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Background: The current World Health Organization classification recognises 12 major subtypes of renal cell carcinoma (RCC). Although these subtypes differ on molecular and clinical levels, they are generally managed as the same disease, simply because they occur in the same organ. Specifically, there is a paucity of tools to risk-stratify patients with papillary RCC (PRCC). The purpose of this study was to develop and evaluate a tool to risk-stratify patients with clinically non-metastatic PRCC following curative surgery.Methods: We studied clinicopathological variables and outcomes of 556 patients, who underwent full resection of sporadic, unilateral, non-metastatic (T1-4, N0-1, M0) PRCC at five institutions. Based on multivariable Fine-Gray competing risks regression models, we developed a prognostic scoring system to predict disease recurrence. This was further evaluated in the 150 PRCC patients recruited to the ASSURE trial. We compared the discrimination, calibration and decision-curve clinical net benefit against the Tumour, Node, Metastasis (TNM) stage group, University of California Integrated Staging System (UISS) and the 2018 Leibovich prognostic groups.Results: We developed the VENUSS score from significant variables on multivariable analysis, which were the presence of VEnous tumour thrombus, NUclear grade, Size, T and N Stage. We created three risk groups based on the VENUSS score, with a 5-year cumulative incidence of recurrence equalling 2.9% in low-risk, 15.4% in intermediate-risk and 54.5% in high-risk patients. 91.7% of low-risk patients had oligometastatic recurrent disease, compared to 16.7% of intermediate-risk and 40.0% of high-risk patients. Discrimination, calibration and clinical net benefit from VENUSS appeared to be superior to UISS, TNM and Leibovich prognostic groups.Conclusions: We developed and tested a prognostic model for patients with clinically non-metastatic PRCC, which is based on routine pathological variables. This model may be superior to standard models and could be used for tailoring postoperative surveillance and defining inclusion for prospective adjuvant clinical trials. [ABSTRACT FROM AUTHOR]

Background: Cell-free tumor-derived DNA (ctDNA) allows non-invasive monitoring of cancers, but its utility in renal cell cancer (RCC) has not been established. Methods: Here, a combination of untargeted and targeted sequencing methods, applied to two independent cohorts of patients (n = 91) with various renal tumor subtypes, were used to determine ctDNA content in plasma and urine. Results: Our data revealed lower plasma ctDNA levels in RCC relative to other cancers of similar size and stage, with untargeted detection in 27.5% of patients from both cohorts. A sensitive personalized approach, applied to plasma and urine from select patients (n = 22) improved detection to ~ 50%, including in patients with early-stage disease and even benign lesions. Detection in plasma, but not urine, was more frequent amongst patients with larger tumors and in those patients with venous tumor thrombus. With data from one extensively characterized patient, we observed that plasma and, for the first time, urine ctDNA may better represent tumor heterogeneity than a single tissue biopsy. Furthermore, in a subset of patients (n = 16), longitudinal sampling revealed that ctDNA can track disease course and may pre-empt radiological identification of minimal residual disease or disease progression on systemic therapy. Additional datasets will be required to validate these findings. Conclusions: These data highlight RCC as a ctDNA-low malignancy. The biological reasons for this are yet to be determined. Nonetheless, our findings indicate potential clinical utility in the management of patients with renal tumors, provided improvement in isolation and detection approaches. [ABSTRACT FROM AUTHOR]