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Combining spatial and single-cell transcriptome data to analyze tertiary lymphoid structures in clear cell renal cell carcinoma reveals prognostic biomarkers
Combining spatial and single-cell transcriptome data to analyze tertiary lymphoid structures in clear cell renal cell carcinoma reveals prognostic biomarkers
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Combining spatial and single-cell transcriptome data to analyze tertiary lymphoid structures in clear cell renal cell carcinoma reveals prognostic biomarkers
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Combining spatial and single-cell transcriptome data to analyze tertiary lymphoid structures in clear cell renal cell carcinoma reveals prognostic biomarkers
Combining spatial and single-cell transcriptome data to analyze tertiary lymphoid structures in clear cell renal cell carcinoma reveals prognostic biomarkers

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Combining spatial and single-cell transcriptome data to analyze tertiary lymphoid structures in clear cell renal cell carcinoma reveals prognostic biomarkers
Combining spatial and single-cell transcriptome data to analyze tertiary lymphoid structures in clear cell renal cell carcinoma reveals prognostic biomarkers
Journal Article

Combining spatial and single-cell transcriptome data to analyze tertiary lymphoid structures in clear cell renal cell carcinoma reveals prognostic biomarkers

2026
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Overview
Background As the predominant and most aggressive subtype of renal cell carcinoma (RCC), clear cell RCC (ccRCC) represents the considerable heterogeneity present across RCC subtypes. Although tertiary lymphoid structures (TLS) are implicated in tumor immunity, their prognostic role and underlying mechanisms in ccRCC remain unclear. Characterizing TLS-associated genes may offer novel insights into disease progression and support improved risk stratification and personalized therapy. Methods The single-cell transcriptome and spatial transcriptome data were utilized to analyze the B-cell infiltration in ccRCC and to screen for differentially expressed genes within TLS of ccRCC. Next, consensus clustering and survival analysis based on Lasso-Cox regression were applied to identify TLS prognostic markers in ccRCC. Subsequently, a prognostic prediction model for ccRCC was established by integrating key clinical characteristics and these prognostic biomarkers. The immunofluorescence experiments were performed on ccRCC clinical specimens to validate the clinical relevance of proteins in candidate biomarkers for ccRCC. Results Aberrant expression of three TLS-associated genes ( CEMIP , PLA2G2A , and IGHGP ) was associated with poor prognosis in ccRCC, identifying them as potential prognostic biomarkers. Then, the protein-coding biomarkers were validated in ccRCC pathological tissue samples by immunofluorescence. Mechanistically, aberrant expression underlies the functional transition in TLS from anti-tumor immunity to tumor promotion, potentially mediated by dysregulation of oncogenic processes via multi-pathway interactions. A prognostic model based on these biomarkers demonstrated high predictive accuracy. Conclusions Combining single-cell analysis with spatial transcriptomic profiling identifies spatially-resolved functional heterogeneity in ccRCC-associated TLS, demonstrating their context-dependent immunomodulatory roles. Aberrant expression of specific TLS-associated proteins is associated with a functional transition from anti-tumor immunity to tumor promotion. CEMIP , PLA2G2A , and IGHGP may serve as potential prognostic biomarkers; derived models achieve high predictive accuracy, highlighting clinical potential. Immunofluorescence confirmed the enrichment of protein-level biomarkers within TLS in ccRCC clinical specimens. Our findings elucidate TLS-related genes regulating tumor-immune interactions, advancing understanding of ccRCC prognosis and providing tools for prediction and personalized therapy.