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A Deep Learning-Generated Mixed Tumor-Stroma Ratio for Prognostic Stratification and Multi-omics Profiling in Bladder

Yifeng He1, Jinbo Xie2, Suquan Zhong3

  • 1Department of Urology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou 510317, China.

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A deep learning model accurately quantifies the tumor-stroma ratio (MTSR) from routine slides, improving bladder cancer (BCa) risk stratification. This MTSR, linked to molecular pathways and predictable via MRI radiomics, aids noninvasive precision management.

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Area of Science:

  • Oncology
  • Computational Pathology
  • Radiomics

Background:

  • Quantifying tumor-stroma architecture on H&E slides can improve bladder cancer (BCa) risk stratification.
  • Developing computational methods for this quantification is crucial for clinical application.

Purpose of the Study:

  • To develop a deep learning model for segmenting whole-slide images and computing the mixed tumor-stroma ratio (MTSR).
  • To evaluate the prognostic value of MTSR in multicenter cohorts.
  • To explore molecular mechanisms underlying MTSR and develop a noninvasive estimation method using multiparametric MRI (mpMRI) radiomics.

Main Methods:

  • A ResNet50 convolutional neural network was trained on The Cancer Genome Atlas (TCGA) BCa slides for segmentation.
  • MTSR was computed, and its prognostic value assessed using Cox regression, Kaplan-Meier analysis, and meta-analysis.
  • Multi-omics (bulk and single-cell RNA sequencing) and mpMRI radiomics analyses were performed.

Main Results:

  • The CNN achieved >90% accuracy for segmentation.
  • A nomogram incorporating MTSR and N stage improved risk prediction.
  • High-MTSR tumors showed increased macrophage infiltration and enrichment of ECM remodeling and TGF-β/WNT signaling pathways.
  • Single-cell analysis identified an ITGB8-high urothelial subtype with distinct WNT activity.
  • The mpMRI radiomics model predicted MTSR status with ~70% accuracy.

Conclusions:

  • Deep learning-derived MTSR is reproducible and prognostic in BCa.
  • MTSR is mechanistically linked to an ITGB8-enriched stromal-oncogenic pathway.
  • mpMRI radiomics enables noninvasive MTSR estimation for integrative BCa risk stratification.