Clinical Parameters Outperform Molecular Subtypes for Predicting Outcome in Bladder Cancer: Results from Multiple Cohorts, Including TCGA

Daley S. Morera, Sarrah L. Hasanali, Daniel Belew, Santu Ghosh, Zachary Klaassen, Andre R. Jordan, Jiaojiao Wang, Martha K. Terris, Roni J. Bollag, Axel S. Merseburger, Arnulf Stenzl, Mark S. Soloway, Vinata B. Lokeshwar

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)62-72
Number of pages11
JournalThe Journal of urology
Volume203
Issue number1
DOIs
StatePublished - Jan 1 2020

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Atlases
Urinary Bladder Neoplasms
Genome
Survival
Neoplasms
Muscles
Recurrence
Kaplan-Meier Estimate
Multivariate Analysis
Neoplasm Metastasis
Adjuvant Chemotherapy
Cisplatin
Publications
Datasets
Sensitivity and Specificity

Keywords

  • molecular diagnostic techniques
  • neoplasm grading
  • neoplasm invasiveness
  • risk
  • urinary bladder neoplasms

ASJC Scopus subject areas

  • Urology

Cite this

Clinical Parameters Outperform Molecular Subtypes for Predicting Outcome in Bladder Cancer : Results from Multiple Cohorts, Including TCGA. / Morera, Daley S.; Hasanali, Sarrah L.; Belew, Daniel; Ghosh, Santu; Klaassen, Zachary; Jordan, Andre R.; Wang, Jiaojiao; Terris, Martha K.; Bollag, Roni J.; Merseburger, Axel S.; Stenzl, Arnulf; Soloway, Mark S.; Lokeshwar, Vinata B.

In: The Journal of urology, Vol. 203, No. 1, 01.01.2020, p. 62-72.

Research output: Contribution to journalArticle

Morera, DS, Hasanali, SL, Belew, D, Ghosh, S, Klaassen, Z, Jordan, AR, Wang, J, Terris, MK, Bollag, RJ, Merseburger, AS, Stenzl, A, Soloway, MS & Lokeshwar, VB 2020, 'Clinical Parameters Outperform Molecular Subtypes for Predicting Outcome in Bladder Cancer: Results from Multiple Cohorts, Including TCGA', The Journal of urology, vol. 203, no. 1, pp. 62-72. https://doi.org/10.1097/JU.0000000000000351
Morera, Daley S. ; Hasanali, Sarrah L. ; Belew, Daniel ; Ghosh, Santu ; Klaassen, Zachary ; Jordan, Andre R. ; Wang, Jiaojiao ; Terris, Martha K. ; Bollag, Roni J. ; Merseburger, Axel S. ; Stenzl, Arnulf ; Soloway, Mark S. ; Lokeshwar, Vinata B. / Clinical Parameters Outperform Molecular Subtypes for Predicting Outcome in Bladder Cancer : Results from Multiple Cohorts, Including TCGA. In: The Journal of urology. 2020 ; Vol. 203, No. 1. pp. 62-72.
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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.

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.

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KW - neoplasm grading

KW - neoplasm invasiveness

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