Building accurate prediction models and identifying predictive biomarkers for treatment response in Muscle-Invasive Bladder Cancer (MIBC) are essential for improving patient survival but remain challenging due to tumor heterogeneity, despite numerous related studies. To address this unmet need, we developed an interpretable Graph-based Multimodal Late Fusion (GMLF) deep learning framework. Integrating histopathology and cell type data from standard H&E images with gene expression profiles derived from RNA sequencing from the SWOG S1314-COXEN clinical trial (ClinicalTrials.gov NCT02177695 2014-06-25), GMLF uncovered new histopathological, cellular, and molecular determinants of response to neoadjuvant chemotherapy. Specifically, we identified key gene signatures that drive the predictive power of our model, including alterations in TP63, CCL5, and DCN. Our discovery can optimize treatment strategies for patients with MIBC, e.g., improving clinical outcomes, avoiding unnecessary treatment, and ultimately, bladder preservation. Additionally, our approach could be used to uncover predictors for other cancers.
NPJ digital medicine. 2025 Mar 22*** epublish ***
Zilong Bai, Mohamed Osman, Matthew Brendel, Catherine M Tangen, Thomas W Flaig, Ian M Thompson, Melissa Plets, M Scott Lucia, Dan Theodorescu, Daniel Gustafson, Siamak Daneshmand, Joshua J Meeks, Woonyoung Choi, Colin P N Dinney, Olivier Elemento, Seth P Lerner, David J McConkey, Bishoy M Faltas, Fei Wang
Weill Cornell Medicine, New York, NY, USA., SWOG Statistics and Data Management Center, Seattle, WA, USA., University of Colorado Comprehensive Cancer Center, Aurora, CO, USA., Children's Hospital of San Antonio, San Antonio, TX, USA., Cedars-Sinai Cancer, Los Angeles, CA, USA., USC Institute of Urology, USC/Norris Comprehensive Cancer Center, Los Angeles, CA, USA., Northwestern University, Chicago, IL, USA., Johns Hopkins University, Baltimore, MD, USA., MD Anderson Cancer Center, Houston, TX, USA., Baylor College of Medicine, Houston, TX, USA., Weill Cornell Medicine, New York, NY, USA. ., Weill Cornell Medicine, New York, NY, USA. .