A Visually Interpretable Histopathology-Based Immune Model Predicts T-effector Biology and Response to Immune checkpoint inhibition in Clear Cell Renal Cell Carcinoma Clinical Trial and Contemporary Real-World Datasets
Averi Perny, Vipul Nataraj Jarmale, Jay Jasti, Hua Zhong, Alana L. Christie, Jeffrey Miyata, Aleksandra W. Nielsen, Panayiotis Kontoyiannis, Dinesh Rakheja, Zora D. Modrusan, Mahrukh A. Huseni, Ward Kadel, James Brugarolas, Payal Kapur, Satwik Rajaram
The paper develops a deep learning model from H&E images to predict T-effector biology and ICI response in ccRCC, showing strong correlation with RNA-based scores and clinical outcomes.
bioRxiv · Sep 1, 2026 · PreprintBioinformatics