Back to Search
Start Over
A novel risk score model based on eight genes and a nomogram for predicting overall survival of patients with osteosarcoma.
- Source :
-
BMC Cancer . 5/24/2020, Vol. 20 Issue 1, p1-12. 12p. 1 Color Photograph, 2 Diagrams, 4 Charts, 3 Graphs. - Publication Year :
- 2020
-
Abstract
- <bold>Background: </bold>This study aims to identify a predictive model to predict survival outcomes of osteosarcoma (OS) patients.<bold>Methods: </bold>A RNA sequencing dataset (the training set) and a microarray dataset (the validation set) were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, respectively. Differentially expressed genes (DEGs) between metastatic and non-metastatic OS samples were identified in training set. Prognosis-related DEGs were screened and optimized by support vector machine (SVM) recursive feature elimination. A SVM classifier was built to classify metastatic and non-metastatic OS samples. Independent prognosic genes were extracted by multivariate regression analysis to build a risk score model followed by performance evaluation in two datasets by Kaplan-Meier (KM) analysis. Independent clinical prognostic indicators were identified followed by nomogram analysis. Finally, functional analyses of survival-related genes were conducted.<bold>Result: </bold>Totally, 345 DEGs and 45 prognosis-related genes were screened. A SVM classifier could distinguish metastatic and non-metastatic OS samples. An eight-gene signature was an independent prognostic marker and used for constructing a risk score model. The risk score model could separate OS samples into high and low risk groups in two datasets (training set: log-rank p < 0.01, C-index = 0.805; validation set: log-rank p < 0.01, C-index = 0.797). Tumor metastasis and RS model status were independent prognostic factors and nomogram model exhibited accurate survival prediction for OS. Additionally, functional analyses of survival-related genes indicated they were closely associated with immune responses and cytokine-cytokine receptor interaction pathway.<bold>Conclusion: </bold>An eight-gene predictive model and nomogram were developed to predict OS prognosis. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14712407
- Volume :
- 20
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- BMC Cancer
- Publication Type :
- Academic Journal
- Accession number :
- 143395703
- Full Text :
- https://doi.org/10.1186/s12885-020-06741-4