中国透明细胞肾细胞癌独特的基因组图谱和预后突变特征

Wenhao Xu , Aihetaimujiang Anwaier , Wangrui Liu , Xi Tian , Jiaqi Su , Guohai Shi , Yuanyuan Qu , Hailiang Zhang , Dingwei Ye
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引用次数: 7

摘要

基因组背景影响癌症的发生和转移,包括透明细胞肾细胞癌(ccRCC)。然而,关注中国ccRCC预后突变特征的报道缺乏。方法共对929例患者进行ccRCC基因组图谱分析,其中包括中国患者(n = 201)、高加索患者(n = 274)和验证队列(n = 454)。然后,使用机器学习算法识别和评估ccRCC中的基因组突变特征(GMS)。分析预后、免疫微环境、与独立临床病理特征的关联以及免疫检查点疗法(ict)的预测反应。结果929例ccRCC患者的DNA变异数据显示,中国人与高加索人在VHL、PBRM1、BAP1、SETD2和KDM5C等最常见基因的基因组突变频率上存在显著差异。PBRM1与VHL和SETD2有显著的共现性。然后,我们成功地鉴定了一个包括FBN1、SHPRH、CELSR1、COL6A6、DST、ABCA13和BAP1突变的7基因突变标记(GMSMut)。gmsmt显著预测进展性进展(P <0.0001, HR = 2.81)和预后不良(P <0.0001, HR = 3.89)。此外,接受GMSMut治疗的ccRCC患者在检测队列中生存率较低(P = 0.020),而在验证队列中接受ict治疗的患者预后较差(P = 0.036)。有趣的是,在GMSMut集群中观察到对ict的良好临床反应,免疫检查点表达升高,肿瘤浸润淋巴细胞丰度增加,特别是CD8+ T细胞,Tregs和巨噬细胞。结论本研究描述了促肿瘤的GMSMut聚类,提高了中国ccRCC患者的预后准确性。我们发现的新的独立预后特征强调了肿瘤表型和ccRCC基因组突变特征之间的关系。
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The unique genomic landscape and prognostic mutational signature of Chinese clear cell renal cell carcinoma

Background

The genomic background affects the occurrence and metastasis of cancers, including clear cell renal cell carcinoma (ccRCC). However, reports focusing on the prognostic mutational signature of Chinese ccRCC are lacking.

Methods

Overall, 929 patients, including a training cohort with Chinese patients (n = 201), a testing cohort with Caucasian patients (n = 274), and a validation cohort (n = 454) were analyzed for the genomic landscape of ccRCC. Then, machine-learning algorithms were used to identify and evaluate the genomic mutational signature (GMS) in ccRCC. Analyses for prognosis, immune microenvironment, association with independent clinicopathological features, and predictive responses for immune checkpoint therapies (ICTs) were performed.

Results

The DNA variation data of 929 patients with ccRCC suggested markedly differential genomic mutational frequency of the most frequent genes, such as VHL, PBRM1, BAP1, SETD2, and KDM5C between the Chinese and Caucasian populations. PBRM1 showed significant co-occurrence with VHL and SETD2. We then successfully identified a seven-gene mutational signature (GMSMut) that included mutations in FBN1, SHPRH, CELSR1, COL6A6, DST, ABCA13, and BAP1. The GMSMut significantly predicted progressive progression (P < 0.0001, HR = 2.81) and poor prognosis (P < 0.0001, HR = 3.89) in the Chinese training cohort. Moreover, ccRCC patients with the GMSMut had poor survival rates in the testing cohort (P = 0.020) and poor outcomes were predicted for those treated with ICTs in the validation cohort (P = 0.036). Interestingly, a favorable clinical response to ICTs, elevated expression of immune checkpoints, and increased abundance of tumor-infiltrated lymphocytes, specifically CD8+ T cells, Tregs, and macrophages, were observed in the GMSMut cluster.

Conclusions

This study described the pro-tumorigenic GMSMut cluster that improved the prognostic accuracy in Chinese patients with ccRCC. Our discovery of the novel independent prognostic signature highlights the relationship between tumor phenotype and genomic mutational characteristics of ccRCC.

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