Exploration of microRNA biomarker panel as a predictor of evolution of pancreatitis to pancreatic ductal adenocarcinoma.

e16343 Background: PDAC (pancreatic ductal adenocarcinoma) is 3rd most common cause of cancer deaths, and is projected to become the 2nd leading cause of cancer death by 2030 even as it comprises only 3.2% of all cancer cases. The most important predictor of survival is resection of early stage cancer. Currently, screening for early detection of PDAC via annual MRI or endoscopic ultrasound (EUS) is recommended only in the 10% of total cases, that have hereditary/ genetic associations. PDAC risk is doubled even 5 years after acute pancreatitis and is 15-16 fold for chronic pancreatitis. Biomarkers such as CA19-9, peptide panels, tumor-associated autoantibodies and microRNAs have been studied for early diagnosis of PDAC. However, biomarkers that can predict risk of PDAC following pancreatitis have not been well studied. This study aims to identify, compare, and extract a differentially expressed microRNA (DEM) panel in serum, that could predict risk of progression to PDAC from pancreatitis. Methods: Two microarray Genomic Spatial Event (GSE) datasets containing pancreatitis (n = 75), PDAC (90), and control samples (164) were used to extract DEM (n = 22), common to both pancreatitis and PDAC. 8 smaller subgroups of DEM (for cost benefit) were derived from bioinformatics methods such as ROC/AUC of expression values, up and downregulated clustering, correlation analysis, miRNA interaction networks, target gene prediction tools, target gene interaction and functional enrichment analysis for all target genes and top modules, as well as decision tree/cross-validated random forest machine learning models. Results: The DEM main group (n = 22) and the smaller subgroups were trained on the original datasets, and were used to predict the risk of pancreatic cancer vs control in a validation set consisting of six other GSE datasets. The main 22miRNA panel had the highest accuracy (0.928), F1(0.976), precision and recall, followed by subgroup 6 (accuracy 0.910, F1 0.968) derived from the target hub genes with the highest interaction (hsa-miR-28-3p, 320b, 320c, 320d, 532-5p, and 423-5p). The associated main pathways were ubi-conjugation and ubiquitin pathway, mRNA splicing/processing/binding, and endocytosis. Conclusions: A new serum 22 microRNA biomarker panel predicting evolution of pancreatitis to pancreatic ductal adenocarcinoma, and it’s associated pathways, has been identified, that also performed very well in distinguishing pancreatic cancer (with or without pancreatitis risk factor) from control. A smaller subpanel of 6 microRNA may have a cost benefit. Further studies with larger samples, specifically differentiating PDAC vs all pancreatic cancer, and acute vs chronic pancreatitis among the samples are needed.