| Literature DB >> 33535616 |
Seon-Kyu Kim1,2, Seong-Hwan Park1,2, Yeong Uk Kim3, Young Joon Byun4, Xuan-Mei Piao4, Pildu Jeong4, Kyeong Kim4,5, Hee Youn Lee4,5, Sung Pil Seo4,5, Ho Won Kang4,5, Won Tae Kim4,5, Yong-June Kim4,5, Sang-Cheol Lee4,5, Sung-Kwon Moon6, Yung Hyun Choi7, Wun-Jae Kim4,5, Seon-Young Kim1,8, Seok Joong Yun4,5.
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.Entities:
Keywords: BCG; gene signature; molecular subtypes; non-muscle-invasive bladder cancer; prognosis
Year: 2021 PMID: 33535616 DOI: 10.3390/ijms22031450
Source DB: PubMed Journal: Int J Mol Sci ISSN: 1422-0067 Impact factor: 5.923