Prognostic related signature predicts the benefits of immunotherapy for kidney renal clear cell carcinoma

Clear cell renal cell carcinoma (ccRCC) stands as the pivotal pathological subtype of renal cell carcinoma. However, there exists a dearth of pertinent biological targets crucial for advancing the clinical application of ccRCC. In our investigation, we employed the weighted gene co-expression network analysis (WGCNA) to discern 13 distinct gene co-expression modules, with the yellow module exhibiting a pronounced association with tumorigenesis. Concurrently, we scrutinized 6147 differentially expressed genes through rigorous differential expression analysis. Through an intersecting approach with the genes within the yellow module, we pinpointed 265 cancer-related genes displaying notable differential expression. Subsequent Cox-regression analysis unveiled that among the 265 genes, four were notably linked to ccRCC prognosis. Furthermore, we executed single-sample gene set enrichment analysis (ssGSEA) on the signature comprising these four genes, subsequently deriving normalized enrichment scores (NESs). This investigation substantiated that the said signature bears significant implications for prognosis, holding the potential to forecast the efficacy of immunotherapy.

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Publication Details

Journal
Discover Oncology
Published
2025-06-19
DOI
https://doi.org/10.1007/s12672-025-02991-5
Citations
1
Primary Topic
Renal cell carcinoma treatment
Type
article
Field-Weighted Citation Impact
1.52
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article

Prognostic related signature predicts the benefits of immunotherapy for kidney renal clear cell carcinoma

Haoxun Zhang, Boju Tao, Guoling Zhang, Chunyang Wang et al.
1 citations
Discover Oncology
Renal cell carcinoma treatment
1.52
article

Prognostic related signature predicts the benefits of immunotherapy for kidney renal clear cell carcinoma

Haoxun Zhang, Boju Tao, Guoling Zhang, Chunyang Wang, Yiwen Liu, Bowen Wang, Feng Xiong
article en
1 citations

Abstract

Clear cell renal cell carcinoma (ccRCC) stands as the pivotal pathological subtype of renal cell carcinoma. However, there exists a dearth of pertinent biological targets crucial for advancing the clinical application of ccRCC. In our investigation, we employed the weighted gene co-expression network analysis (WGCNA) to discern 13 distinct gene co-expression modules, with the yellow module exhibiting a pronounced association with tumorigenesis. Concurrently, we scrutinized 6147 differentially expressed genes through rigorous differential expression analysis. Through an intersecting approach with the genes within the yellow module, we pinpointed 265 cancer-related genes displaying notable differential expression. Subsequent Cox-regression analysis unveiled that among the 265 genes, four were notably linked to ccRCC prognosis. Furthermore, we executed single-sample gene set enrichment analysis (ssGSEA) on the signature comprising these four genes, subsequently deriving normalized enrichment scores (NESs). This investigation substantiated that the said signature bears significant implications for prognosis, holding the potential to forecast the efficacy of immunotherapy.

Discover OncologyVol. 16(1)
Harbin Medical University (CN), First Affiliated Hospital of Harbin Medical University (CN)
Good health and well-being
Openalex Percentile: Top 17%
Renal cell carcinoma treatment
1.52
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Prognostic related signature predicts the benefits of immunotherapy for kidney renal clear cell carcinoma — Haoxun Zhang, Boju Tao, et al. · Discover Oncology (2025) | TGRS Research Map | TGRS