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透明细胞肾细胞癌中分子和免疫格局的分层及预后重要性。

The stratification and prognostic importance of molecular and immune landscapes in clear cell renal cell carcinoma.

作者信息

Zhai Xinyu, Chen Xinglin, Gu Jianyi, Guo Dongdong, Zhan Xiangyang, Tan Mingyue, Xu Dongliang

机构信息

Urology Centre, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.

出版信息

Front Oncol. 2023 Oct 2;13:1256720. doi: 10.3389/fonc.2023.1256720. eCollection 2023.

Abstract

The aim of our research is to explore the various characteristics and genetic profiles of clear cell renal cell carcinoma (ccRCC) in order to discover possible predictors of prognosis and targets for treatment. By utilizing ssGSEA scores, we categorized patients with ccRCC into groups based on their phenotype, distinguishing between low and high. This categorization revealed significant variations in the expression of crucial immune checkpoint genes and Human Leukocyte Antigen (HLA) genes, suggesting the presence of a potential immune evasion tactic in different subtypes of ccRCC. A predictive model was built using genes that are expressed differently and linked to cell death, showing strong effectiveness in categorizing patient risk. Furthermore, we discovered a noteworthy correlation among risk scores, infiltration of immune cells, the expression of genes related to immune checkpoint inhibitors, and diverse clinical features. This indicates that our scoring system for risk could function as a comprehensive gauge of the severity of the disease. The examination of the mutational terrain further highlighted the predominance of particular genetic changes, including VHL and PBRM1 missense mutations. Finally, we have discovered the function of DKK1 in facilitating cell death in ccRCC, presenting an additional possibility for therapeutic intervention. The results of our study suggest the possibility of incorporating molecular information into clinical prediction, which could lead to personalized treatment approaches in ccRCC.

摘要

我们研究的目的是探索透明细胞肾细胞癌(ccRCC)的各种特征和基因图谱,以便发现可能的预后预测指标和治疗靶点。通过利用单样本基因集富集分析(ssGSEA)分数,我们根据ccRCC患者的表型将其分为低、高两组。这种分类揭示了关键免疫检查点基因和人类白细胞抗原(HLA)基因表达的显著差异,表明在ccRCC的不同亚型中存在潜在的免疫逃逸策略。利用表达不同且与细胞死亡相关的基因建立了一个预测模型,该模型在对患者风险进行分类方面显示出强大的有效性。此外,我们发现风险评分、免疫细胞浸润、与免疫检查点抑制剂相关基因的表达以及各种临床特征之间存在显著相关性。这表明我们的风险评分系统可以作为疾病严重程度的综合指标。对突变图谱的研究进一步突出了特定基因变化的优势,包括VHL和PBRM1错义突变。最后,我们发现了DKK1在促进ccRCC细胞死亡中的作用,为治疗干预提供了另一种可能性。我们的研究结果表明将分子信息纳入临床预测的可能性,这可能会导致ccRCC的个性化治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7a9/10577421/025d52c6db6e/fonc-13-1256720-g001.jpg

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