A novel molecular signature for predicting prognosis and immunotherapy response in osteosarcoma based on tumor-infiltrating cell marker genes
Haijun Tang, Shangyu Liu, Xiaoting Luo, Yu Sun, Xiangde Li, Kai Luo, Shijie Liao, Feicui Li, Jiming Liang, Xinli Zhan, Qingjun Wei, Yun Liu, Maolin He
Abstract
Background Tumor infiltrating lymphocytes (TILs), the main component in the tumor microenvironment, play a critical role in the antitumor immune response. Few studies have developed a prognostic model based on TILs in osteosarcoma. Methods ScRNA-seq data was obtained from our previous research and bulk RNA transcriptome data was from TARGET database. WGCNA was used to obtain the immune-related gene modules. Subsequently, we applied LASSO regression analysis and SVM algorithm to construct a prognostic model based on TILs marker genes. What’s more, the prognostic model was verified by external datasets and experiment in vitro . Results Eleven cell clusters and 2044 TILs marker genes were identified. WGCNA results showed that 545 TILs marker genes were the most strongly related with immune. Subsequently, a risk model including 5 genes was developed. We found that the survival rate was higher in the low-risk group and the risk model could be used as an independent prognostic factor. Meanwhile, high-risk patients had a lower abundance of immune cell infiltration and many immune checkpoint genes were highly expressed in the low-risk group. The prognostic model was also demonstrated to be a good predictive capacity in external datasets. The result of RT-qPCR indicated that these 5 genes have differential expression which accorded with the predicting outcomes. Conclusions This study developed a new molecular signature based on TILs marker genes, which is very effective in predicting OS prognosis and immunotherapy response.