Neoantigen immunogenicity prediction is a highly challenging problem in the development of personalised medicines. Low reactivity rates in called neoantigens result in a difficult prediction scenario with limited training datasets. Here we describe ImmugenX, a modular protein language modelling approach to immunogenicity prediction for CD8+ reactive epitopes.
View Article and Find Full Text PDFDisruption of the class I human leukocyte antigen (HLA) molecules has important implications for immune evasion and tumor evolution. We developed major histocompatibility complex loss of heterozygosity (LOH), allele-specific mutation and measurement of expression and repression (MHC Hammer). We identified extensive variability in HLA allelic expression and pervasive HLA alternative splicing in normal lung and breast tissue.
View Article and Find Full Text PDFSchoenfeld and colleagues report, in this issue, a measurable objective response rate in 6/28 (21.4%) of patients with advanced non-small cell lung cancer treated with lifileucel, a cell therapy product based on autologous tumor-infiltrating lymphocytes (TIL). Extending solid evidence in advanced melanoma that led to FDA approval of lifileucel, this new evidence bodes well for treating patients with other common tumor histologies, justifying important efforts by a large number of academic and biotechnology companies engaged in improving the TIL process.
View Article and Find Full Text PDFThe growing scale and dimensionality of multiplexed imaging require reproducible and comprehensive yet user-friendly computational pipelines. TRACERx-PHLEX performs deep learning-based cell segmentation (deep-imcyto), automated cell-type annotation (TYPEx) and interpretable spatial analysis (Spatial-PHLEX) as three independent but interoperable modules. PHLEX generates single-cell identities, cell densities within tissue compartments, marker positivity calls and spatial metrics such as cellular barrier scores, along with summary graphs and spatial visualisations.
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