Roland Seiler1, Hussam Al Deen Ashab2, Nicholas Erho2, Bas W G van Rhijn3, Brian Winters4, James Douglas5, Kim E Van Kessel6, Elisabeth E Fransen van de Putte3, Matthew Sommerlad5, Natalie Q Wang2, Voleak Choeurng2, Ewan A Gibb2, Beatrix Palmer-Aronsten2, Lucia L Lam2, Christine Buerki2, Elai Davicioni2, Gottfrid Sjödahl7, Jordan Kardos8, Katherine A Hoadley8, Seth P Lerner9, David J McConkey10, Woonyoung Choi10, William Y Kim8, Bernhard Kiss11, George N Thalmann11, Tilman Todenhöfer12, Simon J Crabb13, Scott North14, Ellen C Zwarthoff6, Joost L Boormans15, Jonathan Wright4, Marc Dall'Era16, Michiel S van der Heijden3, Peter C Black17. 1. Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada; Department of Urology, University of Bern, Bern, Switzerland. 2. GenomeDx Biosciences, Inc., Vancouver, British Columbia, Canada. 3. Department of Surgical Oncology, Division of Urology, Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands. 4. Department of Urology, University of Washington School of Medicine, Seattle, Washington, USA. 5. Department of Urology, University Hospital of Southampton, Hampshire, UK. 6. Department of Pathology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands. 7. Division of Urological Research, Department of Translational Medicine, Lund University, Malmö, Sweden. 8. Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. 9. Scott Department of Urologic Oncology, Baylor College of Medicine, Houston, Texas, USA. 10. Department of Urology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA. 11. Department of Urology, University of Bern, Bern, Switzerland. 12. Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada. 13. Department of Medical Oncology, University Hospital of Southampton, Hampshire, UK. 14. Cross Cancer Institute, Department of Oncology, University of Alberta Edmonton, Alberta, Canada. 15. Department of Urology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands. 16. UC Davis Comprehensive Cancer Center, Sacramento, California, USA. 17. Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada. Electronic address: pblack@mail.ubc.ca.
Abstract
BACKGROUND: An early report on the molecular subtyping of muscle-invasive bladder cancer (MIBC) by gene expression suggested that response to neoadjuvant chemotherapy (NAC) varies by subtype. OBJECTIVE: To investigate the ability of molecular subtypes to predict pathological downstaging and survival after NAC. DESIGN, SETTING, AND PARTICIPANTS: Whole transcriptome profiling was performed on pre-NAC transurethral resection specimens from 343 patients with MIBC. Samples were classified according to four published molecular subtyping methods. We developed a single-sample genomic subtyping classifier (GSC) to predict consensus subtypes (claudin-low, basal, luminal-infiltrated and luminal) with highest clinical impact in the context of NAC. Overall survival (OS) according to subtype was analyzed and compared with OS in 476 non-NAC cases (published datasets). INTERVENTION: Gene expression analysis was used to assign subtypes. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Receiver-operating characteristics were used to determine the accuracy of GSC. The effect of GSC on survival was estimated by Cox proportional hazard regression models. RESULTS AND LIMITATIONS: The models generated subtype calls in expected ratios with high concordance across subtyping methods. GSC was able to predict four consensus molecular subtypes with high accuracy (73%), and clinical significance of the predicted consensus subtypes could be validated in independent NAC and non-NAC datasets. Luminal tumors had the best OS with and without NAC. Claudin-low tumors were associated with poor OS irrespective of treatment regimen. Basal tumors showed the most improvement in OS with NAC compared with surgery alone. The main limitations of our study are its retrospective design and comparison across datasets. CONCLUSIONS: Molecular subtyping may have an impact on patient benefit to NAC. If validated in additional studies, our results suggest that patients with basal tumors should be prioritized for NAC. We discovered the first single-sample classifier to subtype MIBC, which may be suitable for integration into routine clinical practice. PATIENT SUMMARY: Different molecular subtypes can be identified in muscle-invasive bladder cancer. Although cisplatin-based neoadjuvant chemotherapy improves patient outcomes, we identified that the benefit is highest in patients with basal tumors. Our newly discovered classifier can identify these molecular subtypes in a single patient and could be integrated into routine clinical practice after further validation.
BACKGROUND: An early report on the molecular subtyping of muscle-invasive bladder cancer (MIBC) by gene expression suggested that response to neoadjuvant chemotherapy (NAC) varies by subtype. OBJECTIVE: To investigate the ability of molecular subtypes to predict pathological downstaging and survival after NAC. DESIGN, SETTING, AND PARTICIPANTS: Whole transcriptome profiling was performed on pre-NAC transurethral resection specimens from 343 patients with MIBC. Samples were classified according to four published molecular subtyping methods. We developed a single-sample genomic subtyping classifier (GSC) to predict consensus subtypes (claudin-low, basal, luminal-infiltrated and luminal) with highest clinical impact in the context of NAC. Overall survival (OS) according to subtype was analyzed and compared with OS in 476 non-NAC cases (published datasets). INTERVENTION: Gene expression analysis was used to assign subtypes. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Receiver-operating characteristics were used to determine the accuracy of GSC. The effect of GSC on survival was estimated by Cox proportional hazard regression models. RESULTS AND LIMITATIONS: The models generated subtype calls in expected ratios with high concordance across subtyping methods. GSC was able to predict four consensus molecular subtypes with high accuracy (73%), and clinical significance of the predicted consensus subtypes could be validated in independent NAC and non-NAC datasets. Luminal tumors had the best OS with and without NAC. Claudin-low tumors were associated with poor OS irrespective of treatment regimen. Basal tumors showed the most improvement in OS with NAC compared with surgery alone. The main limitations of our study are its retrospective design and comparison across datasets. CONCLUSIONS: Molecular subtyping may have an impact on patient benefit to NAC. If validated in additional studies, our results suggest that patients with basal tumors should be prioritized for NAC. We discovered the first single-sample classifier to subtype MIBC, which may be suitable for integration into routine clinical practice. PATIENT SUMMARY: Different molecular subtypes can be identified in muscle-invasive bladder cancer. Although cisplatin-based neoadjuvant chemotherapy improves patient outcomes, we identified that the benefit is highest in patients with basal tumors. Our newly discovered classifier can identify these molecular subtypes in a single patient and could be integrated into routine clinical practice after further validation.
Authors: Eva Compérat; Marek Babjuk; Ferran Algaba; Mahul Amin; Fadi Brimo; David Grignon; Donna Hansel; Ondra Hes; Bernard Malavaud; Victor Reuter; Theo van der Kwast Journal: World J Urol Date: 2018-09-14 Impact factor: 4.226
Authors: Izak Faiena; Amirali Salmasi; Neil Mendhiratta; Andrew T Lenis; Aydin Pooli; Alexandra Drakaki; Kiran Gollapudi; Jeremy Blumberg; Allan J Pantuck; Karim Chamie Journal: World J Urol Date: 2018-05-11 Impact factor: 4.226