Development of a blood-based extracellular vesicle classifier for detection of early-stage pancreatic ductal adenocarcinoma.

ABSTRACT:

Background

Pancreatic ductal adenocarcinoma (PDAC) has an overall 5-year survival rate of just 12.5% and thus is among the leading causes of cancer deaths. When detected at early stages, PDAC survival rates improve substantially. Testing high-risk patients can increase early-stage cancer detection; however, currently available liquid biopsy approaches lack high sensitivity and may not be easily accessible.

Methods

Extracellular vesicles (EVs) were isolated from blood plasma that was collected from a training set of 650 patients (105 PDAC stages I and II, 545 controls). EV proteins were analyzed using a machine learning approach to determine which were the most informative to develop a classifier for early-stage PDAC. The classifier was tested on a validation cohort of 113 pa

SUBMITTER: Hinestrosa JP 

PROVIDER: S-EPMC10587093 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature