ArticleTranslational andrology and urology2025
Single-cell multi-omics and spatial transcriptomics reveal the transcriptional regulatory landscape of clear cell renal cell carcinoma.
Article in Translational andrology and urology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Article
- Nutrient-Sensitive Epigenetic Modifiers as Candidate Biomarkers of Metabolic Dysfunction in Obesity: A Nutrigenomic Review.International journal of molecular sciences · 2026Review
- Modulation of Network Plasticity Opens Novel Therapeutic Possibilities in Cancer, Diabetes, and Neurodegeneration.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Advances in the identification of novel cell signatures in benign prostatic hyperplasia and prostate cancer using single-cell RNA sequencing.Frontiers in immunology · 2025Review
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Authors and funding
9 authors.
Funding
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Abstract
Background: Clear cell renal cell carcinoma (ccRCC) represents the most aggressive form of renal cell carcinoma (RCC), distinguished by pronounced intratumoral heterogeneity, extensive metabolic reprogramming, and marked resistance to conventional therapeutic approaches. This study aimed to comprehensively characterize the cellular heterogeneity, epigenetic regulation, and transcription factor (TF) networks in ccRCC by integrating multi-omics data, and to identify functional key genes with prognostic and therapeutic significance. Methods: Single-cell RNA sequencing (scRNA-seq), single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq), and spatial transcriptomics (ST) were integrated to comprehensively explore cellular heterogeneity, epigenetic regulation, and TF networks in ccRCC. To uncover dynamic alterations in gene expression during cellular differentiation, single-cell pseudotime analysis and gene set enrichment analysis (GSEA) were performed. Furthermore, the functional significance of Y-box binding protein 3 ( Results: Single-cell transcriptomic profiling revealed 16 distinct cell populations within the ccRCC tumor microenvironment (TME), including ccRCC tumor cells, exhausted CD8 Conclusions: This study elucidates cellular heterogeneity, the epigenetic regulatory landscape, and the key genes driving ccRCC progression. The integration of multi-omics data offers novel insights into precise diagnostic strategies and therapeutic interventions, highlighting the pivotal role of genes such as
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