ArticleBioscience reports2020
Identification of metastasis and prognosis-associated genes for serous ovarian cancer.
Article in Bioscience reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 20 citations in OpenAlex.
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- Implication of CDKN2A in cuproptosis through defining cuproptosis-related gene signature in ovarian cancer.Journal of Cancer · 2025Article
- DCAF13 promotes ovarian cancer progression by activating FRAS1-mediated FAK signaling pathway.Cellular and molecular life sciences : CMLS · 2024Article
- Identification of necroptosis-related gene signatures for predicting the prognosis of ovarian cancer.Scientific reports · 2024Article
- Identification and validation of IRF6 related to ovarian cancer and biological function and prognostic value.Journal of ovarian research · 2024Article
- Metastasis-Related Signature for Clinically Predicting Prognosis and Tumor Immune Microenvironment of Osteosarcoma Patients.Molecular biotechnology · 2023Article
- Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients.Molecular biotechnology · 2023Article
- Chromosome instability region analysis and identification of the driver genes of the epithelial ovarian cancer cell lines A2780 and SKOV3.Journal of cellular and molecular medicine · 2023Article
- Analysis of risk factors for negative emotions in perioperative period of ovarian cancer patients and their impact on prognosis.Gland surgery · 2023Article
- Correlation of systemic immune-inflammatory response index with clinical data in patients with malignant ovarian tumor.American journal of translational research · 2023Article
- CpG-binding protein CFP1 promotes ovarian cancer cell proliferation by regulating BST2 transcription.Cancer gene therapy · 2022Article
- Single-cell landscape analysis reveals distinct regression trajectories and novel prognostic biomarkers in primary neuroblastoma.Genes & diseases · 2022Article
- Identification of Potential Biomarkers for Progression and Prognosis of Bladder Cancer by Comprehensive Bioinformatics Analysis.Journal of oncology · 2022Article
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- Network-based approach to identify prognosis-related genes in tamoxifen-treated patients with estrogen receptor-positive breast cancer.Bioscience reports · 2021Article
- A Comprehensive Analysis of the Downregulation ofFrontiers in molecular biosciences · 2021Article
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
Serous ovarian cancer is one of the most fatal gynecological tumors with an extremely low 5-year survival rate. Most patients are diagnosed at an advanced stage with wide metastasis. The dysregulation of genes serves an important role in the metastasis progression of ovarian cancer. Differentially expressed genes (DEGs) between primary tumors and metastases of serous ovarian cancer were screened out in the gene expression profile of GSE73168 from Gene Expression Omnibus (GEO). Cytoscape plugin cytoHubba and weighted gene co-expression network analysis (WGCNA) were utilized to select hub genes. Univariate and multivariate Cox regression analyses were used to screen out prognosis-associated genes. Furthermore, the Oncomine validation, prognostic analysis, methylation mechanism, gene set enrichment analysis (GSEA), TIMER database analysis and administration of candidate molecular drugs were conducted for hub genes. Nine hundred and fifty-seven DEGs were identified in the gene expression profile of GSE73168. After using Cytoscape plugin cytoHubba, 83 genes were verified. In co-expression network, the blue module was most closely related to tumor metastasis. Furthermore, the genes in Cytoscape were analyzed, showing that the blue module and screened 17 genes were closely associated with tumor metastasis. Univariate and multivariate Cox regression revealed that the age, stage and STMN2 were independent prognostic factors. The Cancer Genome Atlas (TCGA) suggested that the up-regulated expression of STMN2 was related to poor prognosis of ovarian cancer. Thus, STMN2 was considered as a new key gene after expression validation, survival analysis and TIMER database validation. GSEA confirmed that STMN2 was probably involved in ECM receptor interaction, focal adhesion, TGF beta signaling pathway and MAPK signaling pathway. Furthermore, three candidate small molecule drugs for tumor metastasis (diprophylline, valinomycin and anisomycin) were screened out. The quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and western blot showed that STMN2 was highly expressed in ovarian cancer tissue and ovarian cancer cell lines. Further studies are needed to investigate these prognosis-associated genes for new therapy target.
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