Identification of a Muscle-Invasive Bladder Carcinoma Molecular Subtype of Poor Responders to Neoadjuvant Chemotherapy and High Expression of Targetable Biomarkers - Abstract

Sep 30, 2026

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Neoadjuvant chemotherapy (NACT) is standard for muscle-invasive bladder carcinoma (MIBC) but response varies widely. This study identifies biomarkers and biological processes linked to NACT response using mass spectrometry on 58 TURBT and 30 cystectomy samples from NACT non-responders. Sparse k-means and consensus clustering define proteomic classifications, with probabilistic graphical protein networks and functional node activity testing. Gene set enrichment analysis reveals resistance mechanisms, validated in TCGA.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages17

Reading Time43 min

AccessFree to download

Introduction

Study rationale and standard NACT context

Methods

Sample collection and proteomic profiling

Clustering and protein network analysis

Gene set enrichment and TCGA validation

Results

TURBT-based proteomic classification layers

Survival and response associations

Cystectomy subgroup resistance mechanisms

Conclusions

Targetable biomarker implications for tailored therapy

Article Identification of a Muscle-Invasive Bladder Carcinoma Molecular Subtype of Poor Responders to Neoadjuvant Chemotherapy and High Expression of Targetable Biomarkers Lucía Trilla-Fuertes 1, Jorge Pedregosa-Barbas 2, Eugenia García-Fernández 3, Francisco Zambrana 4, Imanol Martínez-Salas 5, Pablo Gajate 6, Fernando Becerril-Gómez 1, Pedro Lalanda-Delgado 1, Antje Dittmann 7, Rocío López-Vacas 1, Laura Kunz 7, Gustavo Rubio 4, Sandra Nieto-Torrero 8, Ana Pertejo 2, Pilar González-Peramato 3, Juan Ángel Fresno Vara 1,9, Angelo Gámez-Pozo 1,9, *,† and Álvaro Pinto-Marín 2, *,† Academic Editor: Ana Cristina Gonçalves Received: 18 November 2025 Revised: 19 December 2025 Accepted: 31 December 2025 Published: 2 January 2026 Copyright: © 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. 1 Molecular Oncology Lab, INGEMM, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, 28046 Madrid, Spain; [lucia.trilla@salud.madrid.org](lucia.trilla@salud.madrid.org) (L.T.-F.); [fernando.becerril@salud.madrid.org](fernando.becerril@salud.madrid.org) (F.B.-G.); [plalandelg@gmail.com](plalandelg@gmail.com) (P.L.-D.); [rlvacas@salud.madrid.org](rlvacas@salud.madrid.org) (R.L.-V.); [juanangel.fresno@salud.madrid.org](juanangel.fresno@salud.madrid.org) (J.Á .F.V.) 2 Medical Oncology Service, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, 28046 Madrid, Spain; [jorge.pedregosa@salud.madrid.org](jorge.pedregosa@salud.madrid.org) (J.P.-B.); [ana.pertejo@salud.madrid.org](ana.pertejo@salud.madrid.org) (A.P.) 3 Department of Pathology, La Paz University Hospital-IdiPAZ, UAM, 28046 Madrid, Spain; [euge17@yahoo.com](euge17@yahoo.com) (E.G.-F.); [mpilar.gonzalezperamato@salud.madrid.org](mpilar.gonzalezperamato@salud.madrid.org) (P.G.-P.) 4 Medical Oncology Department, Infanta Sofía University Hospital, 28702 Madrid, Spain; [francisco.zambrana@salud.madrid.org](francisco.zambrana@salud.madrid.org) (F.Z.); [gustavo.rubio@slaud.madrid.org](gustavo.rubio@slaud.madrid.org) (G.R.) 5 Medical Oncology Department, IIS-FJD, University Hospital Fundación Jiménez Díaz, 28040 Madrid, Spain; [imanol.martinez@quironsalud.es](imanol.martinez@quironsalud.es) 6 Medical Oncology Department, Hospital Universitario Ramón y Cajal, 28034 Madrid, Spain; [pgajate@oncologiahrc.com](pgajate@oncologiahrc.com) 7 Functional Genomics Center Zurich, University of Zurich/ETH Zurich, 8057 Zurich, Switzerland; [antje.dittmann@fgcz.uzh.ch](antje.dittmann@fgcz.uzh.ch) (A.D.); [laura.kunz@fgcz.uzh.ch](laura.kunz@fgcz.uzh.ch) (L.K.) 8 IdiPAZ Biobank, La Paz University Hospital-IdiPAZ, 28046 Madrid, Spain; [biobanco.hulp@salud.madrid.org](biobanco.hulp@salud.madrid.org) [9](9 Biomedical Research Networking Center on Oncology-CIBERONC)[ Biomedical Research Networking Center on Oncology-CIBERONC](9 Biomedical Research Networking Center on Oncology-CIBERONC), [ISCIII](ISCIII), [28029 Madrid](28029 Madrid), [Spain](Spain) * Correspondence: [angelo.gamez@salud.madrid.org](angelo.gamez@salud.madrid.org) (A.G.-P.); [alvaro.pinto@salud.madrid.org](alvaro.pinto@salud.madrid.org) (Á .P.-M.); Tel.: +34-917-277-263 (A.G.-P.); +34-912-071-238 (Á.P.-M.)† These authors contributed equally to this work. Abstract Neoadjuvant chemotherapy (NACT) is the standard treatment for muscle-invasive bladder carcinoma (MIBC), but its efficacy varies significantly among patients. The aim of this study is the identification of biomarkers and biological processes related to the response to neoadjuvant chemotherapy (NACT) in muscle-invasive bladder carcinoma (MIBC). Fifty-eight transurethral resection (TURBT) samples and thirty cystectomy samples from NACT nonresponders were analyzed using mass spectrometry. Samples were classified with sparse k-means and consensus clustering. Protein networks were built using pr

FAQs

What is the study aiming to identify in muscle-invasive bladder carcinoma?

The study aims to identify biomarkers and biological processes associated with response to neoadjuvant chemotherapy in muscle-invasive bladder carcinoma.

How were samples analyzed to study NACT response?

Fifty-eight TURBT and thirty cystectomy samples from NACT non-responders were analyzed using mass spectrometry, followed by clustering and protein network construction.

What key findings connect proteomic subtypes to outcomes?

The research defines proteomics-based non-responder classifications with actionable targets and shows subtype-specific implications for response and disease-free survival, including improved survival in luminal subgroups with complete response.

Sep 30, 2026

Uploaded by McQueen