Abstract
Hepatocellular carcinoma (HCC) remains a health concern characterized by heterogeneity and high mortality. Surgical resection, radiofrequency ablation, trans-arterial chemoembolization, and liver transplantation offer potentially curative treatments for early-stage disease, but recurrence remains high. Most patients present with advanced-stage HCC, where locoregional therapies are less effective, and systemic treatments-primarily multi-kinase inhibitors and immune checkpoint inhibitors-often yield limited responses. Precision medicine aims to tailor therapy to molecular and genetic profiles, yet its adoption in HCC is hindered by inter-/intra-tumoral heterogeneity and limited biopsy availability. Advances in molecular diagnostics support reintroducing tissue sampling to better characterize genetic, epigenetic, and immunological features. Liquid biopsy offers a minimally invasive method for capturing real-time tumor evolution, overcoming spatial and temporal heterogeneity. Artificial intelligence and machine learning are revolutionizing biomarker discovery, risk stratification, and treatment planning by integrating multi-omics data. Immunological factors such as tumor-infiltrating lymphocytes, natural killer cells, macrophages, and fibroblasts have emerged as determinants of HCC progression and treatment response. Conversion therapy-combining systemic agents with locoregional treatments-has showndemonstrated promise in downstaging unresectable HCC. Ongoing efforts to refine biomarker-driven approaches and optimize multi-modality regimens underscore precision medicine's potential to improve outcomes. PubMed (January 2002-February 2025) was searched for relevant studies.