Abstract
Hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) remains a major cause of mortality, with current selection criteria such as the Milan and UCSF standards relying solely on tumor morphology and failing to fully account for biological aggressiveness. Emerging evidence implicates dysregulated lipid metabolism, particularly sterol regulatory element-binding protein 2 (SREBP2), in HCC progression, yet its prognostic role in post-LT recurrence remains unexplored. To address this gap, this study developed and validated a novel SREBP2-integrated nomogram for improved risk stratification in 206 HCC patients undergoing LT (2015-2022), randomly split into development (n = 144) and validation (n = 62) cohorts. SREBP2 levels were quantified via ELISA (sensitivity: 0.1 ng/mL) and then incorporated into a multivariate Cox model alongside tumor number and AFP to predict recurrence-free survival (RFS). The nomogram demonstrated superior discrimination, with C-indices of 0.778 (development) and 0.796 (validation). High SREBP2 levels (≥ 40 ng/mL) independently predicted recurrence (HR = 1.757, p = 0.011), whereas decision curve analysis confirmed greater clinical net benefit across 1-/3-/5-year RFS predictions. As the first study to integrate SREBP2 into LT candidate selection, this biologically informed nomogram significantly enhances recurrence prediction, offering a refined tool for transplant eligibility assessment and adjuvant therapy guidance in HCC management. By combining molecular biomarkers with clinical parameters, this approach addresses a critical unmet need in optimizing post-LT outcomes.