Microbiome signature of bile from pancreatic and biliary tract cancer patients: A pilot study.

Abstract

e15744 Background: Recent studies especially in murine models have linked meta-organismal pathways in the gut microbial community to cancers of the pancreas and the biliary tract. However, data on microbiome in the biliary pool in patients to establish models for oncogenesis in the pancreatobiliary (PB) habitat have been limited. We analyzed bile collected from a pilot series of patients to identify microbiome signatures associated with malignancy. Methods: We collected bile samples from patients during routine endoscopic retrograde cholangiopancreatography in this study approved by the Cleveland Clinic Institutional Review Board for Human Subjects’ Protection. Of 10 patients, there were 5 with pancreatic ductal adenocarcinoma (PDA), 3 with cholangiocarcinoma (CC), 1 with ampullary adenocarcinoma, and 1 with gallstone pancreatitis. DNA was extracted from bile specimens using PowerViral RNA/DNA Isolation kit. Bacterial 16S rRNA gene amplification and library construction were performed according to the 16S Metagenomic Sequencing Library Preparation guide from Illumina. Post-sequencing analysis was done using QIIME (Quantitative Insights Into Microbial Ecology) and MICCA (MICrobial Community Analysis). Results: Most reads were from phyla Firmicutes (57.9%) and Proteobacteria (14.9%). One benign specimen (pancreatitis) separated clearly from the rest showing 98.9% of reads from Clostridium sensu stricto (phylum Firmicutes). Analysis of beta diversity showed six samples clustering tightly. Of these, 5 were PDA and 1 was CC. A second cluster included remaining 3 samples, 2 with CC and 1 with PDA; this latter had higher abundance of phyla Fusobacteria (90.6%) and Verrucomicrobia (92.9%). Conclusions: Select bacteria are differentially increased in malignant and benign PB diseases. Furthermore, distinct microbiome signatures may be associated with cancer in the pancreatic and biliary habitats. We intend to evaluate these findings in larger sample sizes and determine associations with clinical outcomes and response to treatment.