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肝细胞癌中的缺氧分子特征鉴定出一种风险特征和两种用于临床管理的列线图。

Hypoxia Molecular Characterization in Hepatocellular Carcinoma Identifies One Risk Signature and Two Nomograms for Clinical Management.

作者信息

Liu Zaoqu, Liu Long, Lu Taoyuan, Wang Libo, Li Zhaonan, Jiao Dechao, Han Xinwei

机构信息

Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.

Interventional Institute of Zhengzhou University, Zhengzhou 450052, China.

出版信息

J Oncol. 2021 Jan 20;2021:6664386. doi: 10.1155/2021/6664386. eCollection 2021.

Abstract

Hypoxia is a universal feature in the tumor microenvironment (TME). Nonetheless, the heterogeneous hypoxia patterns of TME have still not been elucidated in hepatocellular carcinoma (HCC). Using consensus clustering algorithm and public datasets, we identified heterogeneous hypoxia subtypes. We also revealed the specific biological and clinical characteristics via bioinformatic methods. The principal component analysis algorithm was employed to develop a hypoxia-associated risk score (HARS). We identified the two hypoxia subtypes: low hypoxia pattern (C1) and high hypoxia pattern (C2). C1 was less sensitive to immunotherapy compared to C2, consistent with the lack of immune cells and immune checkpoints (ICPs) in C1, whereas C2 was the opposite. C2 displayed worse prognosis and higher sensitivity to obatoclax relative to C1, while C1 was more sensitive to sorafenib. The two subtypes also demonstrated subtype-specific genomic variations including mutation, copy number alteration, and methylation. Moreover, we developed and validated a risk signature: HARS, which had excellent performance for predicting prognosis and immunotherapy. We revealed two hypoxia subtypes with distinct biological and clinical characteristics in HCC, which enhanced the understanding of hypoxia pattern. The risk signature was a promising biomarker for predicting prognosis and immunotherapy.

摘要

缺氧是肿瘤微环境(TME)的一个普遍特征。然而,肝细胞癌(HCC)中TME的异质性缺氧模式仍未阐明。利用共识聚类算法和公共数据集,我们识别出了异质性缺氧亚型。我们还通过生物信息学方法揭示了特定的生物学和临床特征。采用主成分分析算法开发了缺氧相关风险评分(HARS)。我们识别出两种缺氧亚型:低缺氧模式(C1)和高缺氧模式(C2)。与C2相比,C1对免疫治疗的敏感性较低,这与C1中缺乏免疫细胞和免疫检查点(ICP)一致,而C2则相反。相对于C1,C2预后较差,对 obatoclax 的敏感性较高,而C1对索拉非尼更敏感。这两种亚型还表现出亚型特异性的基因组变异,包括突变、拷贝数改变和甲基化。此外,我们开发并验证了一种风险特征:HARS,它在预测预后和免疫治疗方面具有出色的表现。我们揭示了HCC中具有不同生物学和临床特征的两种缺氧亚型,这增强了对缺氧模式的理解。该风险特征是预测预后和免疫治疗的一个有前景的生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bff3/7846409/27064da80602/JO2021-6664386.001.jpg

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