ArticleJournal of ovarian research2022
A bioinformatics analysis: ZFHX4 is associated with metastasis and poor survival in ovarian cancer.
Article in Journal of ovarian research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 46 citations in OpenAlex.
- Colitis-Associated Colorectal Cancer-STAT3 Inhibition as a Preventive Strategy.International journal of molecular sciences · 2026Article
- Exploring Molecular Signature and Prognostic Biomarkers in Ovarian Cancer: Insights From Late-Stage, Recurrent, and Metastatic Tumors.Biotechnology and applied biochemistry · 2026Article
- ZFHX4 is necessary for dopaminergic neuron differentiation and controls cell cycle by regulating LIN28A.Stem cell reports · 2026Article
- Mapping of the hSOX10 Proximal Protein Interactome in Human Melanoma.Journal of proteome research · 2026Article
- A machine learning-based basement membrane gene signature model for predicting ovarian cancer survival.Translational cancer research · 2026Article
- Integrated Molecular and Functional Characterization of Cervical Small-Cell Neuroendocrine Carcinoma Using a 3D Organoid Model.International journal of molecular sciences · 2026Article
- Genomic and Demographic Characteristics of Angiosarcoma as Described in the AACR Project GENIE Registry.Cancers · 2025Article
- Mapping of the hSOX10 protein interactome in human melanoma.bioRxiv : the preprint server for biology · 2025Article
- Loss of function of the zinc finger homeobox 4 gene, ZFHX4, underlies a neurodevelopmental disorder.American journal of human genetics · 2025Article
- Lactylation-related risk model for prognostication and therapeutic responsiveness in uterine corpus endometrial carcinoma.Discover oncology · 2025Article
- Molecular subtyping of endometrial cancer via a simplified one-step NGS classifier, ARID1A and ZFHX4 mutations help further subclassify CNL/MSI-H patients.Diagnostic pathology · 2025Article
- Identification of RTP4 facilitating ovarian cancer by bioinformatics analysis and experimental validation.Naunyn-Schmiedeberg's archives of pharmacology · 2025Article
- Predictive value of ZFHX4 mutation for the efficacy of immune checkpoint inhibitors in non-small cell lung cancer and melanoma.Investigational new drugs · 2024Article
- Loss-of-function of the Zinc Finger Homeobox 4 (medRxiv : the preprint server for health sciences · 2024Article
- DNA-methylome-derived epigenetic fingerprint as an immunophenotype indicator of durable clinical immunotherapeutic benefits in head and neck squamous cell carcinoma.Cellular oncology (Dordrecht, Netherlands) · 2024Article
- SMARCB1-Retained and SMARCB1-Deficient SNUC are Genetically Distinct: A Pilot Study Using RNA Sequencing.Journal of neurological surgery. Part B, Skull base · 2024Article
- Article
- A hypoxia-glycolysis-lactate-related gene signature for prognosis prediction in hepatocellular carcinoma.BMC medical genomics · 2024Article
- Novel prognostic marker TGFBI affects the migration and invasion function of ovarian cancer cells and activates the integrin αvβ3-PI3K-Akt signaling pathway.Journal of ovarian research · 2024Article
- Analysis of the Mutational Landscape of Osteosarcomas Identifies Genes Related to Metastasis and Prognosis and Disrupted Biological Pathways of Immune Response and Bone Development.International journal of molecular sciences · 2023Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundMetastasis was the major cause of the high mortality in ovarian cancer. Although some mechanisms of metastasis in ovarian cancer were proposed, few have been targeted in the clinical practice. In the study, we aimed to identify novel genes contributing to metastasis and poor clinical outcome in ovarian cancer from bioinformatics databases.
methodsStudies collecting matched primary tumors and metastases from ovarian cancer patients were searched in the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened by software R language. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis for the DEGs were implemented by Metascape. Venn diagram was plotted to present overlapping DEGs. The associations between the overlapping DEGs and prognosis were tested by Cox proportional hazard regression model using a cohort of ovarian cancer patients from the TCGA database. Genes affecting patients' outcomes significantly were served as hub genes. The mechanisms of the hub genes in promoting ovarian cancer metastasis were then predicted by R software.
resultsTwo gene expression profiles (GSE30587 and GSE73168) met the inclusion criteria and were finally analyzed. A total of 259 genes were significantly differentially expressed in GSE30587, whereas 712 genes were in GSE73168. In GSE30587, DEGs were mainly involved in extracellular matrix (ECM) organization; For GSE73168, most of DEGs showed ion trans-membrane transport activity. There were 9 overlapping genes between the two datasets (RUNX2, FABP4, CLDN20, SVEP1, FAM169A, PGM5, ZFHX4, DCN and TAS2R50). ZFHX4 was proved to be an independent adverse prognostic factor for ovarian cancer patients (HR = 1.44, 95%CI: 1.13-1.83, p = 0.003). Mechanistically, ZFHX4 was positively significantly correlated with epithelial-mesenchymal transition (EMT) markers (r = 0.54, p = 2.59 × 10
conclusionsZFHX4 might promote metastasis in ovarian cancer by regulating EMT and reprogramming ECM. For clinical applications, ZFHX4 was expected to be a prognostic biomarker for ovarian cancer metastasis.
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