Evidence map›Paper›PMID 38726780›Full record

ArticleCombinatorial chemistry & high throughput screening2025

Identifying the Crucial Biomarker of MASH-Related HCC.

Haiyang Zhou, Yinjie Zhang, Yuhang Shen, Shuai Chen, Zhen Yang, Zhihuai Wang, Xihu Qin, Chunfu Zhu

Abstract read
In one paragraph

Article in Combinatorial chemistry & high throughput screening, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

8 authors.

Haiyang ZhouDepartment of General Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, 213000, China.ORCID 0009-0004-6920-9942
Yinjie ZhangDepartment of General Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, 213000, China.ORCID 0009-0000-1618-9651
Yuhang ShenDepartment of General Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, 213000, China.ORCID 0009-0001-8917-7712
Shuai ChenNanjing Medical University, Nanjing, 210000, Jiangsu Province, China.ORCID 0000-0003-2499-3281
Zhen YangDalian Medical University, Dalian, 116000, Liaoning Province, China.ORCID 0000-0001-6700-9729
Zhihuai WangDepartment of General Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, 213000, China.ORCID 0000-0001-7156-3132
Xihu QinDepartment of General Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, 213000, China.ORCID 0000-0002-0031-3379
Chunfu ZhuDepartment of General Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, 213000, China.

Funding

Basic application project of Changzhou Science and Technology Bureau, China CJ20220142Changzhou Medical Innovation Team Project CCX201807Changzhou Science and Technology Program CE20165020China Scholarship Council (CSC) Foundation 202008320386Foundation of Changzhou Medical Center, Nanjing Medical University, China CMCB202221High-Level Medical Talents Training Project of Changzhou 2016CZLJ007Young talent project of Changzhou Health Commission, China CZQM2022007Youth fund of Changzhou Health Commission, China QN202121
6 · The paper itself

Abstract

objectivesThis study aimed to explore the key oncogenic factor of metabolicassociated steatohepatitis (MASH) to hepatocellular carcinoma (HCC).

methodsWe utilized four differential GEO datasets (GSE164760, GSE139602, GSE197112, and GSE49541) to identify the key oncogenic factor for MASH-related HCC. The differential genes were analyzed using the GEO2R algorithm online. The GEPIA online website was used to explore the expression of selected four genes (SPP1, GNMT, CLDN11, and THBS2). The genetic alterations in genes were estimated by the cBioPortal website. The Kaplan-Meier Plotter online database was applied to explore the prognostic value of SPP1. Univariate and multivariate Cox analyses were carried out to further confirm the prognostic value of SPP1. The GO and KEGG enrichment analysis exported associated pathways with SPP1 expression. The positively or negatively related immune cells and immune checkpoint expressions were identified through Pearson correlation analysis. The lipogenesis-associated proteins were detected using western blotting and fluorescence. The high-fat diet (HFD) mouse model was constructed, and liver samples were collected.

resultsSPP1, GNMT, CLDN11, and THBS2 were determined in the transformation process of MASH to liver fibrosis. SPP1 and GNMT were upregulated in the HCC tumor tissue. SPP1, in particular, had the potential to be the prognostic factor through Cox analysis. Remarkably, SPP1 was highly expressed in HCC compared to normal tissues in three independent datasets (GSE121248, GSE14520, and GSE45267). SPP1 is mainly involved in the amplification and deep deletion mutations. SPP1 was found to be strongly correlated with ANXA2 expression, and ANXA2 was also highly expressed in HCC with significant prognostic performance. Moreover, SPP1 was found to participate in the carcinogenic mechanism and correlate with immune cells and immune checkpoint expression. SPP1 knockdown suppressed the SREBP1 and FASN expressions and increased the SIRT1 expression

conclusionSPP1 may be the key oncogenic factor for the transformation of MASH to HCC, and it could be a potential immunotherapeutic target in HCC.

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularFatty LiverLiver NeoplasmsAnimalsDiet, High-FatHumansMaleMiceMice, Inbred C57BLPrognosisBiomarkers, Tumorhepatocellular carcinomaimmuneimmune checkpoints.metabolic associated steatohepatitisSPP1

Identifiers

PMID38726780
PMCPMC12376122

What Socratic holds

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LicenceCC BY
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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 Socratic graph.