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      Germline modifiers of the tumor immune microenvironment implicate drivers of cancer risk and immunotherapy response

      research-article
      1 , 2 , 3 , 4 , 5 , 2 , 2 , 6 , 7 , 6 , 8 , 9 , 2 , 10 , 10 , 7 , 11 , 2 , 12 , 13 , 14 , 15 , 16 , 17 , 16 , 18 , 4 , 19 , 20 , 21 , 4 , 3 , 6 , 16 , 17 ,
      Nature Communications
      Nature Publishing Group UK
      Risk factors, Molecular medicine, Cancer genetics

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          Abstract

          With the continued promise of immunotherapy for treating cancer, understanding how host genetics contributes to the tumor immune microenvironment (TIME) is essential to tailoring cancer screening and treatment strategies. Here, we study 1084 eQTLs affecting the TIME found through analysis of The Cancer Genome Atlas and literature curation. These TIME eQTLs are enriched in areas of active transcription, and associate with gene expression in specific immune cell subsets, such as macrophages and dendritic cells. Polygenic score models built with TIME eQTLs reproducibly stratify cancer risk, survival and immune checkpoint blockade (ICB) response across independent cohorts. To assess whether an eQTL-informed approach could reveal potential cancer immunotherapy targets, we inhibit CTSS, a gene implicated by cancer risk and ICB response-associated polygenic models; CTSS inhibition results in slowed tumor growth and extended survival in vivo. These results validate the potential of integrating germline variation and TIME characteristics for uncovering potential targets for immunotherapy.

          Abstract

          The contribution of genetic factors to the tumour immune microenvironment (TIME) remains to be investigated. Here, the authors suggest the role of TIME eQTLs for target genes involved in reversing immune suppressive features.

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          Most cited references166

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              Hallmarks of Cancer: The Next Generation

              The hallmarks of cancer comprise six biological capabilities acquired during the multistep development of human tumors. The hallmarks constitute an organizing principle for rationalizing the complexities of neoplastic disease. They include sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis. Underlying these hallmarks are genome instability, which generates the genetic diversity that expedites their acquisition, and inflammation, which fosters multiple hallmark functions. Conceptual progress in the last decade has added two emerging hallmarks of potential generality to this list-reprogramming of energy metabolism and evading immune destruction. In addition to cancer cells, tumors exhibit another dimension of complexity: they contain a repertoire of recruited, ostensibly normal cells that contribute to the acquisition of hallmark traits by creating the "tumor microenvironment." Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer. Copyright © 2011 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                hkcarter@health.ucsd.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                12 May 2023
                12 May 2023
                2023
                : 14
                : 2744
                Affiliations
                [1 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Biomedical Sciences Program, , University of California San Diego, ; La Jolla, CA 92093 USA
                [2 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Bioinformatics and Systems Biology Program, , University of California San Diego, ; La Jolla, CA 92093 USA
                [3 ]GRID grid.516081.b, ISNI 0000 0000 9217 9714, Department of Pharmacology, , UCSD Moores Cancer Center, ; La Jolla, CA 92093 USA
                [4 ]GRID grid.48336.3a, ISNI 0000 0004 1936 8075, Laboratory of Cancer Biology and Genetics, , National Cancer Institute, National Institutes of Health (NIH), ; Bethesda, MD 20892 USA
                [5 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Undergraduate Bioengineering Program, Jacobs School of Engineering, , University of California San Diego, ; La Jolla, CA 92093 USA
                [6 ]GRID grid.185006.a, ISNI 0000 0004 0461 3162, La Jolla Institute for Immunology, ; La Jolla, CA 92037 USA
                [7 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Division of Epidemiology, Herbert Wertheim School of Public Health and Human Longevity Science, , University of California San Diego, ; La Jolla, CA 92093 USA
                [8 ]Canyon Crest Academy, San Diego, CA 92130 USA
                [9 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Undergraduate Biology and Bioinformatics Program, , University of California San Diego, ; La Jolla, CA 92093 USA
                [10 ]GRID grid.48336.3a, ISNI 0000 0004 1936 8075, Division of Cancer Epidemiology and Genetics, , National Cancer Institute, National Institutes of Health (NIH), ; Bethesda, MD 20892 USA
                [11 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Pathology, , University of California San Diego, ; La Jolla, CA 92093 USA
                [12 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Division of Biomedical Informatics, Department of Medicine, , University of California San Diego School of Medicine, ; La Jolla, CA 92093 USA
                [13 ]GRID grid.516081.b, ISNI 0000 0000 9217 9714, Center for Personalized Cancer Therapy, Division of Hematology and Oncology, , UC San Diego Moores Cancer Center, ; San Diego, CA 92037 USA
                [14 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Cellular and Molecular Medicine, , University of California San Diego, ; La Jolla, CA 92093 USA
                [15 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Bioengineering, , University of California San Diego, ; La Jolla, CA 92093 USA
                [16 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Moores Cancer Center, , University of California San Diego, ; La Jolla, CA 92093 USA
                [17 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Medicine, Division of Medical Genetics, , University of California San Diego, ; La Jolla, CA 92093 USA
                [18 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, The Laboratory of Immunology and Department of Medicine, , University of California San Diego, ; La Jolla, CA 92093 USA
                [19 ]GRID grid.417423.7, ISNI 0000 0004 0512 8863, Center for Population Neuroscience and Genetics, , Laureate Institute for Brain Research, ; Tulsa, OK 74136 USA
                [20 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Radiology, , University of California San Diego, ; La Jolla, CA 92093 USA
                [21 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Division of Biostatistics, Herbert Wertheim School of Public Health and Human Longevity Science, , University of California San Diego, ; La Jolla, CA 92093 USA
                Author information
                http://orcid.org/0000-0002-7591-6035
                http://orcid.org/0000-0002-4868-1509
                http://orcid.org/0000-0003-2570-7697
                http://orcid.org/0000-0002-9520-1950
                http://orcid.org/0000-0002-9103-9378
                http://orcid.org/0000-0001-5540-465X
                http://orcid.org/0000-0002-5043-2245
                http://orcid.org/0000-0003-2124-2706
                http://orcid.org/0000-0003-4507-329X
                http://orcid.org/0000-0001-8816-6862
                http://orcid.org/0000-0002-1097-4453
                http://orcid.org/0000-0001-5200-2372
                http://orcid.org/0000-0001-9437-2128
                http://orcid.org/0000-0001-7067-9723
                http://orcid.org/0000-0002-1729-2463
                Article
                38271
                10.1038/s41467-023-38271-5
                10182072
                37173324
                f168e10a-ec63-4682-932d-284086465e9d
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 12 May 2022
                : 24 April 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000054, U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI);
                Award ID: R01CA269919
                Award ID: R01CA220009
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
                Funded by: The Mark Foundation for Cancer Research 18-022-ELA
                Funded by: FundRef https://doi.org/10.13039/100000002, U.S. Department of Health & Human Services | National Institutes of Health (NIH);
                Award ID: 1F30CA247168-01
                Award ID: T32CA067754
                Award ID: R00HL122515
                Award ID: R01CA269919
                Award ID: U24CA258406
                Award ID: R01CA220009
                Award ID: R01 CA247551
                Award ID: U01 DE028227
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | National Institutes of Health (NIH)
                Funded by: U.S. Department of Health & Human Services | National Institutes of Health (NIH)
                Funded by: U.S. Department of Health & Human Services | National Institutes of Health (NIH)
                Funded by: U.S. Department of Health & Human Services | National Institutes of Health (NIH)
                Funded by: U.S. Department of Health & Human Services | National Institutes of Health (NIH)
                Funded by: U.S. Department of Health & Human Services | National Institutes of Health (NIH)
                Funded by: U.S. Department of Health & Human Services | National Institutes of Health (NIH)
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                © Springer Nature Limited 2023

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                risk factors,molecular medicine,cancer genetics
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                risk factors, molecular medicine, cancer genetics

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