Evidence map›Paper›PMID 30345303›Full record

Trial reportBioMed research international2018

Identification of Candidate Biomarkers in Malignant Ascites from Patients with Hepatocellular Carcinoma by iTRAQ-Based Quantitative Proteomic Analysis.

Jinyan Zhang, Rong Liang, Jiazhang Wei, Jiaxiang Ye, Qian He, ChunlingYuan, Jiazhou Ye, Yongqiang Li, Zhihui Liu, Yan Lin

Open access · hybridAbstract readClinical Trial
In one paragraph

Trial report in BioMed research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 22% of its field
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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
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  6. PD-L1Cancer immunology, immunotherapy : CII · 2024
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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

10 authors at 3 institutions in 3 countries.

Jinyan ZhangDepartment of Medical Oncology, Affiliated Cancer Hospital of Guangxi Medical University, Nanning 530021, China.ORCID 0000-0002-9874-2744
Rong LiangDepartment of Medical Oncology, Affiliated Cancer Hospital of Guangxi Medical University, Nanning 530021, China.
Jiazhang WeiDepartment of Otolaryngology & Head and Neck, The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, China.
Jiaxiang YeDepartment of Medical Oncology, Affiliated Cancer Hospital of Guangxi Medical University, Nanning 530021, China.
Qian HeInstitute for the Advancement of Higher Education, Hokkaido University, Sapporo 060-0817, Japan.
ChunlingYuanDepartment of Medical Oncology, Affiliated Cancer Hospital of Guangxi Medical University, Nanning 530021, China.
Jiazhou YeDepartment of Hepatobiliary Surgery Oncology, Affiliated Cancer Hospital of Guangxi Medical University, Nanning 530021, China.
Yongqiang LiDepartment of Medical Oncology, Affiliated Cancer Hospital of Guangxi Medical University, Nanning 530021, China.
Zhihui LiuDepartment of Medical Oncology, Affiliated Cancer Hospital of Guangxi Medical University, Nanning 530021, China.
Yan LinDepartment of Medical Oncology, Affiliated Cancer Hospital of Guangxi Medical University, Nanning 530021, China.ORCID 0000-0001-8034-5946
Guangxi Medical University · CNHokkaido University · JPThe People's Hospital of Guangxi Zhuang Autonomous Region · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Almost all the patients with hepatocellular carcinoma (HCC) at advanced stage experience pathological changes of chronic liver cirrhosis, which generally leads to moderate ascites. Recognition of novel biomarkers in malignant ascites could be favorable for establishing a diagnosis for the HCC patients with ascites, and even predicting prognosis, such as risk of distant metastasis. To distinguish the proteomic profiles of malignant ascites in HCC patients from those with nonmalignant liver cirrhosis, an iTRAQ pipeline was built up to analyze the differentially distributed proteins in the malignant ascites from HCC patients (n=10) and benign ascites from hepatic decompensation (HD) controls (n=9). In total, 112 differentially distributed proteins were identified, of which 69 proteins were upregulated and 43 proteins were downregulated (ratio <0.667 or >1.3, respectively) in the malignant ascites. Moreover, 19 upregulated proteins (including keratin 1 protein and rheumatoid factor RF-IP20, ratio>1.5) and 8 downregulated proteins (including carbonic anhydrase 1, ratio<0.667) were identified from malignant ascites samples. Functional categories analyses indicated that membrane proteins, ion regulation, and amino acid metabolism are implicated in the formation of HCC malignant ascites. Pathways mapping revealed that glycolysis/gluconeogenesis and complement/coagulation cascades are the mostly affected cell life activities in HCC malignant ascites, suggesting the key factors in these pathways such as Enolase-1 and fibrinogen are potential ascitic fluid based biomarkers for diagnosis and prognosis for HCC.

Indexed as

Gene Expression Regulation, NeoplasticProteomicsAscitesBiomarkers, TumorCarcinoma, HepatocellularFemaleHumansLiver NeoplasmsMaleNeoplasm ProteinsBiomarkers, TumorNeoplasm Proteins

Identifiers

PMID30345303
PMCPMC6174818
OpenAlexW2894513421

What OpenQuestion holds

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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.