Evidence map›Paper›PMID 24936219›Full record

ArticleAmerican journal of translational research2014

Comparative membrane proteomic analysis between lung adenocarcinoma and normal tissue by iTRAQ labeling mass spectrometry.

Xuede Zhang, Wei Li, Yanli Hou, Zequn Niu, Yujie Zhong, Yuping Zhang, Shuanying Yang

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.0field-weighted citation impact, top 26% 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, 17 citations in OpenAlex.

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  14. Identification of adipophilin as a potential diagnostic tumor marker for lung adenocarcinoma.International journal of clinical and experimental medicine · 2014
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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

7 authors at 1 institution in 1 country.

Xuede ZhangDepartment of Respiratory Medicine, The Second Affiliated Hospital of Medical College, Xi'an Jiaotong University Xi'an, Shannxi 710004, China.
Wei LiDepartment of Respiratory Medicine, The Second Affiliated Hospital of Medical College, Xi'an Jiaotong University Xi'an, Shannxi 710004, China.
Yanli HouDepartment of Respiratory Medicine, The Second Affiliated Hospital of Medical College, Xi'an Jiaotong University Xi'an, Shannxi 710004, China.
Zequn NiuDepartment of Respiratory Medicine, The Second Affiliated Hospital of Medical College, Xi'an Jiaotong University Xi'an, Shannxi 710004, China.
Yujie ZhongDepartment of Respiratory Medicine, The Second Affiliated Hospital of Medical College, Xi'an Jiaotong University Xi'an, Shannxi 710004, China.
Yuping ZhangDepartment of Respiratory Medicine, The Second Affiliated Hospital of Medical College, Xi'an Jiaotong University Xi'an, Shannxi 710004, China.
Shuanying YangDepartment of Respiratory Medicine, The Second Affiliated Hospital of Medical College, Xi'an Jiaotong University Xi'an, Shannxi 710004, China.
Second Affiliated Hospital of Xi'an Jiaotong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung adenocarcinoma, the most common type of lung cancer, has increased in recent years. Prognosis is still poor, and pathogenesis remains unclear. This study aimed to investigate the membrane protein profile differences between lung adenocarcinoma and normal tissue. Manual microdissection was used to isolate the target cells from tumor tissue and normal tissue. iTRAQ labeling combined with 2D-LC-MS/MS yielded a differential expression profile of membrane proteins. Bioinformatic analysis was performed using Gene Ontology, WEGO, PID, and KEGG. S100A14 protein was selectively verified by Western blotting. The relationship of S100A14 expression with clinicopathological features in lung cancer patients was evaluated using immunohistochemistry. As a result, 568 differential proteins were identified; 257 proteins were upregulated and 311 were downregulated. Of these proteins, 48% were found to be membrane bound or membrane associated. These proteins enable the physiological functions of binding, catalysis, molecular transduction, transport, and molecular structure. For these differential proteins, 35 pathways were significantly enriched through the Pathway Interaction Database, whereas 19 pathways were enriched via KEGG. The overexpression and cellular distribution of S100A14 in lung cancer were confirmed. We found that upregulation of S100A14 was associated with well or moderate differentiation. The iTRAQ-coupled 2D-LC-MS/MS technique is a potential method for comparing membrane protein profiles between tumor and normal tissue. Such analysis may also help in identifying novel biomarkers and the mechanisms underlying carcinogenesis.

Indexed as

iTRAQLung adenocarcinomamass spectrometrymembrane proteinproteomic profile

Identifiers

PMID24936219
PMCPMC4058308
OpenAlexW251778098

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.