Author
Listed:
- Di Liu
(Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China)
- Hongli Peng
(Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China)
- Qi Sun
(Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China)
- Zhongyao Zhao
(Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China)
- Xinwei Yu
(Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China
School of Medical and Health Sciences, Edith Cowan University, Perth 6027, Australia)
- Siqi Ge
(Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China
School of Medical and Health Sciences, Edith Cowan University, Perth 6027, Australia)
- Hao Wang
(Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China)
- Honghong Fang
(Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China)
- Qing Gao
(Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China)
- Jiaonan Liu
(Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China)
- Lijuan Wu
(Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China)
- Manshu Song
(Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China)
- Youxin Wang
(Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China
School of Medical and Health Sciences, Edith Cowan University, Perth 6027, Australia)
Abstract
Background: DNA methylation in sputum has been an attractive candidate biomarker for the non-invasive screening and detection of lung cancer. Materials and Methods: Databases including PubMed, Ovid, Cochrane library, Web of Science databases, Chinese Biological Medicine (CBM), Chinese National Knowledge Infrastructure (CNKI), Wanfang, Vip Databases and Google Scholar were searched to collect the diagnostic trials on aberrant DNA methylation in the screening and detection of lung cancer published until 1 December 2016. Indirect comparison meta-analysis was used to evaluate the diagnostic value of the included candidate genes. Results: The systematic literature search yielded a total of 33 studies including a total of 4801 subjects (2238 patients with lung cancer and 2563 controls) and covering 32 genes. We identified that methylated genes in sputum samples for the early screening and auxiliary detection of lung cancer yielded an overall sensitivity of 0.46 (0.41–0.50) and specificity of 0.83 (0.80–0.86). Combined indirect comparisons identified the superior gene of SOX17 (sensitivity: 0.84, specificity: 0.88), CDO1 (sensitivity: 0.78, specificity: 0.67), ZFP42 (sensitivity: 0.87, specificity: 0.63) and TAC1 (sensitivity: 0.86, specificity: 0.75). Conclusions: The present meta-analysis demonstrates that methylated SOX17 , CDO1 , ZFP42 , TAC1 , FAM19A4 , FHIT , MGMT , p16 , and RASSF1A are potential superior biomarkers for the screening and auxiliary detection of lung cancer.
Suggested Citation
Di Liu & Hongli Peng & Qi Sun & Zhongyao Zhao & Xinwei Yu & Siqi Ge & Hao Wang & Honghong Fang & Qing Gao & Jiaonan Liu & Lijuan Wu & Manshu Song & Youxin Wang, 2017.
"The Indirect Efficacy Comparison of DNA Methylation in Sputum for Early Screening and Auxiliary Detection of Lung Cancer: A Meta-Analysis,"
IJERPH, MDPI, vol. 14(7), pages 1-14, June.
Handle:
RePEc:gam:jijerp:v:14:y:2017:i:7:p:679-:d:102461
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References listed on IDEAS
- Gyeongsil Lee & Seung-Won Oh & Seung-Sik Hwang & Ji Won Yoon & Sungchan Kang & Hee-Kyung Joh & Hyuktae Kwon & Jeehyun Kim & Danbee Park, 2017.
"Comparative effectiveness of oral antidiabetic drugs in preventing cardiovascular mortality and morbidity: A network meta-analysis,"
PLOS ONE, Public Library of Science, vol. 12(5), pages 1-16, May.
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"Association between MGMT Promoter Methylation and Non-Small Cell Lung Cancer: A Meta-Analysis,"
PLOS ONE, Public Library of Science, vol. 8(9), pages 1-1, September.
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"The Prognostic Role of RASSF1A Promoter Methylation in Breast Cancer: A Meta-Analysis of Published Data,"
PLOS ONE, Public Library of Science, vol. 7(5), pages 1-7, May.
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