TCR Antigen Identification via Combinatorial Barcoding
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Solution Overview
Problem
Current methods are inefficient in identifying the specific antigen recognized by T-cell receptors, particularly for 'orphan' TCRs, which hinders the development of cancer immunotherapy and autoimmunity treatments, as they require large cell numbers and empirical testing.
Innovation Solution
A method involving combinatorial barcoding of T-cells and tumor neoantigens, where TCRα and TCRβ genes are barcoded, and their cognate antigens identified by sequencing and forming barcoded MHC-neoantigen complexes to match with TCRs, allowing for the identification of cognate antigens through shared cell-specific barcodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If mass spectrometry is used for antigen isolation, then unbiased antigen identification is achieved, but large cell numbers (10^7) are required
Solution Approach 1:
The patent segments the antigen identification process into multiple steps: T-cell isolation, TCR sequencing, neoantigen prediction, and matching. This segmentation allows the use of fewer cells (10^3-10^6) by focusing on specific T-cell populations and their receptors rather than requiring large numbers for bulk analysis.
Solution Approach 2:
The patent introduces TCR sequencing and bioinformatic matching as intermediary steps between T-cell isolation and antigen identification. These intermediaries enable the identification of antigen specificity from limited T-cell samples by characterizing the TCR repertoire and matching it with predicted neoantigens.
2Measurement precision
If pHLA multimers are used to query T-cell specificities, then established T-cell specificities can be identified, but the method is limited to known antigens and requires empirical testing
Solution Approach 1:
The patent performs preliminary bioinformatic analysis to predict neoantigens from tumor sequencing data before experimental validation. This preliminary action identifies candidate antigens in silico, reducing the need for extensive empirical testing with pHLA multimers and enabling the study of previously unknown tumor antigens.
Solution Approach 2:
The patent replaces the mechanical/physical approach of pHLA multimer binding assays with a bioinformatic approach: sequencing TCRs, predicting neoantigens from tumor genomes, and using computational algorithms to match TCRs with their cognate antigens. This substitution eliminates the need for empirical testing with known antigens.
3Measurement precision
If combinatorial barcoding is implemented, then TCR-antigen matching precision is improved, but the process complexity increases
Solution Approach 1:
The patent uses combinatorial barcoding to create molecular copies of TCR sequences and neoantigen sequences with unique identifier tags. These barcoded copies allow high-throughput tracking and matching of TCR-antigen pairs through sequencing, achieving precise matching while automating the process to manage the complexity.
Data Source
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AI summary
The invention is a method of identifying a cognate antigen for a T-cell receptor using neoantigens from a patient's tumor cells combined with the patient's T-cells and using cell sorting, genome sequencing, expressing TCR genes, presenting tumor neoantigens on MHC complex and uniquely barcoding the T-cells where TCR recognition occurs to tag all components of the TCR recognition complex.