Urine supernatant reveals a signature that predicts survival in clear cell renal cell carcinoma.

Unsupervised clustering analysis revealed inflammatory signatures in cell-free urine supernatant of ccRCC patients. Backward stepwise regressions using TCGA data identified transcriptomic risk factors and risk groups associated with OS. A nomogram to predict 2-year and 5-year OS was developed using these risk factors. The DCA revealed that our model was associated with a net benefit improvement compared to the treat all/none strategies CONCLUSION: We defined four novel biomarkers using proteomic and transcriptomic data that distinguish severity of prognosis in ccRCC. We show that these biomarkers can be used in a model to predict 2-year and 5-year OS in ccRCC across different tumor stages. This type of analysis, if validated in the future, provides non-invasive prognostic information that could inform either management or surveillance strategies for patients.