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Wald, N.

Publications and source records attributed to Wald, N..

2 recordsLinked to original sources

A2AR-mediated inhibition of B cell maturation: a novel mechanism of immune suppression in cancer

High levels of extracellular adenosine, highly abundant in the tumor microenvironment, promote immune suppression mainly through the A2AR expressed by tumor-infiltrating immune cells. Here we show that plasma cells are the most negatively affected by adenosine among the immune cells present in the tumor microenvironment. Furthermore, both tonsillar and tumor-associated B cells, including germinal center (GC)-like B cells, plasma cells and plasma blasts (PCs and PBs, respectively, and collectively referred to as antibody-secreting cells (ASCs), express high levels of A2AR. Given the importance of tumor-infiltrating B and PCs in antitumor responses, we investigated how adenosine impairs their numbers and function. Triggering of A2AR inhibited B cell maturation into ASCs and immunoglobulin production in vitro, and impaired upregulation of PC genes upon stimulation. These effects were restored by inupadenant (EOS100850), a potent and highly selective small molecule A2AR antagonist. Spatial transcriptomics analysis of tumor biopsies from patients treated with inupadenant revealed that ASCs specifically increased in tertiary lymphoid structures. Altogether, these data demonstrate that A2AR plays a key role in adenosine-mediated inhibition of B cell maturation toward ASCs through a B cell-intrinsic mechanism, and that this effect is fully reverted by inupadenant.

immunology↗

CytoPro: A computational platform for accurate and robust assessment of cell contributions in bulk expression from diverse tissues and conditions

Cells are the quanta unit of biology and their relative composition in a tissue is the prime driver of bulk tissue gene expression variation. When there is no cell information, deconvolution is an effective tool to achieve cell resolution, which provides important information for learning disease complexity and its interactions with treatments, drugs and/or the environment in a wide variety of contexts. Here we present CytoPro, a production-level tissue and condition-specific deconvolution platform, based on a large collection of human tissue-specific signatures derived from single and sorted cells. CytoPro infer per-sample multiple cell-type composition, given input bulk gene expression. CytoPro includes a rigorous QC pipeline for learning, generating and selecting signatures and performs internal automated validation using multiple QC test criteria including: Comparison to ground truth cytometry and pure sorted cells data, performance evaluation using simulated data including robustness to noise as well as agreement with biological expectations in validation datasets regarding genes and cells. We demonstrate that CytoPro outperforms existing deconvolution tools, in both accuracy and robustness. By exploring multiple datasets with predefined disease phenotypes, and analyzing a use-case of biological treatment response, we show the ability of CytoPro to flush out relevant cell biology in real pathological conditions.

bioinformatics↗