Methylated Cell-Free Tumor DNA in Sputum as a Tool for Diagnosing Lung Cancer-A Systematic Review and Meta-Analysis

Simple Summary Lung cancer is one of the deadliest cancers worldwide, and the prognosis is poor. The disease is potentially curable if detected at an early stage, but currently, the only widely implemented screening tool is low-dose computed tomography. Biomarkers such as methylated tumor DNA may be used for the early detection of lung cancer, and sputum is an appealing, non-invasive sample type. With this systematic review and meta-analysis, we aimed to identify all studies evaluating the quantitative methylation of tumor DNA in sputum samples for lung cancer detection. A systematic overview of all the available evidence may highlight areas of improvement as well as certain high-performing genes to prioritize in future studies.Abstract Lung cancer is the leading cause of cancer-related mortality worldwide. Early diagnosis is pivotal for the prognosis. There is a notable overlap between lung cancer and chronic bronchitis, and the potential use of methylated tumor DNA in sputum as a biomarker for lung cancer detection is appealing. This systematic review and meta-analysis followed the PRISMA 2020 statement. A comprehensive search was conducted in Embase, Medline, Web of Science, and the Cochrane Library, using these search strings: Lung cancer, sputum, and methylated tumor DNA. A total of 15 studies met the eligibility criteria. Studies predominantly utilized a case-control design, with sensitivity ranging from 10 to 93% and specificity from 8 to 100%. A meta-analysis of all genes across studies resulted in a summary sensitivity of 54.3% (95% CI 49.4-59.2%) and specificity of 79.7% (95% CI 75.0-83.7%). Notably, two less explored genes (TAC1, SOX17) demonstrated sensitivity levels surpassing 85%. The study's findings highlight substantial variations in the sensitivity and specificity of methylated tumor DNA in sputum for lung cancer detection. Challenges in reproducibility could stem from differences in tumor site, sample acquisition, extraction methods, and methylation measurement techniques. This meta-analysis provides a foundation for prioritizing high-performing genes, calling for a standardization and refinement of methodologies before potential application in clinical trials.