Triplex High-Resolution Melting Assay for the Simultaneous Assessment of IFNL3 rs12979860, ABCB11 rs2287622, and RNF7 rs16851720 Genotypes in Chronic Hepatitis C Patients  Elena L. Enache, Anca Sin, Liviu S. Enache, Ligia Bancu  The Journal of Molecular Diagnostics  Volume 19, Issue 6, Pages 857-869 (November 2017) DOI: 10.1016/j.jmoldx.2017.07.005 Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions

Figure 1 Representative plots for single-nucleotide polymorphism analysis by triplex high-resolution melting (HRM) assay. A: Typical normalized melting peaks for the three amplicons included in the multiplex genotyping assay. Detailed analysis by sequencing and high-resolution melting for RNF7 rs16851720. B: Representative Sanger sequencing traces for the three rs16851720 genotypes: AA, AC, and CC (the rs16851720 polymorphism site on all traces is highlighted by the rectangle). C: Nonnormalized melting curves and placement of normalization intervals for rs16851720 (the premelt region considered for normalization is delimited by the blue vertical lines, and the post-melt region is delimited by the two red vertical lines). D–G: HRM data transformation by the two methods available in the instrument software: relative fluorescence unit (RFU) difference, consisting of normalization of melting curves (D), followed by RFU difference clustering (E); and dF/dT difference clustering, consisting of calculation of the negatively transformed first derivative of the normalized melting curves (F), followed by dF/dT difference clustering (G). The Journal of Molecular Diagnostics 2017 19, 857-869DOI: (10.1016/j.jmoldx.2017.07.005) Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions

Figure 2 Performance of a predictive model based on triplex single-nucleotide polymorphism (SNP) genotyping data for advanced fibrosis (METAVIR F3 to F4) in chronic hepatitis C patients. A: Validation plot of the model: correspondence between the predicted and observed probability for the presence of advanced fibrosis. Triangles and whiskers represent the observed frequencies and the corresponding 95% CIs, by deciles of predicted probabilities. Bottom of the graph: Spikes show the distribution of the patients according to the predicted probability of advanced fibrosis, stratified by the actual fibrosis stage: advanced fibrosis (F3 to F4) above the x axis and absence of advanced fibrosis (F0 to F2) below the x axis. B: Predicted probabilities in patients with and without advanced fibrosis. Boxplots showing the medians (solid horizontal lines), interquartile ranges (boxes), and minimum-maximum ranges (whiskers); means are shown as solid dots. The discrimination slope of the predictive model for advanced fibrosis was 0.32. C and D: Receiver operating characteristic (ROC) curve (C) and decision curve analysis (D) of the predictive model, including or not including the genotyping information of the three SNPs. The Journal of Molecular Diagnostics 2017 19, 857-869DOI: (10.1016/j.jmoldx.2017.07.005) Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions

Figure 3 Performance of the model based on triplex single-nucleotide polymorphism (SNP) genotyping data for the prediction of sustained virological response (SVR) achievement with pegylated interferon plus ribavirin combination treatment in chronic hepatitis C patients. A: Validation plot of the model: correspondence between the predicted and observed probability of SVR. Triangles and whiskers represent the observed frequencies and the corresponding 95% CIs, by deciles of predicted probabilities. Bottom of the graph: spikes show the distribution of the patients according to the predicted probability of SVR, stratified by outcome: SVR above the x axis, and no SVR below the x axis. B: Predicted probabilities in patients with and without SVR. Boxplots showing the medians (solid horizontal lines), interquartile ranges (boxes), and minimum-maximum ranges (whiskers); means are shown as solid dots. The discrimination slope of the predictive model for SVR was 0.55. C: Receiver operating characteristic (ROC) curve with true-positive and false-positive rates plotted for the decision thresholds discussed in the text. D: Decision curve analysis of the predictive model, including or not including IFNL3 or genotyping information of the three SNPs. The Journal of Molecular Diagnostics 2017 19, 857-869DOI: (10.1016/j.jmoldx.2017.07.005) Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology Terms and Conditions