Evidence map›Paper›PMID 31112107›Full record

ArticleThe Journal of urology2020

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 and 3 more

Abstract read
In one paragraph

Article in The Journal of urology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  9. Similar genetic profile in early and late stage urothelial tract cancer.Journal of cancer research and clinical oncology · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Daley S Morera *Department of Biochemistry and Molecular Biology, Medical College of Georgia, Augusta University, Augusta, Georgia.
Sarrah L Hasanali *Department of Biochemistry and Molecular Biology, Medical College of Georgia, Augusta University, Augusta, Georgia.
Daniel BelewDivision of Urology, Department of Surgery, Medical College of Georgia, Augusta University, Augusta, Georgia.
Santu GhoshBiostatistics and Data Science, Medical College of Georgia, Augusta University, Augusta, Georgia.
Zachary KlaassenDivision of Urology, Department of Surgery, Medical College of Georgia, Augusta University, Augusta, Georgia.
Andre R JordanSheila and David Fuente Graduate Program in Cancer Biology, Sylvester Comprehensive Cancer Center, University of Miami-Miller School of Medicine, Miami, Florida.
Jiaojiao WangDepartment of Biochemistry and Molecular Biology, Medical College of Georgia, Augusta University, Augusta, Georgia.
Martha K TerrisDivision of Urology, Department of Surgery, Medical College of Georgia, Augusta University, Augusta, Georgia.
Roni J BollagDepartments of Pathology, Bio-Repository Alliance of Georgia for Oncology at Georgia Cancer Center, Medical College of Georgia, Augusta University, Augusta, Georgia.
Axel S MerseburgerUniversity-Hospital Schleswig-Holstein, Campus Luebeck, Luebeck, Germany.
Arnulf StenzlDepartments of Urology, Eberhard Karls University Tübingen, Tübingen, Germany.
Mark S SolowayMemorial Healthcare System, Aventura, Florida.
Vinata B LokeshwarDepartment of Biochemistry and Molecular Biology, Medical College of Georgia, Augusta University, Augusta, Georgia.

Funding

Novel Biomarkers for the Clinical Management of Bladder CancerR01CA227277 · NCI · AUGUSTA UNIVERSITY · PI LOKESHWAR, VINATA B · 2018 to 2023
$2.2M
Dietary Combination For Prevention of Metastatic Renal Cell CarcinomaR01CA176691 · NCI · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI LOKESHWAR, VINATA B · 2014 to 2019
$1.7M
Role of SLC13A3 in Renal Cell CarcinomaF31CA210612 · NCI · AUGUSTA UNIVERSITY · PI JORDAN, ANDRE R · 2016 to 2018
$102k
The role of a new molecular driver in bladder cancerF31CA236437 · NCI · AUGUSTA UNIVERSITY · PI MORERA, DALEY · 2019 to 2020
$73k
NCI NIH HHS F31 CA210612NCI NIH HHS F31 CA236437NCI NIH HHS R01 CA176691NCI NIH HHS R01 CA227277
6 · The paper itself

Abstract

purposeStudies 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

methodsWe 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.

resultsMuscle 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).

conclusionsMolecular 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.

Indexed as

Biomarkers, TumorCarcinoma, Transitional CellFemaleHumansKaplan-Meier EstimateMaleNeoplasm GradingNeoplasm InvasivenessNeoplasm MetastasisNeoplasm StagingPhenotypePredictive Value of TestsPrognosisRisk AssessmentRisk FactorsTranscriptomeBiomarkers, Tumormolecular diagnostic techniquesneoplasm gradingneoplasm invasivenessriskurinary bladder neoplasms

Identifiers

PMID31112107
PMCPMC8327783

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.