Background and objective
Nonmetastatic (M0) clear cell renal cell carcinoma (ccRCC) recurs in ∼20% of patients within 5 yr after surgery. With no biomarkers available, recurrence detection relies on radiological imaging. Urine glycosaminoglycan profiles (GAGomes) were previously associated with M0 ccRCC recurrence. We conducted an observational prospective multicentre diagnostic test cohort study to evaluate GAGomes for postsurgery recurrence detection in M0 ccRCC.
Methods
Postsurgical M0 ccRCC patients with a Leibovich score of ≥5 points were included. Follow-up imaging up to 18 mo assessed radiological recurrence (reference standard). Urine GAGomes were measured every 3 mo to compute a GAGome score (index test). Sensitivity and specificity to radiological recurrence were calculated. The lead time between the first positive GAGome score and radiological recurrence was estimated. Bayesian joint modelling estimated recurrence-free survival hazard ratio (HR).
Key findings and limitations
Of the 393 patients screened (January 2020 to November 2021), 134 met the inclusion criteria. The median follow-up was 16 mo (interquartile range [IQR]: 12–18) for those without recurrence. At the last follow-up visit, 16% had recurred. The GAGome score had 90% sensitivity (95% confidence interval [CI]: 62–100%) and 51% specificity (95% CI: 30–71%) to radiological recurrence. The positive and negative predictive values were 26% (95%CI: 4–46%) and 97% (95% CI: 87–100%), respectively. The median lead time was 4.2 mo (IQR: 1.6–6.4). A 10-point GAGome score increase was associated with an HR of 1.62 (95% high density interval: 1.11–2.30) for recurrence. The main limitation was short follow-up time.
Conclusions and clinical implications
GAGome score had very high sensitivity to ccRCC recurrence, resulting in a negative predictive value of 97%. External validation foreseen in the study design aims to confirm its utility to personalise follow-up for M0 ccRCC patients.
AURORAX-0087A: urine glycosaminoglycan surveillance after nephrectomy of intermediate and high-risk non-metastatic clear cell renal cell carcinoma
Surgically-treated non-metastatic renal cell carcinoma (M0RCC) may recur in up to half of the patients, depending on presence of adverse clinical and pathological features. To date, several clinical tools, such as Leibovich score, SSIGN score and ASSURE score, have been developed to predict the risk of recurrence after surgery and consequently to assess the optimal follow-up strategy and to detect early potentially curable recurrences. Nonetheless, these prediction tools may not capture the true biology of the tumour at all.
In the last years, molecular pathways and molecular biomarkers show promising therapeutic potential. These specific molecules can be found in bodily fluids or tissues and include genes, RNAs, proteins, and metabolites that are identified through various “-omics” technologies and may be used for diagnosis and prognosis of several diseases. Among them, metabolomic biomarkers are particularly valuable due to a tumour’s metabolic reprogramming to sustain growth, since these small molecules reflect metabolic activity and processes within a tissue. Indeed, changes in metabolites, such as glycosaminoglycans (GAGs) that are an essential component of the extracellular matrix and play key roles in biological processes such as cell signalling, tissue repair, and inflammation, can indicate disease progression or recurrence.
Recently, the AURORAX-0087A clinical trial has been published in European Urology Oncology. This observational multicentre cohort study included 134 surgically-treated patients with M0 ccRCC and a Leibovich score of ≥5 points (intermediate- / high-risk patients). Patients were followed-up with imaging up to 18 months to assess radiological recurrence (reference standard), while urine glycosaminoglycan (GAGomes) were measured every 3 months to compute a GAGome score (index test). The hypothesis was that postoperative increase of the GAG scores, so called “GAG recurrence”, could predict or detect recurrence at an earlier time-point compared to “radiological recurrence”.
At a median follow-up of 15 months, 21 patients (16%) experienced recurrence, which however were only radiological and not biopsy-proven. The GAGome test showed potential for earlier detection of recurrence (median lead time of 4.2 months) compared to standard imaging with CT scans. In addition, GAGome scores were highly effective at correctly identifying patients with recurrence (90% sensitivity) and at ruling out recurrence (97% negative predictive value).
Therefore, these results have two main implications that might help personalising follow-up and treatment strategy. First, a negative GAGome score could reduce the need for frequent CT scans, potentially leading to reduced radiation exposure, lower healthcare costs, and more personalised follow-up. Second, the GAGome test’s ability to detect recurrence earlier could lead to the detection of minimal residual disease, allowing for timely and potentially more effective treatment.
However, this study does have limitations as well. First, the study showed a moderate-low specificity (51%) meaning that a positive test result doesn’t definitely confirm recurrence. Second, the short follow-up and the inclusion of only clear cell RCC may reduce applicability. Third, further validations are needed in order to demonstrate that the GAGome test is non-inferior to radiological recurrence and ultimately to confirm its utility to personalise follow-up for M0 ccRCC patients.