miRNA Profiling of Magnetic Nanopore–Isolated Extracellular Vesicles for the Diagnosis of Pancreatic Cancer
Abstract
Improved diagnostics for pancreatic ductal adenocarcinoma (PDAC) to detect the disease at earlier, curative stages and to guide treatments is crucial to progress against this disease. The development of a liquid biopsy for PDAC has proven challenging due to the sparsity and variable phenotypic expression of circulating biomarkers. Here we report methods we developed for isolating specific subsets of extracellular vesicles (EV) from plasma using a novel magnetic nanopore capture technique. In addition, we present a workflow for identifying EV miRNA biomarkers using RNA sequencing and machine-learning algorithms, which we used in combination to classify distinct cancer states. Applying this approach to a mouse model of PDAC, we identified a biomarker panel of 11 EV miRNAs that could distinguish mice with PDAC from either healthy mice or those with precancerous lesions in a training set of n = 27 mice and a user-blinded validation set of n = 57 mice (88% accuracy in a three-way classification). These results provide strong proof-of-concept support for the feasibility of using EV miRNA profiling and machine learning for liquid biopsy.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jul 01, 2018
- Source ID
- 10.1158/0008-5472.can-17-3703
Entities
People
- Ben Z Stanger
- David Issadore
- Erica L Carpenter
- Jina Ko
- Junhyong Kim
- Neha Bhagwat
- Stephanie S Yee
- Stephen Fisher
- Taylor Black
- Young-ji Na
Organizations
- Abramson Cancer Center
- American Cancer Society
- Columbia University
- Istituto Superiore di Sanità
- Pancreatic Cancer Action Network
- United States Department of Defense
- University of Pennsylvania