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Review
, 7 (48), 80019-80032

Diagnostic Accuracy of DNA Methylation for Head and Neck Cancer Varies by Sample Type and Number of Markers Tested

Affiliations
Review

Diagnostic Accuracy of DNA Methylation for Head and Neck Cancer Varies by Sample Type and Number of Markers Tested

Xu Ji et al. Oncotarget.

Abstract

Abnormal methylation of certain cancer related genes strongly predicts a diagnosis of head and neck cancer (HNC), while the predictive power of methylation of other DNA markers for HNC remains unclear. To systemically assess the diagnostic value of DNA methylation patterns for HNC and the effect of methylation platform techniques and sample types, we performed a PubMed search for studies of the correlation between DNA methylation and HNC completed before July 2016, and extracted the sensitivity and specificity for methylated biomarkers. Across these studies, DNA methylation showed high sensitivity for diagnosing HNC in solid tissue (0.57), and high specificity in saliva (0.89). Area under the curve (AUC) from summary receiver operating characteristic (SROC) curves revealed that DNA methylation had more diagnostic power in solid tissue (AUC = 0.82) than saliva (AUC = 0.80) or blood (AUC = 0.77). Combinations of multiple methylated genes were more sensitive diagnostic markers than single methylated genes. Our results suggest that the diagnostic accuracy of methylated biomarkers for HNC varied by sample type and were most accurate when results from multiple sample types were considered.

Keywords: DNA methylation; biopsy type; diagnostic accuracy; head and neck cancer; meta-analysis.

Conflict of interest statement

CONFLICTS OF INTEREST

DTR: none; SO: Consulting: Novartis, BMS, MSD; KK: none; TYS: Honoraria: Astra Zeneca, Amgen, BMS, Innate, Jounce, SD; FK: none; IT: none; UK: Honoraria: AmGen, Astra Zeneca, BMS, Glycotope, GSK, Merck Serono, Merck/MSD, Pfizer, Research Support: Innate Pharma, Sirtec, Pfizer.

Figures

Figure 1
Figure 1. Flow chart showing the study retrieval process
Figure 2
Figure 2. Forest plot of estimate of diagnostic accuracy using methylated biomarkers
A. Forest plot of estimate of sensitivity and specificity of methylated biomarkers in saliva. B. Forest plot of estimate of sensitivity and specificity of methylated biomarkers in tissue. C. Forest plot of estimate of sensitivity and specificity of methylated biomarkers in blood.
Figure 3
Figure 3. SROC curves of studies relating to the detection of HNC in different biopsy types
Figure 4
Figure 4. Risk of bias graph
Two authors independently evaluated the items of bias. If the study reported all of the sensitivities and specificities of genes that were measured DNA methylation status, selective reporting was defined as low risk.
Figure 5
Figure 5. Funnel plot to assess bias in estimates of diagnostic odds ratio caused by small-study effects
A. Saliva. B. Solid tissue. C. Blood.

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