机构：[1]Department of Computer Science and Technology, School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, China.[2]Geneplus-Beijing, Beijing 102206, China.[3]Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.[4]Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China.[5]The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510120 Guangdong, China. 6 The Third Affiliated Hospital of Shenzhen University, Shenzhen 518001 Guangdong, China.广东省中医院深圳市罗湖区人民医院深圳医学信息中心
The genetic landscape of clear cell renal cell carcinoma (ccRCC) had been investigated extensively but its evolution patterns remained unclear. Here we analyze the clonal architectures of 473 patients from three different populations. We find that the mutational signatures vary substantially across different populations and evolution stages. The evolution patterns of ccRCC have great inter-patient heterogeneities, with del(3p) being regarded as the common earliest event followed by three early departure points: VHL and PBRM1 mutations, del(14q) and other somatic copy number alterations (SCNAs) including amp(7), del(1p) and del(6q). We identify three prognostic subtypes of ccRCC with distinct clonal architectures and immune infiltrates: long-lived patients, enriched with VHL but depleted of BAP1 mutations, have high levels of Th17 and CD8(+) T cells while short-lived patients with high burden of SCNAs have high levels of Tregs and Th2 cells, highlighting the importance of evaluating evolution patterns in the clinical management of ccRCC.
基金：
This study was supported by the National Natural Science Foundation of China
(81402336 and 31701150), Shenzhen Municipal Government of China
(JCYJ20160429093033251) and Fundamental Research Funds for the Central Universities
(CXTD2017003). Drs Zhao and Jia were partially supported by National
Institutes of Health grant (R01LM012806).
第一作者机构：[1]Department of Computer Science and Technology, School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, China.[2]Geneplus-Beijing, Beijing 102206, China.
共同第一作者：
通讯作者：
推荐引用方式(GB/T 7714)：
Yi Huang,Jiayin Wang,Peilin Jia,et al.Clonal architectures predict clinical outcome in clear cell renal cell carcinoma[J].NATURE COMMUNICATIONS.2019,10:doi:10.1038/s41467-019-09241-7.
APA：
Yi Huang,Jiayin Wang,Peilin Jia,Xiangchun Li,Guangsheng Pei...&Baifeng Zhang.(2019).Clonal architectures predict clinical outcome in clear cell renal cell carcinoma.NATURE COMMUNICATIONS,10,
MLA：
Yi Huang,et al."Clonal architectures predict clinical outcome in clear cell renal cell carcinoma".NATURE COMMUNICATIONS 10.(2019)
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