A novel risk score model based on eight genes and a nomogram for predicting overall survival of patients with osteosarcoma.
BMC Cancer
; 20(1): 456, 2020 May 24.
Article
em En
| MEDLINE
| ID: mdl-32448271
ABSTRACT
BACKGROUND:
This study aims to identify a predictive model to predict survival outcomes of osteosarcoma (OS) patients.METHODS:
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.RESULT:
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.CONCLUSION:
An eight-gene predictive model and nomogram were developed to predict OS prognosis.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias Ósseas
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Biomarcadores Tumorais
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Osteossarcoma
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Nomogramas
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Redes Reguladoras de Genes
Tipo de estudo:
Etiology_studies
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Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Female
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Humans
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Male
/
Middle aged
Idioma:
En
Revista:
BMC Cancer
Assunto da revista:
NEOPLASIAS
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
China