Deamidated Peptides for HLA-A*02 Immunotherapy Targeting
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Solution Overview
Problem
Current cancer treatments face challenges in effectively targeting tumor-specific antigens for immunotherapy, particularly in identifying and utilizing MHC class II peptides directly from tumors, which are crucial for stimulating anti-tumor immune responses without causing autoimmune reactions.
Innovation Solution
Development of novel peptide sequences and their variants derived from HLA class I molecules of human tumor cells that bind to MHC molecules, inducing T cell responses and serving as targets for antibodies and soluble T cell receptors, with a focus on deamidated peptides that exploit aberrant glycosylation patterns in cancer cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If deamidated peptides are used to exploit aberrant glycosylation patterns in cancer cells, then tumor-specific targeting is improved, but specificity and avoidance of autoimmune reactions become more challenging
Solution Approach 1:
The patent applies local quality by targeting specific deamidated peptide sequences that are locally present on tumor cells due to aberrant glycosylation patterns. The antibodies are designed to recognize specific local modifications (deamidation at particular positions) rather than general tumor markers, enabling precise tumor cell identification while sparing normal tissues that lack these specific modifications.
Solution Approach 2:
The patent exploits parameter changes by focusing on post-translational modifications (deamidation) that alter the chemical properties of peptide sequences. These modifications change the charge and structure of specific amino acid residues, creating unique epitopes that can be targeted by antibodies. The deamidation process converts asparagine to aspartic acid, creating a distinct molecular signature on tumor cells that differs from normal cells.
2Reliability
If MHC class II peptides are identified and utilized from tumors, then anti-tumor immune response is stimulated, but the complexity of identification and isolation increases
Solution Approach 1:
The patent applies preliminary action by using in silico methods to predict and identify potential MHC class II binding peptides from tumor-associated antigens before experimental validation. Computational algorithms are used to screen large datasets of tumor protein sequences, predict which peptides will bind to MHC class II molecules with high affinity, and prioritize candidates for further experimental testing. This preliminary computational filtering significantly reduces the complexity and resource requirements of the subsequent experimental isolation and validation processes.
Data Source
AI summary
The invention relates to a peptide comprising an amino acid sequence selected from the group consisting of (i) SEQ ID NO: 1 to SEQ ID NO: 102, and (ii) a variant sequence thereof which maintains capacity to bind to MHC molecule(s) and/or induce T cells cross-reacting with said variant peptide, or a pharmaceutically acceptable salt thereof.