A novel immune cell signature for predicting osteosarcoma prognosis and guiding therapy - Pan, Runsang; Pan, Feng; Zeng, Zhirui; Lei, Shan; Yang, Yan; Yang, Yushi; Hu, Chujiao; Chen, Houping; Tian, Xiaobin (Frontiers in Immunology, 2022)
Dysregulation of infiltration of immune cells in tumor microenvironment participated in the progression of osteosarcoma (OS). During the present study, we explored genes related to immune cell infiltration, and constructed a risk model by them for predicting prognosis of OS and guiding therapy strategy. The gene expression profile of OS were obtained from TARGET and Gene Expression Omnibus, and set as discovery and verification cohort. CIBERSORT and Kaplan survival analysis was used to analyze the effects of immune cells on the overall survival of OS in discovery cohort. Differentially expression genes (DEGs) analysis and protein-protein interaction (PPI) network were used to analyze the genes associated with the infiltration of immune cells. Cox regression analysis was used to select key genes to construct a risk model which classifying the OS tissues into high and low risk group. The prognostic value for survival and metastasis of risk model was analyzed by Kaplan survival analysis and receiver operating characteristic curve (ROC), and immunohistochemical experiments. The immunological characteristics and respond effect for immune checkpoint blockade (ICB) therapy of OS tissues were analyzed by ESTIMATE and Tumor Immune Dysfunction and Exclusion algorithm, while the sensibility for targeted drugs and chemotherapy drugs was analyzed by OncoPredict algorithm. It was demonstrated that high infiltration of resting dendritic cells in OS tissues was associated with poor prognosis. Total 225 DEGs were found between high and low infiltration groups of OS tissues, while 94 genes interacted with others. Through COX analysis, among these 94 genes, 4 genes including AOC3, CDK6, COL22A1 and RNASE6 were used to construct a risk model. This risk model showed remarkable prognostic value for survival and metastasis in both discovery and verification cohorts. Even though high score of microsatellite instability was observed in the high risk group, the ICB respond in high risk group was poor. Furthermore, through OncoPredict, we found high risk group OS tissues were resistant for 7 drugs and sensitivity for 25 drugs. Therefore, our study indicated that the resting dendritic cell signature constructed by AOC3, CDK6, COL22A1 and RNASE6 may contribute to predict the prognosis of osteosarcoma and guide the therapy.