ArticleBioMed research international2022
Recognition of Key Genes in Human Anaplastic Thyroid Cancer via the Weighing Gene Coexpression Network.
Article in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. 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.
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
5 citing papers in PubMed, 6 citations in OpenAlex.
- Identification and validation of a novel prognostic signature and key genes related to development of anaplastic thyroid carcinoma.Discover oncology · 2024Article
- Harnessing Immunity to Treat Advanced Thyroid Cancer.Vaccines · 2023Review
- Update on current diagnosis and management of anaplastic thyroid carcinoma.World journal of clinical oncology · 2023Review
- Identification and Verification of Potential Biomarkers in Renal Ischemia-Reperfusion Injury by Integrated Bioinformatic Analysis.BioMed research international · 2023Article
- Retracted: Recognition of Key Genes in Human Anaplastic Thyroid Cancer via the Weighing Gene Coexpression Network.BioMed research international · 2023Article
Corrections and comments
- Retraction · 2023-12-29Compromised Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Paper Mill · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Methods: For determining pathways and key genes that have relation with development of ATC, differentially expressed genes (DEGs) from GSE33630 as well as GSE65144 expression microarray were screened. Furthermore, we also worked on carrying out the task of constructing a protein-protein interaction (PPI) network and the work of weighing gene coexpression network (WGCNA). DAVID was utilized for the performance of the Gene Ontology (GO) as well as KEGG pathway enrichment analyses for DEGs. We used TCGA THCA data and GSE53072 to further verify the hub gene and hub pathway. Results: We came to the conclusion of the recognition of a total of 1063 genes as DEGs. Analysis regarding functional and pathway enrichment showed that there existed a notable enrichment of upregulated DEGs in the organization of extracellular structure and matrix organization, as well as in organelle fission and nuclear division. The downregulated DEG was markedly gathered in the thyroid hormone metabolic process and generation, as well as in the metabolic process of cellular modified amino acid. We identified 10 hub genes (CXCL8, CDH1, AURKA, CCNA2, FN1, CDK1, ITGAM, CDC20, MMP9, and KIF11) through the PPI network, which might be strongly linked to the carcinogenesis and the development of ATC. In the coexpression network, 6 modules that were relevant to ATC were recognized. The modules were related to the interaction of signaling pathway of p53, Hippo, PI3K/Akt, and ECM-receptor. This hub genes and hub pathway were further successfully validated as a potential biomarker for carcinogenesis and prediction in another database GSE53072. Conclusion: To summarize, this research displayed an illustration of hub genes and pathways that had relation with ATC development, which suggested that DEGs and hub genes, recognized on the basis of bioinformatics analyses, were valuable in the diagnosis for patients with ATC.
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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.