Highly Sensitive Circulating MicroRNA Panel for Accurate Detection of Hepatocellular Carcinoma in Patients With Liver...

Area of Science:

• Oncology
• Molecular Biology
• Biomarker Discovery

Background:

• Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality globally.
• High mortality rates are linked to challenges in early HCC detection.
• Existing diagnostic methods often fail to identify HCC in its early stages.

Purpose of the Study:

• To investigate the diagnostic potential of circulating microRNAs (miRNAs) in serum for hepatocellular carcinoma (HCC).
• To develop and validate a diagnostic model for accurate HCC detection, including early stages.
• To improve patient outcomes through enhanced early cancer diagnosis.

Main Methods:

• Serum samples from 345 HCC patients, 46 chronic hepatitis (CH) patients, 93 liver cirrhosis (LC) patients, and 1,033 healthy individuals were analyzed using miRNA microarrays.
• A diagnostic model was constructed based on the expression levels of a combination of eight miRNAs identified in a discovery set.
• The model's diagnostic performance was evaluated in a validation set.

Main Results:

• A diagnostic model comprising eight specific miRNAs demonstrated high accuracy in discriminating HCC from at-risk controls.
• The model achieved an area under the curve (AUC) of 0.99, with 97.7% sensitivity and 94.7% specificity.
• Crucially, the model successfully detected 98% of stage I HCC cases, significantly outperforming conventional methods.

Conclusions:

• Circulating miRNAs show promise as reliable biomarkers for the accurate detection of hepatocellular carcinoma (HCC).
• The developed miRNA-based model offers a highly accurate method for early-stage HCC detection, maintaining diagnostic accuracy even in stage I.
• This approach has the potential to significantly improve patient outcomes by enabling timely diagnosis and treatment.