A MULTIPLEX DIAGNOSTIC GENE EXPRESSION SIGNATURE STRATIFIES MUSCLE INVASIVE BLADDER CANCER INTO RESPONDERS VS. NON-RESPONDERS TO NEOADJUVANT CHEMOTHERAPY

Date:	April 23, 2025
DOI:	10.1097/01.JU.0001109980.27536.57.34
Category:	N/A
Authors:	Dai, YF (Dai, Yunfeng) ; Sakatani, T (Sakatani, Toru) ; Tanaka, S (Tanaka, Sunao) ; Black, P (Black, Peter) ; Rosser, CJ (Rosser, Charles J.) ; Furuya, H (Furuya, Hideki)
Abstract:	IP14-34

INTRODUCTION AND OBJECTIVE:

Bladder cancer is a biologically heterogeneous disease with variable clinical presentation, outcome and response to therapy. Thus, the clinical utility of a single biomarker for the detection and prediction of biological behavior of bladder cancer is limited. We have developed a multiplex bladder cancer diagnostic test comprised of 10 biomarkers known as a bladder cancer associated diagnostic signature. Here we evaluate whether the biomarkers associated with bladder cancer possesses the ability to prediction the clinical response to neoadjuvant chemotherapy.

METHODS:

Genomic classifier (GC) comprised of 10 mRNA biomarkers (APOE, ANG, A1AT, CA9, IL8, MMP9, MMP10, PAI1, SDC1 and VEGF) for predicting response (partial or complete response) to neoadjuvant chemotherapy (NAC) was developed in a training set (n=82). Performance was assessed in the training set then, we used the leave-one-out cross validation (LOOCV) method to estimate the parameters of a linear discriminant analysis (LDA) classifier and the performance of the classifier was evaluated on the test set. For performance evaluation, we calculated sensitivity, specificity, and a receiver operating characteristic (ROC) curve was used to provide a direct view of how a prediction model functioned at different sensitivity and specificity levels.

RESULTS:

The 10-feature GC achieved an area under the curve (AUC) of 0.761 in the training cohort with an associated 82.3% sensitivity, 62.5% specificity, negative predictive value of 0. 833 and positive predictive value of 60.8.

CONCLUSIONS:

The validated GC (called Nexus-Dx) performed reasonably well in predicting postcystectomy NAC response rates. This may be used to better identify patients who need more aggressive management prior to definitive cystectomy.

Source of Funding:

This work was supported by research grants UH3 CA271377 (CJR), R01 CA277810 (HF/CJR), U54 CA274375-01(HF/CJR) and R01 CA1988887 (CJR)

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Acknowledgements:

The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute, or the National Institute of Health.

The Translational and Basic Science Research in Early Lesions (TBEL) Research Consortia is supported and funded by grants from the National Cancer Institute and the National Institutes of Health under the following award numbers:

Project Number:	Awardee Organization
U54CA274374	Fred Hutchinson Cancer Center
U54CA274375	Houston Methodist Research Institute
U54CA274370	Johns Hopkins University
U54CA274371	UT MD Anderson Cancer Center
U54CA274367	Vanderbilt University Medical Center