ArticleComputational and mathematical methods in medicine2021
Comprehensive Analysis of the Control of Cancer Stem Cell Characteristics in Endometrial Cancer by Network Analysis.
Article in Computational and mathematical methods in medicine, 2021. 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, 11 citations in OpenAlex.
- Heterogeneity characterization and therapeutic marker discovery of endometrial carcinoma using GeoMXT™ digital spatial profiling.Journal of translational medicine · 2026Article
- KIF15 (Kinesin-12): molecular biology, physiological functions, and roles in disease.Journal of cancer research and clinical oncology · 2026Review
- KIF4A in disease pathogenesis and therapeutics: from molecular mechanisms to clinical translation.Biology direct · 2025Review
- ORC6 acts as an effective prognostic predictor for non‑small cell lung cancer and is closely associated with tumor progression.Oncology letters · 2024Article
- Tumor polo-like kinase 4 protein expression reflects lymphovascular invasion, higher Federation of Gynecology and Obstetrics stage, and shortened survival in endometrial cancer patients who undergo surgical resection.BMC women's health · 2024Article
- Integrative Pan-Cancer Analysis of KIF15 Reveals Its Diagnosis and Prognosis Value in Nasopharyngeal Carcinoma.Frontiers in oncology · 2022Article
- In silico Approach for Validating and Unveiling New Applications for Prognostic Biomarkers of Endometrial Cancer.Cancers · 2021Article
- Article
- Expression and Clinical Significance of Origin Recognition Complex Subunit 6 in Breast Cancer - A Comprehensive Bioinformatics Analysis.International journal of general medicine · 2021Article
- Ferroptosis-Related Genes in Lung Adenocarcinoma: Prognostic Signature and Immune, Drug Resistance, Mutation Analysis.Frontiers in genetics · 2021Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCancer stem cells play an important role in endometrial cancer (EC). It is closely related to self-renewal and therapeutic resistance of EC.
methodsIn this study, WGCNA (weighted gene coexpression network analysis) was used to analyze the relationship between genes and clinical features. We also performed immune cell infiltration analysis of a key module by using ImmuCellAI (Immune Cell Abundance Identifier). Then, key genes were verified in the GEO database. Finally, causal relationship analysis and protein-protein interaction analysis were performed in DisNor tool and STRING.
resultThe mRNA expression-based stemness index (mRNAsi) is significantly lower in normal tissues and is significantly higher in individuals with stage IV or high-grade cancer and those who are obese or postmenopausal. Nineteen key genes (ORC6, C1orf112, RAD54L, SGO2, BUB1, PLK4, KIF18B, BUB1B, TTK, NCAPG, XRCC2, CENPF, KIF15, RACGAP1, ARHGAP11A, TPX2, KIF14, KIF4A, and NCAPH) that were enriched mainly in terms related to the cell cycle and DNA replication were selected by weighted gene coexpression network analysis (WGCNA). Based on the key modules, the numbers of NKT cells, NK cells, and neutrophils in the normal group were significantly higher than those in the cancer group. PLK1, CDK1, and MAD2L1, which were correlated with upstream genes, may be an regulated upstream of key genes.
conclusionPLK1, CDK1, and MAD2L1 which were strongly correlated with upstream genes may be a regulated upstream of key genes.
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