Prognostic model for predicting outcome and guiding treatment decision for unresectable hepatocellular carcinoma treated with lenvatinib monotherapy or lenvatinib plus immunotherapy

Predictive Biomarkers of Immune Checkpoint Inhibitor-Based Mono- and Combination Therapies for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is among the most frequent and deadly human cancers worldwide. It has been shown that interaction between immune checkpoint receptors and ligands plays a crucial role in inhibition of T cell-mediated anti-tumor immune responses, thereby assisting tumor cells to evade the host immune surveillance. Therefore, several immune checkpoint inhibitors (ICIs) that selectively block immune checkpoint receptors or ligands have been developed as clinically effective and safe immunotherapeutic agents for treating HCC, including the inhibitors targeting cytotoxic T lymphocyte-associated antigen 4, programmed death 1, and programmed death ligand 1. In addition, various combinations of ICIs and other ICIs or tyrosine kinase inhibitors or vascular endothelial growth factor inhibitors have also emerged as clinically beneficial treatments for HCC. However, the overall response rates of ICI mono-therapy and combination therapy in HCC patients remain unsatisfied, highlighting the urgent need for discovering valuable predictive biomarkers to achieve personalized therapy. This review comprehensively summarizes the literature-based evidence validating a variety of biomarkers with predictive significance for treatment responses and outcomes in HCC patients receiving various ICI-based mono- and combination therapies.

Biomarkers predicting the efficacy of immune checkpoint inhibitors in hepatocellular carcinoma

In recent years, immune checkpoint inhibitors (ICIs) have emerged as a transformative approach in treating advanced hepatocellular carcinoma (HCC). Despite their success, challenges persist, including concerns about their effectiveness, treatment costs, frequent occurrence of treatment-related adverse events, and tumor hyperprogression. Therefore, it is imperative to identify indicators capable of predicting the efficacy of ICIs treatment, enabling optimal patient selection to maximize clinical benefits while minimizing unnecessary toxic side effects and economic losses. This review paper categorizes prognostic biomarkers of ICIs treatment into the following categories: biochemical and cytological indicators, tumor-related markers, imaging and personal features, etiology, gut microbiome, and immune-related adverse events (irAEs). By organizing these indicators systematically, we aim to guide biomarker exploration and inform clinical treatment decisions.