A tissue resident-like phenotype in tumor infiltrating T cells can limit systemic anti-tumor immunity. Enhanced systemic anti-tumor immunity is observed in head and neck cancer patients after neoadjuvant PD-L1 immune checkpoint blockade (ICB) and transforming growth factor β (TGF-β) neutralization. Using T cell receptor (TCR) sequencing and functional immunity assays in a syngeneic model of oral cancer, we dissect the relative contribution of these treatments to enhanced systemic immunity.
View Article and Find Full Text PDFAdvances in artificial intelligence have paved the way for leveraging hematoxylin and eosin-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an indirect two-step approach consisting of (1) DeepPT, a deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response to targeted and immune therapies from the inferred expression values. We show that DeepPT successfully predicts transcriptomics in all 16 The Cancer Genome Atlas cohorts tested and generalizes well to two independent datasets.
View Article and Find Full Text PDFActa Crystallogr E Crystallogr Commun
March 2024
Two compounds, ()-8-{[(-butyl-dimethyl-sil-yl)-oxy]meth-yl}-1-[(2,2,4,6,7-penta-methyl-2,3-di-hydro-benzo-furan-5-yl)sulfon-yl]-1,3,4,6,7,8-hexa-hydro-2-pyrimido[1,2-]pyrimidin-1-ium tri-fluoro-methane-sulfonate, CHNOSSi·CFOS, () and ()-8-(iodo-meth-yl)-1-tosyl-1,3,4,6,7,8-hexa-hydro-2-pyrimido[1,2-]pyrimidin-1-ium iodide, CHINOS·I, (), have been synthesized and characterized. They are bicyclic guanidinium salts and were synthesized from -(-but-oxy-carbon-yl)-l-me-thio-nine (Boc-l-Met-OH). The guanidine is protected by a 2,2,4,6,7-penta-methyl-dihydro-benzo-furan-5-sulfonyl (Pbf, ) or a tosyl () group.
View Article and Find Full Text PDFAdvances in artificial intelligence have paved the way for leveraging hematoxylin and eosin (H&E)-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an approach for predicting response to multiple targeted and immunotherapies from H&E-slides. In difference from existing approaches that aim to predict treatment response directly from the slides, ENLIGHT-DeepPT is an indirect two-step approach consisting of (1) DeepPT, a new deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response based on the DeepPT inferred expression values.
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