Abstract
Non-muscle-invasive bladder cancer (NMIBC) is clinically heterogeneous; thus, many patients fail to respond to treatment and relapse. Here, we identified a molecular signature that is both prognostic and predictive for NMIBC heterogeneity and responses to Bacillus Calmette-Guérin (BCG) therapy. Transcriptomic profiling of 948 NMIBC patients identified a signature-based subtype predictor, MSP888, along with three distinct molecular subtypes: DP.BCG+ (related to progression and response to BCG treatment), REC.BCG+ (related to recurrence and response to BCG treatment), and EP (equivocal prognosis). Patients with the DP.BCG+ subtype showed worse progression-free survival but responded to BCG treatment, whereas those with the REC.BCG+ subtype showed worse recurrence-free survival but responded to BCG treatment. Multivariate analyses revealed that MSP888 showed independent clinical utility for predicting NMIBC prognosis (each p = 0.001 for progression and recurrence, respectively). Comparative analysis of this classifier and previously established molecular subtypes (i.e., Lund taxonomy and UROMOL class) revealed that a great proportion of patients were similar between subtypes; however, the MSP888 predictor better differentiated biological activity or responsiveness to BCG treatment. Our data increase our understanding of the mechanisms underlying the poor prognosis of NMIBC and the effectiveness of BCG therapy, which should improve clinical practice and complement other diagnostic tools.
Highlights
Bladder cancer is responsible for 150,000 deaths annually in the world [1]
Establishment of Distinct Molecular Subtypes Associated with Prognosis of non-muscle-invasive bladder cancer (NMIBC)
When exploring EP subtype-specific pathways, we found that genes involved in PD-1/PD-L1 cancer immunotherapy, DNA damage responses, Sirtuin signaling, and senescence pathways were plentiful (Supplementary Table S3)
Summary
Bladder cancer is responsible for 150,000 deaths annually in the world [1]. Non-muscleinvasive bladder cancer (NMIBC) is the most common subtype of this disease, accounting for approximately 80% of all cases. 20% of these patients experience disease progression to muscle-invasive bladder cancer (MIBC) after treatment, a development associated with a very poor prognosis. Most studies of bladder cancer focused primarily on MIBC [12,13,14], or on combined analysis of NMIBC and MIBC [15], recent studies have examined NMIBC exhibiting several distinct molecular subtypes in an attempt to address tumor heterogeneity [7] and responsiveness to BCG therapy [8]. Previous studies identified the molecular characteristics of NMIBC, they did not provide enough information to identify patients most likely to respond to BCG treatment, or they did not validate the therapeutic relevance independently. We investigated putative genetic signatures expressed by distinct molecular subtypes of NMIBC and examined their utility for predicting prognosis and responses to BCG treatment. To validate the utility of the signature, we constructed a signature-based classifier using a deep learning method and confirmed the independent clinical utility of the classifier and its therapeutic relevance to different subtypes in multiple independent patient cohorts
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