Evidence map›Paper›PMID 42008358›Full record

ArticleBioMed research international2026

SREBP2 as a Novel Biomarker for Posttransplant Hepatocellular Carcinoma Recurrence: A New Prognostic Nomogram.

Jiali Qiu, Lei Cao, Sensheng Bi, Pengyu Han, Zhenglu Wang

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jiali QiuBiological Sample Resource Sharing Center, Tianjin First Central Hospital, Tianjin, China, tj-fch.com.ORCID https://orcid.org/0000-0003-1065-9119
Lei CaoBiological Sample Resource Sharing Center, Tianjin First Central Hospital, Tianjin, China, tj-fch.com.ORCID https://orcid.org/0000-0001-5982-4264
Sensheng BiBiological Sample Resource Sharing Center, Tianjin First Central Hospital, Tianjin, China, tj-fch.com.ORCID https://orcid.org/0009-0003-3308-8491
Pengyu HanBiological Sample Resource Sharing Center, Tianjin First Central Hospital, Tianjin, China, tj-fch.com.ORCID https://orcid.org/0009-0008-4921-0208
Zhenglu WangBiological Sample Resource Sharing Center, Tianjin First Central Hospital, Tianjin, China, tj-fch.com.ORCID https://orcid.org/0009-0005-1741-4087

Funding

Natural Science Foundation of Tianjin City 22JCYBJC01230Tianjin Key Medical Discipline (Specialty) Construction Project TJYXZDXK-3-006ATianjin Key Medical Discipline (Specialty) Construction Project TJYXZDXK-3-026C
6 · The paper itself

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.

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularLiver NeoplasmsLiver TransplantationNeoplasm Recurrence, LocalNomogramsSterol Regulatory Element Binding Protein 2FemaleHumansMaleMiddle AgedPrognosisBiomarkers, TumorSREBF2 protein, humanSterol Regulatory Element Binding Protein 2hepatocellular carcinomaliver transplantationnomogramrecurrence predictionSREBP2

Identifiers

PMID42008358
PMCPMC13094809

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.