ArticleBMC cancer2020
Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer.
Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 36 citations in OpenAlex.
- Binary pyroptosis-amplified self-assembling prodrug nanomedicine enhances immunogenicity and inhibits abdominal metastasis in ovarian cancer.Acta pharmaceutica Sinica. B · 2026Article
- HGF knockdown suppresses ovarian cancer malignancy: insights from a transient receptor potential-related gene model.European journal of medical research · 2025Article
- Review
- Article
- Development and verification of a 7-lncRNA prognostic model based on tumor immunity for patients with ovarian cancer.Journal of ovarian research · 2023Article
- PTTG1IP (PBF) is a prognostic marker and correlates with immune infiltrate in ovarian cancer.American journal of translational research · 2023Article
- A 9‑gene expression signature to predict stage development in resectable stomach adenocarcinoma.BMC gastroenterology · 2022Article
- A novel immune-related gene signature predicting survival in sarcoma patients.Molecular therapy oncolytics · 2022Article
- Review
- Identification of key genes associated with polycystic ovary syndrome (PCOS) and ovarian cancer using an integrated bioinformatics analysis.Journal of ovarian research · 2022Article
- Clinical significance of metabolism-related genes and FAK activity in ovarian high-grade serous carcinoma.BMC cancer · 2022Article
- Applications of machine learning in tumor-associated macrophages.Frontiers in immunology · 2022Review
- Identification and Validation of the Diagnostic Characteristic Genes of Ovarian Cancer by Bioinformatics and Machine Learning.Frontiers in genetics · 2022Article
- Considering Computational Mathematics IGHG3 as Malignant Melanoma Is Associated with Immune Infiltration of Malignant Melanoma.BioMed research international · 2022Article
- Identification of a glycolysis-related gene signature for survival prediction of ovarian cancer patients.Cancer medicine · 2021Article
- Article
- Correction to: Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer.BMC cancer · 2021Article
- Angiogenesis-Related Immune Signatures Correlate With Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity in Hepatocellular Carcinoma.Frontiers in molecular biosciences · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundOvarian cancer (OV) is one of the most common malignant tumors of gynecology oncology. The lack of effective early diagnosis methods and treatment strategies result in a low five-year survival rate. Also, immunotherapy plays an important auxiliary role in the treatment of advanced OV patient, so it is of great significance to find out effective immune-related tumor markers for the diagnosis and treatment of OV.
methodsBased on the consensus clustering analysis of single-sample gene set enrichment analysis (ssGSEA) score transformed via The Cancer Genome Atlas (TCGA) mRNA profile, we obtained two groups with high and low levels of immune infiltration. Multiple machine learning methods were conducted to explore prognostic genes associated with immune infiltration. Simultaneously, the correlation between the expression of mark genes and immune cells components was explored.
resultsA prognostic classifier including 5 genes (CXCL11, S1PR4, TNFRSF17, FPR1 and DHRS95) was established and its robust efficacy for predicting overall survival was validated via 1129 OV samples. Some significant variations of copy number on gene loci were found between two risk groups and it showed that patients with fine chemosensitivity has lower risk score than patient with poor chemosensitivity (P = 0.013). The high and low-risk groups showed significantly different distribution (P < 0.001) of five immune cells (Monocytes, Macrophages M1, Macrophages M2, T cells CD4 menory and T cells CD8).
conclusionThe present study identified five prognostic genes associated with immune infiltration of OV, which may provide some potential clinical implications for OV treatment.
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