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Identifying expressed somatic mutations from single-cell RNA sequencing data de novo is challenging but highly valuable. We propose RESA – Recurrently Expressed SNV Analysis, a computational framework to identify expressed somatic mutations from scRNA-seq data. RESA achieves an average precision of 0.77 on three in silico spike-in datasets. In extensive benchmarking against existing methods using 19 datasets, RESA consistently outperforms them. Furthermore, we applied RESA to analyze intratumor mutational heterogeneity in a melanoma drug resistance dataset. By enabling high precision detection of expressed somatic mutations, RESA substantially enhances the reliability of mutational analysis in scRNA-seq. RESA is available at https://github.com/ShenLab-Genomics/RESA. [ABSTRACT FROM AUTHOR]

Tumors create an immunosuppressive tumor microenvironment by altering protein expression, but also by changing their glycosylation status, like altered expression of sialoglycans. Sialoglycans are capped with sialic acid sugar residues and are recognized by Siglec immune receptors. Siglec-7 is an inhibitory immune receptor similar to PD-1, and is emerging as glycoimmune checkpoint exploited by cancer cells to evade the immune system. However, the exact cellular and molecular conditions required for Siglec-7-mediated immune cell inhibition remain largely unknown. Here, we report on the development of a chimeric Siglec-7 cell system that enables dissection of Siglec-7 signaling, rather than Siglec-7 binding. Antibody-induced clustering, sialic acid-containing polymers, and highly sialylated erythrocytes effectively induced Siglec-7 signaling, thereby validating functionality of this reporter system. Moreover, the system reveals tumor cell-dependent Siglec-7 signaling. Tumor-associated conditions important for Siglec-7 signaling were defined, such as Siglec-7 ligand expression levels, presence of the known Siglec-7 ligand CD43, and sialic acid availability for sialylation of glycans. Importantly, therapeutic targeting of the Siglec-7/sialic acid axis using a sialyltransferase inhibitor resulted in strong reduction of Siglec-7 signaling. In conclusion, using a newly established cellular tool, we defined a set of tumor-associated conditions that influence Siglec-7 signaling. Moreover, the system allows to assess the efficacy of novel cancer drugs interfering with the Siglec-7/sialic acid axis as immunotherapy to treat cancer. [ABSTRACT FROM AUTHOR]

Type 1 diabetes (T1D) is a disease of both autoimmunity and β-cells. The β-cells play an active role in their own demise by mounting defense mechanisms that are insufficient at best, and that can become even deleterious in the long term. This complex crosstalk is important to understanding the physiological defense mechanisms at play in healthy conditions, their alterations in the T1D setting, and therapeutic agents that may boost such mechanisms. Robust protocols to develop stem-cell-derived islets (SC-islets) from human pluripotent stem cells (hPSCs), and islet-reactive cytotoxic CD8+ T-cells from peripheral blood mononuclear cells offer unprecedented opportunities to study this crosstalk. Challenges to develop in vitro β-cell killing models include the cluster morphology of SC-islets, the relatively weak cytotoxicity of most autoimmune T-cells and the variable behavior of in vitro expanded CD8+ T-cells. These challenges may however be highly rewarding in light of the opportunities offered by such models. Herein, we discuss these opportunities including: the β-cell/immune crosstalk in an islet microenvironment; the features that make β-cells more sensitive to autoimmunity; therapeutic agents that may modulate β-cell vulnerability; and the possibility to perform analyses in an autologous setting, i.e., by generating T-cell effectors and SC-islets from the same donor. [ABSTRACT FROM AUTHOR]

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