Abstract 5459: Inflammatory gene-based subtyping of osteosarcoma patients reveals the association of inflammation in tumor microenvironment with better survival
Authors: Liu Yang, Yalan Sheng, Shuangying Qiao, Desheng Hu, Debajyoti Chowdhury, Hiu Fung Yip, Zheng Chen, Yun He, Aiping Lu, Fangfei Li
Journal: Cancer Research (2024)

Abstract Introduction:Inflammation has a significant impact on the tumor microenvironment (TME) of osteosarcoma (OS). Nevertheless, due to the high heterogenecity and variable inflammatory characteristics among OS patients, it is still unclear which inflammatory factors or immune/stroma cell types are crucially associated with OS prognosis. Therefore, it is essential to explore the immune infiltration pattern and the related core inflammatory genes in OS. Method:We combined bulk RNA-seq data of 88 osteosarcoma (OS) patients from the TARGET database and single cell RNA-seq data in GSE152048 from the NCBI Gene Expression Omnibus. Firstly, we calculated the inflammatory gene expression matrix of bulk RNA-seq data by combining 80 inflammatory gene sets (3427 genes in total) from the MSigDB using the gene set variation analysis (GSVA). Secondly, consensus clustering was executed to evaluate the stability of clustering for the above matrix. Furthermore, the overall survival and differential expression analyses were used to screen for core inflammatory genes. Immune infiltration patterns among groups were profiled with CIBERSORT. Finally, we employed the scRNA-seq series to evaluate cell-level information to identify the survival-associated cell subpopulations using the Seurat package. The t-SNE was used for dimensionality reduction and cluster identification. Results:88 osteosarcoma (OS) patients were clustered into two distinct groups according to the consensus clustering of our formed GSVA inflammatory gene expression matrix. Group 1 (43 patients) exhibited evident inflammation features, while Group 2 (45 patients) displayed limited inflammation features. Patients from Group 1 had significantly better overall survival than those from Group 2. The difference in immune infiltration pattern of two groups were examined using bulk RNA-seq data. Group 1 showed a higher population of macrophages and CD8+ T cells compared to Group 2, implying high inflammatory features might lead to a better immune activation of TME in patients. To explore the factors and cell types that contributes to restricted immune infiltration and activation in OS TME, scRNA-seq data of 11 OS patient tissues were analyzed. Consistently with bulk RNA seq analysis, the 338 up-regulated genes from Group 1 were mainly expressed in immune cells including macrophages and myeloid cells. Interestingly, the 64 up-regulated genes from Group 2 were found nearly uniformly expressed in two type of non-immune cells: myoblasts and chondroblastic cells. Conclusion:Inflammatory gene-based subtyping of osteosarcoma (OS) patients reveals that the inflammation in TME led by myeloid-derived immune cells including macrophage is associated with better prognosis. Furthermore, myoblasts and chondroblastic cells might contribute to the limited inflammation response in OS TME. Citation Format: Liu Yang, Yalan Sheng, Shuangying Qiao, Desheng Hu, Debajyoti Chowdhury, Hiu Fung Yip, Zheng Chen, Yun He, Aiping Lu, Fangfei Li. Inflammatory gene-based subtyping of osteosarcoma patients reveals the association of inflammation in tumor microenvironment with better survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5459.