ArticleOncotarget2016
In silico pathway analysis in cervical carcinoma reveals potential new targets for treatment.
Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Genes associated with epithelial mesenchymal transition (EMT) in cervical cancer progression.Discover oncology · 2025Article
- TAB2 Promotes Immune Escape and Chemoresistance Through NF-κB Pathway Activation in Cervical Cancer.Journal of cellular and molecular medicine · 2025Article
- Integrative Analysis of Shared Pathogenic Genes and Potential Mechanisms inMediators of inflammation · 2025Article
- Analysis of miR-497/195 cluster identifies new therapeutic targets in cervical cancer.BMC research notes · 2024Article
- The role of NF-κB in carcinogenesis of cervical cancer: opportunities and challenges.Molecular biology reports · 2024Review
- ESRRB Inhibits the TGFβ Signaling Pathway to Drive Cell Proliferation in Cervical Cancer.Cancer research · 2023Article
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- Bioinformatics analysis of differentially expressed genes and pathways in the development of cervical cancer.BMC cancer · 2021Article
- Targeting the PD-1 Axis with Pembrolizumab for Recurrent or Metastatic Cancer of the Uterine Cervix: A Brief Update.International journal of molecular sciences · 2021Review
- Dysregulation of Transcription Factor Networks Unveils Different Pathways in Human Papillomavirus 16-Positive Squamous Cell Carcinoma and Adenocarcinoma of the Uterine Cervix.Frontiers in oncology · 2021Article
- CDK1 serves as a novel therapeutic target for endometrioid endometrial cancer.Journal of Cancer · 2021Article
- RANK-RANKL Signaling in Cancer of the Uterine Cervix: A Review.International journal of molecular sciences · 2019Review
- Identification of Key Genes and Pathways in Cervical Cancer by Bioinformatics Analysis.International journal of medical sciences · 2019Article
- Sex-specific epigenetic mediators between early life social disadvantage and adulthood BMI.Epigenomics · 2018Article
- Identification of key candidate genes and small molecule drugs in cervical cancer by bioinformatics strategy.Cancer management and research · 2018Article
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- Interactome analysis of gene expression profiles of cervical cancer reveals dysregulated mitotic gene clusters.American journal of translational research · 2017Article
- Epigenetic Mediators Between Childhood Socioeconomic Disadvantage and Mid-Life Body Mass Index: The New England Family Study.Psychosomatic medicineArticle
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An in silico pathway analysis was performed in order to improve current knowledge on the molecular drivers of cervical cancer and detect potential targets for treatment. Three publicly available Affymetrix gene expression data-sets (GSE5787, GSE7803, GSE9750) were retrieved, vouching for a total of 9 cervical cancer cell lines (CCCLs), 39 normal cervical samples, 7 CIN3 samples and 111 cervical cancer samples (CCSs). Predication analysis of microarrays was performed in the Affymetrix sets to identify cervical cancer biomarkers. To select cancer cell-specific genes the CCSs were compared to the CCCLs. Validated genes were submitted to a gene set enrichment analysis (GSEA) and Expression2Kinases (E2K). In the CCSs a total of 1,547 probe sets were identified that were overexpressed (FDR < 0.1). Comparing to CCCLs 560 probe sets (481 unique genes) had a cancer cell-specific expression profile, and 315 of these genes (65%) were validated. GSEA identified 5 cancer hallmarks enriched in CCSs (P < 0.01 and FDR < 0.25) showing that deregulation of the cell cycle is a major component of cervical cancer biology. E2K identified a protein-protein interaction (PPI) network of 162 nodes (including 20 drugable kinases) and 1626 edges. This PPI-network consists of 5 signaling modules associated with MYC signaling (Module 1), cell cycle deregulation (Module 2), TGFβ-signaling (Module 3), MAPK signaling (Module 4) and chromatin modeling (Module 5). Potential targets for treatment which could be identified were CDK1, CDK2, ABL1, ATM, AKT1, MAPK1, MAPK3 among others. The present study identified important driver pathways in cervical carcinogenesis which should be assessed for their potential therapeutic drugability.
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Registered trials
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