ArticleFrontiers in genetics2020
A Novel Six-Gene Signature for Prognosis Prediction in Ovarian Cancer.
Article in Frontiers in genetics, 2020. 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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Who cites it
14 citing papers in PubMed.
- Development and validation of gene expression-based signature for high-grade serous ovarian cancer.Journal of ovarian research · 2026Article
- Cracking the code: predicting tumor microenvironment enabled chemoresistance with machine learning in the human tumoroid models.npj biomedical innovations · 2025Article
- A Prognostic Nomogram Based on an Immunogenic Cell Death and Endoplasmic Reticulum Stress-Related Gene Signature for Ovarian Cancer.International journal of women's health · 2025Article
- Comparative Analysis of Gene Expression Analysis Methods for RNA in Situ Hybridization Images.The Journal of molecular diagnostics : JMD · 2024Article
- Identification of key biomarkers and associated pathways of pancreatic cancer using integrated transcriptomic and gene network analysis.Saudi journal of biological sciences · 2023Article
- Integrated analysis of single-cell RNA-seq and bulk RNA-seq unveils heterogeneity and establishes a novel signature for prognosis and tumor immune microenvironment in ovarian cancer.Journal of ovarian research · 2023Article
- A risk model of gene signatures for predicting platinum response and survival in ovarian cancer.Journal of ovarian research · 2022Article
- Article
- Multi-modal Profiling of the Extracellular Matrix of Human Fallopian Tubes and Serous Tubal Intraepithelial Carcinomas.The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society · 2022Article
- Integrating cell cycle score for precise risk stratification in ovarian cancer.Frontiers in genetics · 2022Article
- Integrative Analysis From Multicenter Studies Identifies a WGCNA-Derived Cancer-Associated Fibroblast Signature for Ovarian Cancer.Frontiers in immunology · 2022Article
- Identification of a glycolysis-related gene signature for survival prediction of ovarian cancer patients.Cancer medicine · 2021Article
- Systematic analysis of the relationship between ovarian cancer prognosis and alternative splicing.Journal of ovarian research · 2021Article
- Bioengineering strategies to control epithelial-to-mesenchymal transition for studies of cardiac development and disease.APL bioengineering · 2021Review
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Authors and funding
2 authors.
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Abstract
Ovarian cancer (OC) is the most malignant tumor in the female reproductive tract. Although abundant molecular biomarkers have been identified, a robust and accurate gene expression signature is still essential to assist oncologists in evaluating the prognosis of OC patients. In this study, samples from 367 patients in The Cancer Genome Atlas (TCGA) database were subjected to mRNA expression profiling. Then, we used a gene set enrichment analysis (GSEA) to screen genes correlated with epithelial-mesenchymal transition (EMT) and assess their prognostic power with a Cox proportional regression model. Six genes (TGFBI, SFRP1, COL16A1, THY1, PPIB, BGN) associated with overall survival (OS) were used to construct a risk assessment model, after which the patients were divided into high-risk and low-risk groups. The six-gene signature was an independent prognostic biomarker of OS for OC patients based on the multivariate Cox regression analysis. In addition, the six-gene model was validated with samples from the Gene Expression Omnibus (GEO) database. In summary, we established a six-gene signature relevant to the prognosis of OC, which might become a therapeutic tool with clinical applications in the future.
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