Department of Orthopedics, The First Hospital of China Medical University, Shenyang, Liaoning Province 110001, P.R. China.
Aging (Albany NY). 2023 Jun 2;15(11):4820-4843. doi: 10.18632/aging.204764.
Osteosarcoma is the most common bone malignancy in teenagers, and warrants effective measures for diagnosis and prognosis. Oxidative stress (OS) is the key driver of several cancers and other diseases.
The TARGET-osteosarcoma database was employed as the training cohort and GSE21257 and GSE39055 was applied for external validation. The patients were classified into the high- and low-risk groups based on the median risk score of each sample. ESTIMATE and CIBERSORT were applied for the evaluation of tumor microenvironment immune infiltration. GSE162454 of single-cell sequencing was employed for analyzing OS-related genes.
Based on the gene expression and clinical data of 86 osteosarcoma patients in the TARGET database, we identified eight OS-related genes, including MAP3K5, G6PD, HMOX1, ATF4, ACADVL, MAPK1, MAPK10, and INS. In both the training and validation sets, the overall survival of patients in the high-risk group was significantly worse than that in the low-risk group. The ESTIMATE algorithm revealed that patients in the high-risk group had higher tumor purity but lower immune score and stromal score. In addition, the CIBERSORT algorithm showed that the M0 and M2 macrophages were the predominant infiltrating cells in osteosarcoma. Based on the expression analysis of immune checkpoint, CD274(PDL1), CXCL12, BTN3A1, LAG3, and IL10 were identified as potential immune therapy targets. Analysis of the single cell sequencing data also revealed the expression patterns of OS-related genes in different cell types.
An OS-related prognostic model can accurately provide the prognosis of osteosarcoma patients, and may help identify suitable candidates for immunotherapy.
骨肉瘤是青少年中最常见的骨恶性肿瘤，需要有效的诊断和预后措施。氧化应激（OS）是多种癌症和其他疾病的关键驱动因素。
采用 TARGET-osteosarcoma 数据库作为训练队列，GSE21257 和 GSE39055 进行外部验证。根据每个样本的中位数风险评分，将患者分为高风险组和低风险组。ESTIMATE 和 CIBERSORT 用于评估肿瘤微环境免疫浸润。单细胞测序的 GSE162454 用于分析 OS 相关基因。
基于 TARGET 数据库中 86 例骨肉瘤患者的基因表达和临床数据，我们鉴定出 8 个 OS 相关基因，包括 MAP3K5、G6PD、HMOX1、ATF4、ACADVL、MAPK1、MAPK10 和 INS。在训练集和验证集中，高风险组患者的总生存率明显低于低风险组。ESTIMATE 算法显示，高风险组患者的肿瘤纯度较高，但免疫评分和基质评分较低。此外，CIBERSORT 算法显示 M0 和 M2 巨噬细胞是骨肉瘤中主要浸润细胞。基于免疫检查点表达分析，CD274（PDL1）、CXCL12、BTN3A1、LAG3 和 IL10 被确定为潜在的免疫治疗靶点。单细胞测序数据的分析还揭示了 OS 相关基因在不同细胞类型中的表达模式。
OS 相关预后模型可以准确提供骨肉瘤患者的预后，并可能有助于确定合适的免疫治疗候选者。
