Ann Med. 2025 Dec;57(1):2490830. doi: 10.1080/07853890.2025.2490830. Epub 2025 Apr 18.
ABSTRACT
BACKGROUND: Renal cell carcinoma (RCC) is a heterogeneous malignancy with diverse gene expression patterns, molecular landscapes, and differentiation characteristics of tumor cells. It is imperative to develop molecular RCC classification based on tumor cell differentiation for precise risk stratification and personalized therapy.
METHODS: We obtained scRNA-seq profiles from GSE159115 and bulk RNA-seq profiles from TCGA-KIRC cohort. We then performed scRNA-seq cluster analysis, monocle2 pseudotime analysis, and prognostic analysis to obtain tumor cell differentiation-related prognostic genes (TCDGs). Subsequently, we conducted consensus clustering to construct the RCC tumor cell differentiation-related prognostic classification (RCC-TCDC) and implemented prognostic and multi-omics analyses. Moreover, we utilized Lasso regression to help develop a multivariable prognostic model. In addition, we performed correlation analysis and Cmap algorithm for regulatory network establishment and candidate inhibitor prediction. We eventually included 370 kidney neoplasm patients in Xinhua cohort to undergo immunohistochemical staining and scoring for classification and comprehensive statistical analyses, including Chi-square tests, Kaplan-Meier survival analyses, and multivariable Cox regression analysis .
RESULTS: 32 TCDGs were identifiedand RCC-TCDC was constructed to classify TCGA-KIRC patients into RCC-low differentiation (RCC-LD) (S100A11+ SH3BGRL3+, high risk), RCC-moderate differentiation (TSPAN7+, medium risk), and RCC-high differentiation (RCC-HD) (AQP1+ NPR3+, low risk). Notably, RCC-LD was validated as anindependent risk factor for both OS (p = 0.015, HR = 14.0, 95%CI = 1.67-117.8) and PFS (p = 0.010, HR = 4.0, 95%CI = 1.39-11.7) of RCC patients in Xinhua cohort, taking RCC-HD as reference.
CONCLUSIONS: We constructed and validated a robust molecular classification system, RCC-TCDC, elucidating three distinct RCC subtypes.
PMID:40248945 | DOI:10.1080/07853890.2025.2490830
