DOI QR코드

DOI QR Code

High Resolution Melting Analysis for Epidermal Growth Factor Receptor Mutations in Formalin-fixed Paraffin-embedded Tissue and Plasma Free DNA from Non-small Cell Lung Cancer Patients

  • Jing, Chang-Wen (Clinical Cancer Research Center, Jiangsu Cancer Hospical) ;
  • Wang, Zhuo (Clinical Cancer Research Center, Jiangsu Cancer Hospical) ;
  • Cao, Hai-Xia (Department of Epidemiology, Jiangsu Cancer Hospical) ;
  • Ma, Rong (Clinical Cancer Research Center, Jiangsu Cancer Hospical) ;
  • Wu, Jian-Zhong (Clinical Cancer Research Center, Jiangsu Cancer Hospical)
  • Published : 2013.11.30

Abstract

Background:The aim of the research was to explore a cost effective, fast, easy to perform, and sensitive method for epidermal growth factor receptor (EGFR) mutation testing. Methods: High resolution melting analysis (HRM) was introduced to evaluate the efficacy of the analysis for dectecting EGFR mutations in exons 18 to 21 using formalin-fixed paraffin-embedded (FFPE) tissues and plasma free DNA from 120 patients. Results: The total EGFR mutation rate was 37.5% (45/120) detected by direct sequencing. There were 48 mutations in 120 FFPE tissues assessed by HRM. For plasma free DNA, the EGFR mutation rate was 25.8% (31/120). The sensitivity of HRM assays in FFPE samples was 100% by HRM. There was a low false-positive mutation rate but a high false-negative rate in plasma free DNA detected by HRM. Conclusions: Our results show that HRM analysis has the advantage of small tumor sample need. HRM applied with plasma free DNA showed a high false-negative rate but a low false-positive rate. Further research into appropriate methods and analysis needs to be performed before HRM for plasma free DNA could be accepted as an option in diagnostic or screening settings.

Keywords

References

  1. Do H, Krypuy M, Mitchell PL, et al (2008). High resolution melting analysis for rapid and sensitive EGFR and KRAS mutation detection in formalin fixed paraffin embedded biopsies. BMC Cancer, 8, 142. https://doi.org/10.1186/1471-2407-8-142
  2. Goto K, Ichinose Y, Ohe Y, et al (2012). Epidermal growth factor receptor mutation status in circulating free DNA in serum: from IPASS, a phase III study of gefitinib or carboplatin/paclitaxel in non-small cell lung cancer. J Thorac Oncol, 7, 115-21. https://doi.org/10.1097/JTO.0b013e3182307f98
  3. Govindan R, Page N, Morgensztern D, et al (2006). Changing epidemiology of small-cell lung cancer in the United States over the last 30 years: analysis of the surveillance, epidemiologic, and end results database. J Clin Oncol, 24, 4539-44. https://doi.org/10.1200/JCO.2005.04.4859
  4. Hu C, Liu X, Chen Y, et al (2012). Direct serum and tissue assay for EGFR mutation in non-small cell lung cancer by high-resolution melting analysis. Oncol Rep, 28, 1815-21. https://doi.org/10.3892/or.2012.1987
  5. Jian G, Songwen Z, Ling Z, et al (2010). Prediction of epidermal growth factor receptor mutations in the plasma/pleural effusion to efficacy of gefitinib treatment in advanced non-small cell lung cancer. J Cancer Res Clin Oncol, 136, 1341-7. https://doi.org/10.1007/s00432-010-0785-z
  6. Jiang B, Liu F, Yang L, et al (2011). Serum detection of epidermal growth factor receptor gene mutations using mutant-enriched sequencing in Chinese patients with advanced non-small cell lung cancer. J Int Med Res, 39, 1392-401. https://doi.org/10.1177/147323001103900425
  7. Kim HR, Lee SY, Hyun DS, et al (2013). Detection of EGFR mutations in circulating free DNA by PNA-mediated PCR clamping. J Exp Clin Cancer Res, 32, 50. https://doi.org/10.1186/1756-9966-32-50
  8. Kimura H, Kasahara K, Kawaishi M, et al (2006a). Detection of epidermal growth factor receptor mutations in serum as a predictor of the response to gefitinib in patients with non-small-cell lung cancer. Clin Cancer Res, 12, 3915-21. https://doi.org/10.1158/1078-0432.CCR-05-2324
  9. Kimura H, Kasahara K, Shibata K, et al (2006b). EGFR mutation of tumor and serum in gefitinib-treated patients with chemotherapy-naive non-small cell lung cancer. J Thorac Oncol, 1, 260-7. https://doi.org/10.1016/S1556-0864(15)31577-X
  10. Krypuy M, Ahmed AA, Etemadmoghadam D, et al (2007). High resolution melting for mutation scanning of TP53 exons 5-8. BMC Cancer, 7, 168. https://doi.org/10.1186/1471-2407-7-168
  11. Kuang Y, Rogers A, Yeap BY, et al (2009). Non-invasive detection of EGFR T790M in gefitinib or erlotinib resistant non-small cell lung cancer. Clin Cancer Res, 15, 2630-6. https://doi.org/10.1158/1078-0432.CCR-08-2592
  12. Mack PC, Holland WS, Burich RA, et al (2009). EGFR mutations detected in plasma are associated with patient outcomes in erlotinib plus docetaxel-treated non-small cell lung cancer. J Thorac Oncol, 4, 1466-72. https://doi.org/10.1097/JTO.0b013e3181bbf239
  13. Maemondo M, Inoue A, Kobayashi K, et al (2010). Gefitinib or chemotherapy for non-small-cell lung cancer with mutated EGFR. N Engl J Med, 362, 2380-8. https://doi.org/10.1056/NEJMoa0909530
  14. Maheswaran S, Sequist LV, Nagrath S, et al (2008). Detection of mutations in EGFR in circulating lung-cancer cells. N Engl J Med, 359, 366-77. https://doi.org/10.1056/NEJMoa0800668
  15. Mitsudomi T, Morita S, Yatabe Y, et al (2010). Gefitinib versus cisplatin plus docetaxel in patients with non-small-cell lung cancer harbouring mutations of the epidermal growth factor receptor (WJTOG3405): an open label, randomised phase 3 trial. Lancet Oncol, 11, 121-8. https://doi.org/10.1016/S1470-2045(09)70364-X
  16. Nicholson RI, Gee JM, Harper ME. (2001). EGFR and cancer prognosis. Eur J Cancer, 37 Suppl 4, S9-15.
  17. Nomoto K, Tsuta K, Takano T, et al (2006). Detection of EGFR mutations in archived cytologic specimens of non-small cell lung cancer using high-resolution melting analysis. Am J Clin Pathol, 126, 608-15. https://doi.org/10.1309/N5PQNGW2QKMX09X7
  18. Pathak AK, Bhutani M, Kumar S, et al (2006). Circulating cell-free DNA in plasma/serum of lung cancer patients as a potential screening and prognostic tool. Clin Chem, 52, 1833-42.
  19. Scaltriti M and Baselga J (2006). The epidermal growth factor receptor pathway: a model for targeted therapy. Clin Cancer Res, 12, 5268-72. https://doi.org/10.1158/1078-0432.CCR-05-1554
  20. Shigematsu H, Lin L, Takahashi T, et al (2005). Clinical and biological features associated with epidermal growth factor receptor gene mutations in lung cancers. J Natl Cancer Inst, 97, 339-46. https://doi.org/10.1093/jnci/dji055
  21. Sozzi G, Conte D, Leon M, et al (2003). Quantification of free circulating DNA as a diagnostic marker in lung cancer. J Clin Oncol, 21, 3902-8. https://doi.org/10.1200/JCO.2003.02.006
  22. Takano EA, Mitchell G, Fox S B, et al (2008). Rapid detection of carriers with BRCA1 and BRCA2 mutations using high resolution melting analysis. BMC Cancer, 8, 59. https://doi.org/10.1186/1471-2407-8-59
  23. Thatcher N, Chang A, Parikh P, et al (2005). Gefitinib plus best supportive care in previously treated patients with refractory advanced non-small-cell lung cancer: results from a randomised, placebo-controlled, multicentre study (Iressa Survival Evaluation in Lung Cancer). Lancet, 366, 1527-37. https://doi.org/10.1016/S0140-6736(05)67625-8
  24. Wojdacz TK, Dobrovic A (2007). Methylation-sensitive high resolution melting (MS-HRM): a new approach for sensitive and high-throughput assessment of methylation. Nucleic Acids Res, 35, e41. https://doi.org/10.1093/nar/gkm013
  25. Zhou C, Wu YL, Chen G, et al (2011). Erlotinib versus chemotherapy as first-line treatment for patients with advanced EGFR mutation-positive non-small-cell lung cancer (OPTIMAL, CTONG-0802): a multicentre, open-label, randomised, phase 3 study. Lancet Oncol, 12, 735-42. https://doi.org/10.1016/S1470-2045(11)70184-X

Cited by

  1. High Feasibility of Liquid-Based Cytological Samples for Detection of EGFR Mutations in Chinese Patients with NSCLC vol.15, pp.18, 2014, https://doi.org/10.7314/APJCP.2014.15.18.7885
  2. Non-invasive approaches to monitor EGFR-TKI treatment in non-small-cell lung cancer vol.8, pp.1, 2015, https://doi.org/10.1186/s13045-015-0193-6
  3. Latest technological developments in the analysis of circulating tumor DNA vol.28, pp.2, 2016, https://doi.org/10.1007/s11825-016-0089-z
  4. Is the determination of ctDNA a scientific “spy” that foresees cancer? vol.7, pp.2, 2017, https://doi.org/10.5320/wjr.v7.i2.35
  5. Incorporating blood-based liquid biopsy information into cancer staging: time for a TNMB system? vol.29, pp.2, 2018, https://doi.org/10.1093/annonc/mdx766
  6. Tissue or blood: which is more suitable for detection of EGFR mutations in non-small cell lung cancer? vol.33, pp.1, 2018, https://doi.org/10.5301/ijbm.5000256
  7. Circulating tumor DNA (ctDNA) in the era of personalized cancer therapy vol.17, pp.1, 2018, https://doi.org/10.1007/s40200-018-0334-x
  8. Role of circulating tumor DNA in the management of early-stage lung cancer vol.9, pp.5, 2018, https://doi.org/10.1111/1759-7714.12622