ArticleInternational journal of molecular sciences2022
Bioinformatics Screening of Potential Biomarkers from mRNA Expression Profiles to Discover Drug Targets and Agents for Cervical Cancer.
Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.
- Exploration of key drug target proteins highlighting their related regulatory molecules, functional pathways and drug candidates associated with delirium: evidence from meta-data analyses.BMC geriatrics · 2023Pooled it
- Zeste White 10 May Serve as a Prognostic Biomarker and Therapeutic Target for Human Breast Cancer.Breast cancer : basic and clinical research · 2026Article
- In-silico discovery of druggable molecular signatures that drive dengue fever to severe dengue fever highlighting common pathogenesis through single-cell RNA-Seq analysis.Scientific reports · 2025Article
- How human papillomavirus (HPV) targets DNA repair pathways for viral replication: from guardian to accomplice.Microbiology and molecular biology reviews : MMBR · 2025Review
- HCCS Serves as Potential Prognostic Biomarker and Therapeutic Target in Human Breast Cancer.International journal of breast cancer · 2025Article
- The miRNA-mRNA Regulatory Network in Human Hepatocellular Carcinoma by Transcriptomic Analysis From GEO.Cancer reports (Hoboken, N.J.) · 2025Article
- Prediction of Cervical Cancer Progression Leveraging HPV16 Integration-Related Genes.International journal of women's health · 2025Article
- Discovery of Essential Genes as Possible Targets for Prostate Cancer Drug Development.International journal of genomics · 2025Article
- Elevated Serum IL-6 as a Negative Prognostic Biomarker in Glioblastoma: Integrating Bioinformatics and Clinical Validation.Journal of Cancer · 2025Article
- Identification of hub fatty acid metabolism-related genes and immune infiltration in IgA nephropathy.Renal failure · 2024Article
- Sanguinarine identified as a natural dual inhibitor of AURKA and CDK2 through network pharmacology and bioinformatics approaches.Scientific reports · 2024Article
- Untargeted metabolomics-based network pharmacology reveals fermented brown rice towards anti-obesity efficacy.NPJ science of food · 2024Article
- Meta-2OM: A multi-classifier meta-model for the accurate prediction of RNA 2'-O-methylation sites in human RNA.PloS one · 2024Article
- Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer.Bioinformatics and biology insights · 2024Article
- Article
- Identification of neutrophil extracellular traps and crosstalk genes linking inflammatory bowel disease and osteoporosis by integrated bioinformatics analysis and machine learning.Scientific reports · 2023Article
- Identifying TME signatures for cervical cancer prognosis based on GEO and TCGA databases.Heliyon · 2023Article
- Computational Biology Helps Understand How Polyploid Giant Cancer Cells Drive Tumor Success.Genes · 2023Review
- Article
- Identification of host genomic biomarkers from multiple transcriptomics datasets for diagnosis and therapies of SARS-CoV-2 infections.PloS one · 2023Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
Abstract
Bioinformatics analysis has been playing a vital role in identifying potential genomic biomarkers more accurately from an enormous number of candidates by reducing time and cost compared to the wet-lab-based experimental procedures for disease diagnosis, prognosis, and therapies. Cervical cancer (CC) is one of the most malignant diseases seen in women worldwide. This study aimed at identifying potential key genes (KGs), highlighting their functions, signaling pathways, and candidate drugs for CC diagnosis and targeting therapies. Four publicly available microarray datasets of CC were analyzed for identifying differentially expressed genes (DEGs) by the LIMMA approach through GEO2R online tool. We identified 116 common DEGs (cDEGs) that were utilized to identify seven KGs (AURKA, BRCA1, CCNB1, CDK1, MCM2, NCAPG2, and TOP2A) by the protein-protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of KGs revealed some important functions and signaling pathways that were significantly associated with CC infections. The interaction network analysis identified four TFs proteins and two miRNAs as the key transcriptional and post-transcriptional regulators of KGs. Considering seven KGs-based proteins, four key TFs proteins, and already published top-ranked seven KGs-based proteins (where five KGs were common with our proposed seven KGs) as drug target receptors, we performed their docking analysis with the 80 meta-drug agents that were already published by different reputed journals as CC drugs. We found Paclitaxel, Vinorelbine, Vincristine, Docetaxel, Everolimus, Temsirolimus, and Cabazitaxel as the top-ranked seven candidate drugs. Finally, we investigated the binding stability of the top-ranked three drugs (Paclitaxel, Vincristine, Vinorelbine) by using 100 ns MD-based MM-PBSA simulations with the three top-ranked proposed receptors (AURKA, CDK1, TOP2A) and observed their stable performance. Therefore, the proposed drugs might play a vital role in the treatment against CC.
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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 Socratic graph.