PD13-06: Utility of a Molecular Signature for Predicting Recurrence and Progression in Non-Muscle-Invasive Bladder Cancer Patients: Comparison with the EORTC, CUETO and 2021 EAU Risk Groups
Introduction: The utility of the clinicopathological risk estimators such as European Organization for Research and Treatment of Cancer (EORTC), Spanish Urology Association for Oncological Treatment (CUETO) models and EAU risk groups for predicting prognosis of non-muscle-invasive bladder cancer (NMIBC) is controversial. The aim of this study was to compare the utility of a molecular signature-based subtype predictor (MSP888) with the EORTC, CUETO risk tables and 2021 EAU risk groups in NMIBC patients. Methods: A total of 178 NMIBC patients from Chungbuk National University Hospital (CBNUH) were enrolled, and the predictive value of the MSP888, EORTC, CUETO and 2021 EAU risk scores was compared. Of the 178 patients, 49 were newly analyzed by the RNA-sequencing for transcriptomic profiling, and their MSP888 subtype was evaluated according to previously developed molecular classifiers. The ability of the EORTC score, MSP888, Lund and UROMOL molecular subtypes to predict progression of 460 NMIBC patients from the UROMOL project was assessed. Results: Cox regression analyses showed that the MSP888 subtype was an independent predictor of NMIBC progression in the CBNUH cohort (P < 0.05). Particularly in patients not treated with BCG, MSP888 significantly linked with risk of disease recurrence and progression (both P < 0.05). However, the EORTC, CUETO and 2021 EAU risk scores showed disappointing results with respect to estimating the NMIBC prognosis in the CBNUH cohort. The MSP888, Lund and UROMOL subtypes demonstrated a similar capacity to predict progression of NMIBC patients in the UROMOL cohort (all P < 0.05). Conclusions: The molecular clustering predictor MSP888 is favorable for stratifying NMIBC patients to facilitate optimal treatment. SOURCE OF Funding: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education (grant numbers- 2020R1I1A3062508 and 2021R1I1A1A01050891); and NRF funded by the Ministry of Science and ICT (MIST) (grant number- 2020R1F1A1068488); and NRF funded by the Korean government (grant numbers- 2014M3C9A306855425, 2021M3H9A209695312, and 2022R1A2C200848011); and by a grant from the Korea Research Institute of Bioscience and Biotechnology (KRIBB) Research Initiative Program (grant number- KGM5192221); and by a grant of the MD-PhD/Medical Scientist Training Program through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health and Welfare, Republic of Korea.
