ArticleCancer cell international2020
Identification of molecular markers associated with the progression and prognosis of endometrial cancer: a bioinformatic study.
Article in Cancer cell international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 31 citations in OpenAlex.
- Clinical overall survival prediction and disease characteristics of locally advanced non-small cell lung cancer: an integrated analysis based on the SEER and TCGA databases.Translational cancer research · 2026Article
- Molecular Pathways and Biomarkers in Endometrial Carcinoma: Paving the Way for Precision Medicine.Anti-cancer agents in medicinal chemistry · 2026Review
- Identification and validation of the important role of KIF11 in the development and progression of endometrial cancer.Journal of translational medicine · 2025Article
- Comprehensive analysis of potential biomarkers for the diagnosis and prognosis of Cervical squamous cell carcinoma - based on GEO and TCGA databases.Frontiers in oncology · 2025Article
- Disease characteristics and clinical specific survival prediction of spinal ependymoma: a genetic and population-based study.Frontiers in neurology · 2024Article
- Expression Profiles of Hypoxia-Related Genes of Cancers Originating from Anatomically Similar Locations Using TCGA Database Analysis.Medicines (Basel, Switzerland) · 2023Article
- The neurological and non-neurological roles of the primary microcephaly-associated protein ASPM.Frontiers in neuroscience · 2023Review
- Article
- Construction of a Prognosis-Related Gene Signature by Weighted Gene Coexpression Network Analysis in Ewing Sarcoma.Computational and mathematical methods in medicine · 2022Article
- NCAPG as a Novel Prognostic Biomarker in Glioma.Frontiers in oncology · 2022Article
- Bioinformatic analysis identifying FGF1 gene as a new prognostic indicator in clear cell Renal Cell Carcinoma.Cancer cell international · 2021Article
- Identification of HCC Subtypes With Different Prognosis and Metabolic Patterns Based on Mitophagy.Frontiers in cell and developmental biology · 2021Article
- Screening and Identification of Hub Genes in the Corticosteroid Resistance Network in Human Airway Epithelial CellsFrontiers in pharmacology · 2021Article
- Identification of a Four-Gene Signature With Prognostic Significance in Endometrial Cancer Using Weighted-Gene Correlation Network Analysis.Frontiers in genetics · 2021Article
- Screening of Hub Genes Associated with Pulmonary Arterial Hypertension by Integrated Bioinformatic Analysis.BioMed research international · 2021Article
- Identification of 6 Hub Proteins and Protein Risk Signature of Colorectal Cancer.BioMed research international · 2020Article
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEndometrial cancer (EC) is one kind of women cancers. Bioinformatic technology could screen out relative genes which made targeted therapy becoming conventionalized.
methodsGSE17025 were downloaded from GEO. The genomic data and clinical data were obtained from TCGA. R software and bioconductor packages were used to identify the DEGs. Clusterprofiler was used for functional analysis. STRING was used to assess PPI information and plug-in MCODE to screen hub modules in Cytoscape. The selected genes were coped with functional analysis. CMap could find EC-related drugs that might have potential effect. Univariate and multivariate Cox proportional hazards regression analyses were performed to predict the risk of each patient. Kaplan-Meier curve analysis could compare the survival time. ROC curve analysis was performed to predict value of the genes. Mutation and survival analysis in TCGA database and UALCAN validation were completed. Immunohistochemistry staining from Human Protein Atlas database. GSEA, ROC curve analysis, Oncomine and qRT-PCR were also performed.
resultsFunctional analysis showed that the upregulated DEGs were strikingly enriched in chemokine activity, and the down-regulated DEGs in glycosaminoglycan binding. PPI network suggested that NCAPG was the most relevant protein. CMap identified 10 small molecules as possible drugs to treat EC. Cox analysis showed that BCHE, MAL and ASPM were correlated with EC prognosis. TCGA dataset analysis showed significantly mutated BHCE positively related to EC prognosis. MAL and ASPM were further validated in UALCAN. All the results demonstrated that the two genes might promote EC progression. The profile of ASPM was confirmed by the results from immunohistochemistry. ROC curve demonstrated that the mRNA levels of two genes exhibited difference between normal and tumor tissues, indicating their diagnostic efficiency. qRT-PCR results supported the above results. Oncomine results showed that DNA copy number variation of MAL was significantly higher in different EC subtypes than in healthy tissues. GSEA suggested that the two genes played crucial roles in cell cycle.
conclusionBCHE, MAL and ASPM are tumor-related genes and can be used as potential biomarkers in EC treatment.
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