A novel molecular classification method for osteosarcoma based on tumor cell differentiation trajectories.
A novel molecular classification method for osteosarcoma based on tumor cell differentiation trajectories.
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基于肿瘤细胞分化轨迹的骨肉瘤分子分类新方法
DOI：
10.1038/s41413-022-00233-w
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发表时间：
2023-01-02
期刊：
影响因子：
12.7
通讯作者：
Xiao, Jianru
中科院分区：
文献类型：
--
作者：
Zhang, Hao;Wang, Ting;Gong, Haiyi;Jiang, Runyi;Zhou, Wang;Sun, Haitao;Huang, Runzhi;Wang, Yao;Wu, Zhipeng;Xu, Wei;Li, Zhenxi;Huang, Quan;Cai, Xiaopan;Lin, Zaijun;Hu, Jinbo;Jia, Qi;Ye, Chen;Wei, Haifeng;Xiao, Jianru
根据分子特征对肿瘤进行细分，可以方便治疗选择，提高癌症患者的应答率。然而，骨肉瘤(OS)涉及的高度复杂的细胞来源限制了传统的批量RNA测序在OS亚型中的应用。单细胞RNA测序(scRNA-seq)在识别细胞异质性方面具有很大的前景。然而，这项技术很少被用于肿瘤亚型的研究。通过分析6个常规OS和9个松质骨(CB)样本的scRNA-seq数据，我们在OS和CB样本中鉴定了29个簇，并从肿瘤干细胞(CSC)样亚群中发现了3个分化轨迹，这使得我们将OS样本分为三组。使用目标数据集进一步检查分类模型。OS各亚组的预后和可能的药物敏感性不同，OS三个分化分支中的OS细胞与OS微环境中的其他簇显示出明显的相互作用。此外，我们还通过对138例OS标本的IHC染色验证了分类模型，显示B组患者的预后较差。此外，我们描述了CSCs的新的转录程序，并强调了EZH2在OS的CSCs中的激活。这些发现提供了一种基于scRNA-seq的新的细分方法，为揭示OS中CSCs的分子特征提供了新的线索，为OS的精确治疗和治疗开发提供了有价值的参考。
Subclassification of tumors based on molecular features may facilitate therapeutic choice and increase the response rate of cancer patients. However, the highly complex cell origin involved in osteosarcoma (OS) limits the utility of traditional bulk RNA sequencing for OS subclassification. Single-cell RNA sequencing (scRNA-seq) holds great promise for identifying cell heterogeneity. However, this technique has rarely been used in the study of tumor subclassification. By analyzing scRNA-seq data for six conventional OS and nine cancellous bone (CB) samples, we identified 29 clusters in OS and CB samples and discovered three differentiation trajectories from the cancer stem cell (CSC)-like subset, which allowed us to classify OS samples into three groups. The classification model was further examined using the TARGET dataset. Each subgroup of OS had different prognoses and possible drug sensitivities, and OS cells in the three differentiation branches showed distinct interactions with other clusters in the OS microenvironment. In addition, we verified the classification model through IHC staining in 138 OS samples, revealing a worse prognosis for Group B patients. Furthermore, we describe the novel transcriptional program of CSCs and highlight the activation of EZH2 in CSCs of OS. These findings provide a novel subclassification method based on scRNA-seq and shed new light on the molecular features of CSCs in OS and may serve as valuable references for precision treatment for and therapeutic development in OS.
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