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Updated: Mar 14, 2026

Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors

Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors

Published on: March 29, 2019

Multiplatform Biomarker Discovery for Bladder Cancer Recurrence Diagnosis.

Marine De Paoli¹, Selma Gogalic², Ursula Sauer²

¹AXO Science SAS, 34 rue du Mail, 69004 Lyon, France.

Disease Markers

|September 24, 2016

Summary

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A new multiparameter panel combining urinary biomarkers and clinical data accurately detects bladder cancer recurrence. This noninvasive tool offers a promising alternative for lifelong bladder cancer surveillance.

Area of Science:

Urology
Oncology
Biomarker Discovery

Background:

Nonmuscle invasive bladder cancer (BCa) has a high recurrence rate, necessitating lifelong surveillance.
Current surveillance methods like cystoscopy are invasive.
Urinary biomarkers show potential for noninvasive BCa recurrence detection, but single markers lack sufficient accuracy.

Purpose of the Study:

To develop and validate a multiparameter panel for diagnosing recurrent bladder cancer.
To combine urinary biomarkers and clinical parameters for improved diagnostic accuracy.
To establish a noninvasive tool for BCa surveillance.

Main Methods:

Candidate urinary biomarkers were quantified using a multiplatform strategy (multiplexed microarray and ELISA).
Urine samples from BCa patients with and without recurrence were analyzed.

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Last Updated: Mar 14, 2026

Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors

Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors

Published on: March 29, 2019

A Murine Orthotopic Bladder Tumor Model and Tumor Detection System

A Murine Orthotopic Bladder Tumor Model and Tumor Detection System

Published on: January 12, 2017

An Orthotopic Bladder Cancer Model for Gene Delivery Studies

An Orthotopic Bladder Cancer Model for Gene Delivery Studies

Published on: December 1, 2013

Multivariate statistical analysis integrated biomarker data with clinical parameters (past recurrences, BCG therapies, stage at diagnosis).

Main Results:

The optimal panel achieved an AUC of 0.91, outperforming individual markers.
The panel includes six biomarkers (cadherin-1, IL-8, ErbB2, IL-6, EN2, VEGF-A) and three clinical parameters.
This combination demonstrated superior accuracy in diagnosing BCa recurrence.

Conclusions:

A multiparameter panel comprising urinary biomarkers and clinical data can serve as an effective noninvasive tool for BCa surveillance.
This approach may significantly impact the clinical management of bladder cancer.
Further validation in an independent cohort is recommended.