Abstract
BackgroundMetastasized clear cell renal cell carcinoma (ccRCC) is associated with a poor prognosis. Almost one-third of patients with non-metastatic tumors at diagnosis will later progress with metastatic disease. These patients need to be identified already at diagnosis, to undertake closer follow up and/or adjuvant treatment. Today, clinicopathological variables are used to risk classify patients, but molecular biomarkers are needed to improve risk classification to identify the high-risk patients which will benefit most from modern adjuvant therapies. Interestingly, DNA methylation profiling has emerged as a promising prognostic biomarker in ccRCC. This study aimed to derive a model for prediction of tumor progression after nephrectomy in non-metastatic ccRCC by combining DNA methylation profiling with clinicopathological variables.MethodsA novel cluster analysis approach (Directed Cluster Analysis) was used to identify molecular biomarkers from genome-wide methylation array data. These novel DNA methylation biomarkers, together with previously identified CpG-site biomarkers and clinicopathological variables, were used to derive predictive classifiers for tumor progression.ResultsThe “triple classifier” which included both novel and previously identified DNA methylation biomarkers together with clinicopathological variables predicted tumor progression more accurately than the currently used Mayo scoring system, by increasing the specificity from 50% in Mayo to 64% in our triple classifier at 85% fixed sensitivity. The cumulative incidence of progress (pCIP5yr) was 7.5% in low-risk vs 44.7% in high-risk in M0 patients classified by the triple classifier at diagnosis.ConclusionsThe triple classifier panel that combines clinicopathological variables with genome-wide methylation data has the potential to improve specificity in prognosis prediction for patients with non-metastatic ccRCC.
Highlights
Metastasized clear cell renal cell carcinoma is associated with a poor prognosis
Descriptive analysis of the clear cell renal cell carcinoma (ccRCC) cohort A total of 115 patients were included in this study, 57% were men, and the median age was 65 (± 11.6) years at diagnosis
Chi-square tests were used for testing independence between categorical variables and Mann–Whitney U tests were used for comparisons between continuous variables
Summary
Metastasized clear cell renal cell carcinoma (ccRCC) is associated with a poor prognosis. Almost onethird of patients with non-metastatic tumors at diagnosis will later progress with metastatic disease. These patients need to be identified already at diagnosis, to undertake closer follow up and/or adjuvant treatment. This study aimed to derive a model for prediction of tumor progression after nephrectomy in non-metastatic ccRCC by combining DNA methylation profiling with clinicopathological variables. Renal cell carcinoma (RCC) is the most common type of kidney cancer and clear cell RCC (ccRCC) constitutes 75% of RCC cases [3]. Non-metastatic patients with a high risk of tumor progression might benefit from an intensified follow-up to improve early diagnosis of tumor recurrence, and in the long run, be candidates for adjuvant treatment. It is essential to identify those patients already at diagnosis by reliable biomarkers with high sensitivity and specificity
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