Evidence map›Paper›PMID 31709285›Full record

ArticleData in brief2019

Dataset for quantitative phospho-proteomics analysis of a serial hepatoma cell lines with increasing invasion and metastasis potential.

Xiaohua Xing, Hui Yuan, Ying Sun, Kun Ke, Xiuqing Dong, Hui Chen, Xiaolong Liu, Bixing Zhao, Aimin Huang

Abstract read
In one paragraph

Article in Data in brief, 2019. 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

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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

9 authors.

Xiaohua XingThe United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, People's Republic of China.
Hui YuanThe United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, People's Republic of China.
Ying SunThe United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, People's Republic of China.
Kun KeThe United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, People's Republic of China.
Xiuqing DongThe United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, People's Republic of China.
Hui ChenThe First Affiliated Hospital of Fujian Medical University, Fuzhou, 350007, People's Republic of China.
Xiaolong LiuThe United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, People's Republic of China.
Bixing ZhaoThe United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, People's Republic of China.
Aimin HuangThe School of Basic Medical Sciences, Fujian Medical University, Fuzhou, 350004, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatoma is one of the most common malignant tumor, and most patients have very poor prognosis. Early prediction and intervention of the hepatoma recurrence/metastasis are the most effective way to improve the patients' clinical outcomes. Here, we used isobaric tags for relative and absolute quantitation (iTRAQ) based quantitative phospho-proteomics approach to identify biomarkers associated with hepatoma recurrence/metastasis in hepatoma cell lines with increasing metastasis ability. In total, 75 phosphorylated peptides corresponding to 60 phosphoproteins were significantly dysregulated. Bioinformatics analysis (GO, KEGG and IPA) allowed these data to be organized into distinct categories. These data represent the first in-depth proteomics analysis of a serial hepatoma cell lines with increasing invasion and metastasis potential. The data are related to (Xing et al., 2019).

Indexed as

ANXA2Tyr23FLNASer2152HepatomaPrognosisQuantitative phospho-proteomics

Identifiers

PMID31709285
PMCPMC6833346

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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.