ArticleScientific reports2021
A comprehensive transcriptomic landscape of cholangiocarcinoma based on bioinformatics analysis from large cohort of patients.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 11 citations in OpenAlex.
- Genetic Uncertainties Fueling Cholangiocarcinoma Progression.Current genomics · 2025Review
- Unveil Intrahepatic Cholangiocarcinoma Heterogeneity through the Lens of Omics and Multi-Omics Approaches.Cancers · 2024Review
- Review
- Human Vγ9Vδ2 T cell expansion and their cytotoxic responses against cholangiocarcinoma.Scientific reports · 2024Article
- A transcriptome based molecular classification scheme for cholangiocarcinoma and subtype-derived prognostic biomarker.Nature communications · 2024Article
- Redox-Cycling "Mitocans" as Effective New Developments in Anticancer Therapy.International journal of molecular sciences · 2023Article
- Genetic Variant of CXCR1 (rs2234671) Associates with Clinical Outcome in Perihilar Cholangiocarcinoma.Liver cancer · 2022Article
- Article
- MiRNA-196-5p Promotes Proliferation and Migration in Cholangiocarcinoma via HAND1/Wnt/Journal of oncology · 2022Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cholangiocarcinoma (CCA) is a group of malignancies emerging in the biliary tree and is associated with a poor patient prognosis. Although the anatomical location is the only worldwide accepted classification basis, it still has bias. The current study integrates the whole-genome expression data from several big cohorts in the literature, to screen and provide a comprehensive bioinformatic analysis, in order to better classify molecular subtypes and explore an underlying cluster mechanism related to anatomy and geographical regions. Differentially expressed protein-coding genes (DEGs) were identified for CCA as well as subtypes. Biological function enrichment analysis-Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis-was applied and identified different DEGs enriched signaling pathways in CCA subtypes. A co-expression network was presented by Weighted gene co-expression network analysis package and modules related to specific phenotypes were identified. Combined with DEGs, hub genes in the given module were demonstrated through protein-protein interaction network analysis. Finally, DEGs which significantly related to patient overall survival and disease-free survival time were selected, including ARHGAP21, SCP2, UBIAD1, TJP2, RAP1A and HDAC9.
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Registered trials
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.