Construction and validation of a regulatory T cells-based classification of renal cell carcinoma: an integrated bioinformatic analysis and clinical cohort study.

IF 6.6 2区医学 Q1 Medicine

Cellular Oncology Pub Date : 2024-12-23 DOI:10.1007/s13402-024-01030-9

Yuntao Yao, Yifan Liu, Bingnan Lu, Guo Ji, Lei Wang, Keqin Dong, Zihui Zhao, Donghao Lyu, Maodong Wei, Siqi Tu, Xukun Lyu, Yuanan Li, Runzhi Huang, Wang Zhou, Guofeng Xu, Xiuwu Pan, Xingang Cui

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引用次数: 0

Abstract

Purpose: Renal cell carcinoma (RCC), exhibiting remarkable heterogeneity, can be highly infiltrated by regulatory T cells (Tregs). However, the relationship between Treg and the heterogeneity of RCC remains to be explored.

Methods: We acquired single-cell RNA-seq profiles and 537 bulk RNA-seq profiles of TCGA-KIRC cohort. Through clustering, monocle2 pseudotime and prognostic analyses, we identified Treg states-related prognostic genes (TSRPGs), then constructing the RCC Treg states-related prognostic classification (RCC-TSC). We also explored its prognostic significance and multi-omics landmarks. Additionally, we utilized correlation analysis to establish regulatory networks, and predicted candidate inhibitors. More importantly, in Xinhua cohort of 370 patients with kidney neoplasm, we used immunohistochemical (IHC) staining for classification, then employing statistical analyses including Chi-square tests and multivariate Cox proportional hazards regression analysis to explore its clinical relevance.

Results: We defined 44 TSRPGs in four different monocle states, and identified high immune infiltration RCC (HIRC, LAG3+, Mki67+) as the highly exhausted subtype with the worst prognosis in RCC-TSC (p < 0.001). BATF-LAG3-immune cells axis might be its underlying metastasis-related mechanism. Immunotherapy and inhibitors including sunitinib potentially conferred best therapeutic effects for HIRC. Furthermore, we successfully validated HIRC subtype as an independent prognostic factor within the Xinhua cohort (OS, HR = 16.68, 95% CI = 1.88-148.1, p = 0.011; PFS, HR = 4.43, 95% CI = 1.55-12.6, p = 0.005).

Conclusion: Through integrated bioinformatics analysis and a large-sample retrospective clinical study, we successfully established RCC-TSC and a diagnostic kit, which could stratify RCC patients with different prognosis and to guide personalized treatment.

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基于调节性T细胞的肾细胞癌分类的构建和验证：综合生物信息学分析和临床队列研究。

目的：肾细胞癌（RCC）具有显著的异质性，可被调节性T细胞（Tregs）高度浸润。然而，Treg与RCC异质性之间的关系仍有待探讨。方法：获取TCGA-KIRC队列的单细胞RNA-seq图谱和537个群体RNA-seq图谱。通过聚类、monocle2伪时间和预后分析，确定Treg状态相关预后基因（tsrpg），构建RCC Treg状态相关预后分类（RCC- tsc）。我们还探讨了其预后意义和多组学里程碑。此外，我们利用相关分析建立调控网络，并预测候选抑制剂。更重要的是，在新华队列的370例肾脏肿瘤患者中，我们采用免疫组化（IHC）染色进行分类，然后采用卡方检验和多变量Cox比例风险回归分析等统计分析来探讨其临床相关性。结果：我们定义了4种不同单片状态下的44种tsrpg，并确定了高免疫浸润RCC （HIRC, LAG3+, Mki67+）是RCC- tsc中高度耗尽的亚型，预后最差（p < 0.001）。batf - lag3免疫细胞轴可能是其潜在的转移相关机制。包括舒尼替尼在内的免疫疗法和抑制剂可能为HIRC提供最佳治疗效果。此外，我们成功地在新华队列中验证了HIRC亚型是一个独立的预后因素(OS, HR = 16.68, 95% CI = 1.88-148.1, p = 0.011；PFS, HR = 4.43, 95% CI = 1.55 ~ 12.6, p = 0.005)。结论：通过综合生物信息学分析和大样本回顾性临床研究，成功建立了RCC- tsc及诊断试剂盒，可对不同预后的RCC患者进行分层，指导个性化治疗。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cellular Oncology Biochemistry, Genetics and Molecular Biology-Cancer Research

CiteScore

10.40

自引率

1.50%

发文量

审稿时长

16 weeks

期刊介绍： The Official Journal of the International Society for Cellular Oncology Focuses on translational research Addresses the conversion of cell biology to clinical applications Cellular Oncology publishes scientific contributions from various biomedical and clinical disciplines involved in basic and translational cancer research on the cell and tissue level, technical and bioinformatics developments in this area, and clinical applications. This includes a variety of fields like genome technology, micro-arrays and other high-throughput techniques, genomic instability, SNP, DNA methylation, signaling pathways, DNA organization, (sub)microscopic imaging, proteomics, bioinformatics, functional effects of genomics, drug design and development, molecular diagnostics and targeted cancer therapies, genotype-phenotype interactions. A major goal is to translate the latest developments in these fields from the research laboratory into routine patient management. To this end Cellular Oncology forms a platform of scientific information exchange between molecular biologists and geneticists, technical developers, pathologists, (medical) oncologists and other clinicians involved in the management of cancer patients. In vitro studies are preferentially supported by validations in tumor tissue with clinicopathological associations.