ArticleBioMed research international2026
SREBP2 as a Novel Biomarker for Posttransplant Hepatocellular Carcinoma Recurrence: A New Prognostic Nomogram.
Article in BioMed research international, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- SREBP2 as a Novel Biomarker for Posttransplant Hepatocellular Carcinoma Recurrence: A New Prognostic Nomogram.BioMed research international · 2026Article
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Authors and funding
5 authors.
Funding
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.
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