Single-cell transcriptome analysis revealing the intratumoral heterogeneity of ccRCC and validation of MT2A in pathogenesis

IF 3.9 4区 生物学 Q1 GENETICS & HEREDITY
Jie Wang, Zili Zuo, Zongze Yu, Zhigui Chen, Xiangdi Meng, Zhaosen Ma, Jiqiang Niu, Rui Guo, Lisa Jia Tran, Jing Zhang, Tianxiao Jiang, Fangdie Ye, Baoluo Ma, Zhou Sun
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引用次数: 3

Abstract

Clear-cell renal cell carcinoma (ccRCC) appears as the most common type of kidney cancer, the carcinogenesis of which has not been fully elucidated. Tumor heterogeneity plays a crucial role in cancer progression, which could be largely deciphered by the implement of scRNA-seq. The bulk and single-cell RNA expression profile is obtained from TCGA and study conducted by Young et al. We utilized UMAP, TSNE, and clustering algorithm Louvain for dimensionality reduction and FindAllMarkers function for determining the DEGs. Monocle2 was utilized to perform pseudo-time series analysis. SCENIC was implemented for transcription factor analysis of each cell subgroup. A series of WB, CFA, CCK-8, and EDU analysis was utilized for the validation of the role of MT2A in ccRCC carcinogenesis. We observed higher infiltration of T/NK and B cells in tumorous tissues, indicating the role of immune cells in ccRCC carcinogenesis. Transcription factor analysis revealed the activation of EOMES and ETS1 in CD8 + T cells, while CAFs were divided into myo-CAFs and i-CAFs, with i-CAFs showing distinct enrichment of ATF3, JUND, JUNB, EGR1, and XBP1. Through cell trajectory analysis, we discerned three distinct stages of cellular evolution, where State2 symbolizes normal renal tubular cells that underwent transitions into State1 and State3 as the CNV score ascended. Functional enrichment examination revealed an amplification of interferon gamma and inflammatory response pathways within tumor cells. The consensus clustering algorithm yielded two molecular subtypes, with cluster 2 being associated with advanced tumor stages and an abundance of infiltrated immune cells. We identified 17 prognostic genes through Cox and LASSO regression models and used them to construct a prognostic model, the efficacy of which was verified in multiple cohorts. Furthermore, we investigated the role of MT2A, one of our hub genes, in ccRCC carcinogenesis, and found it to regulate proliferation and migration of malignant cells. We depicted a detailed single-cell landscape of ccRCC, with special focus on CAFs, endothelial cells, and renal tubular cells. A prognostic model of high stability and accuracy was constructed based on the DEGs. MT2A was found to be actively implicated in ccRCC carcinogenesis, regulating proliferation and migration of the malignant cells.

Abstract Image

单细胞转录组分析揭示了ccRCC的肿瘤内异质性和MT2A在发病机制中的验证
透明细胞肾细胞癌(ccRCC)是最常见的肾癌类型,其癌变机制尚未完全阐明。肿瘤异质性在癌症进展中起着至关重要的作用,这在很大程度上可以通过实施scRNA-seq来破译。大体积和单细胞RNA表达谱来自TCGA,由Young等人进行研究。我们使用UMAP、TSNE和Louvain聚类算法进行降维,使用FindAllMarkers函数确定deg。利用Monocle2进行伪时间序列分析。采用SCENIC对各细胞亚组进行转录因子分析。我们利用WB、CFA、CCK-8和EDU等一系列分析来验证MT2A在ccRCC癌变中的作用。我们观察到肿瘤组织中T/NK和B细胞的浸润增加,表明免疫细胞在ccRCC癌变中的作用。转录因子分析显示,CD8 + T细胞中EOMES和ETS1被激活,而CAFs分为myo-CAFs和i-CAFs,其中i-CAFs富集ATF3、JUND、JUNB、EGR1和XBP1。通过细胞轨迹分析,我们发现了三个不同的细胞进化阶段,其中State2代表正常肾小管细胞,随着CNV评分的上升,这些细胞转变为State1和State3。功能富集检查显示肿瘤细胞内干扰素γ和炎症反应途径的扩增。共识聚类算法产生了两种分子亚型,其中聚类2与肿瘤晚期和浸润免疫细胞的丰度有关。我们通过Cox和LASSO回归模型鉴定出17个预后基因,并利用它们构建预后模型,在多个队列中验证其有效性。此外,我们还研究了我们的枢纽基因之一MT2A在ccRCC癌变中的作用,发现它可以调节恶性细胞的增殖和迁移。我们描绘了ccRCC的详细单细胞景观,特别关注CAFs,内皮细胞和肾小管细胞。在此基础上建立了一个稳定、准确的预测模型。MT2A被发现积极参与ccRCC的癌变,调节恶性细胞的增殖和迁移。
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来源期刊
CiteScore
3.50
自引率
3.40%
发文量
92
审稿时长
2 months
期刊介绍: Functional & Integrative Genomics is devoted to large-scale studies of genomes and their functions, including systems analyses of biological processes. The journal will provide the research community an integrated platform where researchers can share, review and discuss their findings on important biological questions that will ultimately enable us to answer the fundamental question: How do genomes work?
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