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Discover Oncology
Article . 2022 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Discover Oncology
Article . 2022
Data sources: DOAJ
https://dx.doi.org/10.60692/mf...
Other literature type . 2022
Data sources: Datacite
https://dx.doi.org/10.60692/j0...
Other literature type . 2022
Data sources: Datacite
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Metadata analysis to explore hub of the hub-genes highlighting their functions, pathways and regulators for cervical cancer diagnosis and therapies

تحليل البيانات الوصفية لاستكشاف محور الجينات المحورية التي تسلط الضوء على وظائفها ومساراتها ومنظميها لتشخيص سرطان عنق الرحم وعلاجاته
Authors: Md. Selim Reza; Md. Alim Hossen; Md. Harun-Or-Roshid; Mst. Ayesha Siddika; Md. Hadiul Kabir; Md. Nurul Haque Mollah;

Metadata analysis to explore hub of the hub-genes highlighting their functions, pathways and regulators for cervical cancer diagnosis and therapies

Abstract

AbstractCervical cancer (CC) is considered as the fourth most common women cancer globally.that shows malignant features of local infiltration and invasion into adjacent organs and tissues. There are several individual studies in the literature that explored CC-causing hub-genes (HubGs), however, we observed that their results are not so consistent. Therefore, the main objective of this study was to explore hub of the HubGs (hHubGs) that might be more representative CC-causing HubGs compare to the single study based HubGs. We reviewed 52 published articles and found 255 HubGs/studied-genes in total. Among them, we selected 10 HubGs (CDK1, CDK2, CHEK1, MKI67, TOP2A, BRCA1, PLK1, CCNA2, CCNB1, TYMS) as the hHubGs by the protein–protein interaction (PPI) network analysis. Then, we validated their differential expression patterns between CC and control samples through the GPEA database. The enrichment analysis of HubGs revealed some crucial CC-causing biological processes (BPs), molecular functions (MFs) and cellular components (CCs) by involving hHubGs. The gene regulatory network (GRN) analysis identified four TFs proteins and three miRNAs as the key transcriptional and post-transcriptional regulators of hHubGs. Then, we identified hHubGs-guided top-ranked FDA-approved 10 candidate drugs and validated them against the state-of-the-arts independent receptors by molecular docking analysis. Finally, we investigated the binding stability of the top-ranked three candidate drugs (Docetaxel, Temsirolimus, Paclitaxel) by using 100 ns MD-based MM-PBSA simulations and observed their stable performance. Therefore the finding of this study might be the useful resources for CC diagnosis and therapies.

Related Organizations
Keywords

FOS: Computer and information sciences, Candidate gene, Cyclin-dependent kinase 1, Bioinformatics, Hub genes (HubGs), Gene Set Enrichment Analysis, Cell cycle, Gene, Pathology and Forensic Medicine, Computational biology, Biochemistry, Genetics and Molecular Biology, Health Sciences, Genetics, KRAS, Molecular Biology, Biology, RC254-282, Candidate drugs, Cancer, microRNA, Research, In silico, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Life Sciences, Hub of the HubGs (hHubGs), Integrated bioinformatics analysis, Role of Pim Oncogenes in Tumorigenesis, Cervical cancer (CC), Analysis of Gene Interaction Networks, FOS: Biological sciences, Regulation of RNA Processing and Function, HRAS, Mutation, Cervical cancer, Medicine

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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
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    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Top 10%
Average
Top 10%
Green
gold