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Biology subjects

Schienstock, D.

Publications and source records attributed to Schienstock, D..

2 recordsLinked to original sources

Antigen reactivity defines tissue-resident memory and exhausted T cells in tumours

CD8+ T cells are a key weapon in the therapeutic armamentarium against cancer. While CD8+CD103+ T cells with a tissue-resident memory T (TRM) cell phenotype have been favourably correlated with patient prognoses1-6, the tumour microenvironment also contains dysfunctional exhausted T (TEX) cells that exhibit a myriad of TRM-like features, leading to conflation of these two populations. Here, we deconvolute TRM and TEX cells within the intratumoural CD8+CD103+ T cell pool across human cancers, ascribing markers and gene signatures that distinguish these CD8+ populations and enable their functional distinction. We found that while TRM cells exhibit superior functionality and are associated with long-term survival post-tumour resection, they are not associated with responsiveness to immune checkpoint blockade. Deconvolution of the two populations showed that tumour-associated TEX and TRM cells are clonally distinct, with the latter comprising both tumour-independent bystanders and tumour-specific cells segregated from their cognate antigen. Intratumoural TRM cells can be forced towards an exhausted fate when chronic antigen stimulation occurs, arguing that the presence or absence of continuous antigen exposure within the microenvironment is the key distinction between respective tumour-associated TEX and TRM populations. These results suggest unique roles for TRM and TEX cells in tumour control, underscoring the need for distinct strategies to harness these T cell populations in novel cancer therapies.

immunology↗

Cecelia: a multifunctional image analysis toolbox for decoding spatial cellular interactions and behaviour

With the ever-increasing complexity of microscopy modalities, it is imperative to have computational workflows that allow researchers to process and perform in-depth quantitative analysis of the resulting images. However, workflows that enable flexible, interactive and intuitive analysis from raw images to analysed data are lacking. We present Cecelia, a toolbox that integrates various open-source packages into a coherent data management suite to make quantitative image analysis accessible for non-specialists.

bioinformatics↗