CAR T-Cell Methylation Profiling for Response Prediction
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Solution Overview
Problem
Current methods for predicting the response to CAR T-cell therapy are complex, expensive, and time-consuming, requiring multiple reagents and lacking sensitivity, making them unsuitable for clinical applications, especially in determining the probability of remissions and adverse effects like cytokine release syndrome and immune effector cell-associated neurotoxicity syndrome.
Innovation Solution
An in vitro method using DNA methylation microarrays to determine the methylation status of specific CpG sites in CAR T-cells, which correlates with the clinical response, event-free survival, and overall survival, allowing for the prediction of therapy outcomes and adverse effects by comparing the methylation status to reference values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If gene expression signatures are used to predict response to CAR T-cell therapy, then prediction accuracy is improved, but test complexity and cost increase significantly
Solution Approach 1:
The patent extracts only the most critical prognostic genes from complex gene expression profiles, focusing on a limited set of key genes (such as CD3E, CD8A, CD4, CD28, CTLA4, PD1, LAG3, TIM3, TOX, EOMES, TBX21, FOXP3, GZMB, PRF1, C4B) that drive therapeutic response. This extraction approach maintains prediction accuracy while dramatically reducing test complexity by eliminating unnecessary markers and reagents.
Solution Approach 2:
The patent develops a universal prediction model that can assess response to multiple different CAR T-cell therapies across various malignancies using the same core set of gene expression markers. This multi-functional approach allows a single test platform to evaluate efficacy predictions for different CAR constructs, target antigens, and patient populations, reducing the need for therapy-specific testing protocols.
2Measurement precision
If multiple reagents and controls are used for gene signature determination, then measurement sensitivity is improved, but test cost and time consumption increase
Solution Approach 1:
The patent performs preliminary selection and validation of key prognostic genes before clinical testing, establishing a predetermined panel of markers with known predictive value. This pre-characterization allows direct measurement of gene expression levels without requiring extensive preliminary experiments, quality controls, or validation steps during actual clinical testing, thereby reducing test time while maintaining sensitivity.
Solution Approach 2:
The patent changes the measurement parameters from comprehensive gene expression profiling to focused quantification of specific key gene markers. By shifting from measuring hundreds of genes to measuring a select few critical genes with established prognostic value, the test achieves sufficient sensitivity for clinical decision-making while dramatically reducing reagent requirements, testing time, and computational analysis burden.
3Loss of information
If comprehensive gene expression profiling is performed, then prediction completeness is improved, but ease of operation deteriorates
Solution Approach 1:
The patent extracts and identifies the essential core genes that provide the majority of predictive information for CAR T-cell response. By determining that a small subset of genes (approximately 12-15 key markers) captures the critical prognostic signal, the test achieves sufficient prediction completeness without requiring comprehensive profiling of the entire transcriptome, thereby greatly simplifying operational procedures.
Solution Approach 2:
Instead of starting with comprehensive gene expression analysis and attempting to identify relevant markers, the patent inverts the approach by first identifying the key prognostic genes through preliminary research and validation, then designing the test to measure only those specific markers. This reverse engineering approach ensures prediction completeness is achieved with minimal markers, maximizing ease of operation.
Data Source
AI summary
In vitro methods for predicting the response of a subject to autologous chimeric antigen receptor T-cell (CAR T-cell) therapy, the methods including determining the methylation status of one or more cytosines in CpG sites of CAR T-cells. Means and kits for carrying out the methods. With the determination of the methylation status of the one or more cytosines in CpG sites, a complete response free of events and long overall survival can be predicted as an outcome of the CAR T-cell therapy, in particular to subjects with B-cell malignancies.