ArticleJournal of Cancer2020
Bioinformatics analysis and identification of potential genes related to pathogenesis of cervical intraepithelial neoplasia.
Article in Journal of Cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 32 citations in OpenAlex.
- Integrative Analyses of Individual Patient Genomic-Data to Discover Novel Biomarkers: Application to Cervical Pre-Cancer DNA-Methylation Datasets.Cancer informatics · 2026Article
- An integrative approach toward identification and analysis of therapeutic targets involved in HPV pathogenesis with a focus on carcinomas.Cancer biomarkers : section A of Disease markers · 2023Article
- Metadata analysis to explore hub of the hub-genes highlighting their functions, pathways and regulators for cervical cancer diagnosis and therapies.Discover oncology · 2022Article
- Bioinformatics Screening of Potential Biomarkers from mRNA Expression Profiles to Discover Drug Targets and Agents for Cervical Cancer.International journal of molecular sciences · 2022Article
- Deep Learning-Based Multi-Omics Integration Robustly Predicts Relapse in Prostate Cancer.Frontiers in oncology · 2022Article
- A regulatory miRNA-mRNA network is associated with transplantation response in acute kidney injury.Human genomics · 2021Article
- Development and validation of a novel N6-methyladenosine (m6A)-related multi- long non-coding RNA (lncRNA) prognostic signature in pancreatic adenocarcinoma.Bioengineered · 2021Article
- Maintaining the Balance of Intestinal Flora through the Diet: Effective Prevention of Illness.Foods (Basel, Switzerland) · 2021Article
- A role of TTI1 in the colorectal cancer by promoting proliferation.Translational cancer research · 2021Article
- Computational Analysis of the Global Effects ofGenes · 2020Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this study was to explore and identify the key genes and signal pathways contributing to cervical intraepithelial neoplasia (CIN). The gene expression profiles of GSE63514 were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened performing with packages in software R. After Gene ontology terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyzing, and Gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA) was used to analyze these genes. Then sub-modules were subsequently analyzed base CIN grade, and protein-protein interaction (PPI) network of DEGs were constructed. 537 DEGs were screened in total, consisting 331 up-regulated genes and 206 down-regulated genes in CIN samples compared to normal samples. The most DEGs were enriched in chromosomal region in cellular component (CC), organelle fission inbiological process (BP) and ATPase activity in molecular function (MF). KEGG pathway enrichment analyzing found the DEGs were mainly concentrated in 10 pathways. The results of GSEA mainly enriched in 4 functional sets: E2F-Targets, G2M-Checkpoint, Mitotic-Spindle and Spermatogenesis. A total of 6 modules were identified by WCGNA. Subsequently, grey module was the highest correlation (Cor=0.78, P=5e-22) and 31 genes were taken as candidate hub genes for CIN high grade risk (weighted correlation coefficients >0.80). Finally, diagnostic analysis showed that in addition to CCDC7, the expression levels of the remaining 13 DEGs have a high diagnostic value (AUC>0.8 and P<0.05). These findings provided a new sight into the understanding of molecular functions for CIN.
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