TY - JOUR
T1 - Clinical Parameters Outperform Molecular Subtypes for Predicting Outcome in Bladder Cancer
T2 - Results from Multiple Cohorts, Including TCGA
AU - Morera, Daley S.
AU - Hasanali, Sarrah L.
AU - Belew, Daniel
AU - Ghosh, Santu
AU - Klaassen, Zachary
AU - Jordan, Andre R.
AU - Wang, Jiaojiao
AU - Terris, Martha K.
AU - Bollag, Roni J.
AU - Merseburger, Axel S.
AU - Stenzl, Arnulf
AU - Soloway, Mark S.
AU - Lokeshwar, Vinata B.
N1 - Funding Information:
ACKNOWLEDGMENT Dr. Gottfrid Sjodahl, Division of Urological Research, Department of Translational Medicine, Lund University, Skane University Hospital, Malmo, Sweden provided the subtype identifiers of specimens in TCGA data set according to the Lund taxonomy and the Consensus classifications. Cynthia Soloway, and Dr. Bal Lokeshwar provided input and critically read and edited the manuscript.
Funding Information:
Approximately 50% of the research reported in this publication was supported by the NCI (National Cancer Institute) of the NIH (National Institutes of Health), under the awards 1R01CA227277-01A1 (VBL), 1F31 CA236437-01 (DSM) and 1F31CA210612-01 (ARJ) and 25% from the USAMRDC (United States Army Medical Research and Development Command) of the Department of Defense, under award number W81XWH-18-1-0277 (VBL). Additionally, 25% of this work was supported by Augusta University funds. The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
Publisher Copyright:
Copyright © 2020 by AMERICAN UROLOGICAL ASSOCIATION EDUCATION AND RESEARCH, INC.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Purpose:Studies indicate that molecular subtypes in muscle invasive bladder cancer predict the clinical outcome. We evaluated whether subtyping by a simplified method and established classifications could predict the clinical outcome.Materials and Methods:We subtyped institutional cohort 1 of 52 patients, including 39 with muscle invasive bladder cancer, an Oncomine™ data set of 151 with muscle invasive bladder cancer and TCGA (The Cancer Genome Atlas) data set of 402 with muscle invasive bladder cancer. Subtyping was done using simplified panels (MCG-1 and MCG-Ext) which included only transcripts common in published studies and were analyzed for predicting metastasis, and cancer specific, overall and recurrence-free survival. TCGA data set was further analyzed using the Lund taxonomy, the Bladder Cancer Molecular Taxonomy Group Consensus and TCGA 2017 mRNA subtype classifications.Results:Muscle invasive bladder cancer specimens from cohort 1 and the Oncomine data set showed intratumor heterogeneity for transcript and protein expression. MCG-1 subtypes did not predict the outcome on univariate or Kaplan-Meier analysis. On multivariate analysis N stage (p ≤0.007), T stage (p ≤0.04), M stage (p=0.007) and/or patient age (p=0.01) predicted metastasis, cancer specific and overall survival, and/or the cisplatin based adjuvant chemotherapy response. In TCGA data set publications showed that subtypes risk stratified patients for overall survival. Consistently the MCG-1 and MCG-Ext subtypes were associated with overall but not recurrence-free survival on univariate and Kaplan-Meier analyses. TCGA data set included 21 low grade specimens of the total of 402 and subtypes associated with tumor grade (p=0.005). However, less than 1% of muscle invasive bladder cancer cases are low grade. In only high grade specimens the MCG-1 and MCG-Ext subtypes could not predict overall survival. On univariate analysis subtypes according to the Bladder Cancer Molecular Taxonomy Group Consensus, TCGA 2017 and the Lund taxonomy were associated with tumor grade (p <0.0001) and overall survival (p=0.01 to <0.0001). Regardless of classification, subtypes had about 50% to 60% sensitivity and specificity to predict overall and recurrence-free survival. On multivariate analyses N stage and lymphovascular invasion consistently predicted recurrence-free and overall survival (p=0.039 and 0.003, respectively).Conclusions:Molecular subtypes reflect bladder tumor heterogeneity and are associated with tumor grade. In multiple cohorts and subtyping classifications the clinical parameters outperformed subtypes for predicting the outcome.
AB - Purpose:Studies indicate that molecular subtypes in muscle invasive bladder cancer predict the clinical outcome. We evaluated whether subtyping by a simplified method and established classifications could predict the clinical outcome.Materials and Methods:We subtyped institutional cohort 1 of 52 patients, including 39 with muscle invasive bladder cancer, an Oncomine™ data set of 151 with muscle invasive bladder cancer and TCGA (The Cancer Genome Atlas) data set of 402 with muscle invasive bladder cancer. Subtyping was done using simplified panels (MCG-1 and MCG-Ext) which included only transcripts common in published studies and were analyzed for predicting metastasis, and cancer specific, overall and recurrence-free survival. TCGA data set was further analyzed using the Lund taxonomy, the Bladder Cancer Molecular Taxonomy Group Consensus and TCGA 2017 mRNA subtype classifications.Results:Muscle invasive bladder cancer specimens from cohort 1 and the Oncomine data set showed intratumor heterogeneity for transcript and protein expression. MCG-1 subtypes did not predict the outcome on univariate or Kaplan-Meier analysis. On multivariate analysis N stage (p ≤0.007), T stage (p ≤0.04), M stage (p=0.007) and/or patient age (p=0.01) predicted metastasis, cancer specific and overall survival, and/or the cisplatin based adjuvant chemotherapy response. In TCGA data set publications showed that subtypes risk stratified patients for overall survival. Consistently the MCG-1 and MCG-Ext subtypes were associated with overall but not recurrence-free survival on univariate and Kaplan-Meier analyses. TCGA data set included 21 low grade specimens of the total of 402 and subtypes associated with tumor grade (p=0.005). However, less than 1% of muscle invasive bladder cancer cases are low grade. In only high grade specimens the MCG-1 and MCG-Ext subtypes could not predict overall survival. On univariate analysis subtypes according to the Bladder Cancer Molecular Taxonomy Group Consensus, TCGA 2017 and the Lund taxonomy were associated with tumor grade (p <0.0001) and overall survival (p=0.01 to <0.0001). Regardless of classification, subtypes had about 50% to 60% sensitivity and specificity to predict overall and recurrence-free survival. On multivariate analyses N stage and lymphovascular invasion consistently predicted recurrence-free and overall survival (p=0.039 and 0.003, respectively).Conclusions:Molecular subtypes reflect bladder tumor heterogeneity and are associated with tumor grade. In multiple cohorts and subtyping classifications the clinical parameters outperformed subtypes for predicting the outcome.
KW - molecular diagnostic techniques
KW - neoplasm grading
KW - neoplasm invasiveness
KW - risk
KW - urinary bladder neoplasms
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U2 - 10.1097/JU.0000000000000351
DO - 10.1097/JU.0000000000000351
M3 - Article
C2 - 31112107
AN - SCOPUS:85076331692
SN - 0022-5347
VL - 203
SP - 62
EP - 72
JO - Journal of Urology
JF - Journal of Urology
IS - 1
ER -