ArticleTranslational cancer research2020
Analysis of differentially expressed mRNAs and the prognosis of cholangiocarcinoma based on TCGA database.
Article in Translational cancer research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Article
- AURKB activates EMT through PI3K/AKT signaling axis to promote ICC progression.Discover oncology · 2023Article
- DNA Damage Response Inhibitors in Cholangiocarcinoma: Current Progress and Perspectives.Cells · 2022Review
- Identification and validation of a novel ferroptosis-related gene signature for prognosis and potential therapeutic target prediction in cholangiocarcinoma.Frontiers in immunology · 2022Article
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Authors and funding
5 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe effective evaluation of cholangiocarcinoma (CCA) is challenging due to a lack of accurate screening tools. Consequently, there is an urgent need to screen out effective biomarkers. Bioinformatics analysis on a substantial amount of transcriptomic data to screen biomolecules allows for the verification of histological samples, and can provide a new method for CCA biomolecule screening in diagnosis and prognosis.
methodsEdgeR model was used to analyze The Cancer Genome Atlas (TCGA)-extracted CCA data set, and to determine the differential expression of mRNAs. Based on this, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to perform functional and pathway enrichment analysis. Subsequently, a protein interaction network was also established to identify the key differential node genes. Then, the previously determined differential genes were analyzed to establish a link between these genes and clinical prognosis. Finally, we used tissue samples to realize our results via IHC, Western blot and qRT-PCR.
resultsA total of 5,561 differential mRNAs were screened, including 3,473 upregulated genes and 2,088 downregulated genes. GO and KEGG enrichment analysis showed that the upregulated genes had significantly enriched cell adhesion, concentrated chromosomal motility, and microtubule motility. Downregulated genes were significantly enriched in heterologous metabolism and exosomes. Furthermore, we found upregulated genes were significantly enriched in the cancer pathways and cell cycle. Downregulated genes were enriched in the metabolic pathways and biosynthesis of antibiotics. Ten hub genes were screened out through the protein interaction network; among these, the
conclusionsThe upregulated genes were significantly enriched in the biological processes of cell division, cell cycle, and related cell components.
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