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IMS 2026 | Overcoming challenges in TCR mapping for personalized immunotherapy in multiple myeloma
David Avigan, MD, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, discusses the technical challenges of translating antigen receptor (TCR) mapping into clinical practice. He highlights limitations in current HLA-restricted approaches and peptide selection, while noting the potential for artificial intelligence (AI) and improved databases to identify reliable antigen pairs and help guide treatment decisions. This interview took place at the 23rd International Myeloma Society (IMS) Annual Meeting in Glasgow, UK.
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Transcript
So there are very big challenges and many of them right now are technical. Right now the types of technology we use to link peptides to TCRs are mostly based on dextramers which are restricted by HLA and of course the peptides that you ultimately test and you’re limited in their number may not be the full representation or may not have really the jewel that you need to go after. And so there is the possibility of missing parts of the story through this kind of approach...
So there are very big challenges and many of them right now are technical. Right now the types of technology we use to link peptides to TCRs are mostly based on dextramers which are restricted by HLA and of course the peptides that you ultimately test and you’re limited in their number may not be the full representation or may not have really the jewel that you need to go after. And so there is the possibility of missing parts of the story through this kind of approach. That will change over time. And one can imagine even with the use of devices like AI to help better pair based on structure or based on what we know already in the database to actually create TCR peptide pairs that are reliable. Right now, that kind of databases are still very much in evolution. And then we could really immediately look at a patient’s T cells and know exactly what they’re targeting and what we want to accentuate.
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