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  • Title: Paired box 5 methylation detection by droplet digital PCR for ultra-sensitive deep surgical margins analysis of head and neck squamous cell carcinoma.
    Author: Hayashi M, Guerrero-Preston R, Sidransky D, Koch WM.
    Journal: Cancer Prev Res (Phila); 2015 Nov; 8(11):1017-26. PubMed ID: 26304463.
    Abstract:
    Molecular deep surgical margin analysis has been shown to predict locoregional recurrences of head and neck squamous cell carcinoma (HNSCC). To improve the accuracy and versatility of the analysis, we used a highly tumor-specific methylation marker and highly sensitive detection technology to test DNA from surgical margins. Histologically cancer-negative deep surgical margin samples were prospectively collected from 82 eligible HNSCC surgeries by an imprinting procedure (n = 75) and primary tissue collection (n = 70). Bisulfite-treated DNA from each sample was analyzed by both conventional quantitative methylation-specific PCR (QMSP) and QMSP by droplet digital PCR (ddQMSP) targeting Paired box 5 (PAX5) gene promoter methylation. The association between the presence of PAX5 methylation and locoregional recurrence-free survival (LRFS) was evaluated. PAX5 methylation was found in 68.0% (51 of 75) of tumors in the imprint samples and 71.4% (50 of 70) in the primary tissue samples. Among cases that did not have postoperative radiation (n = 31 in imprint samples, n = 29 in tissue samples), both conventional QMSP and ddQMSP revealed that PAX5 methylation-positive margins was significantly associated with poor LRFS by univariate analysis. In particular, ddQMSP increased detection of the PAX5 marker from 29% to 71% in the nonradiated imprint cases. Also, PAX5 methylated imprint margins were an excellent predictor of poor LRFS [HR, 3.89; 95% confidence interval (CI), 1.19-17.52; P = 0.023] by multivariate analysis. PAX5 methylation appears to be an excellent tumor-specific marker for molecular deep surgical margin analysis of HNSCC. Moreover, the ddQMSP assay displays increased sensitivity for methylation marker detection.
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