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Updated: Jul 11, 2025
The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
Published on: January 22, 2013
Artificial Intelligence in Pathomics and Genomics of Renal Cell Carcinoma
J Everett Knudsen1, Joseph M Rich1, Runzhuo Ma1
1Catherine & Joseph Aresty Department of Urology, USC Institute of Urology, Center for Robotic Simulation & Education, University of Southern California, Los Angeles, CA, USA.
Abstract:
The integration of artificial intelligence (AI) with histopathology images and gene expression patterns has led to the emergence of the dynamic fields of pathomics and genomics. These fields have revolutionized renal cell carcinoma (RCC) diagnosis and subtyping and improved survival prediction models. Machine learning has identified unique gene patterns across RCC subtypes and grades, providing insights into RCC origins and potential treatments, as targeted therapies. The combination of pathomics and genomics using AI opens new avenues in RCC research, promising future breakthroughs and innovations that patients and physicians can anticipate.
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