Multiple "Omics" data-based biomarker screening for hepatocellular carcinoma diagnosis

Area of Science:

• Hepatocellular Carcinoma Research
• Biomarker Discovery
• Genomics and Omics Technologies

Background:

• Hepatocellular carcinoma (HCC) diagnosis faces challenges due to significant prognostic differences between early and late stages.
• Alpha-fetoprotein (AFP) is a common HCC biomarker, but its suboptimal sensitivity and specificity limit diagnostic accuracy.
• There is a critical need for improved diagnostic tools for HCC, particularly for early detection.

Purpose of the Study:

• To review and discuss novel biomarkers for HCC diagnosis derived from advanced "omics" data.
• To evaluate the diagnostic performance of these emerging biomarkers, focusing on early-stage HCC.
• To analyze the advantages and disadvantages of various omics-derived biomarkers for HCC detection.

Main Methods:

• Comprehensive literature review of studies utilizing next-generation sequencing and multiple "omics" data (genomics, epigenomics, transcriptomics, proteomics, metabolomics, metagenomics).
• Analysis of identified and validated biomarkers, panels, and models for HCC diagnosis.
• Assessment of diagnostic performance metrics for reviewed biomarkers.

Main Results:

• Multiple biotechnologies and "omics" approaches have successfully screened for HCC diagnostic biomarkers.
• Numerous effective biomarkers, panels, and models have been identified and validated.
• A significant number of these novel biomarkers demonstrate good diagnostic performance, especially for early HCC detection.

Conclusions:

• "Omics"-derived biomarkers represent a significant advancement in HCC diagnostic capabilities.
• These novel biomarkers show potential to overcome the limitations of current methods like AFP.
• Further research and validation are crucial for the clinical application of these promising HCC diagnostic tools.