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      Single-cell reconstruction of the early maternal–fetal interface in humans

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          Is Open Access

          NK Cells Stimulate Recruitment of cDC1 into the Tumor Microenvironment Promoting Cancer Immune Control

          Summary Conventional type 1 dendritic cells (cDC1) are critical for antitumor immunity, and their abundance within tumors is associated with immune-mediated rejection and the success of immunotherapy. Here, we show that cDC1 accumulation in mouse tumors often depends on natural killer (NK) cells that produce the cDC1 chemoattractants CCL5 and XCL1. Similarly, in human cancers, intratumoral CCL5, XCL1, and XCL2 transcripts closely correlate with gene signatures of both NK cells and cDC1 and are associated with increased overall patient survival. Notably, tumor production of prostaglandin E2 (PGE2) leads to evasion of the NK cell-cDC1 axis in part by impairing NK cell viability and chemokine production, as well as by causing downregulation of chemokine receptor expression in cDC1. Our findings reveal a cellular and molecular checkpoint for intratumoral cDC1 recruitment that is targeted by tumor-derived PGE2 for immune evasion and that could be exploited for cancer therapy.
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            Single-cell sequencing reveals dissociation-induced gene expression in tissue subpopulations

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              Is Open Access

              A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data

              (2013)
              Motivation: Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. Results: We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. Availability: http://samtools.sourceforge.net. Contact: hengli@broadinstitute.org.

                Author and article information

                Journal
                Nature
                Nature
                Springer Nature America, Inc
                0028-0836
                1476-4687
                November 2018
                November 14 2018
                November 2018
                : 563
                : 7731
                : 347-353
                Article
                10.1038/s41586-018-0698-6
                30429548
                6b68f6c8-028f-4d56-84be-0c4be6fd7e16
                © 2018

                http://www.springer.com/tdm

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