ArticleOncology letters2018
Identification of differentially expressed genes in cervical cancer by bioinformatics analysis.
Article in Oncology letters, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Effect of microRNA-141-3p, E2F3, CDK3, and KAT2B overexpression on histologic tumor grade and metastasis status in untreated breast cancer tissues.BioImpacts : BI · 2025Article
- Multidimensional outlook on the pathophysiology of cervical cancer invasion and metastasis.Molecular and cellular biochemistry · 2023Review
- Construction of miRNA-mRNA networks for the identification of lung cancer biomarkers in liquid biopsies.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023Article
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- Nuclear factor IB is downregulated in vulvar squamous cell carcinoma (VSCC): Unravelling differentially expressed genes in VSCC through gene expression dataset analysis.Oncology letters · 2021Article
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- Article
- Direct-acting Antiviral in the Treatment of Chronic Hepatitis C: Bonuses and Challenges.International journal of medical sciences · 2020Review
- The Landscape of Iron Metabolism-Related and Methylated Genes in the Prognosis Prediction of Clear Cell Renal Cell Carcinoma.Frontiers in oncology · 2020Article
- Co-expression network analysis identified atypical chemokine receptor 1 (ACKR1) association with lymph node metastasis and prognosis in cervical cancer.Cancer biomarkers : section A of Disease markers · 2020Article
- CD38 affects the biological behavior and energy metabolism of nasopharyngeal carcinoma cells.International journal of oncology · 2019Article
- Identification of Key Genes and Pathways in Cervical Cancer by Bioinformatics Analysis.International journal of medical sciences · 2019Article
- Identification of candidate biomarkers correlated with the diagnosis and prognosis of cervical cancer via integrated bioinformatics analysis.OncoTargets and therapy · 2019Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cervical cancer is the most common gynecological malignancy. In recent years, the incidence of cervical cancer has had a younger trend. Cervical cancer morbidity and mortality rates have been significantly reduced due to recent decades of cervical cytology screening leading to the early detection and treatment of cervical cancer and precancerous lesions. There are a number of methods used to treat cervical cancer and improve the survival rate. However, the prevalence and recurrence rates of cervical cancer are increasing every year. There is an urgent requirement for a better understanding of the molecular mechanism cervical cancer development. The present study used scientific information retrieval from the Gene Expression Omnibus database to download the GSE26511 dataset, which contained 39 samples, including 19 cervical cancer lymph node-positive samples and 20 cervical cancer lymph node-negative samples. Using Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis, and weighted gene co-expression network analysis, 1,263 differentially expressed genes were found that affected the biological processes, including 'cell cycle process', 'signaling pathways', 'immune response', 'cell activation', 'regulation of immune system process' and 'inflammatory response'. These areas should be the focus of study for cervical cancer in the future.
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