Review
BibTex RIS Cite

Moleküler Tanıda Yüksek Çözünürlüklü Erime Yöntemi ve Klinik Önemi

Year 2017, Volume: 7 Issue: 1, 20 - 26, 15.03.2017

Abstract

Her geçen gün moleküler biyoloji alanında teknolojinin gelişmesiyle paralel, birçok yeni moleküler analiz yöntemleri ortaya çıkmaktadır. Biz de bu derlemede, moleküler tanıda önemli olduğu gösterilmiş olan Yüksek Çözünürlüklü Erime (High Resolution Melting) (HRM) analizini, uygulama alanlarını ve klinikte yapılmış çalışmalarla önemini anlatmayı amaçladık. HRM kapalı tüp sisteminde, Polimeraz Zincir Reaksiyonu (PZR: PCR) sonrasına dayalı genetik varyasyonları belirlemek için kullanılan yeni bir yöntemdir. HRM’nin çalışma prensibi nükleik asit örneklerinin erime davranışına dayanmaktadır. Çift zincirli DNA’nın denatürasyonu erime sıcaklığının artmasıyla oluşan floresan değişikliklerinin saptanmasıyla belirlenir. Wild type (yaban tip) ve heterozigot örneklerinin farklılıkları erime grafiklerinde kolaylıkla saptanabilmektedir. Bu yöntemde erime eğrisi analiziyle daha fazla bilgi ve detay elde edilebilmektedir. HRM analizi, örneklerin sekans, uzunluk, guanin sitozin (GC) içeriğine göre ayrımını yapabilmektedir. Popülasyonda yaygın görülen tek nükleotit değişikliklerinin (SNP) tespiti, hastalıklarla ilişkili gen mutasyon taramaları ve DNA metilasyon analizleri HRM yöntemi ile hızlı ve güvenilir bir şekilde tanımlanabilmektedir. PZR ürünlerindeki nükleotit dizi değişimleri ve çeşitli varyasyonlar DNA erime eğrisi şekilleriyle HRM yönteminde saptanabilmektedir. Kombine yeni nesil DNA boyaları ve geliştirilen gen tarama yazılımları sayesinde güçlü analiz yapabilme kapasitesinin yanı sıra kolay uygulanabilirliği ve düşük maliyetli olma özelliği ile gerçek zamanlı HRM yöntemi pek çok klinik uygulamada ön plana çıkmaktadır. 

References

  • 1. Ririe KM, Rasmussen RP, Wittwer CT. Product differentiation by analysis of DNA melting curves during the polymerase chain reaction. Anal Biochem 1997; 245: 154-60. [CrossRef] 2. Wittwer CT, Herrmann MG, Gundry CN, Elenitoba-Johnson KS. Real-time multiplex PCR assays. Methods 2001; 25: 430-42. [CrossRef] 3. Gundry CN, Bernard PS, Herrmann MG, Reed GH, Wittwer CT. Rapid F508del and F508C assay using fluorescent hybridization probes. Genet Test 1999; 3: 365-70. [CrossRef] 4. Taylor CF. Mutation scanning using high-resolution melting. Biochem Soc Trans 2009; 37: 433-7. [CrossRef] 5. Fadhil W, Ibrahem S, Seth R, Ilyas M. Quick-multiplex-consensus (QMC)- PCR followed by high-resolution melting: a simple and robust method for mutation detection in formalin-fixed paraffin-embedded tissue. J Clin Pathol 2010; 63: 134-40. [CrossRef] 6. Gallegos Ruiz MI, Floor K, Rijmen F, Grünberg K, Rodriguez JA, Giaccone G. EGFR and K-ras mutation analysis in non-small cell lung cancer: comparison of paraffin embedded versus frozen specimens. Cell Oncol 2007; 29: 257-64. 7. Eischeid AC. SYTO dyes and EvaGreen outperform SYBR Green in real-time PCR. BMC Res Notes 2011; 4: 263. [CrossRef] 8. Monis PT, Giglio S, Saint CP. Comparison of SYTO9 and SYBR Green I for real-time polymerase chain reaction and investigation of the effect of dye concentration on amplification and DNA melting curve analysis. Anal Biochem 2005; 340: 24-34. [CrossRef] Dirican ve Akkiprik. HRM Yöntemleri ve Uygulamaları Clin Exp Health Sci 2017; 7(1): 20-6 24 9. Chanock SJ, Burdett L, Yeager M, Llaca V, Langerød A, Presswalla S, et al. Somatic sequence alterations in twenty-one genes selected by expression profile analysis of breast carcinomas. Breast Cancer Res 2007; 9: R5. [CrossRef] 10. White H, Potts G. Mutation Scanning by High Resolution Melt Analysis. Evaluation of Rotor-Gene 6000 (Corbett Life Science), HR-1 and 384-Well Lightscanner (Idaho Technology) Wessex, UK: National Genetics Reference Laboratory; 2006. 11. Garritano S, Gemignani F, Voegele C, Nguyen-Dumont T, Le Calvez-Kelm F, De Silva D, et al. Determining the effectiveness of High Resolution Melting analysis for SNP genotyping and mutation scanning at the TP53 locus. BMC Genet 2009; 10: 5. [CrossRef] 12. Dirican E, Kaya Z, Gullu G, Peker I, Ozmen T, Gulluoglu BM, et al. Detection of PIK3CA gene mutations with HRM analysis and association with IGFBP-5 expression levels in breast cancer. Asian Pac J Cancer Prev 2014; 15: 9327-33. [CrossRef] 13. Moghadam AA, Mahjoubi F, Reisi N, Vosough P. Investigation of FANCA gene in Fanconi anaemia patients in Iran. Indian J Med Res 2016; 143: 184-96. [CrossRef] 14. Tserga A, Chatziandreou I, Michalopoulos NV, Patsouris E, Saetta AA. Mutation of genes of the PI3K/AKT pathway in breast cancer supports their potential importance as biomarker for breast cancer aggressiveness. Virchows Arch 2016; 469: 35-43. [CrossRef] 15. Chang YS, Lin CY, Yang SF, Ho CM, Chang JG. Analysing the mutational status of adenomatous polyposis coli (APC) gene in breast cancer. Cancer Cell Int 2016; 16: 23. [CrossRef] 16. Takano EA, Mitchell G, Fox SB, Dobrovic A. Rapid detection of carriers with BRCA1 and BRCA2 mutations using high resolution melting analysis. BMC Cancer 2008; 8: 59. [CrossRef] 17. Tan AY, Westerman DA, Carney DA, Seymour JF, Juneja S, Dobrovic A. Detection of NPM1 exon 12 mutations and FLT3 - internal tandem duplications by high resolution melting analysis in normal karyotype acute myeloid leukemia. J Hematol Oncol 2008; 1: 10. [CrossRef] 18. Do H, Solomon B, Mitchell PL, Fox SB, Dobrovic A. Detection of the transforming AKT1 mutation E17K in non-small cell lung cancer by high resolution melting. BMC Res Notes 2008; 1: 14. [CrossRef] 19. Lin SY, Su YN, Hung CC, Tsay W, Chiou SS, Chang CT, et al. Mutation spectrum of 122 hemophilia A families from Taiwanese population by LD-PCR, DHPLC, multiplex PCR and evaluating the clinical application of HRM. BMC Med Genet 2008; 9: 53. [CrossRef] 20. Ebberink MS, Kofster J, Wanders RJ, Waterham HR. Spectrum of PEX6 mutations in Zellweger syndrome spectrum patients. Hum Mutat 2010; 31: E1058-70. [CrossRef] 21. López-Villar I, Ayala R, Wesselink J, Morillas JD, López E, Marín JC, et al. Simplifying the detection of MUTYH mutations by high resolution melting analysis. BMC Cancer 2010; 10: 408. [CrossRef] 22. Khor GH, Anisah Froemming GR, Zain RB, Abraham TM, Lin TK. Involvement of CELSR3 hypermethylation in primary oral squamous cell carcinoma. Asian Pac J Cancer Prev 2016; 17: 219-23. [CrossRef] 23. Sun Y, Li S, Shen K, Ye S, Cao D, Yang J. DAPK1, MGMT and RARB promoter methylation as biomarkers for high-grade cervical lesions. Int J Clin Exp Pathol 2015; 8: 14939-45. 24. Shao Y, Zhang W, Zhang C, Wu Q, Yang H, Zhang J, et al. High-resolution melting analysis of BLU methylation levels in gastric, colorectal, and pancreatic cancers. Cancer Invest 2010; 28: 642-8. [CrossRef] 25. Heitzer E, Bambach I, Dandachi N, Horn M, Wolf P. PTCH promoter methylation at low level in sporadic basal cell carcinoma analysed by three different approaches. Exp Dermatol 2010; 19: 926-8. [CrossRef] 26. Nicoś M, Krawczyk P, Powrózek T, Szudy P, Jarosz B, Sawicki M, et al. PIK3CA mutations detected in patients with central nervous system metastases of non-small cell lung cancer. Anticancer Res 2016; 36: 2243-9. 27. Draht MX, Smits KM, Jooste V, Tournier B, Vervoort M, Ramaekers C, et al. Analysis of RET promoter CpG island methylation using methylation-specific PCR (MSP), pyrosequencing, and methylation-sensitive high-resolution melting (MS-HRM): impact on stage II colon cancer patient outcome. Clin Epigenetics 2016; 8: 44. [CrossRef] 28. Chang YC, Chang YS, Chang CC, Liu TC, Ko YC, Lee CC, et al. Development of a high-resolution melting method for the screening of TNFAIP3 gene mutations. Oncol Rep 2016; 35: 2936-42. [CrossRef] 29. Koochak A, Rakhshani N, Karbalaie Niya MH, Tameshkel FS, Sohrabi MR, Babaee MR, et al. Mutation analysis of KRAS and BRAF genes in metastatic colorectal cancer: a first large scale study from Iran. Asian Pac J Cancer Prev 2016; 17: 603-8. [CrossRef] 30. Zhao X, Xiao J, Wang H, Ren X, Gao J, Wu Y, et al. Spectrum of COL1A1/2 mutations and gene diagnosis in Chinese patients with osteogenesis imperfecta. Zhonghua Yi Xue Za Zhi 2015; 95: 3484-9. 31. Tian M, Zhao B, Zhang J, Martin FL, Huang Q, Liu L, et al. Association of environmental benzo[a]pyrene exposure and DNA methylation alterations in hepatocellular carcinoma: A Chinese case-control study. Sci Total Environ 2016; 541: 1243-52. [CrossRef] 32. Spitzwieser M, Holzweber E, Pfeiler G, Hacker S, Cichna-Markl M. Applicability of HIN-1, MGMT and RASSF1A promoter methylation as biomarkers for detecting field cancerization in breast cancer. Breast Cancer Res 2015; 17: 125. [CrossRef] 33. Destouni A, Poulou M, Kakourou G, Vrettou C, Tzetis M, Traeger-Synodinos J, et al. Single-cell high resolution melting analysis: A novel, generic, pre-implantation genetic diagnosis (PGD) method applied to cystic fibrosis (HRMA CF-PGD). J Cyst Fibros 2016; 15: 163-70. [CrossRef] 34. Liu L, Sun L, Li C, Li X, Zhang Y, Yu Y, et al. Quantitative detection of methylation of FHIT and BRCA1 promoters in the serum of ductal breast cancer patients. Biomed Mater Eng 2015; 26: S2217-22. [CrossRef] 35. Runov AL, Vonsky MS, Mikhelson VM. DNA methylation level and telomere length as a basis for the biological aging clock model construction. Tsitologiia 2015; 57: 192-6. 36. Qiu C, Zhi Y, Shen Y, Gong J, Li Y, Rong S, et al. Performance of the HPV16 L1 methylation assay and HPV E6/E7 mRNA test for the detection of squamous intraepithelial lesions in cervical cytological samples. J Virol Methods 2015; 224: 35-41. [CrossRef] 37. Odell ID, Cloud JL, Seipp M, Wittwer CT. Rapid species identification within the Mycobacterium chelonae-abscessus group by highresolution melting analysis of hsp65 PCR products. Am J Clin Pathol 2005; 123: 96- 101. [CrossRef] 38. Gago S, Zaragoza Ó, Cuesta I, Rodríguez-Tudela JL, Cuenca-Estrella M, Buitrago MJ. High-resolution melting analysis for identification of the Cryptococcus neoformans-Cryptococcus gattii complex. J Clin Microbiol 2011; 49: 3663-6. [CrossRef] 39. Daniels R, Ndiaye D, Wall M, McKinney J, Séne PD, Sabeti PC, et al. Rapid, field-deployable method for genotyping and discovery of single-nucleotide polymorphisms associated with drug resistance in Plasmodium falciparum. Antimicrob Agents Chemother 2012; 56: 2976-86. [CrossRef] 40. Kovanda A, Poljak M. Real-time polymerase chain reaction assay based on high-resolution melting analysis for the determination of the rs12979860 polymorphism involved in hepatitis C treatment response. J Virol Methods 2011; 175: 125-8.[CrossRef] 41. Wu D, Fu X, Wen Y, Liu B, Deng Z, Dai L, et al. High-resolution melting combines with Bayes discriminant analysis: a novel hepatitis C virus genotyping method. Clin Exp Med 2016 May 13. [Epub ahead of print] [CrossRef] 42. Bezdicek M, Lengerova M, Ricna D, Weinbergerova B, Kocmanova I, Volfova P, et al. Rapid detection of fungal pathogens in bronchoalveolar lavage samples using panfungal PCR combined with high resolution melting analysis. Med Mycol 2016; 54: 714-24. [CrossRef] 43. Sharma K, Modi M, Kaur H, Sharma A, Ray P, Varma S. rpoB gene high-resolution melt curve analysis: a rapid approach for diagnosis and screening of drug resistance in tuberculous meningitis. Diagn Microbiol Infect Dis 2015; 83: 144-9. [CrossRef] Clin Exp Health Sci 2017; 7(1): 20-6 Dirican ve Akkiprik. HRM Yöntemleri ve Uygulamaları 25 44. Zampieri RA, Laranjeira-Silva MF, Muxel SM, Stocco de Lima AC, Shaw JJ, Floeter-Winter LM. high resolution melting analysis targeting hsp70 as a fast and efficient method for the discrimination of leishmania species. PLoS Negl Trop Dis 2016; 10: e0004485. [CrossRef] 45. Pu LM, Nan N, Yang Z, Jin ZN. Association between SUMO4 polymorphisms and type 2 diabetes mellitus. Yi Chuan 2012; 34: 315-25. [CrossRef] 46. Deng JQ, Liu BQ, Wang Y, Liu W, Cai JF, Long R, et al. Y-STR genetic screening by high-resolution melting analysis. Genet Mol Res 2016; 15. [CrossRef] 47. Yimniam W, Jindadamrongwech S. Scanning for α-Hemoglobin variants by high-resolution melting analysis. J Clin Lab Anal 2016; 30: 633-40. [CrossRef] 48. Pindurová E, Zourková A, Zrůstová J, Juřica J, Pavelka A. Alternative reliable method for cytochrome P450 2D6 poor metabolizers genotyping. Mol Biotechnol 2013; 53: 29-40. [CrossRef] 49. Chen T, Murrell M, Fowdar J, Roy B, Grealy R, Griffiths LR. Investigation of the role of the GABRG2 gene variant in migraine. J Neurol Sci 2012; 318: 112-4. [CrossRef] 50. Whittall RA, Scartezini M, Li K, Hubbart C, Reiner Z, Abraha A, et al. Development of a high-resolution melting method for mutation detection in familial hypercholesterolaemia patients. Ann Clin Biochem 2010; 47: 44-55. [CrossRef]

High Resolution Melting Method in Molecular Diagnostics and Their Clinical Importance

Year 2017, Volume: 7 Issue: 1, 20 - 26, 15.03.2017

Abstract

Along with the development of technology in the field of molecular biology, many new molecular analyses are being developed each day. In this review, we aim to explain high-resolution melting (HRM) analysis, which has been shown to be important in molecular diagnostics, its applications, and its importance in the areas of clinical practice. The HRM system in a closed tube is used to determine post-polymerase chain reaction (PCR)-based genetic variations as a new method. The working principle of HRM is based on the melting behavior of nucleic acid samples. The denaturation of double-stranded DNA is determined by detecting the fluorescence change caused by increased melting temperature. The differences between wild-type and heterozygous samples may be easily detected in melting graphics. Using this method, melting curve analysis can be performed with more precision. In HRM analysis, the samples can be distinguished according to the guanine cytosine (GC) content and sequence length. Thus, the detection of common single-nucleotide polymorphisms (SNPs) in the population, scanning of gene mutations associated with diseases, and analysis of DNA methylation can be performed quickly and reliably using the HRM method. Nucleotide sequence variations and several variations in the PCR products can be detected with the DNA melting curve shape using the HRM method. In addition to being low-cost and easily implementable, the real-time HRM method enables powerful analysis because of the combined new-generation DNA dyes and developed gene scanning software, thereby standing out in many clinical applications.

References

  • 1. Ririe KM, Rasmussen RP, Wittwer CT. Product differentiation by analysis of DNA melting curves during the polymerase chain reaction. Anal Biochem 1997; 245: 154-60. [CrossRef] 2. Wittwer CT, Herrmann MG, Gundry CN, Elenitoba-Johnson KS. Real-time multiplex PCR assays. Methods 2001; 25: 430-42. [CrossRef] 3. Gundry CN, Bernard PS, Herrmann MG, Reed GH, Wittwer CT. Rapid F508del and F508C assay using fluorescent hybridization probes. Genet Test 1999; 3: 365-70. [CrossRef] 4. Taylor CF. Mutation scanning using high-resolution melting. Biochem Soc Trans 2009; 37: 433-7. [CrossRef] 5. Fadhil W, Ibrahem S, Seth R, Ilyas M. Quick-multiplex-consensus (QMC)- PCR followed by high-resolution melting: a simple and robust method for mutation detection in formalin-fixed paraffin-embedded tissue. J Clin Pathol 2010; 63: 134-40. [CrossRef] 6. Gallegos Ruiz MI, Floor K, Rijmen F, Grünberg K, Rodriguez JA, Giaccone G. EGFR and K-ras mutation analysis in non-small cell lung cancer: comparison of paraffin embedded versus frozen specimens. Cell Oncol 2007; 29: 257-64. 7. Eischeid AC. SYTO dyes and EvaGreen outperform SYBR Green in real-time PCR. BMC Res Notes 2011; 4: 263. [CrossRef] 8. Monis PT, Giglio S, Saint CP. Comparison of SYTO9 and SYBR Green I for real-time polymerase chain reaction and investigation of the effect of dye concentration on amplification and DNA melting curve analysis. Anal Biochem 2005; 340: 24-34. [CrossRef] Dirican ve Akkiprik. HRM Yöntemleri ve Uygulamaları Clin Exp Health Sci 2017; 7(1): 20-6 24 9. Chanock SJ, Burdett L, Yeager M, Llaca V, Langerød A, Presswalla S, et al. Somatic sequence alterations in twenty-one genes selected by expression profile analysis of breast carcinomas. Breast Cancer Res 2007; 9: R5. [CrossRef] 10. White H, Potts G. Mutation Scanning by High Resolution Melt Analysis. Evaluation of Rotor-Gene 6000 (Corbett Life Science), HR-1 and 384-Well Lightscanner (Idaho Technology) Wessex, UK: National Genetics Reference Laboratory; 2006. 11. Garritano S, Gemignani F, Voegele C, Nguyen-Dumont T, Le Calvez-Kelm F, De Silva D, et al. Determining the effectiveness of High Resolution Melting analysis for SNP genotyping and mutation scanning at the TP53 locus. BMC Genet 2009; 10: 5. [CrossRef] 12. Dirican E, Kaya Z, Gullu G, Peker I, Ozmen T, Gulluoglu BM, et al. Detection of PIK3CA gene mutations with HRM analysis and association with IGFBP-5 expression levels in breast cancer. Asian Pac J Cancer Prev 2014; 15: 9327-33. [CrossRef] 13. Moghadam AA, Mahjoubi F, Reisi N, Vosough P. Investigation of FANCA gene in Fanconi anaemia patients in Iran. Indian J Med Res 2016; 143: 184-96. [CrossRef] 14. Tserga A, Chatziandreou I, Michalopoulos NV, Patsouris E, Saetta AA. Mutation of genes of the PI3K/AKT pathway in breast cancer supports their potential importance as biomarker for breast cancer aggressiveness. Virchows Arch 2016; 469: 35-43. [CrossRef] 15. Chang YS, Lin CY, Yang SF, Ho CM, Chang JG. Analysing the mutational status of adenomatous polyposis coli (APC) gene in breast cancer. Cancer Cell Int 2016; 16: 23. [CrossRef] 16. Takano EA, Mitchell G, Fox SB, Dobrovic A. Rapid detection of carriers with BRCA1 and BRCA2 mutations using high resolution melting analysis. BMC Cancer 2008; 8: 59. [CrossRef] 17. Tan AY, Westerman DA, Carney DA, Seymour JF, Juneja S, Dobrovic A. Detection of NPM1 exon 12 mutations and FLT3 - internal tandem duplications by high resolution melting analysis in normal karyotype acute myeloid leukemia. J Hematol Oncol 2008; 1: 10. [CrossRef] 18. Do H, Solomon B, Mitchell PL, Fox SB, Dobrovic A. Detection of the transforming AKT1 mutation E17K in non-small cell lung cancer by high resolution melting. BMC Res Notes 2008; 1: 14. [CrossRef] 19. Lin SY, Su YN, Hung CC, Tsay W, Chiou SS, Chang CT, et al. Mutation spectrum of 122 hemophilia A families from Taiwanese population by LD-PCR, DHPLC, multiplex PCR and evaluating the clinical application of HRM. BMC Med Genet 2008; 9: 53. [CrossRef] 20. Ebberink MS, Kofster J, Wanders RJ, Waterham HR. Spectrum of PEX6 mutations in Zellweger syndrome spectrum patients. Hum Mutat 2010; 31: E1058-70. [CrossRef] 21. López-Villar I, Ayala R, Wesselink J, Morillas JD, López E, Marín JC, et al. Simplifying the detection of MUTYH mutations by high resolution melting analysis. BMC Cancer 2010; 10: 408. [CrossRef] 22. Khor GH, Anisah Froemming GR, Zain RB, Abraham TM, Lin TK. Involvement of CELSR3 hypermethylation in primary oral squamous cell carcinoma. Asian Pac J Cancer Prev 2016; 17: 219-23. [CrossRef] 23. Sun Y, Li S, Shen K, Ye S, Cao D, Yang J. DAPK1, MGMT and RARB promoter methylation as biomarkers for high-grade cervical lesions. Int J Clin Exp Pathol 2015; 8: 14939-45. 24. Shao Y, Zhang W, Zhang C, Wu Q, Yang H, Zhang J, et al. High-resolution melting analysis of BLU methylation levels in gastric, colorectal, and pancreatic cancers. Cancer Invest 2010; 28: 642-8. [CrossRef] 25. Heitzer E, Bambach I, Dandachi N, Horn M, Wolf P. PTCH promoter methylation at low level in sporadic basal cell carcinoma analysed by three different approaches. Exp Dermatol 2010; 19: 926-8. [CrossRef] 26. Nicoś M, Krawczyk P, Powrózek T, Szudy P, Jarosz B, Sawicki M, et al. PIK3CA mutations detected in patients with central nervous system metastases of non-small cell lung cancer. Anticancer Res 2016; 36: 2243-9. 27. Draht MX, Smits KM, Jooste V, Tournier B, Vervoort M, Ramaekers C, et al. Analysis of RET promoter CpG island methylation using methylation-specific PCR (MSP), pyrosequencing, and methylation-sensitive high-resolution melting (MS-HRM): impact on stage II colon cancer patient outcome. Clin Epigenetics 2016; 8: 44. [CrossRef] 28. Chang YC, Chang YS, Chang CC, Liu TC, Ko YC, Lee CC, et al. Development of a high-resolution melting method for the screening of TNFAIP3 gene mutations. Oncol Rep 2016; 35: 2936-42. [CrossRef] 29. Koochak A, Rakhshani N, Karbalaie Niya MH, Tameshkel FS, Sohrabi MR, Babaee MR, et al. Mutation analysis of KRAS and BRAF genes in metastatic colorectal cancer: a first large scale study from Iran. Asian Pac J Cancer Prev 2016; 17: 603-8. [CrossRef] 30. Zhao X, Xiao J, Wang H, Ren X, Gao J, Wu Y, et al. Spectrum of COL1A1/2 mutations and gene diagnosis in Chinese patients with osteogenesis imperfecta. Zhonghua Yi Xue Za Zhi 2015; 95: 3484-9. 31. Tian M, Zhao B, Zhang J, Martin FL, Huang Q, Liu L, et al. Association of environmental benzo[a]pyrene exposure and DNA methylation alterations in hepatocellular carcinoma: A Chinese case-control study. Sci Total Environ 2016; 541: 1243-52. [CrossRef] 32. Spitzwieser M, Holzweber E, Pfeiler G, Hacker S, Cichna-Markl M. Applicability of HIN-1, MGMT and RASSF1A promoter methylation as biomarkers for detecting field cancerization in breast cancer. Breast Cancer Res 2015; 17: 125. [CrossRef] 33. Destouni A, Poulou M, Kakourou G, Vrettou C, Tzetis M, Traeger-Synodinos J, et al. Single-cell high resolution melting analysis: A novel, generic, pre-implantation genetic diagnosis (PGD) method applied to cystic fibrosis (HRMA CF-PGD). J Cyst Fibros 2016; 15: 163-70. [CrossRef] 34. Liu L, Sun L, Li C, Li X, Zhang Y, Yu Y, et al. Quantitative detection of methylation of FHIT and BRCA1 promoters in the serum of ductal breast cancer patients. Biomed Mater Eng 2015; 26: S2217-22. [CrossRef] 35. Runov AL, Vonsky MS, Mikhelson VM. DNA methylation level and telomere length as a basis for the biological aging clock model construction. Tsitologiia 2015; 57: 192-6. 36. Qiu C, Zhi Y, Shen Y, Gong J, Li Y, Rong S, et al. Performance of the HPV16 L1 methylation assay and HPV E6/E7 mRNA test for the detection of squamous intraepithelial lesions in cervical cytological samples. J Virol Methods 2015; 224: 35-41. [CrossRef] 37. Odell ID, Cloud JL, Seipp M, Wittwer CT. Rapid species identification within the Mycobacterium chelonae-abscessus group by highresolution melting analysis of hsp65 PCR products. Am J Clin Pathol 2005; 123: 96- 101. [CrossRef] 38. Gago S, Zaragoza Ó, Cuesta I, Rodríguez-Tudela JL, Cuenca-Estrella M, Buitrago MJ. High-resolution melting analysis for identification of the Cryptococcus neoformans-Cryptococcus gattii complex. J Clin Microbiol 2011; 49: 3663-6. [CrossRef] 39. Daniels R, Ndiaye D, Wall M, McKinney J, Séne PD, Sabeti PC, et al. Rapid, field-deployable method for genotyping and discovery of single-nucleotide polymorphisms associated with drug resistance in Plasmodium falciparum. Antimicrob Agents Chemother 2012; 56: 2976-86. [CrossRef] 40. Kovanda A, Poljak M. Real-time polymerase chain reaction assay based on high-resolution melting analysis for the determination of the rs12979860 polymorphism involved in hepatitis C treatment response. J Virol Methods 2011; 175: 125-8.[CrossRef] 41. Wu D, Fu X, Wen Y, Liu B, Deng Z, Dai L, et al. High-resolution melting combines with Bayes discriminant analysis: a novel hepatitis C virus genotyping method. Clin Exp Med 2016 May 13. [Epub ahead of print] [CrossRef] 42. Bezdicek M, Lengerova M, Ricna D, Weinbergerova B, Kocmanova I, Volfova P, et al. Rapid detection of fungal pathogens in bronchoalveolar lavage samples using panfungal PCR combined with high resolution melting analysis. Med Mycol 2016; 54: 714-24. [CrossRef] 43. Sharma K, Modi M, Kaur H, Sharma A, Ray P, Varma S. rpoB gene high-resolution melt curve analysis: a rapid approach for diagnosis and screening of drug resistance in tuberculous meningitis. Diagn Microbiol Infect Dis 2015; 83: 144-9. [CrossRef] Clin Exp Health Sci 2017; 7(1): 20-6 Dirican ve Akkiprik. HRM Yöntemleri ve Uygulamaları 25 44. Zampieri RA, Laranjeira-Silva MF, Muxel SM, Stocco de Lima AC, Shaw JJ, Floeter-Winter LM. high resolution melting analysis targeting hsp70 as a fast and efficient method for the discrimination of leishmania species. PLoS Negl Trop Dis 2016; 10: e0004485. [CrossRef] 45. Pu LM, Nan N, Yang Z, Jin ZN. Association between SUMO4 polymorphisms and type 2 diabetes mellitus. Yi Chuan 2012; 34: 315-25. [CrossRef] 46. Deng JQ, Liu BQ, Wang Y, Liu W, Cai JF, Long R, et al. Y-STR genetic screening by high-resolution melting analysis. Genet Mol Res 2016; 15. [CrossRef] 47. Yimniam W, Jindadamrongwech S. Scanning for α-Hemoglobin variants by high-resolution melting analysis. J Clin Lab Anal 2016; 30: 633-40. [CrossRef] 48. Pindurová E, Zourková A, Zrůstová J, Juřica J, Pavelka A. Alternative reliable method for cytochrome P450 2D6 poor metabolizers genotyping. Mol Biotechnol 2013; 53: 29-40. [CrossRef] 49. Chen T, Murrell M, Fowdar J, Roy B, Grealy R, Griffiths LR. Investigation of the role of the GABRG2 gene variant in migraine. J Neurol Sci 2012; 318: 112-4. [CrossRef] 50. Whittall RA, Scartezini M, Li K, Hubbart C, Reiner Z, Abraha A, et al. Development of a high-resolution melting method for mutation detection in familial hypercholesterolaemia patients. Ann Clin Biochem 2010; 47: 44-55. [CrossRef]
There are 1 citations in total.

Details

Primary Language Turkish
Subjects Health Care Administration
Journal Section Articles
Authors

Ebubekir Dirican This is me

Mustafa Akkiprik This is me

Publication Date March 15, 2017
Submission Date May 23, 2016
Published in Issue Year 2017 Volume: 7 Issue: 1

Cite

APA Dirican, E., & Akkiprik, M. (2017). Moleküler Tanıda Yüksek Çözünürlüklü Erime Yöntemi ve Klinik Önemi. Clinical and Experimental Health Sciences, 7(1), 20-26.
AMA Dirican E, Akkiprik M. Moleküler Tanıda Yüksek Çözünürlüklü Erime Yöntemi ve Klinik Önemi. Clinical and Experimental Health Sciences. March 2017;7(1):20-26.
Chicago Dirican, Ebubekir, and Mustafa Akkiprik. “Moleküler Tanıda Yüksek Çözünürlüklü Erime Yöntemi Ve Klinik Önemi”. Clinical and Experimental Health Sciences 7, no. 1 (March 2017): 20-26.
EndNote Dirican E, Akkiprik M (March 1, 2017) Moleküler Tanıda Yüksek Çözünürlüklü Erime Yöntemi ve Klinik Önemi. Clinical and Experimental Health Sciences 7 1 20–26.
IEEE E. Dirican and M. Akkiprik, “Moleküler Tanıda Yüksek Çözünürlüklü Erime Yöntemi ve Klinik Önemi”, Clinical and Experimental Health Sciences, vol. 7, no. 1, pp. 20–26, 2017.
ISNAD Dirican, Ebubekir - Akkiprik, Mustafa. “Moleküler Tanıda Yüksek Çözünürlüklü Erime Yöntemi Ve Klinik Önemi”. Clinical and Experimental Health Sciences 7/1 (March 2017), 20-26.
JAMA Dirican E, Akkiprik M. Moleküler Tanıda Yüksek Çözünürlüklü Erime Yöntemi ve Klinik Önemi. Clinical and Experimental Health Sciences. 2017;7:20–26.
MLA Dirican, Ebubekir and Mustafa Akkiprik. “Moleküler Tanıda Yüksek Çözünürlüklü Erime Yöntemi Ve Klinik Önemi”. Clinical and Experimental Health Sciences, vol. 7, no. 1, 2017, pp. 20-26.
Vancouver Dirican E, Akkiprik M. Moleküler Tanıda Yüksek Çözünürlüklü Erime Yöntemi ve Klinik Önemi. Clinical and Experimental Health Sciences. 2017;7(1):20-6.

14639   14640