Metastatic risk stratification of clear cell renal cell carcinoma patients based on genomic aberrations

Abstract

Prognostic markers for the definition of the individual metastatic risk in renal cell carcinoma are still missing. The aim of our study was to establish a total number of specific aberrations (TNSA) genetic score as a new prognostic test for metastatic risk evaluation. Fluorescence in situ hybridization (FISH) was performed on isolated cell nuclei of 100 ccRCCs (50 M1/50 M0) and 100 FFPE sections (second cohort, 32 M1/68 M0). For each chromosomal region (1q21.3, 7q36.3, 9p21.3p24.1, 20q11.21q13.32) cut-off values were determined by receiver-operator curve (ROC)-curve analysis. TNSA was calculated based on the dichotomized specific CNVs.The prognostic significance of CNVs was proven by Cox and logistic regression. TNSA was the best predictor of metastasis and recurrence free survival in both cohorts. We derived an algorithm for risk stratification by combining TNSA and T-category, which increased the prognostic accuracy to 87% (specificity = 86%, sensitivity = 88%). This model divides patients into two risk groups with significantly different RFS, CSS, and OS (P = 3.8×10 −5 , P = 5×10 −6 and P = 3.57×10 −8 respectively). The genetic risk model was superior to Leibovich score and was able to identify patients with metachronous metastatic spread which were incorrectly classified as "low" or "intermediate risk." We present a new tool for individual risk stratification by combining genetic alterations with clinico-pathologic parameters. Interphase FISH proves to be a dependable method for prognostic evaluation in primary tumor tissue on isolated cell nuclei as well as on FFPE sections. Especially in organ-confined tumors the genetic score seems to be an important tool to identify patients at high risk for metastatic disease.

Genomic and Transcriptomic Profiling of Brain Metastases

“…Without a cohort of primary tumor samples in patients who were confirmed to not have developed brain metastases to compare against it is impossible to make definitive statements, but this suggests that gain of MCL1 could be an early driver of metastasis. MCL1 has been implicated in both the metastasis of clear cell renal carcinoma [ 61 ] and recurrence of breast cancer [ 62 ]. A combined 55% of samples had FAT1 lesions, predominantly as del4q35.2 (48%), with a minority of samples (14%) with mutations.…”

Biomarkers for Renal Cell Carcinoma Recurrence: State of the Art

“…The combination of both showed an increase of the prognostic accuracy to 87%. The model was able to classify the patients in two risk groups with different recurrence free survival, cancer specific survival, and overall survival [38]. The model was also better than the Leibovich risk group classification system (C-index 0.848 vs. 0.742) [38].…”

“…Indeed, area under the curve ranged between 65.1 and 76.0% when logistic regression models were used versus 73.6 and 79.6% when deep neural network models were employed [37]. Similarly, Grimm et al relied on an algorithm for risk stratification of metastases in patients with ccRCC [38]. The algorithm combined the total number of specific aberration genetic score and T-category.…”

Biomarker: der Weg zur individualisierten Therapie bei Nierenzelltumoren

“…Die Wertigkeit dieses Scores wurde mittels FISH an 200 unabhängigen Fällen validiert [18]. Der neu entwickelte Algorithmus unter Berücksichtigung der TNSA und der T-Kategorie erwies sich als einzige unabhängiger prognostischer Parameter für das Metastasierungsrisiko und war dem Leibovich-Score überlegen [18]. Der Score führte zu einer deutlichen Verbesserung der Risikobewertung insbesondere in der "intermediate risk" Gruppe.…”

“…TNSA (total number of specific aberrations) score definiert [17]. Die Wertigkeit dieses Scores wurde mittels FISH an 200 unabhängigen Fällen validiert [18]. Der neu entwickelte Algorithmus unter Berücksichtigung der TNSA und der T-Kategorie erwies sich als einzige unabhängiger prognostischer Parameter für das Metastasierungsrisiko und war dem Leibovich-Score überlegen [18].…”