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

{"title":"Construction and validation of a regulatory T cells-based classification of renal cell carcinoma: an integrated bioinformatic analysis and clinical cohort study.","authors":"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","doi":"10.1007/s13402-024-01030-9","DOIUrl":null,"url":null,"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.","PeriodicalId":9690,"journal":{"name":"Cellular Oncology","volume":" ","pages":""},"PeriodicalIF":6.6000,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cellular Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s13402-024-01030-9","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}

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.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

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.