ArticleOncology letters2020
Identification of key pathways and genes shared between Crohn's disease and breast cancer using bioinformatics analysis.
Article in Oncology letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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Who cites it
5 citing papers in PubMed, 10 citations in OpenAlex.
- Exploring genetic associations of Crohn's disease and ulcerative colitis with extraintestinal cancers in European and East Asian populations.Frontiers in immunology · 2024Article
- Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer.Medicina (Kaunas, Lithuania) · 2023Article
- Crohn's disease and breast cancer: a literature review of the mechanisms and treatment.Internal and emergency medicine · 2023Review
- Appraising the causal association between Crohn's disease and breast cancer: a Mendelian randomization study.Frontiers in oncology · 2023Article
- Somatic mutational profiles and germline polygenic risk scores in human cancer.Genome medicine · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patients with Crohn's disease (CD) have a high risk of developing breast cancer, suggesting that there may be shared molecular mechanisms underlying CD and breast cancer. The purpose of the present study was to identify the critical genes and pathways underlying these molecular similarities using bioinformatics analysis. Publicly available microarray expression data from the Gene Expression Omnibus were analyzed, and a total of 53 overlapping differentially expressed genes (DEGs) between the CD (vs. controls) and breast cancer (vs. controls) groups were identified. These common DEGs were then subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Subsequently, a gene interaction network of the DEGs was constructed using Cytoscape software, with its plug-in cytoHubba and Molecular Complex Detection. The gene interaction network and module analysis demonstrated that prostaglandin G/H synthase 2, interleukin (
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Registered trials
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