Cell Differentiation Trajectory-Associated Molecular Classification of Osteosarcoma.
Cell Differentiation Trajectory-Associated Molecular Classification of Osteosarcoma.
复制标题
骨肉瘤的细胞分化轨迹相关分子分类
DOI：
10.3390/genes12111685
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发表时间：
2021-10-23
期刊：
影响因子：
3.5
通讯作者：
Tao H
中科院分区：
文献类型：
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作者：
Xu A;Qian C;Lin J;Yu W;Jin J;Liu B;Tao H
本研究旨在研究骨肉瘤细胞的分化轨迹，构建具有各自特征的分子亚型，并生成用于预测预后的多基因特征。使用来自骨肉瘤样品的集成单细胞 RNA 测序 (scRNA-seq) 数据、批量 RNA-seq 数据和微阵列数据进行分析。通过 scRNA-seq 数据，时间相关以及分化相关基因被识别为骨肉瘤肿瘤干细胞相关基因（OSCG）。在基因表达综合（GEO）队列中，根据预后 OSCG 将骨肉瘤患者分为两个亚型，发现分子分型成功预测了总体生存率、肿瘤微环境和免疫浸润状态。此外，还揭示了通过预后 OSCG 影响骨肉瘤的可用药物。生成基于 3-OSCG 的预后风险评分特征，并通过结合其他临床病理独立预后因素、诊断分期，建立列线图来预测个体生存概率。在外部独立的 TARGET 队列中，对分子类型、3 基因特征以及列线图进行了验证。总之，骨肉瘤细胞分化在肿瘤预后和微环境等许多方面占据着至关重要的地位，为该疾病提供了有前景的治疗靶点。
This study aims to investigate the differentiation trajectory of osteosarcoma cells and to construct molecular subtypes with their respective characteristics and generate a multi-gene signature for predicting prognosis. Integrated single-cell RNA-sequencing (scRNA-seq) data, bulk RNA-seq data and microarray data from osteosarcoma samples were used for analysis. Via scRNA-seq data, time-related as well as differentiation-related genes were recognized as osteosarcoma tumor stem cell-related genes (OSCGs). In Gene Expression Omnibus (GEO) cohort, osteosarcoma patients were classified into two subtypes based on prognostic OSCGs and it was found that molecular typing successfully predicted overall survival, tumor microenvironment and immune infiltration status. Further, available drugs for influencing osteosarcoma via prognostic OSCGs were revealed. A 3-OSCG-based prognostic risk score signature was generated and by combining other clinic-pathological independent prognostic factor, stage at diagnosis, a nomogram was established to predict individual survival probability. In external independent TARGET cohort, the molecular types, the 3-gene signature as well as nomogram were validated. In conclusion, osteosarcoma cell differentiation occupies a crucial position in many facets, such as tumor prognosis and microenvironment, suggesting promising therapeutic targets for this disease.
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影响因子：
64.5
作者：
Lee DF;Su J;Kim HS;Chang B;Papatsenko D;Zhao R;Yuan Y;Gingold J;Xia W;Darr H;Mirzayans R;Hung MC;Schaniel C;Lemischka IR
通讯作者：
Lemischka IR
DOI：
10.1073/pnas.0906549106
发表时间：
2009-08-18
影响因子：
11.1
作者：
Chan, Keith Syson;Espinosa, Inigo;Weissman, Irving L.
通讯作者：
Weissman, Irving L.
影响因子：
7.3
作者：
Mohseny, Alexander B.;Szuhai, Karoly;Hogendoorn, Pancras C. W.
通讯作者：
Hogendoorn, Pancras C. W.
影响因子：
3.9
作者：
Duerinck, J.;Du Four, S.;Neyns, B.
通讯作者：
Neyns, B.
影响因子：
5.7
作者：
通讯作者：
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