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Biology subjects

Sneddon, S.

Publications and source records attributed to Sneddon, S..

2 recordsLinked to original sources

Comprehensive Functional Self-Antigen Screening to Assess Cross-Reactivity in a Promiscuous Engineered T-cell Receptor

T cell receptor therapeutics are an emerging modality of biologic and cell-based medicines with the unique ability to target intracellular antigens and finely discriminate between healthy and infected or mutated cells. An obstacle to the development of new T cell receptor therapeutics is the difficulty in engineering these proteins for enhanced therapeutic efficacy while avoiding introduction of unexpected off-target autoreactivity. In this study, we apply a functional high-throughput screening assay, Tope-seq, to detecting cross-reactive epitopes in libraries of >5 x 105 unique peptide-coding sequences. We retrospectively analyze an affinity-enhanced engineered T cell receptor, which previously failed clinical trials due to severe off-target toxicity caused by epitope cross-reactivity, by comprehensive functional testing against all genome-coded self-antigens. Using the Tope-seq methodology, we were able to identify the epitope mediating off-target reactivity at a significance threshold of p < 0.01 in first-pass bulk screening. We also identified other potential cross-reactive epitopes of the engineered TCR of-interest, suggesting that the need for assessing promiscuity in TCR based therapeutics is larger than previously appreciated.

immunology↗

Interactome comparison of human embryonic stem cell lines with the inner cell mass and trophectoderm

Human embryonic stem cells (hESCs) derived from the pluripotent Inner cell mass (ICM) of the blastocyst are fundamental tools for understanding human development, yet are not identical to their tissue of origin. To investigate this divergence we compared the transcriptomes of genetically paired ICM and trophectoderm (TE) samples with three hESC lines: MAN1, HUES3 and HUES7 at similar passage. We generated inferred interactome networks using transcriptomic data unique to the ICM or TE, and defined a hierarchy of modules (highly connected regions with shared function). We compared network properties and the modular hierarchy and show that the three hESCs had limited overlap with ICM specific transcriptome (6%-12%). However this overlap was enriched for network properties related to transcriptional activity in ICM (p=0.016); greatest in MAN1 compared to HUES3 (p=0.048) or HUES7 (p=0.012). The hierarchy of modules in the ICM interactome contained a greater proportion of MAN1 specific gene expression (46%) compared to HUES3 (28%) and HUES7 (25%) (p=9.0x10-4). These findings show that traditional methods based on transcriptome overlap are not sufficient to identify divergence of hESCs from ICM. Our approach also provides a valuable approach to the quantification of differences between hESC lines. And Manchester Academic Health Sciences Centre

developmental biology↗