Artificial Intelligence Analysis of Histopathology Slides to Develop Biomarkers of Response to Immunotherapy in Kidney Cancer
Abstract
Immunotherapy has emerged as a promising new therapy for kidney cancer with durable clinical responses in a subset of the patients. However, discovery of biomarkers that predict patient response to immunotherapy has thus far been unsuccessful. Diverse sets of biomarkers have been proposed (e.g., PDL1 immunohistochemistry, tumor mutation burden, gene expression signatures), but have failed to validate in clinical studies. There is an urgent need to identify predictive biomarkers for selecting kidney cancer patients most likely to respond to immunotherapy. Histology slides, which are utilized primarily for cancer diagnosis, have been shown to contain a wealth of information using artificial intelligence (AI). While recent advances in AI can accurately predict kidney cancer subtypes, to the best of our knowledge, models to predict response to therapy have not been explored.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2023
- Accession Number
- AD1225070
Entities
People
- Anupama Reddy