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Induction of Invasive Transitional Cell Bladder Carcinoma in Immune Intact Human MUC1 Transgenic Mice: A Model for Immunotherapy Development
Published on: October 30, 2013
Identification of a Muscle-Invasive Bladder Carcinoma Molecular Subtype of Poor Responders to Neoadjuvant
Lucía Trilla-Fuertes1, Jorge Pedregosa-Barbas2, Eugenia García-Fernández3
1Molecular Oncology Lab, INGEMM, La Paz University Hospital-IdiPAZ, Paseo de la Castellana 261, 28046 Madrid, Spain.
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 non-responders were analyzed using mass spectrometry. Samples were classified with sparse k-means and consensus clustering. Protein networks were built using probabilistic graphical models, grouped into functional nodes, and analyzed for activity differences. Gene set enrichment analysis was applied to identify resistance mechanisms, and results were validated using The Cancer Genome Atlas (TCGA) cohort. Proteomic analysis revealed two independent classifications in TURBT samples. The first (Layer1) divided tumors into three groups, including one NACT non-responder subtype not aligned with traditional luminal or basal classifications but characterized by high expression of targetable markers NECTIN4 and Her2. The second (Layer3) separated luminal-papillary tumors from luminal-infiltrated/luminal and basal tumors. While Layer3 groups did not differ in NACT response, they showed distinct disease-free survival outcomes. Importantly, complete response to NACT was linked to improved survival in luminal subgroups but not in basal tumors, suggesting subtype-specific prognostic implications. Finally, analysis of cystectomy samples identified unique mechanisms of resistance for each subgroup, suggesting tailored therapeutic approaches. Two classification systems were defined as follows: one identified a proteomics-based non-responder group with actionable targets, and the other linked tumor subtype to prognosis. Distinct resistance mechanisms suggest opportunities for subtype-specific therapies, supporting improved management and treatment development for MIBC patients.
Insights
This study identifies new ways to classify muscle-invasive bladder cancer (MIBC) based on proteomics. These classifications reveal actionable targets and distinct resistance mechanisms, paving the way for tailored neoadjuvant chemotherapy (NACT) treatments.
Area of Science:
- Oncology
- Proteomics
- Genomics
Background:
- Neoadjuvant chemotherapy (NACT) is standard for muscle-invasive bladder carcinoma (MIBC), but patient responses vary.
- Identifying biomarkers for NACT response is crucial for improving patient outcomes.
Purpose of the Study:
- To identify biomarkers and biological processes associated with NACT response in MIBC.
- To discover new classifications and resistance mechanisms for tailored therapies.
Main Methods:
- Mass spectrometry analysis of transurethral resection (TURBT) and cystectomy samples from MIBC patients.
- Sparse k-means, consensus clustering, and probabilistic graphical models for sample classification and network analysis.
- Gene set enrichment analysis and validation using The Cancer Genome Atlas (TCGA) cohort.
Main Results:
- Two proteomic classifications of TURBT samples were identified: Layer1 and Layer3.
- Layer1 revealed a novel NACT non-responder subtype with high expression of NECTIN4 and Her2.
- Layer3 separated tumors based on luminal and basal subtypes, showing distinct survival outcomes and subtype-specific prognostic implications for NACT response.
Conclusions:
- Proteomic profiling can define MIBC subtypes with distinct NACT responses and prognoses.
- Identification of actionable targets and resistance mechanisms supports the development of subtype-specific therapies for MIBC.
- Tailored therapeutic strategies based on these classifications can improve MIBC management and treatment outcomes.
