ArticleCancer biomarkers : section A of Disease markers2017
Identification of key genes in endometrioid endometrial adenocarcinoma via TCGA database.
Article in Cancer biomarkers : section A of Disease markers, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 17 citations in OpenAlex.
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- Significance of a PTEN Mutational Status-Associated Gene Signature in the Progression and Prognosis of Endometrial Carcinoma.Oxidative medicine and cellular longevity · 2022Article
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- Investigating the Role of Telomere and Telomerase Associated Genes and Proteins in Endometrial Cancer.Methods and protocols · 2020Article
- Identification of a five-gene signature for predicting the progression and prognosis of stage I endometrial carcinoma.Oncology letters · 2020Article
- Candidate lncRNA-microRNA-mRNA networks in predicting non-small cell lung cancer and related prognosis analysis.Journal of cancer research and clinical oncology · 2020Article
- Knockdown of SLCO4C1 inhibits cell proliferation and metastasis in endometrial cancer through inactivating the PI3K/Akt signaling pathway.Oncology reports · 2020Article
- Expression of Selected Epithelial-Mesenchymal Transition Transcription Factors in Endometrial Cancer.BioMed research international · 2020Article
- Silenced ZNF154 Is Associated with Longer Survival in Resectable Pancreatic Cancer.International journal of molecular sciences · 2019Article
- Identification of key genes and pathways between type I and type II endometrial cancer using bioinformatics analysis.Oncology letters · 2019Article
- Upregulation of PITX2 Promotes Letrozole Resistance Via Transcriptional Activation of IFITM1 Signaling in Breast Cancer Cells.Cancer research and treatment · 2019Article
- Co-expression Network Analysis Elucidated a Core Module in Association With Prognosis of Non-functioning Non-invasive Human Pituitary Adenoma.Frontiers in endocrinology · 2019Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUnderstanding the molecular mechanisms is important in development and therapy of endometrioid endometrial adenocarcinoma.
objectiveTo identify key genes in endometrioid endometrial adenocarcinoma.
methodsThe data of mRNA, miRNA and DNA methylation were downloaded from The Cancer Genome Atlas (TCGA) database and differential analysis was performed. Then, bioinformatic analysis was used to explore the regulatory mechanisms of miRNA and DNA methylation on gene expression. The regulatory network between differentially expressed miRNAs and target genes was established. Finally, the quantitative RT-PCR was applied to validate the bioinformatics results.
resultsWe obtained biological omics data of 381 patients with endometrioid endometrial adenocarcinoma from TCGA data portal. After data processing, up to 2068 DEGs and 69 differentially expressed miRNAs were identified. Prediction and correlation analysis revealed that 175 DEGs that were not only the target genes but also negatively correlated with the screened differentially expressed miRNAs. After the integrated analysis of differentially methylated CpG islands and DEGs, 16 related genes were obtained. The quantitative RT-PCR results were roughly consistent with the bioinformatics analysis.
conclusionsThe altered DEGs (ZEB1, ZEB2, TIMP2, TCF4, CYP1B1, PITX1, PITX2, ZNF154 and TSPYL5) may be involved in tumor differentiation of endometrioid endometrial adenocarcinoma and could be used as potential therapeutic targets for the disease.
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