Author:
Zhang Yiming,He Rong,Lei Xuan,Mao Lianghao,Yin Zhengyu,Zhong Xinyu,Cao Wenbing,Zheng Qiping,Li Dapeng
Abstract
Research on the implications of ferroptosis in tumors has increased rapidly in the last decades. There are evidences that ferroptosis is involved in several aspects of cancer biology, including tumor progression, metastasis, immunomodulation, and therapeutic response. Nonetheless, the interaction between ferroptosis-related lncRNAs (FRLs) and the osteosarcoma immune microenvironment is poorly understood. In this study, a risk model composed of FRLs was developed using univariate and LASSO Cox regression analyses. On the basis of this model, FRL scores were calculated to systematically explore the role of the model in predicting the prognosis and immune characteristics of osteosarcoma patients. Survival analysis showed that osteosarcoma samples with lower FRL-score had better overall survival. After predicting the abundance of immune cells in osteosarcoma microenvironment by single-sample gene-set enrichment analysis (ssGSEA) and ESTIMATE analysis, we found that the FRL-score could distinguish immune function, immune score, stromal score, tumor purity, and tumor infiltration of immune cells in different osteosarcoma patients. In addition, FRL-score was also associated with immune checkpoint gene expression and half-maximal inhibitory concentration of chemotherapeutic agents. Finally, we confirmed that knockdown of RPARP-AS1 suppressed the malignant activity of osteosarcoma cells in vitro experiments. In general, the FRL-based prognostic signature could promote our understanding of the immune microenvironment characteristics of osteosarcoma and guide more effective treatment regimens.
Funder
Natural Science Foundation of Jiangsu Province
Shenzhen Science and Technology Innovation Program
Jiangsu Provincial Key Research and Development Program
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献