ArticlePeerJ2020
Identification of significant genes signatures and prognostic biomarkers in cervical squamous carcinoma via bioinformatic data.
Article in PeerJ, 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.
- Construction and validation of a novel prognostic risk model in cervical cancer: integrating lactylation-related genes linked to radiotherapy‑associated transcriptional changes.Discover oncology · 2026Article
- A Novel Eight-Gene Signature for Lipid Metabolism Predicts the Progression of Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma.Reproductive sciences (Thousand Oaks, Calif.) · 2024Article
- Oncogenic Potential of Replication Factor C Subunit 4: Correlations with Tumor Progression and Assessment of Potential Inhibitors.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Article
- Sequential gene expression analysis of cervical malignant transformation identifies RFC4 as a novel diagnostic and prognostic biomarker.BMC medicine · 2022Article
- MCM2 in human cancer: functions, mechanisms, and clinical significance.Molecular medicine (Cambridge, Mass.) · 2022Review
- Article
- RFC4 promotes the progression and growth of Oral Tongue squamous cell carcinoma in vivo and vitro.Journal of clinical laboratory analysis · 2021Article
- Multi-Omics Analysis Identified TMED2 as a Shared Potential Biomarker in Six Subtypes of Human Cancer.International journal of general medicine · 2021Article
- Replication Factor C Subunit 4 Plays a Role in Human Breast Cancer Cell Progression.Cancer genomics & proteomicsArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCervical squamous cancer (CESC) is an intractable gynecological malignancy because of its high mortality rate and difficulty in early diagnosis. Several biomarkers have been found to predict the prognose of CESC using bioinformatics methods, but they still lack clinical effectiveness. Most of the existing bioinformatic studies only focus on the changes of oncogenes but neglect the differences on the protein level and molecular biology validation are rarely conducted.
methodsGene set data from the NCBI-GEO database were used in this study to compare the differences of gene and protein levels between normal and cancer tissues through significant pathway selection and core gene signature analysis to screen potential clinical biomarkers of CESC. Subsequently, the molecular and protein levels of clinical samples were verified by quantitative transcription PCR, western blot and immunohistochemistry.
resultsThree differentially expressed genes (RFC4, MCM2, TOP2A) were found to have a significant survival (
conclusionThis study identified three potential biomarkers (RFC4, MCM2, TOP2A) of CESC which may be useful to clarify the underlying mechanisms of CESC and predict the prognosis of CESC patients.
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