The Indirect Efficacy Comparison of DNA Methylation in Sputum for Early Screening and Auxiliary Detection of Lung Cancer: A Meta-Analysis
Open Access
- 23 June 2017
- journal article
- research article
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 14 (7) , 679
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.Keywords
Funding Information
- National Natural Science Foundation of China (81370083, 81673247)
- National Natural Sciences Foundation of China (NSFC)-Australian National Health and Medical Research Council (NHMRC) Joint Research Project (NSFC 81561128020-NHMRC APP1112767)
- Beijing Nova Program (Z141107001814058)
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