In Silico Derivation of HLA-Specific Alloreactivity Potential from Whole Exome Sequencing of Stem Cell Transplant Donors and Recipients: Understanding the Quantitative Immuno-biology of Allogeneic Transplantation
Max Jameson-Lee, Vishal Koparde, Phil Griffith, Allison F. Scalora,, Juliana K. Sampson, Haniya Khalid, Nihar U. Sheth, Michael Batalo, Myrna G., Serrano, Catherine H. Roberts, Michael L. Hess, Gregory A. Buck, Michael C., Neale, Masoud H. Manjili, Amir A. Toor

TL;DR
This study uses whole exome sequencing and bioinformatics to quantify the potential alloreactivity in HLA-matched stem cell transplant pairs, revealing extensive minor antigen variation that impacts graft-versus-host disease outcomes.
Contribution
It introduces a novel in silico method to assess HLA-specific alloreactivity potential based on sequencing data and peptide-HLA binding predictions.
Findings
High number of peptides predicted to bind HLA in each donor-recipient pair.
Unrelated donors tend to present more peptides than related donors.
Minor histocompatibility antigen variation is extensive even in HLA-matched pairs.
Abstract
Donor T cell mediated graft vs. host effects may result from the aggregate alloreactivity to minor histocompatibility antigens (mHA) presented by the HLA in each donor-recipient pair (DRP) undergoing stem cell transplantation (SCT). Whole exome sequencing has demonstrated extensive nucleotide sequence variation in HLA-matched DRP. Non-synonymous single nucleotide polymorphisms (nsSNPs) in the GVH direction (polymorphisms present in recipient and absent in donor) were identified in 4 HLA-matched related and 5 unrelated DRP. The nucleotide sequence flanking each SNP was obtained utilizing the ANNOVAR software package. All possible nonameric-peptides encoded by the non-synonymous SNP were then interrogated in-silico for their likelihood to be presented by the HLA class I molecules in individual DRP, using the Immune-Epitope Database (IEDB) SMM algorithm. The IEDB-SMM algorithm predicted a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
