ArticleData in brief2016
Data from a comparative proteomic analysis of tumor-derived lung-cancer CD105(+) endothelial cells.
Article in Data in brief, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
- Article
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Increasing evidence indicates that tumor-derived endothelial cells (TECs) are more relevant for the study of tumor angiogenesis and for screening antiangiogenic drugs than normal ECs (NECs). In this data article, high-purity (>98%) primary CD105(+) NECs and TECs purified from a mouse Lewis lung carcinoma model bearing 0.5 cm tumors were identified using 2D-PAGE and Matrix-assisted laser desorption/ionization tandem mass spectrometry (MALDI-MS/MS). All the identified proteins were categorized functionally by Gene Ontology (GO) analysis, and gene-pathway annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, protein-protein interaction networks were also built. The proteomics and bioinformatics data presented here provide novel insights into the molecular characteristics and the early modulation of the TEC proteome in the tumor microenvironment.
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Registered trials
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