Identifying sorafenib benefit among patients with hepatocellular carcinoma: A transcriptomic and genomic approach

Sorafenib has been a cornerstone of hepatocellular carcinoma (HCC) therapy; however, its efficacy is limited, and identifying patients who will benefit from sorafenib is challenging. We aimed to identify predictive biomarkers of sorafenib benefit in patients with HCC.

Gene expression data from 33 HCC tumors treated with sorafenib were analyzed to construct a prediction model aimed at identifying patients with greater benefit from sorafenib treatment. The robustness of the predictor was validated using gene expression data from two phase III clinical trials, IMbrave150 and STORM.

The analysis of transcriptome data revealed a 50-gene signature, the KUSS50 (Korea University Sorafenib Signature with 50 genes), that exhibited high predictive power in identifying patients who benefited from sorafenib treatment in a training cohort. Validation in two independent cohorts - IMbrave150 (n = 48) and BIOSTORM (n = 67) -demonstrated high specificity for predicting sorafenib benefit (AUC: 87.1%, p = 1.8 × 10^-4 and 90.8%, p = 1.0 × 10^-7, respectively). Genomic analyses identified distinct molecular characteristics associated with the KUSS50-defined benefit subtype, including an increased mutation rate and activation of ferroptosis, suggesting increased baseline ferroptotic activity in these HCCs, which may sensitize them to sorafenib. The benefit subtype also overlapped with previously defined HCC subtypes associated with stemness and aggressiveness. Conversely, the non-benefit subtype correlated with β-catenin mutations and increased tumor purity, underscoring its biological significance.

The KUSS50 is a clinically actionable biomarker that may optimize patient selection for sorafenib treatment in HCC, potentially improving outcomes. Further exploration of the underlying biology of KUSS50-defined subtypes - particularly the role of ferroptosis in sorafenib sensitivity - may yield additional therapeutic insights.

This study identifies the KUSS50, a novel 50-gene signature, as a predictive biomarker for identifying patients with hepatocellular carcinoma (HCC) who are likely to benefit from sorafenib treatment. The findings have significant implications for the clinical management of HCC, particularly in optimizing treatment strategies and enhancing patient outcomes. The ability to predict the benefit of sorafenib treatment with high specificity allows for more personalized therapy, reducing unnecessary exposure to ineffective treatments. This approach can be directly applied by clinicians to improve treatment selection, ultimately leading to better patient outcomes. Additionally, understanding the molecular mechanisms underlying the KUSS50-defined subtypes may pave the way for new therapeutic strategies and interventions aimed at improving the efficacy of sorafenib and other treatments in patients with HCC.