Development and Validation of an Exosome-Based and Machine Learning Powered Liquid Biopsy for the Detection of Early-Onset Colorectal Cancer

What this Trial Is About

Early-onset colorectal cancer (EOCRC), diagnosed before age 50, is increasingly common and now accounts for 10-15% of new colorectal cancer cases. It is a leading cause of cancer-related death in young adults. This study focuses on developing a non-invasive blood test using microRNA markers to detect EOCRC early, aiming to improve timely diagnosis and reduce mortality. Researchers plan to use advanced technologies like machine learning to enhance detection accuracy. The study involves analyzing blood samples to develop a liquid biopsy test that measures circulating cell-free and exosomal microRNAs associated with tumor biology. Researchers will create two separate microRNA panels and then combine them using machine learning models to improve sensitivity and specificity. The process includes three phases: RNA sequencing, panel development and training, followed by validation in an independent group of patients and controls. Participants include individuals under 50 with or without colorectal cancer. The study collects plasma samples and clinical data to assess the test's accuracy, including sensitivity and specificity, over about one year. The research aims to produce a cost-effective, patient-friendly screening method for EOCRC, potentially increasing screening participation and improving patient outcomes.

Early Onset Colorectal Cancer Detection