, 0.1 mol/L TEAA; and buffer B, 0.1 mol/L TEAA with 25% acetonitrile. Samples were eluted at a linear gradient of buffer B over a 4.5-minute period at a constant flow rate of 0.9 ml/minute. The starting gradient varied among fragments, depending on the DNA sequence and fragment size, and was determined by the WAVEMAKER software. The chromatograms of each fragment were compared with those of the wild type, and fragments containing heteroduplexes with a shorter retention time compared with wild-type fragments were sequenced to confirm putative sequence variations. PCR products (20 μl) were purified using a QIAquick PCR Purification kit (Qiagen Inc., Germany). The subsequent purified products were subjected to cycle sequencing in both forward and reverse directions using a BigDye Terminator Cycle Sequencing version 3.1 kit (PE Applied Biosystems). Sequencing reaction contained purified PCR product (1.5 ng/μl), Terminator Ready Reaction mix (4 μl), and primer (3.3 pmol) in a 10-μl reaction. Cycle sequencing was performed according to the manufacturer's instructions. The products from each reaction were electrophoresed in an Applied Biosystems PRISM 3100 DNA Sequencer. The sequences for each fragment were aligned to the wild-type sequences obtained from GenBank and analyzed for sequence variation using Sequencher software (Gene Codes Corp., Ann Arbor, MI). GenBank nos. NM000249, NM000251, and NM000179 were used as the MLH1, MSH2, and MSH6 wild-type cDNA reference sequences, respectively, and American College of Medical Genetics (ACMG) guidelines were followed for interpretation of sequence variation (www.acmg.net). A total of 23 known positive controls from HNPCC patients containing sequence variations in the MLH1, MSH2, and MSH6 genes were analyzed, and the results are shown in Table 2 and Figure 1. Of these, 5 represented unique mutations within the sample set, whereas 18 were recurrent mutations that had been identified in different laboratories reported in the literature. This sample set represented seven missense, six deletion, two nonsense, two splicing, one insertion, and one indel type mutation. All were detected by DHPLC analysis using temperature algorithm for analysis (Table 1). Thus, the sensitivity of DHPLC analysis for these known mutations was 100%. Sequence analysis of this sample set as well as the 40 wild-type controls identified several additional variants (missense mutations), representing polymorphisms, which are commonly found in these genes (Figure 2). The temperatures for detection of mutations are shown in the Table 2. Most of the mutations were detected at all three temperatures, but some were detected at only the low and the medium temperatures. This is dependent on the sequence composition and position of the mutation within the sequence. AT-rich sequences are easier to melt and are hence detected at lower temperatures compared with GC-rich sequences, which melt at high temperatures. Exon 1 of MSH2 and MSH6 was found to be particularly GC rich and difficult to design primers.Table 2Summary of Mutations Detected by DHPLCMutation name (based on)DHPLC†Three temperatures of DHPLC analysis are designated low, medium, and high (TL, TMD, and TH, respectively). +, positive; −, negative.SampleGeneExonCodonNucleotideMutationMethod*Method previously used to identify mutation.TLTMDTH153MLH15delAGinsGTT385385delAGinsGTTSSCP+++242MLH19G>CIVS8-1IVS8-1G>CSSCP++−151MLH116delAAG1852-18541852-1854delAAGSSCP+++144MLH116AA>GC1852-1853K618ASSCP+++145MLH116ddCA1778-17791778-1779delCASSCP+++152MLH117delC19461946GdelCSSCP++−146MLH119G>A2146V716MSSCP++−233MSH21A>C97T33PSSCP++−234MSH23A>G380N127SSSCP++−147 and 610MSH25A>T3′ intron942+3A>TSSCP++−148MSH29C>T493Q493XSSCP++−609MSH210delG21132113delGCSGE++−154MSH212C>T1865P622LSSCP+++235MSH212G>C1906A636PSSCP++−243MSH213C>T2038R680XSSCP+++264MSH64-3T>C1526V509ASSCP+++265MSH66delGA35113511-3512delGASSCP+++266MSH69insGTCA39883988-3991insGTCASSCP+++267MSH69delACTA–IVS9+11delACTASSCP+++268MSH69delACTA–IVS9+11delACTASSCP+++* Method previously used to identify mutation.† Three temperatures of DHPLC analysis are designated low, medium, and high (TL, TMD, and TH, respectively). +, positive; −, negative. Open table in a new tab Figure 2DHPLC profiles for MLH1, MSH2, and MSH6 polymorphisms. The DHPLC profiles of HNPCC patients with polymorphisms in mismatch repair genes are shown for all of the mutations in MLH1, MSH2, and MSH6 used for assay validation compared with the wild-type profiles, respectively.View Large Image Figure ViewerDownload Hi-res image Download (PPT) The elution profiles shown in Figure 2 were found to be reproducible under different conditions such as change of new buffer, change of column, and amount of PCR product injected. The reproducibility of the elution profiles is represented in Figure 1 in MSH2 942 + 3A>T and MSH6 for the mutation IVS9 + 11delACTA in which more than one positive control was available. This region is flanked on either side by SNPs and also a repeat of the ACTA sequence. Car
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