Department of Spine Surgery, Zhongshan Hospital Xiamen University, Xiamen University, 201-209 Hubin South Road, Xiamen, Fujian, 361004, People's Republic of China.
Shanghai Synyi Medical Technology Co., Ltd, Shanghai, 201203, People's Republic of China.
Biochem Genet. 2023 Dec;61(6):2363-2381. doi: 10.1007/s10528-023-10374-0. Epub 2023 Apr 11.
Little progress has been made in the treatment and prognosis of osteosarcoma in the past 40 years. Tumor microenvironment (TME) plays a critical role in the progression of osteosarcoma. This study aims to determine immune-associated prognostic biomarkers for osteosarcoma patients. With the help of analytical tools including ESTIMATE, differential gene expression, LASSO, and univariate cox and multivariate cox regression analysis, osteosarcoma gene expression data from Gene Expression Omnibus (GEO) databases were investigated. Following the establishment of a prognostic risk score model, internal and external validations using the GEO and TARGET databases were carried out. A total of 44 and 55 samples respectively in the GSE21257 and the TARGET databases were included. Our analysis found 93 differentially expressed genes (DEGs) between the high and low-ImmuneScore groups. Through univariate cox and LASSO analysis, ALOX5AP was identified as an indicator of TME in osteosarcomas. ALOX5AP was then used to construct a prognostic risk model. Internal and external verification revealed that higher expression of ALOX5AP was correlated with lower risk. Through the CIBERSORT algorithm, the level of CD8 T cells was found to negatively correlate with the risk score. This study revealed that ALOX5AP is an indicator for predicting high CD8 lymphocyte infiltration and "hot" tumor microenvironment in osteosarcomas. Thus, ALOX5AP has the potential to act as a biomarker for effective immunotherapies in osteosarcoma patients.
在过去的 40 年中，骨肉瘤的治疗和预后方面几乎没有取得进展。肿瘤微环境（TME）在骨肉瘤的进展中起着关键作用。本研究旨在确定骨肉瘤患者的免疫相关预后生物标志物。本研究借助 ESTIMATE、差异基因表达、LASSO、单因素 COX 和多因素 COX 回归分析等分析工具，对 GEO 数据库中的骨肉瘤基因表达数据进行了研究。在建立预后风险评分模型后，利用 GEO 和 TARGET 数据库进行了内部和外部验证。GSE21257 数据库和 TARGET 数据库中分别包含了 44 个和 55 个样本。我们的分析发现，高免疫评分组和低免疫评分组之间有 93 个差异表达基因（DEGs）。通过单因素 COX 和 LASSO 分析，发现 ALOX5AP 是骨肉瘤中 TME 的标志物。然后，ALOX5AP 被用来构建预后风险模型。内部和外部验证表明，ALOX5AP 表达水平越高，风险越低。通过 CIBERSORT 算法，发现 CD8 T 细胞的水平与风险评分呈负相关。本研究表明，ALOX5AP 是预测骨肉瘤中 CD8 淋巴细胞浸润和“热”肿瘤微环境的标志物。因此，ALOX5AP 有可能成为骨肉瘤患者有效免疫治疗的生物标志物。
