Development of a Clinically Applicable NanoString-Based Gene Expression Classifier for Muscle-Invasive Bladder Cancer Molecular Stratification

Transcriptional profiling of muscle-invasive bladder cancer (MIBC) using RNA sequencing (RNA-seq) technology has demonstrated the existence of intrinsic basal and luminal molecular subtypes that vary in their prognosis and response to therapy. However, routine use of RNA-seq in a clinical setting is...

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Bibliographic Details
Published inCancers Vol. 14; no. 19; p. 4911
Main Authors Olkhov-Mitsel, Ekaterina, Yu, Yanhong, Lajkosz, Katherine, Liu, Stanley K., Vesprini, Danny, Sherman, Christopher G., Downes, Michelle R.
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.10.2022
MDPI
Subjects
Bladder cancer
Cancer
Cancer therapies
Chemotherapy
Classification
Decision making
Diagnosis
GATA-3 protein
Gene expression
Genetic aspects
Genetic screening
Health aspects
Histology
Immunohistochemistry
Invasiveness
Literature reviews
Methods
Pathology
Patients
Primary care
Prognosis
Ribonucleic acid
RNA
Software
Statistical analysis
Survival
Transcriptomics
Tumors
Canada
United States > US
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Summary:Transcriptional profiling of muscle-invasive bladder cancer (MIBC) using RNA sequencing (RNA-seq) technology has demonstrated the existence of intrinsic basal and luminal molecular subtypes that vary in their prognosis and response to therapy. However, routine use of RNA-seq in a clinical setting is restricted by cost and technical difficulties. Herein, we provide a single-sample NanoString-based seven-gene (KRT5, KRT6C, SERPINB13, UPK1A, UPK2, UPK3A and KRT20) MIBC molecular classifier that assigns a luminal and basal molecular subtype. The classifier was developed in a series of 138 chemotherapy naïve MIBCs split into training (70%) and testing (30%) datasets. Further, we validated the previously published CK5/6 and GATA3 immunohistochemical classifier which showed high concordance of 96.9% with the NanoString-based gene expression classifier. Immunohistochemistry-based molecular subtypes significantly correlated with recurrence-free survival (RFS) and disease-specific survival (DSS) in univariable (p  =  0.006 and p  =  0.011, respectively) and multivariate cox regression analysis for DSS (p = 0.032). Used sequentially, the immunohistochemical- and NanoString-based classifiers provide faster turnaround time, lower cost per sample and simpler data analysis for ease of clinical implementation in routine diagnostics.
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ISSN:2072-6694
2072-6694
DOI:10.3390/cancers14194911