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Bio-miR: A prognostic microRNA-based signature for localized clear cell renal cell carcinoma.

2022; Lippincott Williams & Wilkins; Volume: 40; Issue: 16_suppl Linguagem: Inglês

10.1200/jco.2022.40.16_suppl.e16519

1527-7755

Álvaro Pinto, Lucía Trilla‐Fuertes, Jesús Miranda, Naveen Vasudev, Eugenia García‐Fernández, Rocío López Vacas, Nathalia de Carvalho Dias Miranda, Michelle Wilson, Elena López‐Camacho, A. Pertejo, Maria Isabel Lumbreras-Herrera, Joanne Carlson Brown, Andrea Zapater‐Moros, Guillermo de Velasco, Daniel Castellano, María Pilar González-Peramato, Enrique Espinosa, Rosamonde E. Banks, Juan Ángel Fresno Vara, Angelo Gámez‐Pozo,

Ferroptosis and cancer prognosis

e16519 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 in disease-free survival (DFS) in medium-high risk localized ccRCC, increasing the need for better patient stratification tools. In this study, we have defined and validated a molecular signature, Bio-miR, based on the expression of nine microRNAs, with prognostic value in ccRCC. Methods: The discovery and two validation cohorts (Leeds-UK and Spain) consisted of patients with resected localized (stage Ib-III) ccRCC and no adjuvant therapy. miRNA expression was analyzed using microarrays and validated using qPCR in FFPE nephrectomy tissues. Cox regression was used to define the best microRNAs combination to predict risk of relapse. Results: In the discovery cohort (n = 71), DFS at 5 years was 93.9% amongst Bio-miR-defined low-risk patients and 61.6% in high-risk patients (HR = 6.9 (3.4-42.9), p < 0.001). Cancer-specific survival at 5 years was 95.7% and 86.4% in low- and high-risk patients, respectively (HR = 7.7 (1.7-35.1), p < 0.01). Bio-miR compared favorably with different histopathological factors and UISS and Karakiewicz´s nomograms. In the Leeds validation cohort (n = 75/95 passing qPCR quality control), patients defined as low-risk had a 5-year DFS rate of 94% versus 62% in high-risk defined disease. In this cohort Bio-miR was able to divide the Leibovich intermediate-risk population into two groups with divergent five-year DFS rates (100% vs 71%). In the Spanish validation cohort (n = 180), DFS rates at 5 years were 82.9% in the low-risk group and 58.7% in the high-risk group (HR = 2.4 (1.4-4.4); p < 0.005). Applying the inclusion criteria from the phase III KEYNOTE-564 trial, Bio-miR identifies a small low-risk population who could be spared adjuvant treatment. Conversely, amongst patients excluded from the study due to low-risk features, Bio-miR defines a high-risk population (DFS at five years of 50%) who should be prioritized for adjuvant therapy. Conclusions: We define and validate a nine-microRNA based signature capable of dichotomizing patients with localized ccRCC into low- and high-risk groups based on risk of relapse. Importantly, Bio-miR acts independently of tumor stage and grade and could, therefore, help refine the selection of patients for adjuvant therapy as well as inform the design of future adjuvant ccRCC trials.