Qi Lin, Chen Fangyue, Wang Lu, Yang Zhimin, Zhang Wenchao, Li Zhi-Hong
Department of Orthopedics, The Second Xiangya Hospital, Central South University, Changsha, China.
Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Changsha, China.
Front Pharmacol. 2023 Mar 1;14:1136184. doi: 10.3389/fphar.2023.1136184. eCollection 2023.
Soft-tissue sarcoma (STS) is a massive threat to human health due to its high morbidity and malignancy. STS also represents more than 100 histologic and molecular subtypes, with different prognosis. There is growing evidence that anoikis play a key role in the proliferation and invasion of tumors. However, the effects of anoikis in the immune landscape and the prognosis of STS remain unclear. We analyzed the genomic and transcriptomic profiling of 34 anoikis-related genes (ARGs) in patient cohort of pan-cancer and STS from The Cancer Genome Atlas (TCGA) database. Single-cell transcriptome was used to disclose the expression patterns of ARGs in specific cell types. Gene expression was further validated by real-time PCR and our own sequencing data. We established the Anoikis cluster and Anoikis subtypes by using unsupervised consensus clustering analysis. An anoikis scoring system was further built based on the differentially expressed genes (DEGs) between Anoikis clusters. The clinical and biological characteristics of different groups were evaluated. The expressions of most ARGs were significantly different between STS and normal tissues. We found some common ARGs profiles across the pan-cancers. Network of 34 ARGs demonstrated the regulatory pattern and the association with immune cell infiltration. Patients from different Anoikis clusters or Anoikis subtypes displayed distinct clinical and biological characteristics. The scoring system was efficient in prediction of prognosis and immune cell infiltration. In addition, the scoring system could be used to predict immunotherapy response. Overall, our study thoroughly depicted the anoikis-related molecular and biological profiling and interactions of ARGs in STS. The Anoikis score model could guide the individualized management.
软组织肉瘤（STS）因其高发病率和恶性程度对人类健康构成巨大威胁。STS还代表了100多种组织学和分子亚型，预后各不相同。越来越多的证据表明，失巢凋亡在肿瘤的增殖和侵袭中起关键作用。然而，失巢凋亡在免疫格局和STS预后中的作用仍不清楚。我们分析了来自癌症基因组图谱（TCGA）数据库的泛癌和STS患者队列中34个失巢凋亡相关基因（ARG）的基因组和转录组谱。单细胞转录组用于揭示ARG在特定细胞类型中的表达模式。基因表达通过实时PCR和我们自己的测序数据进一步验证。我们使用无监督一致性聚类分析建立了失巢凋亡簇和失巢凋亡亚型。基于失巢凋亡簇之间的差异表达基因（DEG）进一步构建了失巢凋亡评分系统。评估了不同组的临床和生物学特征。大多数ARG在STS和正常组织之间的表达有显著差异。我们在泛癌中发现了一些常见的ARG谱。34个ARG的网络展示了调控模式以及与免疫细胞浸润的关联。来自不同失巢凋亡簇或失巢凋亡亚型的患者表现出不同的临床和生物学特征。该评分系统在预测预后和免疫细胞浸润方面是有效的。此外，该评分系统可用于预测免疫治疗反应。总体而言，我们的研究全面描绘了STS中失巢凋亡相关的分子和生物学谱以及ARG的相互作用。失巢凋亡评分模型可以指导个体化管理。
