A novel molecular signature for predicting prognosis and immunotherapy response in osteosarcoma based on tumor-infiltrating cell marker genes

被引:7
作者
Tang, Haijun [1 ]
Liu, Shangyu [1 ]
Luo, Xiaoting [2 ]
Sun, Yu [1 ]
Li, Xiangde [3 ]
Luo, Kai [1 ]
Liao, Shijie [4 ]
Li, Feicui [1 ]
Liang, Jiming [1 ]
Zhan, Xinli [1 ]
Wei, Qingjun [4 ]
Liu, Yun [1 ]
He, Maolin [1 ]
机构
[1] Guangxi Med Univ, Dept Spine & Osteopath Surg, Affiliated Hosp 1, Nanning, Guangxi, Peoples R China
[2] Guangxi Med Univ, Dept Pharm, Affiliated Hosp 1, Nanning, Guangxi, Peoples R China
[3] Guangxi Med Univ, Dept Radiotherapy, Affiliated Hosp 2, Nanning, Guangxi, Peoples R China
[4] Guangxi Med Univ, Dept Orthoped, Affiliated Hosp 1, Nanning, Guangxi, Peoples R China
来源
FRONTIERS IN IMMUNOLOGY | 2023年 / 14卷
基金
中国国家自然科学基金;
关键词
osteosarcoma; tumor infiltrating lymphocytes; single-cell RNA sequencing; risk score; immunology; STEM-CELLS; CANCER; HEAD; LYMPHOCYTES; DIAGNOSIS; SURVIVAL; TILS;
D O I
10.3389/fimmu.2023.1150588
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
BackgroundTumor 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. MethodsScRNA-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. ResultsEleven 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. ConclusionsThis study developed a new molecular signature based on TILs marker genes, which is very effective in predicting OS prognosis and immunotherapy response.
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页数:11
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