Biomarker Stratification for Immune Checkpoint Therapy Response
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Solution Overview
Problem
Current immune checkpoint therapies yield inconsistent responses across cancer types, with many subjects not benefiting despite treatment, and there is a lack of biomarkers to predict response or resistance to these therapies.
Innovation Solution
Identify mutations in SWI/SNF complex subunits, chromatin modifiers like KDM6A, and EGFR signaling components to predict response to immune checkpoint therapies by measuring biomarker amounts or activities in patient samples, comparing them to controls, and using these markers for patient stratification and treatment recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If immune checkpoint therapy is administered to all cancer patients, then some patients may benefit from durable responses and long-lasting survival benefit, but many patients do not exhibit therapeutic benefit or relapse, resulting in inconsistent treatment outcomes
Solution Approach 1:
The patent segments the cancer patient population into distinct groups based on biomarker profiles (mutational load, neoantigen presentation, transcriptomic signatures, microbiome features, immune cell infiltration, SWI/SNF pathway alterations). This segmentation allows identification of specific patient subsets who are most likely to respond to immune checkpoint therapy, thereby improving response consistency within each segment while maintaining broad applicability across different cancer types through multiple biomarker categories.
Solution Approach 2:
The patent performs preliminary biomarker assessment and patient stratification before administering immune checkpoint therapy. By evaluating multiple biomarkers in advance (mutational load, neoantigen presentation, transcriptomic signatures, microbiome features, immune cell infiltration, SWI/SNF pathway status), the system predicts which patients are most likely to benefit, allowing for pre-treatment optimization of therapy selection and improving overall treatment consistency.
2Measurement precision
If multiple biomarkers are evaluated to predict treatment response, then prediction accuracy improves, but the complexity of the diagnostic process increases
Solution Approach 1:
The patent develops a universal multi-biomarker assessment platform that simultaneously evaluates multiple predictive factors (mutational load, neoantigen presentation, transcriptomic signatures, microbiome features, immune cell infiltration, SWI/SNF pathway status) through integrated methodologies. This multi-functional approach achieves high prediction accuracy by considering multiple biological dimensions while streamlining the overall diagnostic process through a unified assessment framework that can be applied across different cancer types.
Solution Approach 2:
The patent merges multiple previously separate biomarker assessment methodologies into a single integrated predictive framework. By combining genomic analysis (mutational load, neoantigen presentation), transcriptomic profiling, microbiome characterization, immune phenotyping, and SWI/SNF pathway evaluation into a unified assessment system, the patent achieves comprehensive prediction accuracy while reducing the complexity of performing multiple separate tests.
Data Source
AI summary
The present invention is based on the identification of novel biomarkers predictive of responsiveness to anti-immune checkpoint therapies.