Classification of renal cell carcinoma based on immunogenomic profiling

Renal cell carcinoma (RCC) is the most common type of kidney cancer. Several studies have identified RCC subtypes based on genomic profiling. However, few studies have explored the stratification of RCC based on immune-associated gene sets, which may contribute to the optimal classification of patie...

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Main Authors: Yanfei Chen, Sian Chen, Jun Zou, Jiehui Zhong, Xuejin Zhu, Qingbiao Chen, Bin Wang, Weide Zhong
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:All Life
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Online Access:http://dx.doi.org/10.1080/26895293.2025.2467662
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author Yanfei Chen
Sian Chen
Jun Zou
Jiehui Zhong
Xuejin Zhu
Qingbiao Chen
Bin Wang
Weide Zhong
author_facet Yanfei Chen
Sian Chen
Jun Zou
Jiehui Zhong
Xuejin Zhu
Qingbiao Chen
Bin Wang
Weide Zhong
author_sort Yanfei Chen
collection DOAJ
description Renal cell carcinoma (RCC) is the most common type of kidney cancer. Several studies have identified RCC subtypes based on genomic profiling. However, few studies have explored the stratification of RCC based on immune-associated gene sets, which may contribute to the optimal classification of patients with RCC who respond to immunotherapy. By analyzing the molecular and clinical data of RCC obtained from The Cancer Genome Atlas database, we classified RCC hierarchically based on the scores of 29 immune-associated gene sets, which were generated by single-sample gene-set enrichment analysis. The three RCC subtypes were Cluster1 (C1), Cluster2 (C2) and Cluster3 (C3), and they had distinct prognoses. The C1 subtype was associated with worse survival than the others, but the prognoses of the C2 and C3 subtypes were not significantly different. The three RCC subtypes also had distinct DNA damage markers, key immune characteristics, proportions of tumor-infiltrating immune cells, and gene expressions of immunomodulators. In addition to the immune-related pathways, some cancer-associated pathways were also overactivated for the C1 subtype, these included apoptosis and the PI3K-Akt signaling pathway. Finally, this study showed that immune signature-based classification has potential clinical implications for RCC treatment.
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spelling doaj-art-abd32f1fdf6740e09e8e96632dca0bb52025-08-20T02:45:42ZengTaylor & Francis GroupAll Life2689-53072025-12-0118110.1080/26895293.2025.24676622467662Classification of renal cell carcinoma based on immunogenomic profilingYanfei Chen0Sian Chen1Jun Zou2Jiehui Zhong3Xuejin Zhu4Qingbiao Chen5Bin Wang6Weide Zhong7Jinan UniversityGuangzhou Medical UniversityThe Third Affiliated Hospital of Guangzhou Medical UniversityThe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou Medical UniversitySouthern Medical UniversityGuangzhou Medical UniversityJinan UniversityRenal cell carcinoma (RCC) is the most common type of kidney cancer. Several studies have identified RCC subtypes based on genomic profiling. However, few studies have explored the stratification of RCC based on immune-associated gene sets, which may contribute to the optimal classification of patients with RCC who respond to immunotherapy. By analyzing the molecular and clinical data of RCC obtained from The Cancer Genome Atlas database, we classified RCC hierarchically based on the scores of 29 immune-associated gene sets, which were generated by single-sample gene-set enrichment analysis. The three RCC subtypes were Cluster1 (C1), Cluster2 (C2) and Cluster3 (C3), and they had distinct prognoses. The C1 subtype was associated with worse survival than the others, but the prognoses of the C2 and C3 subtypes were not significantly different. The three RCC subtypes also had distinct DNA damage markers, key immune characteristics, proportions of tumor-infiltrating immune cells, and gene expressions of immunomodulators. In addition to the immune-related pathways, some cancer-associated pathways were also overactivated for the C1 subtype, these included apoptosis and the PI3K-Akt signaling pathway. Finally, this study showed that immune signature-based classification has potential clinical implications for RCC treatment.http://dx.doi.org/10.1080/26895293.2025.2467662renal cell carcinomagenomic profilingimmune signature
spellingShingle Yanfei Chen
Sian Chen
Jun Zou
Jiehui Zhong
Xuejin Zhu
Qingbiao Chen
Bin Wang
Weide Zhong
Classification of renal cell carcinoma based on immunogenomic profiling
All Life
renal cell carcinoma
genomic profiling
immune signature
title Classification of renal cell carcinoma based on immunogenomic profiling
title_full Classification of renal cell carcinoma based on immunogenomic profiling
title_fullStr Classification of renal cell carcinoma based on immunogenomic profiling
title_full_unstemmed Classification of renal cell carcinoma based on immunogenomic profiling
title_short Classification of renal cell carcinoma based on immunogenomic profiling
title_sort classification of renal cell carcinoma based on immunogenomic profiling
topic renal cell carcinoma
genomic profiling
immune signature
url http://dx.doi.org/10.1080/26895293.2025.2467662
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AT jiehuizhong classificationofrenalcellcarcinomabasedonimmunogenomicprofiling
AT xuejinzhu classificationofrenalcellcarcinomabasedonimmunogenomicprofiling
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