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Abstract Background Ewing sarcoma (ES) is the second most common primary malignant bone tumor mainly occurring in children, adolescents and young adults with high metastasis and mortality. Autophagy has been reported to be involved in the survival of ES, but the role remains unclear. Therefore, it’s necessary to investigate the prognostic value of autophagy related genes using bioinformatics methods. Results ATG2B, ATG10 and DAPK1 were final screened genes for a prognostic model. KM and risk score plots showed patients in high score group had better prognoses both in training and validation sets. C-indexes of the model for training and validation sets were 0.68 and 0.71, respectively. Calibration analyses indicated the model had high prediction accuracy in training and validation sets. The AUC values of ROC for 1-, 3-, 5-year prediction were 0.65, 0.73 and 0.84 in training set, 0.88, 0.73 and 0.79 in validation set, which suggested high prediction accuracy of the model. Decision curve analyses showed that patients could benefit much from the model. Differential and functional analyses suggested that autophagy and apoptosis were upregulated in high risk score group. Conclusions ATG2B, ATG10 and DAPK1 were autophagy related genes with potential protective function in ES. The prognostic model established by them exhibited excellent prediction accuracy and discriminatory capacities. They might be used as potential prognostic biomarkers and therapeutic targets in ES.

Background: Ewing sarcoma (ES) is the second most common primary malignant bone tumor mainly occurring in children, adolescents and young adults with high metastasis and mortality. Autophagy has been reported to be involved in the survival of ES, but the role remains unclear. Therefore, it's necessary to investigate the prognostic value of autophagy related genes using bioinformatics methods. Results: ATG2B, ATG10 and DAPK1 were final screened genes for a prognostic model. KM and risk score plots showed patients in high score group had better prognoses both in training and validation sets. C-indexes of the model for training and validation sets were 0.68 and 0.71, respectively. Calibration analyses indicated the model had high prediction accuracy in training and validation sets. The AUC values of ROC for 1-, 3-, 5-year prediction were 0.65, 0.73 and 0.84 in training set, 0.88, 0.73 and 0.79 in validation set, which suggested high prediction accuracy of the model. Decision curve analyses showed that patients could benefit much from the model. Differential and functional analyses suggested that autophagy and apoptosis were upregulated in high risk score group. Conclusions: ATG2B, ATG10 and DAPK1 were autophagy related genes with potential protective function in ES. The prognostic model established by them exhibited excellent prediction accuracy and discriminatory capacities. They might be used as potential prognostic biomarkers and therapeutic targets in ES. [ABSTRACT FROM AUTHOR]