Abstract 1473P
Background
Prognosis of localized clear cell renal cell carcinoma (ccRCC) patients is estimated by nomograms based on clinico-pathological factors. However, clinical guidelines do not recommend their use. Recently, pembrolizumab has demonstrated benefit as adjuvant therapy only in disease-free survival (DFS) in high-risk localized ccRCC, increasing the need for better patient stratification tools.
Methods
miRNA expression was analyzed in FFPE nephrectomy tissues in the discovery and validation cohorts (Leeds-UK and Spain) including untreated, localized (stage Ib-III) ccRCC patients. 9 miRNAs for predict risk of relapse were defined and combined into Bio-miR. Molecular characterization of risk-based groups was done using proteomics and probabilistic graphical models (PGM).
Results
In the discovery cohort (n=71), DFS at 5 years was 93.9% in Bio-miR low-risk and 61.6% in high-risk patients (HR=6.9, p<0.001). Bio-miR compared favorably with UISS and Karakiewicz´s nomograms. In the Leeds-UK cohort (n=75), low-risk patients had a 5-year DFS rate of 94% vs 62% in high-risk, dividing the Leibovich intermediate-risk population into two risk groups (5-year DFS 100% vs 71%). In the Spanish cohort (n=180), DFS rates at 5 years were 82.9% in the low-risk and 58.7% in the high-risk group (HR=2.4; p<0.005). Amongst patients excluded from the KEYNOTE-564 due to low-risk features, Bio-miR defines a high-risk population who should be prioritized for adjuvant therapy. 124 proteins were differentially expressed between Bio-miR low and high-risk groups, mainly related to focal adhesion, metabolism and angiogenesis. PGM defined differences between low- and high-risk tumors in complement activation and translation functional nodes.
Conclusions
We defined and validated a Bio-miR, dichotomizing patients with localized ccRCC into low- and high-risk relapse groups. Bio-miR acts independently of tumor stage and grade and could refine the selection of patients for adjuvant therapy and improve design of future adjuvant ccRCC trials. Molecular characterization of risk groups highlighted some processes that could be useful in tailored treatments.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
EPIC-XS-823839-H2020; CDTI IDI-20200073.
Disclosure
A. Pinto Marin: Financial Interests, Personal, Invited Speaker: Pfizer, BMS, Ipsen, Novartis, Roche, Merck, MSD, Janssen, Astellas, Bayer, Sanofi. G.A. De Velasco Oria: Financial Interests, Personal, Advisory Board: Pfizer, Astellas, BMS, MSD, Ipsen, Bayer, Eusa P., Merck; Financial Interests, Personal, Invited Speaker: Pfizer, astellas, BMS, MSD, Roche, Ipsen, Merck; Financial Interests, Institutional, Research Grant: Roche. All other authors have declared no conflicts of interest.