ArticleFrontiers in oncology2023
Integrative analysis of transcriptomic landscape and urinary signature reveals prognostic biomarkers for clear cell renal cell carcinoma.
Article in Frontiers in oncology, 2023. 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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4 citing papers in PubMed, 3 citations in OpenAlex.
- Article
- TGFBI in tumors and the tumor immune microenvironment: functional roles, mechanisms, and therapeutic targeting.Frontiers in immunology · 2026Review
- Identification and validation of prognostic biomarkers in ccRCC: immune-stromal score and survival prediction.BMC cancer · 2025Article
- Multimodal data integration using machine learning to predict the risk of clear cell renal cancer metastasis: a retrospective multicentre study.Abdominal radiology (New York) · 2024Article
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Authors and funding
10 authors at 1 institution in 1 country.
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Abstract
Background: Clear cell renal cell carcinoma (ccRCC) patients with venous tumor thrombus (VTT) have poor prognosis. We aimed to reveal features of ccRCC with VTT and develop a urine-based prognostic classifier to predict ccRCC prognosis through integrative analyses of transcriptomic landscape and urinary signature. Methods: RNA sequencing was performed in five patients with ccRCC thrombus-tumor-normal tissue triples, while mass spectrometry was performed for urine samples from 12 ccRCC and 11 healthy controls. A urine-based classifier consisting of three proteins was developed to predict patients' survival and validated in an independent cohort. Results: Transcriptomic analysis identified 856 invasion-associated differentially expressed genes (DEGs). Furthermore, proteomic analysis showed 133 differentially expressed proteins (DEPs). Integration of transcriptomic landscape and urinary signature reveals 6 urinary detectable proteins (VSIG4, C3, GAL3ST1, TGFBI, AKR1C3, P4HB) displaying abundance changes consistent with corresponding genes in transcriptomic profiling. According to TCGA database, VSIG4, TGFBI, and P4HB were significantly overexpressed in patients with shorter survival and might be independent prognostic factors for ccRCC (all p<0.05). A prognostic classifier consisting of the three DEPs highly associated with survival performed satisfactorily in predicting overall survival (HR=2.0, p<0.01) and disease-free survival (HR=1.6, p<0.001) of ccRCC patients. The ELISA analysis of urine samples from an independent cohort confirmed the satisfied predictive power of the classifier for pathological grade (AUC=0.795, p<0.001) and stage (AUC=0.894, p<0.001). Conclusion: Based on integrative analyses of transcriptomic landscape and urinary signature, the urine-based prognostic classifier consisting of VSIG4, TGFBI, and P4HB has satisfied predictive power of ccRCC prognosis and may facilitate ccRCC molecular subtyping and treatment.
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