From Theory to Practice: Which Biomarkers Are Ready for Predicting Response in Advanced HCC?

Area of Science:

• Hepatobiliary Oncology
• Translational Biomarker Research
• Precision Medicine

Background:

• Advanced hepatocellular carcinoma (HCC) treatment selection is empirical due to limited predictive biomarkers.
• Despite therapeutic advances, few tools guide upfront first-line treatment decisions.

Purpose of the Study:

• To review and synthesize predictive biomarkers for advanced HCC.
• To distinguish clinically applicable biomarkers from exploratory ones.
• To identify unmet needs in biomarker-driven HCC treatment selection.

Main Methods:

• Literature review and synthesis of practice-oriented data on predictive biomarkers in advanced HCC.
• Evaluation of biomarker robustness, feasibility, and clinical translatability.
• Categorization of biomarkers into clinically actionable and investigational.

Main Results:

• Limited biomarkers are robust for real-world use; most offer on-treatment insights, not upfront guidance.
• Actionable parameters include ALBI score (prognostic), early Alpha-fetoprotein (AFP) decline, and anti-drug antibodies (ADA) (on-treatment).
• Investigational biomarkers (liquid biopsy, AI, radiomics, proteomics) offer mechanistic insights but lack validation; proteomics shows future potential.

Conclusions:

• Current biomarkers offer limited predictive value for upfront advanced HCC treatment selection.
• Integrated, multi-omic strategies combining tissue, liquid biopsy, and imaging, validated in prospective trials, are needed for precision medicine.
• Proteomics represents a promising avenue for developing biologically grounded pre-treatment stratification tools.