Fig. 3

Selection of diagnostic miRNA candidates based on robustness and relationship with PBca. a Selection diagram of diagnostic miRNA candidates and miRNA signature for diagnostic index. b Examples of robustness evaluation of miRNAs. Left: example of robust miRNA, hsa-miR-665. Right: example of unrobust miRNA, hsa-miR-125a-3p. Evaluation was performed using two tests [black circle: HC in the exploratory set (set1, n = 150), red circle: HC in prior obtained data (set2, n = 150)]. x-axis: mean of three internal control miRNAs; y-axis: miRNA signals; rsq: regression squared of regression curve; slope: slope of regression curve. c WGCNA results: module–trait relationship between eigengene modules and clinical factors. Pearson correlation coefficients (r) and p-values are shown in each column. d Ridge regression coefficient for detecting PBCA in the exploratory set. x-axis: absolute values of ridge regression coefficients. Red dashed lines indicate the threshold for the selection of coefficients. ROC curves using Index-1, Index-2, or CA19-9 for discriminating patients with PBca from healthy participants in the exploratory (e), validation (f), and independent validation sets (g). AUC values are shown in each figure. Int-con, mean of internal control miRNAs; rsq, regression squared; slope, slope of regression line; PBca, pancreatic or biliary tract cancer; HC, healthy control; logCEA, CEA (U/mL) in logarithm with base 2; logCA19-9, CA19-9 (U/mL) in logarithm with base 2; cT, cN, cM: Union for UICC clinical TNM classification; PLT, platelet count