Evaluating a Liquid Biopsy Using Exosomes and Machine Learning to Differentiate Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma in Primary Liver Cancer

What this Trial Is About

Primary liver cancers, including hepatocellular carcinoma HCC and intrahepatic cholangiocarcinoma ICC, are major causes of cancer deaths worldwide. These two cancer types have different origins and require distinct treatments, but it is often challenging to tell them apart before surgery. This research aims to develop and validate a non-invasive liquid biopsy test using exosomal microRNA analysis powered by machine learning to help doctors accurately distinguish between HCC and ICC before treatment. The study will proceed in three phases first, comprehensive RNA sequencing of exosomal microRNAs from patients with HCC and ICC second, development and training of a diagnostic panel using advanced machine learning to identify a biomarker for differential diagnosis and third, validation of this biomarker in an independent group of patients with these liver cancers. This approach focuses on creating a cost-effective and clinic-friendly test with high accuracy, avoiding invasive tissue sampling. Participants diagnosed with HCC or ICC who have undergone standard diagnostic procedures and have provided blood samples before any treatment will be involved. Researchers will analyze these samples to measure test sensitivity, specificity, and accuracy over about one year. The study will monitor the ability of the liquid biopsy test, named ELUCIDATE, to correctly differentiate between these cancers to improve patient care and treatment decisions through less invasive methods.

An Exosome-Based Liquid Biopsy for the Differential Diagnosis of Primary Liver Cancer