Evidence map›Paper›PMID 36770959›Full record

ArticleMolecules (Basel, Switzerland)2023

Glycoproteomic Analysis of Urinary Extracellular Vesicles for Biomarkers of Hepatocellular Carcinoma.

Dejun Li, Shengnan Jia, Shuyue Wang, Lianghai Hu

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 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

4 authors.

Dejun LiCenter for Supramolecular Chemical Biology, School of Life Sciences, Jilin University, Changchun 130012, China.
Shengnan JiaDepartment of Hepatopancreatobiliary Medicine, The Second Hospital, Jilin University, Changchun 130041, China.
Shuyue WangCenter for Supramolecular Chemical Biology, School of Life Sciences, Jilin University, Changchun 130012, China.
Lianghai HuCenter for Supramolecular Chemical Biology, School of Life Sciences, Jilin University, Changchun 130012, China.

Funding

Jilin Province Health Project No. 2020SCZT057 to SN.J.National Natural Science Foundation of China No. 21675061
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) accounts for the most common form of primary liver cancer cases and constitutes a major health problem worldwide. The diagnosis of HCC is still challenging due to the low sensitivity and specificity of the serum α-fetoprotein (AFP) diagnostic method. Extracellular vesicles (EVs) are heterogeneous populations of phospholipid bilayer-enclosed vesicles that can be found in many biological fluids, and have great potential as circulating biomarkers for biomarker discovery and disease diagnosis. Protein glycosylation plays crucial roles in many biological processes and aberrant glycosylation is a hallmark of cancer. Herein, we performed a comprehensive glycoproteomic profiling of urinary EVs at the intact N-glycopeptide level to screen potential biomarkers for the diagnosis of HCC. With the control of the spectrum-level false discovery rate ≤1%, 756 intact N-glycopeptides with 154 N-glycosites, 158 peptide backbones, and 107 N-glycoproteins were identified. Out of 756 intact N-glycopeptides, 344 differentially expressed intact N-glycopeptides (DEGPs) were identified, corresponding to 308 upregulated and 36 downregulated N-glycopeptides, respectively. Compared to normal control (NC), the glycoproteins LG3BP, PIGR and KNG1 are upregulated in HCC-derived EVs, while ASPP2 is downregulated. The findings demonstrated that specific site-specific glycoforms in these glycoproteins from urinary EVs could be potential and efficient non-invasive candidate biomarkers for HCC diagnosis.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsBiomarkersBiomarkers, TumorGlycopeptidesGlycoproteinsHumansBiomarkersBiomarkers, TumorGlycopeptidesGlycoproteinsbiomarkerextracellular vesiclesglycoproteomichepatocellular carcinomamass spectrometryN-glycosylation

Identifiers

PMID36770959
PMCPMC9919939

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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.