| Summary: | 碩士 === 臺北醫學大學 === 醫學技術學系 === 94 === Purpose: Lung cancer is the leading cause of cancer deaths in Taiwan. Traditional radiography and sputum cytology have not been successfully reducing lung cancer mortality. It’s urgent to develop high sensitive molecular marker panel for large early lung cancer screening.
Strategy: Carcinogenesis is a multi-step process resulting from the accumulation of errors in vital regulatory pathways. The present study was designed to select multiple DNA markers, which have high sensitivity and specificity to serve as diagnostic biomarkers for lung cancer detection.
Methods: Part I, we examined the promoter hypermethylation of three tumor suppressor genes (FHIT, p16INK4a, and RARβ) by methylation-specific PCR (MSP), and the instability of eight microsatellite markers (D3S1234, D3S1285, D5S1456, D9S286, D9S942, GATA49D12, D13S170, and D17S786) by loss of heterozygosity (LOH) and microsatellite instability (MSI) analyses in lung tumor cells and matched sputum specimens from 83 lung cancer patients. Part II, we examined the promoter hypermethylation of six tumor suppressor genes (BLU, CDH13, FHIT, p16INK4a, RARβ, and RASSF1A) by MSP assay in lung tumor tissues and matched plasma specimens from 63 lung cancer patients. In addition, the DNA concentration in plasma was tested in 63 lung cancer patients and 36 cancer-free individuals. The 36 cancer-free individuals were also used as the negative control of part I study.
Results: Part I sputum study, based on the results of sensitivity, specificity, and concordance from each marker analyzed, we selected seven biomarkers, which were LOH of D9S286, D9S942, GATA49D12, and D13S170, MSI of D9S942, and methylation of p16INK4a and RARβ. In addition, the odds ratio of D9S942 LOH in sputum was 5.6 (95% confidence interval, CI: 1.78~19.46, P=0.003), and the odds ratio of p16INK4a methylation in sputum was 4.15 (95% CI: 1.46~15.02, P=0.006). Using a definition that patient with cancer risk had alteration in more than two among seven selected biomarkers, we achieved a sensitivity of 80%, a specificity of 72%, and a concordance of 77%.
Part II plasma study, p16INK4a, RARβ, and RASSF1A genes had higher promoter hypermethylation frequencies. In addition, the odds ratio of p16INK4a methylation and RASSF1A methylation in plasma was 6.18 (95%CI: 1.89~28.0, P=0.002) and 6.02 (95% CI: 1.82~27.52, P=0.002), respectively. Using a definition of risk individual showing alteration in more than one of the three selected biomarkers, we achieved a sensitivity of 74%, a specificity of 78%, and a concordance of 75%. The regression model calculated from the training set (43 cancer patients, 22 cancer-free individuals) had a match score of 82% comparing to the test set (20 cancer patients, 14 cancer-free individuals). The new regression model Y =0.35＋0.30 (BLU methyl)＋1.84(p16INK4a methyl)＋1.70 (RASSF1A methyl), which calculated by overall cases (63 cancer patients, 36 cancer-free individuals), achieved a sensitivity of 77%, a specificity of 90%, and a concordance of 79%. In addition, the DNA concentration of plasma showed that the median DNA concentration of lung cancer patients (63.47ng/μl) was significantly higher than cancer-free individuals (38.50ng/μl) (P<0.0001). When the cut-off value was defined as 50 ng/μl of the DNA concentration in plasma, we achieved a sensitivity of 71% and a specificity of 61%. Additionally, the odds ratio of the DNA concentration in plasma determined by this cut-off value was 3.42 (95%CI: 1.47~8.25, P=0.004).
Conclusion: These selected early-etiologically associated biomarkers such as the seven selected LOH and methylation markers in spututm and DNA concentration in plasma can potentially be tested as supplement biomarkers for early lung cancer detection in the future.
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