ArticleMedicine2020
Screening and identification of key biomarkers for retinoblastoma: Evidence from bioinformatics analysis.
Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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.
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
3 citing papers in PubMed, 4 citations in OpenAlex.
- Risk of secondary tumours in patients with non-metastatic and metastatic human retinoblastoma.Eye (London, England) · 2023Article
- Exploration of retinoblastoma pathogenesis with bioinformatics.Translational cancer research · 2021Article
- ARMT: An automatic RNA-seq data mining tool based on comprehensive and integrative analysis in cancer research.Computational and structural biotechnology journal · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRetinoblastoma (RB) is one of the most common malignant tumors in pediatrics; to clarify the cause of RB, a lot of manpower and material resources have been invested but have not been well explained.
methodsTo identify the candidate genes in the occurrence and development of the disease, we downloaded the microarray datasets GSE97508, GSE92987, and GSE24673 from the gene expression database (GEO). The differentially expressed gene (DEG) was identified and functional enrichment analysis was performed. The protein-protein interaction network was constructed and analyzed by String and Cytoscape.
resultsA total of 74 DEGs were identified, including 40 up-regulated genes and 34 down-regulated genes. The rich functions and pathways of DEG include regulating mitosis, cell cycle, DNA transcription process, promoting protein phosphorylation, regulating energy metabolism in vivo, promoting the binding of some macromolecular complexes, and regulating the cell cycle. Twenty-four HUB genes were identified. Biological process analysis showed that these genes were mainly enriched in regulating energy metabolism in vivo, promoting the binding of some small molecules and regulating the cell cycle. Survival analysis showed that DGPDC1, NDC80, SHCBP, TOP2A, and DLGAP5 may be involved in the occurrence, invasion, or recurrence of RB.
conclusionIn conclusion, screening DEGs and HUB genes in RB can help us to better understand the mechanism of the occurrence and development of RB at the molecular level, and provide candidate targets for the diagnosis and treatment of RB.
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Registered trials
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