Comparison of quantification algorithms for circulating cell-free DNA methylation biomarkers in blood plasma from cancer patients

Abstract

Background SHOX2 and SEPT9 methylation in circulating cell-free DNA (ccfDNA) in blood are established powerful and clinically valuable biomarkers for diagnosis, staging, prognosis, and monitoring of cancer patients. The aim of the present study was to evaluate different quantification algorithms (relative quantification, absolute quantification, quasi-digital PCR) with regard to their clinical performance.MethodsMethylation analyses were performed in a training cohort (141 patients with head and neck squamous cell carcinoma [HNSCC], 170 control cases) and a testing cohort (137 HNSCC cases, 102 controls). DNA was extracted from plasma samples, bisulfite-converted, and analyzed via quantitative real-time PCR. SHOX2 and SEPT9 methylations were assessed separately and as panel [meanSEPT9/SHOX2] using the ΔCT method for absolute quantification and the ΔΔCT-method for relative quantification. Quasi-digital PCR was defined as the number of amplification-positive PCR replicates. The diagnostic (sensitivity, specificity, area under the curve (AUC) of the receiver operating characteristic (ROC)) and prognostic accuracy (hazard ratio (HR) from Cox regression) were evaluated.ResultsSporadic methylation in control samples necessitated the introduction of cutoffs resulting in 61–63% sensitivity/90–92% specificity (SEPT9/training), 53–57% sensitivity/87–90% specificity (SHOX2/training), and 64–65% sensitivity/90–91% specificity (meanSEPT9/SHOX2/training). Results were confirmed in a testing cohort with 54–56% sensitivity/88–90% specificity (SEPT9/testing), 43–48% sensitivity/93–95% specificity (SHOX2/testing), and 49–58% sensitivity/88–94% specificity (meanSEPT9/SHOX2/testing). All algorithms showed comparable cutoff-independent diagnostic accuracy with largely overlapping 95% confidence intervals (SEPT9: AUCtraining = 0.79–0.80; AUCtesting = 0.74–0.75; SHOX2: AUCtraining = 0.78–0.81, AUCtesting = 0.77–0.79; meanSEPT9/SHOX2: AUCtraining = 0.81–0.84, AUCtesting = 0.80). The accurate prediction of overall survival was possible with all three algorithms (training cohort: HRSEPT9 = 1.23-1.90, HRSHOX2 = 1.14-1.85, HRmeanSEPT9/SHOX2 =1.19-1.89 ; testing cohort: HRSEPT9 =1.22-1.67, HRSHOX2 = 1.15-1.71, HRmeanSEPT9/SHOX2 = 1.12-1.77).ConclusionThe concordant clinical performance based on different quantification algorithms allows for the application of various diagnostic platforms for the analysis of ccfDNA methylation biomarkers.Electronic supplementary materialThe online version of this article (10.1186/s13148-017-0425-4) contains supplementary material, which is available to authorized users.

Hypermethylation of the SEPT9 Gene Suggests Significantly Poor Prognosis in Cancer Patients: A Systematic Review and Meta-Analysis

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Soluble immune checkpoint molecules: Serum markers for cancer diagnosis and prognosis

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DNA methylation biomarkers in peripheral blood of patients with head and neck squamous cell carcinomas. A systematic review

“…two duplicates found during the screening) and left 38 papers for assessment. The full text assessment resulted in the further exclusion of 31 studies and the inclusion of a total of 7 studies for final analysis [34][35][36][37][38][39][40] (Fig 1). The reference lists of the included articles were screened for additional relevant articles, but none met the inclusion criteria.…”