Hepatocellular carcinoma (HCC) is often diagnosed at an advanced stage, and early detection is critical for improving patient outcomes. Despite this, reliable non-invasive biomarkers for early-stage HCC are limited.
This study seeks to develop a multi-omics-based liquid biopsy assay, especially focusing on ncRNAs (e.g. tsRNA, miRNA, circRNA, lncRNA, etc.) for accurate detection of early-stage HCC.
Adults aged 18 to 100 years.
A histologically confirmed diagnosis of hepatocellular carcinoma.
A clinically diagnosed as chronic liver disease, including chronic hepatitis or liver cirrhosis, without evidence of hepatocellular carcinoma.
Healthy volunteers without known liver disease or malignancy.
Lack of or inability to provide informed consent
History of other active malignancies within the past 5 years
Previous liver transplantation
Severe systemic infection or inflammatory disease at the time of enrollment
Individuals who were diagnosed with hepatocellular carcinoma. Individuals who were diagnosed with chronic liver disease Healthy donors
Case-control
Retrospective
Small RNA sequence
Diagnostic testComprehensive small RNA sequencing of serum or plasma-derived cf-tsRNAs to identify candidate biomarkers distinguishing HCC from NDC.
Rt-qPCR
Diagnostic testConstruction of integrated cf- tsmiRNAs diagnostic classifier using machine learning
Rt-qPCR
Diagnostic testPCR-based validation of the tsRNA panel
Diagnostic performance of the integrated multi-omics signature for hepatocellular carcinoma detection
To evaluate the diagnostic accuracy of the model for distinguishing patients with hepatocellular carcinoma from chronic liver disease and healthy controls, as assessed by the area under the operating characteristic curve (AUC), sensitivity, and specificity.
Validation of the diagnostic model in independent cohorts
To assess the reproducibility and generalizability of the diagnostic model using independent validation cohorts.
Identification of etiology-associated omics profiles in hepatocellular carcinoma
To characterize differences in omics patterns among HBV-, HCV-, and NBNC-related hepatocellular carcinoma cases, using integrated high-throughput multi-omics analysis.
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