Plasma microRNA-15a/16-1-based machine learning for early detection of hepatitis B virus-related hepatocellular carcinoma.

ABSTRACT:

Background and aims

Hepatocellular carcinoma (HCC), which is prevalent worldwide and has a high mortality rate, needs to be effectively diagnosed. We aimed to evaluate the significance of plasma microRNA-15a/16-1 (miR-15a/16) as a biomarker of hepatitis B virus-related HCC (HBV-HCC) using the machine learning model. This study was the first large-scale investigation of these two miRNAs in HCC plasma samples.

Methods

Using quantitative polymerase chain reaction, we measured the plasma miR-15a/16 levels in a total of 766 participants, including 74 healthy controls, 335 with chronic hepatitis B (CHB), 47 with compensated liver cirrhosis, and 310 with HBV-HCC. The diagnostic performance of miR-15a/16 was examined using a machine learning model and compared with that of alpha-fet

SUBMITTER: Wei H 

PROVIDER: S-EPMC11771275 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature