Research Paper Volume 13, Issue 1 pp 619—645

A three-gene signature based on tumour microenvironment predicts overall survival of osteosarcoma in adolescents and young adults

Feature selection of risk score model. (A) Selection of tuning parameters in the Lasso regression analysis based on 1,000 cross-validations. (B) Lasso regression analysis coefficients. (C) The importance of XGBoost machine learning screening the top 30 genes. (D) Multivariate analysis of 3 genes (COCH, MYOM2, PDE1B) and establishment of the regression equation. (E–G) Kaplan-Meier curve analysis of the relationship between the expression levels of COCH, MYOM2 and PDE1B, respectively, and the prognosis of OSs patients.

Figure 4. Feature selection of risk score model. (A) Selection of tuning parameters in the Lasso regression analysis based on 1,000 cross-validations. (B) Lasso regression analysis coefficients. (C) The importance of XGBoost machine learning screening the top 30 genes. (D) Multivariate analysis of 3 genes (COCH, MYOM2, PDE1B) and establishment of the regression equation. (EG) Kaplan-Meier curve analysis of the relationship between the expression levels of COCH, MYOM2 and PDE1B, respectively, and the prognosis of OSs patients.