研究动态
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利用单细胞RNA转录组解析骨肉瘤调节性T细胞的异质性和免疫抑制功能。

Deciphering the heterogeneity and immunosuppressive function of regulatory T cells in osteosarcoma using single-cell RNA transcriptome.

发表日期:2023 Sep 01
作者: Debin Cheng, Zhao Zhang, Zhenzhou Mi, Weidong Tao, Dong Liu, Jun Fu, Hongbin Fan
来源: COMPUTERS IN BIOLOGY AND MEDICINE

摘要:

成骨肉瘤(OS)是一种高度侵袭性且预后不良的恶性肿瘤。肿瘤微环境(TME)在OS的发生和发展中起着重要作用。调节性T细胞(Tregs)已知可促进免疫抑制、肿瘤进展、侵袭和转移。然而,Tregs在OS的TME中的作用尚不清楚。本研究利用单细胞RNA测序(scRNA-seq)数据鉴定了OS TME中的Tregs和其他各类细胞群集。采用基因集变异分析(GSVA)来研究OS和相邻组织中Tregs的信号通路。使用CellChat和iTalk软件包来分析细胞间通讯。此外,我们基于TARGET数据库的批量RNA-seq建立了一个基于Tregs特异基因的预后模型,并使用Gene Expression Omnibus数据集进行验证。利用pRRophetic软件包预测药物敏感性。免疫组化用于验证OS中候选基因的表达。基于以上方法,我们发现OS样本有较高的Tregs浸润。GSVA揭示了与OS中Tregs相关的氧化磷酸化、血管生成和哺乳动物雷帕霉素复合物1(mTORC1)通路显著活化。通过细胞间通讯分析,我们发现Tregs通过C-X-C模体化学因子配体(CXCL)信号与成骨细胞、内皮细胞和髓样细胞相互作用;尤其是,它们通过CXCL12/转化生长因子β1(TGFB1)强烈影响C-X-C模体化学因子受体4(CXCR4)的表达,并通过CXCL12/TGFB1与其他细胞群集相互作用,从而共同促进肿瘤生长和进展。随后,通过单变量、最小绝对收缩和选择算子回归(LASSO)和多变量分析筛选出两个Tregs特异基因(CD320和MAF),构建了一个预后模型,该模型在两个独立队列中显示出良好的预后准确性。此外,药物敏感性分析表明,高Tregs风险的OS患者对舒尼替尼、索拉非尼和阿昔替尼敏感。我们还通过免疫组化验证了CD320和MAF在OS组织中与相邻组织相比显著上调。总的来说,本研究揭示了OS TME中Tregs的异质性,为该癌症的侵袭和治疗提供了新的见解。Copyright © 2023 The Authors. Published by Elsevier Ltd. All rights reserved.
Osteosarcoma (OS) is a highly invasive malignant neoplasm with poor prognosis. The tumor microenvironment (TME) plays an essential role in the occurrence and development of OS. Regulatory T cells (Tregs) are known to facilitate immunosuppression, tumor progression, invasion, and metastasis. However, the effect of Tregs in the TME of OS remains unclear. In this study, single-cell RNA sequencing (scRNA-seq) data was used to identify Tregs and various other cell clusters in the TME of OS. Gene set variation analysis (GSVA) was used to investigate the signaling pathways in Tregs from OS and adjacent tissues. The CellChat and iTALK packages were used to analyze cellular communication. In addition, a prognostic model was established based on the Tregs-specific genes using bulk RNA-seq from the TARGET database, and it was verified using a Gene Expression Omnibus dataset. The pRRophetic package was used to predict drug sensitivity. Immunohistochemistry was used to verify the expression of candidate genes in OS. Based on the above methods, we showed that the OS samples were highly infiltrated with Tregs. GSVA revealed that oxidative phosphorylation, angiogenesis and mammalian target of rapamycin complex 1 (mTORC1) were highly activated in Tregs from OS compared with those from adjacent tissues. Using cellular communication analysis, we found that Tregs interacted with osteoblastic, endothelial, and myeloid cells via C-X-C motif chemokine ligand (CXCL) signaling; particularly, they strongly affected the expression of C-X-C motif chemokine receptor 4 (CXCR4) and interacted with other cell clusters through CXCL12/transforming growth factor β1 (TGFB1) to collectively enable tumor growth and progression. Subsequently, two Tregs-specific genes-CD320 and MAF-were screened through univariate, least absolute shrinkage and selection operator regression (LASSO) and multivariate analysis to construct a prognostic model, which showed excellent prognostic accuracy in two independent cohorts. In addition, drug sensitivity analysis demonstrated that OS patients at high Tregs risk were sensitive to sunitinib, sorafenib, and axitinib. We also used immunohistochemistry to validate that CD320 and MAF were significantly upregulated in OS tissues compared with adjacent tissues. Overall, this study reveals the heterogeneity of Tregs in the OS TME, providing new insights into the invasion and treatment of this cancer.Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.