Liu Xu, Li Xiaoyang, Yu Shengji
Department of Orthopedics, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, P.R. China.
Oncol Lett. 2024 Feb 14;27(4):151. doi: 10.3892/ol.2024.14284. eCollection 2024 Apr.
Anoikis is highly associated with tumor cell apoptosis and tumor prognosis; however, the specific role of anoikis-related genes (ARGs) in soft tissue sarcoma (STS) remains to be fully elucidated. The present study aimed to use a variety of bioinformatics methods to determine differentially expressed anoikis-related genes in STS and healthy tissues. Subsequently, three machine learning algorithms, Least Absolute Shrinkage and Selection Operator, Support Vector Machine and Random Forest, were used to screen genes with the highest importance score. The results of the bioinformatics analyses demonstrated that CASP8 and FADD-like apoptosis regulator (CFLAR) exhibited the highest importance score. Subsequently, the diagnostic and prognostic value of CFLAR in STS development was determined using multiple public and in-house cohorts. The results of the present study demonstrated that CFLAR may be considered a diagnostic and prognostic marker of STS, which acts as an independent prognostic factor of STS development. The present study also aimed to explore the potential role of CFLAR in the STS tumor microenvironment, and the results demonstrated that CFLAR significantly enhanced the immune response of STS, and exerted a positive effect on the infiltration of CD8 T cells and M1 macrophages in the STS immune microenvironment. Notably, the aforementioned results were verified using multiplex immunofluorescence analysis. Collectively, the results of the present study demonstrated that CFLAR may act as a novel diagnostic and prognostic marker for STS, and may positively regulate the immune response of STS. Thus, the present study provided a novel theoretical basis for the use of CFLAR in STS diagnosis, in predicting clinical outcomes and in tailoring individualized treatment options.
失巢凋亡与肿瘤细胞凋亡及肿瘤预后高度相关；然而，失巢凋亡相关基因（ARGs）在软组织肉瘤（STS）中的具体作用仍有待充分阐明。本研究旨在运用多种生物信息学方法，确定STS组织和健康组织中差异表达的失巢凋亡相关基因。随后，使用三种机器学习算法，即最小绝对收缩和选择算子、支持向量机和随机森林，筛选出重要性得分最高的基因。生物信息学分析结果表明，含半胱氨酸的天冬氨酸蛋白水解酶8和FADD样凋亡调节因子（CFLAR）的重要性得分最高。随后，利用多个公共数据集和内部队列确定CFLAR在STS发生发展中的诊断和预后价值。本研究结果表明，CFLAR可被视为STS的诊断和预后标志物，它是STS发生发展的独立预后因素。本研究还旨在探讨CFLAR在STS肿瘤微环境中的潜在作用，结果表明CFLAR显著增强了STS的免疫反应，并对STS免疫微环境中CD8 T细胞和M1巨噬细胞的浸润发挥了积极作用。值得注意的是，上述结果通过多重免疫荧光分析得到了验证。总体而言，本研究结果表明，CFLAR可能作为STS的一种新型诊断和预后标志物，并可能对STS的免疫反应起到正向调节作用。因此，本研究为CFLAR在STS诊断、预测临床结果及制定个体化治疗方案中的应用提供了新的理论依据。
