Biology subjects

Heather, J. M.

Publications and source records attributed to Heather, J. M..

4 recordsLinked to original sources

bioRxiv2024

The differential immunological impact of photon vs proton radiation therapy in high grade lymphopenia

Radiation therapy has long been a cornerstone of cancer treatment. More recently, immune checkpoint blockade has also been applied across a variety of cancers, often leading to remarkable response rates. However, photon-based radiotherapy - which accounts for the vast majority - is also known to frequently induce profound lymphopenia, which might limit the efficacy of immune system based combinations. Proton beam therapy is known to produce a less drastic lymphopenia, which raises the possibility of greater synergy with immunotherapy. In this study we aimed to explore the exact nature of the differential impact of the two radiation modalities upon the immune system. We used multiparametric flow cytometry and deep sequencing of rearranged TCRb loci to investigate a cohort of 20 patients with gastrointestinal tumors who received either therapy. Proton-treated patients remained relatively stable throughout treatment for most metrics considered, whereas those who received photons saw a profound depletion in naive T cells, increase in effector/memory populations, and loss of TCR diversity. The repertoires of photon-treated patients underwent oligoclonal expansion after their lymphocyte count nadirs, particularly of CD8+ Temra cells, driving this reduction in diversity. Across the entire cohort, this reduction in post-nadir diversity inversely correlated with the overall survival time of those patients who died. This raises the possibility that increased adoption of proton-based or other lymphocyte sparing radiotherapy regimes may lead to better survival in cancer patients.

immunology↗

bioRxiv2023

AIRR-C Human IG Reference Sets: curated sets of immunoglobulin heavy and light chain germline genes

Analysis of an individuals immunoglobulin (IG) gene repertoire requires the use of high-quality germline gene Reference Sets. The Adaptive Immune Receptor Repertoire-Community (AIRR-C) Reference Sets have been developed to include only human IG heavy and light chain alleles that have been confirmed by evidence from multiple high-quality sources. By including only those alleles with a high level of support, including some new sequences that currently lack official names, AIRR-seq analysis will have greater accuracy and studies of the evolution of immunoglobulin genes, their allelic variants and the expressed immune repertoire will be facilitated. Although containing less than half the previously recognised IG alleles (e.g. just 198 IGHV sequences), the Reference Sets eliminated erroneous calls and provided excellent coverage when tested on a set of repertoires from 99 individuals comprising over 4 million V(D)J rearrangements. To improve AIRR-seq analysis, some alleles have been extended to deal with short 3 or 5 truncations that can lead them to be overlooked by alignment utilities. To avoid other challenges for analysis programs, exact paralogs (e.g. IGHV1-69*01 and IGHV1-69D*01) are only represented once in each set, though alternative sequence names are noted in accompanying metadata. The Reference Sets also include novel alleles: 8 IGHV alleles, 2 IGKV alleles and 5 IGLV alleles. The version-tracked AIRR-C Reference Sets are freely available at the OGRDB website (https://ogrdb.airr-community.org/germline_sets/Human) and will be regularly updated to include newly-observed and previously-reported sequences that can be confirmed by new high-quality data.

genomics↗

bioRxiv2021

Stitchr: stitching coding TCR nucleotide sequences from V/J/CDR3 information

The study and manipulation of T cell receptors (TCRs) is central to multiple fields across basic and translational immunology research. Produced by V(D)J recombination, TCRs are often only recorded in the literature and data repositories as a combination of their V and J gene symbols, plus their hypervariable CDR3 amino acid sequence. However, numerous applications require full-length coding nucleotide sequences. Here we present Stitchr, a software tool developed to specifically address this limitation. Given minimal V/J/CDR3 information, Stitchr produces complete coding sequences representing a fully spliced TCR cDNA. Due to its modular design, Stitchr can be used for TCR engineering using either published germline or novel/modified variable and constant region sequences. Sequences produced by Stitchr were validated by synthesizing and transducing TCR sequences into Jurkat cells, recapitulating the expected antigen specificity of the parental TCR. Using a companion script, Thimble, we demonstrate that Stitchr can process a million TCRs in under ten minutes using a standard desktop personal computer. By systemizing the production and modification of TCR sequences, we propose that Stitchr will increase the speed, repeatability, and reproducibility of TCR research. Stitchr is available on GitHub.

immunology↗

bioRxiv2019

The naive T-cell receptor repertoire has an extremely broad distribution of clone sizes

The human naive T-cell receptor (TCR) repertoire is extremely diverse and accurately estimating its distribution is challenging. We address this challenge by combining a quantitative sequencing protocol of TCRA and TCRB sequences with computational modelling. We observed the vast majority of TCR chains only once in our samples, confirming the enormous diversity of the naive repertoire. However, a substantial number of sequences were observed multiple times within samples, and we demonstrated that this is due to expression by many cells in the naive pool. We reason that and {beta} chains are frequently observed due to a combination of selective processes and summation over multiple clones expressing these chains. We test the contribution of both mechanisms by predicting samples from phenomenological and mechanistically modelled repertoire distributions. By comparing these with sequencing data, we show that frequently observed chains are likely to be derived from multiple clones. Still, a neutral model of T-cell homeostasis cannot account for the observed distributions. We conclude that the data are only compatible with distributions of many small clones in combination with a sufficient number of very large naive T-cell clones, the latter most likely as a result of peripheral selection.

immunology↗