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Mortimer, P.

Publications and source records attributed to Mortimer, P..

2 recordsLinked to original sources

CISH, a novel intracellular immune checkpoint, in comparison and combination to existing and emerging cancer immune checkpoints

Over the past decade, Immuno-Oncology has largely focused on blocking inhibitory surface receptors like PD-1 to enhance T cell anti-tumor activity. However, intracellular immune checkpoints such as CISH, which function independently of tumor-expressed ligands, offer powerful and previously untapped therapeutic potential. As a downstream regulator of TCR signaling, CISH controls T cell activation, expansion, and neoantigen reactivity. Though historically considered undruggable, recent advances in CRISPR engineering have enabled functional interrogation of these targets. We demonstrate that CISH deletion enhances T cell activation and anti-cancer functions more effectively than other emerging intracellular checkpoints. In CAR-T cells, CISH inactivation significantly increased sensitivity to tumor antigen, enabling robust recognition and killing even at low antigen levels, conditions that often lead to treatment failure with conventional T cell therapies, mirroring antigen escape scenarios seen in solid tumors. Our findings further validate CISH as a potent and druggable intracellular checkpoint capable of boosting anti-tumor T cell responses across diverse cancer types, independent of PD-L1 status. The underlying mechanisms of CISH inhibition may help explain the positive outcomes reported in recent clinical studies of this approach in solid tumor immunotherapy.

cancer biology↗

Many unreported crop pests and pathogens are probably already present

Biotic invasions threaten global biodiversity and ecosystem function, and present challenges to agriculture where invasive pest species require major economic investment in control and can cause significant production losses. Pest Risk Analysis (PRA) is key to prioritizing agricultural biosecurity efforts, but is hampered by incomplete knowledge of current crop pest and pathogen distributions. Here we develop predictive models of current pest distributions and test these models using new observations at sub-national resolution. We apply generalized linear models (GLM) to estimate presence probabilities for 1901 crop pests in the CABI pest distribution database. We test model predictions for 100 unobserved pests in the Peoples Republic of China (PRC), against observations of these pests abstracted from the Chinese literature which has hitherto been omitted from databases on global pest distributions. Finally, we predict occurrences of all unobserved pests globally. Presence probability increases with host presence, presence in neighbouring regions, and global prevalence, and decreases with mean distance from coast, per capita GDP, and host number. The models are good predictors of pest presence in Provinces of the PRC, with AUC values of 0.76 - 0.80. Large numbers of currently unobserved, but probably present pests, are predicted in China, India, southern Brazil and some countries of the former USSR. GLMs can predict presences of pseudo-absent pests at sub-national resolution. Controlling for countries scientific capacity improves model fit. The Chinese scientific literature has been largely inaccessible to Western academia but contains important information that can support PRA. Prior studies have often assumed that unreported pests in a global distribution database is a true absence. Our analysis provides a method for quantifying pseudo-absences to enable improved PRA and species distribution modelling.

ecology↗