ArticleCancers2021
A Novel Four-Gene Prognostic Signature for Prediction of Survival in Patients with Soft Tissue Sarcoma.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- P53 Inhibition Diminishes IGSF9 Gene Activity to Promote DNA Repair and Exacerbate the Progression of Colon Cancer.Journal of biochemical and molecular toxicology · 2026Article
- Advancing Prognostics in Oncology: Developing a Machine Learning Model for Predicting 2-Year and 5-Year Survival Rates in Patients with Undifferentiated Pleomorphic Sarcoma.Annals of surgical oncology · 2025Article
- Comprehensive analysis of co-expressed genes with TDP-43: prognostic and therapeutic potential in lung adenocarcinoma.Journal of cancer research and clinical oncology · 2024Article
- Exploring the relationship between metabolism and immune microenvironment in osteosarcoma based on metabolic pathways.Journal of biomedical science · 2024Article
- Pancreatic Juice-Derived microRNA-4516 and microRNA-4674 as Novel Biomarkers for Pancreatic Ductal Adenocarcinoma.Gastro hep advances · 2024Article
- High Expression of POGK Predicts Poor Prognosis in Patients with Hepatocellular Carcinoma.Current oncology (Toronto, Ont.) · 2022Article
- Procollagen-Lysine, 2-Oxoglutarate 5-Dioxygenase Family: Novel Prognostic Biomarkers and Tumor Microenvironment Regulators for Lower-Grade Glioma.Frontiers in cellular neuroscience · 2022Article
- Construction of a prognostic model related to copper dependence in breast cancer by single-cell sequencing analysis.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Soft tissue sarcomas (STS), a group of rare malignant tumours with high tissue heterogeneity, still lack effective clinical stratification and prognostic models. Therefore, we conducted this study to establish a reliable prognostic gene signature. Using 189 STS patients' data from The Cancer Genome Atlas database, a four-gene signature including DHRS3, JRK, TARDBP and TTC3 was established. A risk score based on this gene signature was able to divide STS patients into a low-risk and a high-risk group. The latter had significantly worse overall survival (OS) and relapse free survival (RFS), and Cox regression analyses showed that the risk score is an independent prognostic factor. Nomograms containing the four-gene signature have also been established and have been verified through calibration curves. In addition, the predictive ability of this four-gene signature for STS metastasis free survival was verified in an independent cohort (309 STS patients from the Gene Expression Omnibus database). Finally, Gene Set Enrichment Analysis indicated that the four-gene signature may be related to some pathways associated with tumorigenesis, growth, and metastasis. In conclusion, our study establishes a novel four-gene signature and clinically feasible nomograms to predict the OS and RFS. This can help personalized treatment decisions, long-term patient management, and possible future development of targeted therapy.
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