ArticleCancer cell international2022
Establishment and validation of a novel invasion-related gene signature for predicting the prognosis of ovarian cancer.
Article in Cancer cell international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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23 citing papers in PubMed, 34 citations in OpenAlex.
- Exploring Molecular Signature and Prognostic Biomarkers in Ovarian Cancer: Insights From Late-Stage, Recurrent, and Metastatic Tumors.Biotechnology and applied biochemistry · 2026Article
- Insights into Ovarian Cancer: Unraveling the Role of DNA Double-strand Break-related Genes in Pathogenesis and Therapeutic Avenues.Reproductive sciences (Thousand Oaks, Calif.) · 2026Review
- Establishment of a Prognostic Necroptosis-Related lncRNA Signature in Ovarian Cancer.Combinatorial chemistry & high throughput screening · 2026Article
- Pan cohort immune biomarker of CD8 lymphocyte activation enabling HGSOC outcome prediction and treatment response.Discover oncology · 2025Article
- Identification of DNA methylation based prognostic subtype and signature in epithelial ovarian cancer.Human genetics · 2025Article
- Kinesin superfamily proteins in ovarian cancer: from molecular mechanisms to clinical applications.Medical oncology (Northwood, London, England) · 2025Review
- The role of collagen type VI alpha 6 chain as a potential tumor suppressor in breast cancer: an immune regulation perspective.BMC cancer · 2025Article
- Identification of a Novel Pyroptosis-Related lncRNAs Prognosis Model and Subtypes in Ovarian Cancer.Phenomics (Cham, Switzerland) · 2025Article
- The role of SPI1/VSIG4/THBS1 on glioblastoma progression through modulation of the PI3K/AKT pathway.Journal of advanced research · 2025Article
- Transcription factor networks and novel immune biomarkers reveal key prognostic and therapeutic insights in ovarian cancer.Discover oncology · 2025Article
- Senescence-Related LncRNAs: Pioneering Indicators for Ovarian Cancer Outcomes.Phenomics (Cham, Switzerland) · 2024Review
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- Analysis of prognostic value of lactate metabolism-related genes in ovarian cancer based on bioinformatics.Journal of ovarian research · 2024Article
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- Identification of glycosyltransferase-related genes signature and integrative analyses in patients with ovarian cancer.American journal of clinical and experimental immunology · 2024Article
- Elucidating the role of tumor-associated ALOX5+ mast cells with transformative function in cervical cancer progression via single-cell RNA sequencing.Frontiers in immunology · 2024Article
- Identification and validation of a prognostic model based on immune-related genes in ovarian carcinoma.PeerJ · 2024Article
- Unveiling the cellular landscape: insights from single-cell RNA sequencing in multiple myeloma.Frontiers in immunology · 2024Article
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9 authors at 1 institution in 2 countries.
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Abstract
backgroundOvarian cancer (OC) is an invasive gynaecologic cancer with a high cancer-related death rate. The purpose of this study was to establish an invasion-related multigene signature to predict the prognostic risk of OC.
methodsWe extracted 97 invasion-related genes from The Cancer Genome Atlas (TCGA) database. Then, the ConsensusClusterPlus and limma packages were used to calculate differentially expressed genes (DEGs). To calculate the immune scores of the molecular subtypes, we used ESTIMATE to evaluate the stromal score, immune score and ESTIMATE score. MCP-counter and the GSVA package ssgsea were used to evaluate the types of infiltrating immune cells. Survival and nomogram analyses were performed to explore the prognostic value of the signature. Finally, qPCR, immunohistochemistry staining and functional assays were used to evaluate the expression and biological abilities of the signature genes in OC.
resultsBased on the consistent clustering of invasion-related genes, cases in the OC datasets were divided into two subtypes. A significant difference was observed in prognosis between the two subtypes. Most genes were highly expressed in the C1 group. Based on the C1 group genes, we constructed an invasion-related 6-gene prognostic risk model. Furthermore, to verify the signature, we used the TCGA-test and GSE32062 and GSE17260 chip datasets for testing and finally obtained a good risk prediction effect in those datasets. Moreover, the results of the qPCR and immunohistochemistry staining assays revealed that KIF26B, VSIG4 and COL6A6 were upregulated and that FOXJ1, MXRA5 and CXCL9 were downregulated in OC tissues. The functional study showed that the expression of KIF26B, VSIG4, COL6A6, FOXJ1, MXRA5 and CXCL9 can regulate the migration and invasion abilities of OC cells.
conclusionWe developed a 6-gene prognostic stratification system (FOXJ1, MXRA5, KIF26B, VSIG4, CXCL9 and COL6A6) that is independent of clinical features. These results suggest that the signature could potentially be used to evaluate the prognostic risk of OC patients.
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