Although liquid biopsy of blood is useful for cancer diagnosis and prediction of prognosis, diagnostic and prognostic value of ctDNA in bile fluid for BTCs are not clear yet. To determine whether liquid biopsy for circulating tumor DNA (ctDNA) can replace tissue biopsy when assessing somatic mutations in biliary tract cancers (BTCs). Bile samples were obtained from 42 patients with BTC. Matched formalin-fixed paraffin-embedded (FFPE) samples were obtained from 20 of these patients and matched plasma samples from 16 of them. Droplet digital PCR (ddPCR) was used for detection KRAS somatic mutation. KRAS mutations were identified in the bile ctDNA of 20 of 42 (48%) patients. Patients with mutant KRAS showed significantly worse survival than those with wild-type KRAS (2-year survival rates: 0% vs. 55.5%, respectively; p = 0.018). There was 80.0% mutational concordance between the paired bile ctDNA and FFPE samples, and 42.9% between the plasma and FFPE samples. On transcriptomic sequencing of one set of paired bile and FFPE samples, expression level of KRAS-associated signaling oncogenes in the bile and tissue samples showed a strong positive correlation (r = 0.991, p < 0.001). Liquid biopsy of bile reliably detect mutational variants within the bile ctDNA of BTC patients. These results suggest that bile is an effective biopsy fluid for ctDNA analysis.

Background: Intrahepatic cholangiocarcinoma (IHCC) is highly aggressive primary hepatic malignancy with an increasing incidence. Objective: This study aimed to develop machine learning-based radiomic clustering using F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) for predicting recurrence-free survival (RFS) and overall survival (OS) in IHCC. Methods: We retrospectively reviewed pretreatment F-18 FDG PET/CT scans of 60 IHCC patients who underwent surgery without neoadjuvant treatment between January 2008 and July 2020. Radiomic features such as first order, shape, and gray level were extracted from the scans of 52 patients and analyzed using unsupervised hierarchical clustering. Results: Of the 60 patients, 36 experienced recurrence and 31 died during follow-up. Eight patients with a negative FDG uptake were classified as Group 0. The unsupervised hierarchical clustering analysis divided the total cohort into three clusters (Group 1: n = 27; Group 2: n = 23; Group 3: n = 2). The Kaplan–Meier curves showed significant differences in RFS and OS among the clusters (p < 0.0001). Multivariate analyses showed that the PET radiomics grouping was an independent prognostic factor for RFS (hazard ratio (HR) = 3.03, p = 0.001) and OS (HR = 2.39, p = 0.030). Oxidative phosphorylation was significantly activated in Group 1, and the KRAS, P53, and WNT β-catenin pathways were enriched in Group 2. Conclusions: This study demonstrated that machine learning-based PET radiomics clustering can preoperatively predict prognosis and provide valuable information complementing the genomic profiling of IHCC.

Background Early detection of pancreatic cancer (PCA) remains a major challenge due to the lack of reliable biomarkers. Methods We investigated bile-derived N6-methyladenosine (m ⁶ A) modification as a diagnostic biomarker. Bile samples were obtained from patients with PCA (n = 7), biliary tract cancer (BTC; n = 35), and common bile duct (CBD) stones (n = 9). Global m6A levels were quantified using an ELISA-based colorimetric assay. Results Global m6A levels were markedly elevated in PCA bile (6.75 ± 1.25%) compared with BTC (1.25 ± 0.15%) and CBD controls (0.5 ± 0.1%) ( p < 0.001; Fig. 1). ROC analysis demonstrated excellent discrimination (AUC = 1.00, optimal cut-off = 1.1%). Consistent results were observed in pancreatic juice samples (AUC = 1.00, cut-off = 3.7%). Conclusions The results demonstrated distinct m⁶A elevation in bile from PCA patients (Fig. 1), supporting its translational potential as a minimally invasive biomarker. Validation in larger cohorts is warranted. These findings provide a proof-of-concept foundation for bile-based RNA methylation profiling in pancreatic cancer.