Renal cell carcinoma treatment

This study creates a mouse model of VHL-/-TSC1-/- ccRCC, identifies metabolic and redox reprogramming, and highlights NRF2 as a therapeutic target.

The paper shows TFE3 fusions upregulate CD44 and SPP1 in tRCC, with potential therapeutic implications.

This paper identifies plasma proteomic biomarkers for diagnosing and prognosticating clear cell renal cell carcinoma through longitudinal mass spectrometry profiling.

This paper uses absolute quantitative proteomics to identify patient-specific drug repurposing strategies for clear cell and papillary renal cell carcinoma.

This study identifies 59 gene expression programs in RCC that reveal subtype identity and metastatic trajectories, including a metastatic signature linked to poor clinical outcomes.

The paper identifies site-dependent drug-biomarker associations in ccRCC using patient-derived models and multi-omic data, revealing discrepancies between genomic predictions and functional drug responses.

The paper develops a machine learning model to predict treatment response in RCC patients using individual-sample RNAseq data, finding that standardization methods affect cluster predictions.

The paper integrates single-cell multi-omics data to identify prognostic markers and mechanisms of progression in clear cell renal cell carcinoma.

The paper identifies isoform-level changes in ccRCC using DTU analysis, revealing subgroups with distinct survival outcomes and potential biomarkers.

The paper investigates sex-specific effects of Vhl and Vhl/Pbrm1 mutations in renal proximal tubule cells, revealing differences in lipid droplet accumulation and clonal expansion between males and females.

This study identifies Profilin-1 as a driver of chromophobe renal cell carcinoma progression by promoting proliferation, invasion, and resistance to oxidative stress.

This study identifies collagen VI as a key ECM component in ccRCC stroma, showing its role in shaping tumor structure, function, and immune response, with implications for TKI therapy.

The paper identifies a 13-gene transcriptomic signature that predicts intravascular tumor extension in renal cell carcinoma using RNA sequencing data from multiple cohorts.

The paper evaluates immune-infiltrated patient-derived tumor organoids as preclinical models for renal cell carcinoma, showing they retain immune signatures and hypoxic signaling relevant to the original tumors.

The paper identifies DUSP15 as a chRCC-selective biomarker through transcriptomic analysis and links it to an immune-metabolic tumor state.

This study uses proteomics to characterize sporadic ccRCC, identifying a matrix-dense pseudocapsule and five tumor subtypes with distinct biological features.

The paper identifies CDK9 inhibition as a therapeutic strategy for translocation renal cell carcinoma through phenotypic screening and mechanistic analysis.

This study shows bisantrene enhances the effectiveness of tyrosine kinase inhibitors in ccRCC by sustaining AKT inhibition and overcoming TKI resistance.

This study identifies CDK4/6 and mTORC1 pathway activation in tRCC and shows that their dual inhibition synergistically suppresses tRCC cell growth in vitro and xenografts in vivo.

The paper identifies a transcriptional transition state in ccRCC cells that drives sarcomatoid transformation and enhances immunotherapy response via macrophage and T-cell interactions.

This paper develops a machine learning framework for therapeutic target discovery in ccRCC, identifying 16 targets and novel mechanisms with superior efficacy to standard-of-care drugs.

The paper uses proteomics data and machine learning to identify protein signatures distinguishing renal cell carcinomas from normal tissues and different subtypes.

This study uses AI-based image analysis and multi-omics profiling to link morphological features with molecular changes in ccRCC, identifying unique molecular profiles in aggressive rhabdoid tumors.

This paper identifies a novel molecular subtype of papillary renal cell carcinoma (pRCC) characterized by HIF-pathway overactivation, associated with poor prognosis and distinct biological features.

The paper identifies DNA methylation subtypes from transcriptomes to guide sunitinib and immunotherapy selection in renal cancer, finding hyper-methylated tumors respond better to atezolizumab plus bevacizumab.

The paper identifies FAP-expressing EMT-associated cancer cells in highly inflamed localized ccRCC as an aggressive, immunosuppressive subtype linked to poor prognosis and metastasis.

The paper uses long-read spatial transcriptomics on ccRCC tumoroids to reveal gene and isoform expression heterogeneity, identifying distinct functional tumor clusters and isoform-specific patterns.

The paper analyzes RNAseq data to identify alternative splicing patterns associated with tumor thrombus formation in clear-cell renal cell carcinoma.

This study identifies hub genes associated with cure in chromophobe cell renal carcinoma using WGCNA and the defective Gompertz model, finding ten genes with strong predictive value.