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      Reprogramming of T cell‐derived small extracellular vesicles using IL2 surface engineering induces potent anti‐cancer effects through miRNA delivery

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          Abstract

          T cell‐derived small extracellular vesicles (sEVs) exhibit anti‐cancer effects. However, their anti‐cancer potential should be reinforced to enhance clinical applicability. Herein, we generated interleukin‐2‐tethered sEVs (IL2‐sEVs) from engineered Jurkat T cells expressing IL2 at the plasma membrane via a flexible linker to induce an autocrine effect. IL2‐sEVs increased the anti‐cancer ability of CD8 + T cells without affecting regulatory T (T reg) cells and down‐regulated cellular and exosomal PD‐L1 expression in melanoma cells, causing their increased sensitivity to CD8 + T cell‐mediated cytotoxicity. Its effect on CD8 + T and melanoma cells was mediated by several IL2‐sEV‐resident microRNAs (miRNAs), whose expressions were upregulated by the autocrine effects of IL2. Among the miRNAs, miR‐181a‐3p and miR‐223‐3p notably reduced the PD‐L1 protein levels in melanoma cells. Interestingly, miR‐181a‐3p increased the activity of CD8 + T cells while suppressing T reg cell activity. IL2‐sEVs inhibited tumour progression in melanoma‐bearing immunocompetent mice, but not in immunodeficient mice. The combination of IL2‐sEVs and existing anti‐cancer drugs significantly improved anti‐cancer efficacy by decreasing PD‐L1 expression in vivo. Thus, IL2‐sEVs are potential cancer immunotherapeutic agents that regulate both immune and cancer cells by reprogramming miRNA levels.

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          Most cited references72

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          Fast gapped-read alignment with Bowtie 2.

          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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            edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

            Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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              BEDTools: a flexible suite of utilities for comparing genomic features

              Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                ykm31@dgist.ac.kr
                mcbaek@knu.ac.kr
                Journal
                J Extracell Vesicles
                J Extracell Vesicles
                10.1002/(ISSN)2001-3078
                JEV2
                Journal of Extracellular Vesicles
                John Wiley and Sons Inc. (Hoboken )
                2001-3078
                29 November 2022
                December 2022
                : 11
                : 12 ( doiID: 10.1002/jev2.v11.12 )
                : 12287
                Affiliations
                [ 1 ] Department of Molecular Medicine, CMRI, Exosome Convergence Research Center (ECRC), School of Medicine Kyungpook National University Daegu Republic of Korea
                [ 2 ] Department of New Biology DGIST Daegu Republic of Korea
                [ 3 ] New Biology Research Center DGIST Daegu Republic of Korea
                [ 4 ] Department of Neural Development and Disease Korea Brain Research Institute Daegu Republic of Korea
                [ 5 ] Eye Center, Medical Center, Faculty of Medicine University of Freiburg Freiburg Germany
                [ 6 ] Division of Translational Science National Cancer Center 323 Ilsan‐ro, Ilsandong‐gu Goyang‐si Gyeonggi‐do Republic of Korea
                [ 7 ] Department of Life Sciences Pohang University of Science and Technology (POSTECH) Gyeongsangbuk‐do Republic of Korea
                [ 8 ] Institute of Convergence Science Yonsei University Seoul Republic of Korea
                [ 9 ] ImmunoBiome Pohang Republic of Korea
                [ 10 ] Section of Molecular Pharmacology and Toxicology, Laboratory of Membrane Biochemistry and Biophysics National Institute on Alcohol Abuse and Alcoholism (NIAAA) Bethesda Maryland USA
                Author notes
                [*] [* ] Correspondence

                Moon‐Chang Baek, Department of Molecular Medicine, CMRI, Exosome Convergence Research Center (ECRC), School of Medicine, Kyungpook National University, Daegu, 41944, Republic of Korea.

                Email: mcbaek@ 123456knu.ac.kr

                Kyungmoo Yea, Department of New Biology, DGIST, Daegu, 43024, Republic of Korea.

                Email: ykm31@ 123456dgist.ac.kr

                Author information
                https://orcid.org/0000-0002-8502-7370
                https://orcid.org/0000-0001-8584-8382
                https://orcid.org/0000-0003-3528-2397
                https://orcid.org/0000-0002-4266-1048
                Article
                JEV212287
                10.1002/jev2.12287
                9709340
                36447429
                5f6b94f4-600d-41e6-b71a-8848d39070da
                © 2022 The Authors. Journal of Extracellular Vesicles published by Wiley Periodicals, LLC on behalf of the International Society for Extracellular Vesicles.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 28 September 2022
                : 30 March 2022
                : 14 November 2022
                Page count
                Figures: 6, Tables: 0, Pages: 18, Words: 11427
                Funding
                Funded by: Ministry of Science and ICT, South Korea , doi 10.13039/501100014188;
                Award ID: 2017M3A9G8083382
                Award ID: 2019M3A9H1103607
                Award ID: 2020M3A9I4039539
                Award ID: 2021R1A5A2021614
                Award ID: 21‐DGRIP‐01
                Award ID: NCC‐2032052020
                Funded by: Joint Research Project of Institutes of Science and Technology
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                December 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.1 mode:remove_FC converted:30.11.2022

                cancer,exosomal pd‐l1,interleukin‐2,pd‐l1,small extracellular vesicle,small extracellular vesicle engineering

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