KRASi

KRASi profiles temporal proteomic responses to KRAS G12C inhibition to identify adaptive mechanisms and inform drug-combination strategies.

Key Features:

• Comprehensive Proteomic Profiling: Quantifies 10,805 proteins across pancreatic and lung cancer models in two-dimensional (2D) and three-dimensional (3D) cellular environments.
• Mass Spectrometry-Based Quantitative Temporal Proteomics: Applies mass spectrometry-based quantitative temporal proteomics to capture dynamic changes in protein abundance over time.
• Bioinformatics Workflow: Employs advanced bioinformatics workflows to analyze complex proteomic datasets and detect patterns of adaptation.
• Identification of Adaptive Pathways: Identifies acute and long-term mechanisms of adaptation in KRAS G12C-driven tumors from temporal proteomic data.
• Prediction of Drug Combinations: Predicts drug combinations to overcome resistance to KRAS G12C inhibitors, highlighting combinations with PI3K, HSP90, CDK4/6, and SHP2 inhibitors that can convert cytostatic into cytotoxic responses.

Scientific Applications:

• Resistance Mechanism Elucidation: Dissects proteomic adaptations underlying resistance to KRAS G12C-targeted therapies.
• Combination Therapy Design: Informs selection of combination treatments to enhance efficacy and durability against KRAS G12C-driven cancers.

Methodology:

Mass spectrometry-based quantitative temporal proteomics and advanced bioinformatics workflows.