Molecular subtyping studies found 5-15% of bladder tumors had transcriptome profiles consistent with NE carcinoma but lacked NE histology.1,2 Identifying these NE variants prior to their phenotypic expression may have prognostic implications and modify treatment recommendations.
In this study, the authors present the results of using a robust genomic classifier trained to identify NE carcinoma. Transcriptome-wide expression profiles were generated for 576 MIBC patients collected from seven institutions. Model training included profiles generated from TURBT and RC specimens from 320 patients prior to treatment with NAC or chemo-radiation. The validation cohorts consisted of 256 RC specimens (no prior systemic treatment), a chemo-radiation cohort, a NAC cohort, and a Decipher assay cohort. Using 10 MIBC-related gene sets, a model was built to predict patients with a NE carcinoma expression profile.
In the training set of 320 patients, hierarchical clustering using a panel of 54 genes showed a cluster of 17 patients (5.3%) with a NE carcinoma expression profile. These patients had significantly worse 1-year progression free survival (65% vs 82% for NE vs overall; p = 0.046).
Using the genomic model in the validation set, 7 tumors were classified (2.7%) as NE with 4 (57%) patients dying from the disease at 1 year after RC. Within 3 years of RC, 100% (7/7) of patients with predicted NE tumors had died.
After adjusting for various clinical and pathological factors, patients with predicted NE tumors had a 6.40 increased risk of all-cause mortality (p = 0.001).
Based on this the authors have concluded that their gene expression signature is able to identify a particularly high-risk group that may need treatment intensification, alternative chemotherapy or clinical trials. Further validation is obviously required.
Presented by: Jonathan Wright, MD, University of Washington
Co-Authors: Marc Dall'era, Trinity Bivalacqua, Roland Seiler, Yang Liu, Ewan Gibb, Natalie Qiqi Wang, Nicholas Erho, Mohammed Alshalalfa, Elai Davicioni, Jason A. Efstathiou, James G. Douglas, Joost L Boormans, Michiel Simon Van Der Heijden, Yair Lotan, Peter C. Black
Written by: Thenappan Chandrasekar, MD, Clinical Fellow, University of Toronto, Twitter: @tchandra_uromd at the 2018 American Society of Clinical Oncology Genitourinary (ASCO GU) Cancers Symposium, February 8-10, 2018 - San Francisco, CA
1. Robertson AG et al. Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer. Cell. 2017 Oct 19;171(3):540-556.e25. doi: 10.1016/j.cell.2017.09.007. Epub 2017 Oct 5.
2. Sjödahl G et al. Molecular classification of urothelial carcinoma: global mRNA classification versus tumour-cell phenotype classification. J Pathol. 2017 May;242(1):113-125. doi: 10.1002/path.4886. Epub 2017 Mar 28.