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      Cross-cancer evaluation of polygenic risk scores for 16 cancer types in two large cohorts

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          Abstract

          Even distinct cancer types share biological hallmarks. Here, we investigate polygenic risk score (PRS)-specific pleiotropy across 16 cancers in European ancestry individuals from the Genetic Epidemiology Research on Adult Health and Aging cohort (16,012 cases, 50,552 controls) and UK Biobank (48,969 cases, 359,802 controls). Within cohorts, each PRS is evaluated in multivariable logistic regression models against all other cancer types. Results are then meta-analyzed across cohorts. Ten positive and one inverse cross-cancer associations are found after multiple testing correction. Two pairs show bidirectional associations; the melanoma PRS is positively associated with oral cavity/pharyngeal cancer and vice versa, whereas the lung cancer PRS is positively associated with oral cavity/pharyngeal cancer, and the oral cavity/pharyngeal cancer PRS is inversely associated with lung cancer. Overall, we validate known, and uncover previously unreported, patterns of pleiotropy that have the potential to inform investigations of risk prediction, shared etiology, and precision cancer prevention strategies.

          Abstract

          While genetic loci shared between cancer types have been identified, cross-cancer relationships for polygenic risk scores have not been well studied. Here, the authors have developed polygenic risk scores for 16 cancers in two large cohorts and identified positive and inverse cross-cancer associations.

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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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            The UK Biobank resource with deep phenotyping and genomic data

            The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.
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              The 2016 revision of the World Health Organization classification of lymphoid neoplasms.

              A revision of the nearly 8-year-old World Health Organization classification of the lymphoid neoplasms and the accompanying monograph is being published. It reflects a consensus among hematopathologists, geneticists, and clinicians regarding both updates to current entities as well as the addition of a limited number of new provisional entities. The revision clarifies the diagnosis and management of lesions at the very early stages of lymphomagenesis, refines the diagnostic criteria for some entities, details the expanding genetic/molecular landscape of numerous lymphoid neoplasms and their clinical correlates, and refers to investigations leading to more targeted therapeutic strategies. The major changes are reviewed with an emphasis on the most important advances in our understanding that impact our diagnostic approach, clinical expectations, and therapeutic strategies for the lymphoid neoplasms.
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                Author and article information

                Contributors
                jwitte@ucsf.edu
                lori.sakoda@kp.org
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                12 February 2021
                12 February 2021
                2021
                : 12
                : 970
                Affiliations
                [1 ]GRID grid.266102.1, ISNI 0000 0001 2297 6811, Department of Epidemiology and Biostatistics, , University of California San Francisco, ; San Francisco, CA USA
                [2 ]GRID grid.280062.e, ISNI 0000 0000 9957 7758, Division of Research, , Kaiser Permanente Northern California, ; Oakland, CA USA
                [3 ]GRID grid.266102.1, ISNI 0000 0001 2297 6811, Helen Diller Family Comprehensive Cancer Center, , University of California San Francisco, ; San Francisco, CA USA
                [4 ]GRID grid.266102.1, ISNI 0000 0001 2297 6811, Program in Biological and Medical Informatics, University of California San Francisco, ; San Francisco, CA USA
                [5 ]GRID grid.266102.1, ISNI 0000 0001 2297 6811, Institute for Human Genetics, , University of California San Francisco, ; San Francisco, CA USA
                [6 ]GRID grid.266102.1, ISNI 0000 0001 2297 6811, Department of Medicine, , University of California San Francisco, ; San Francisco, CA USA
                [7 ]GRID grid.266102.1, ISNI 0000 0001 2297 6811, Department of Urology, , University of California San Francisco, ; San Francisco, CA USA
                [8 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Department of Health System Science, , Kaiser Permanente Bernard J. Tyson School of Medicine, ; Pasadena, CA USA
                Author information
                http://orcid.org/0000-0003-0316-8303
                http://orcid.org/0000-0003-3537-2608
                http://orcid.org/0000-0001-5542-6891
                http://orcid.org/0000-0002-7330-5900
                http://orcid.org/0000-0001-9136-1175
                http://orcid.org/0000-0002-5599-8387
                http://orcid.org/0000-0002-5829-8191
                http://orcid.org/0000-0001-6893-4449
                http://orcid.org/0000-0002-0900-5735
                Article
                21288
                10.1038/s41467-021-21288-z
                7880989
                33579919
                f3c51fd6-f351-4079-94d7-95034cf5d734
                © The Author(s) 2021

                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
                : 26 May 2020
                : 19 January 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000054, U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI);
                Award ID: K07CA188142
                Award ID: K24CA169004
                Award ID: R01CA088164
                Award ID: R01CA201358
                Award ID: U01CA127298
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
                Funded by: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
                Funded by: FundRef https://doi.org/10.13039/100000049, U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging);
                Award ID: R25CA112355
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)
                Funded by: FundRef https://doi.org/10.13039/100000867, Robert Wood Johnson Foundation (RWJF);
                Funded by: FundRef https://doi.org/10.13039/100001370, Wayne and Gladys Valley Foundation;
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                cancer epidemiology,cancer genetics
                Uncategorized
                cancer epidemiology, cancer genetics

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