Proteogenomics of clear cell renal cell carcinoma response to tyrosine kinase inhibitor

Area of Science:

• Oncology
• Genomics
• Proteomics

Background:

• Sunitinib is a tyrosine kinase inhibitor (TKI) used for advanced renal cell carcinoma (ccRCC).
• Clinical outcomes with Sunitinib therapy show significant variability among patients.
• Understanding the molecular basis of this variability is crucial for optimizing treatment.

Purpose of the Study:

• To investigate the molecular drivers of differential clinical outcomes in ccRCC patients treated with Sunitinib.
• To identify biomarkers predictive of Sunitinib response and resistance.
• To explore the role of the tumor microenvironment in ccRCC response to TKI therapy.

Main Methods:

• Proteogenomic profiling of 115 ccRCC tumors from patients undergoing Sunitinib treatment.
• Proteomic and phosphoproteomic analysis to assess signaling pathway activation.
• Immune landscape characterization of the tumor microenvironment.
• Development of a multi-omics classifier for predicting treatment response.

Main Results:

• Chromosome 7q gain-induced mTOR signaling activation is associated with poor Sunitinib response.
• Aristolochic acid signature and VHL mutation synergistically enhance glycolysis, correlating with better prognosis.
• mTOR signaling activation is implicated in non-response to Sunitinib.
• Diverse tumor microenvironment subsets were identified in ccRCC.
• A multi-omics classifier achieved high accuracy (AUROC 0.98) in distinguishing responders from non-responders.

Conclusions:

• Molecular characteristics of ccRCC, including genomic alterations and metabolic profiles, significantly influence Sunitinib response.
• Identifying specific molecular signatures can predict patient outcomes and guide personalized TKI therapy selection.
• The developed multi-omics classifier offers a promising tool for stratifying ccRCC patients for Sunitinib treatment.