ArticleOncology letters2017
Bioinformatic identification of candidate genes induced by trichostatin A in BGC-823 gastric cancer cells.
Article in Oncology letters, 2017. 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
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Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
- Tumor Immunometabolism Characterization in Ovarian Cancer With Prognostic and Therapeutic Implications.Frontiers in oncology · 2021Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of the present study was to identify the candidate genes induced by trichostatin A (TSA) in BGC-823 gastric cancer (GC) cells and to explore the possible inhibition mechanism of TSA in GC. Gene expression data were obtained through chip detection, and differentially expressed genes (DEGs) between GC cells treated with TSA and untreated GC cells (control group) were identified. Gene ontology analysis of the DEGs was performed using the database for annotation, visualization and integrated discovery. Then sub-pathway enrichment analysis was performed and a microRNA (miRNA) regulatory network was constructed. We selected 76 DEGs, among which 43 were downregulated genes and 33 were upregulated genes. By sub-pathway enrichment analysis of the DEGs, the propanoate metabolism pathway was selected as the sub-pathway. By constructing a miRNA regulatory network, we identified that
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