Evidence map›Paper›PMID 41847173›Full record

ArticleInternational journal of general medicine2026

Prediction of Biomarkers for Hepatocellular Carcinoma Based on Proteomics and Phosphoproteomics.

Xueying Sun, Hui Huang, Qiqi Zhang, Xu Cao, Duo Zhang, Xiaofei Wang, Xiwei Lu, Chunwen Pu

Abstract read
In one paragraph

Article in International journal of general medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xueying SunDepartment of Biobank, Dalian Public Health Clinical Center, Dalian, 116001, People's Republic of China.ORCID 0000-0001-9486-6486
Hui HuangDepartment of Biobank, Dalian Public Health Clinical Center, Dalian, 116001, People's Republic of China.
Qiqi ZhangDepartment of Biobank, Dalian Public Health Clinical Center, Dalian, 116001, People's Republic of China.
Xu CaoDepartment of Biobank, Dalian Public Health Clinical Center, Dalian, 116001, People's Republic of China.ORCID 0000-0003-1017-4752
Duo ZhangDepartment of Biobank, Dalian Public Health Clinical Center, Dalian, 116001, People's Republic of China.
Xiaofei WangDepartment of Biobank, Dalian Public Health Clinical Center, Dalian, 116001, People's Republic of China.
Xiwei LuDepartment of Biobank, Dalian Public Health Clinical Center, Dalian, 116001, People's Republic of China.
Chunwen PuDepartment of Biobank, Dalian Public Health Clinical Center, Dalian, 116001, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: It is well recognized that the proteomic plays a critical role in hepatocellular carcinoma (HCC) progression. However, the mechanisms of these proteins, particularly those regulated by phosphorylation, remain incompletely understood. This study aims to systematically characterize stage-specific molecular features of HCC to elucidate the key proteins and post-translational modification (PTM) networks that drive malignant transformation, and to identify candidate core biomarkers and therapeutic targets. Patients and Methods: Relative quantitative proteomics and TMT-labeled quantitative phosphoproteomics were used to identify hepatocellular carcinoma tissue (HCT), adjacent noncancerous tissue (ANT), and liver cirrhosis tissue (LCT). Functional enrichment analysis was performed with the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO); upstream kinases were predicted using PhosphoSitePlus (PSP), and protein-protein interaction (PPI) data were downloaded from STRING for network scoring and downstream analyses. Results: Integrated profiling revealed coordinated alterations in protein abundance and phosphorylation in HCT that were absent between ANT and LCT, indicating non-linear, multi-pathway convergence during tumorigenesis. A multi-tier scoring scheme prioritized 12 overlapping core driver proteins, including fructose-bisphosphate aldolase B (ALDOB), fumarylacetoacetase (FAH), argininosuccinate synthase (ASS1), cytochrome P450 2C8 (CYP2C8), and cytochrome P450 4A11 (CYP4A11). These proteins were significantly enriched in lipid, amino-acid, and carbohydrate metabolic pathways. Notably, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) showed unchanged total protein abundance but a marked reduction in phosphorylation in HCT vs. LCT, indicating stage-specific regulation dominated by post-translational modification. Kinase prediction further suggested potential cross-pathway reprogramming of phosphorylation signaling. Conclusion: The cytochrome P450 enzymes CYP4A11 and CYP2C8 (lipid metabolism), the amino-acid metabolism enzymes ASS1 and FAH, and the carbohydrate metabolism enzymes ALDOB and GAPDH were identified as key regulatory proteins in HCC progression. Aberrant phosphorylation of ALDOB and phosphorylation-dependent regulation of GAPDH, together with cross-pathway signaling rewiring, provide novel mechanistic insights into HCC pathogenesis.

Indexed as

biomarkerhepatocellular carcinomaphosphoproteomicsproteomics

Identifiers

PMID41847173
PMCPMC12989690

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.