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      METTL1 promotes tumorigenesis through tRNA-derived fragment biogenesis in prostate cancer

      research-article
      1 , 2 , 1 , 2 , 3 , 1 , 2 , 1 , 2 , 4 , 5 , 1 , 2 , 5 , 5 , 6 , 5 , 5 , 7 , 5 , 7 , 5 , 7 , 1 , 1 , 2 , 8 , 9 , 10 , 11 , 1 , 12 , 7 , 13 , 14 , 13 , 7 , 13 , 14 , 5 , 15 , 5 , 15 , 16 , 5 , 5 , 5 , 16 , 17 , 2 , 18 , 1 , 10 , 11 , 8 , 19 , 20 , 21 , 22 , 5 , 6 , 7 , 12 , 23 , 1 , 2 , 5 ,
      Molecular Cancer
      BioMed Central
      Epitranscriptome, RNA modifications, Prostate cancer, 7-methylguanosine, tRNA fragments, Tumour microenvironment (TME), Interferon, Immune checkpoint blockade

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          Abstract

          Newly growing evidence highlights the essential role that epitranscriptomic marks play in the development of many cancers; however, little is known about the role and implications of altered epitranscriptome deposition in prostate cancer. Here, we show that the transfer RNA N 7-methylguanosine (m 7G) transferase METTL1 is highly expressed in primary and advanced prostate tumours. Mechanistically, we find that METTL1 depletion causes the loss of m 7G tRNA methylation and promotes the biogenesis of a novel class of small non-coding RNAs derived from 5'tRNA fragments. 5'tRNA-derived small RNAs steer translation control to favour the synthesis of key regulators of tumour growth suppression, interferon pathway, and immune effectors. Knockdown of Mettl1 in prostate cancer preclinical models increases intratumoural infiltration of pro-inflammatory immune cells and enhances responses to immunotherapy. Collectively, our findings reveal a therapeutically actionable role of METTL1-directed m 7G tRNA methylation in cancer cell translation control and tumour biology.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12943-023-01809-8.

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

            Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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              limma powers differential expression analyses for RNA-sequencing and microarray studies

              limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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                Author and article information

                Contributors
                sandra.blanco@usal.es
                Journal
                Mol Cancer
                Mol Cancer
                Molecular Cancer
                BioMed Central (London )
                1476-4598
                29 July 2023
                29 July 2023
                2023
                : 22
                : 119
                Affiliations
                [1 ]GRID grid.4711.3, ISNI 0000 0001 2183 4846, Centro de Investigación del Cáncer and Instituto de Biología Molecular y Celular del Cáncer, , Consejo Superior de Investigaciones Científicas (CSIC)-University of Salamanca, ; 37007 Salamanca, Spain
                [2 ]GRID grid.411258.b, Instituto de Investigación Biomédica de Salamanca (IBSAL), , Hospital Universitario de Salamanca, ; 37007 Salamanca, Spain
                [3 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Washington University School of Medicine in St. Louis, ; 660S. Euclid Ave, St. Louis, MO 63110 USA
                [4 ]GRID grid.12380.38, ISNI 0000 0004 1754 9227, Present Address: Department of Neurosurgery, Cancer Center Amsterdam, Amsterdam UMC, , Vrije Universiteit Amsterdam, ; 1081 HV Amsterdam, The Netherlands
                [5 ]GRID grid.420175.5, ISNI 0000 0004 0639 2420, CIC bioGUNE, Basque Research and Technology Alliance (BRTA), ; Bizkaia Technology Park, 801 Bld, 48160 Derio, Bizkaia Spain
                [6 ]GRID grid.424810.b, ISNI 0000 0004 0467 2314, Ikerbasque, Basque Foundation for Science, ; 48011 Bilbao, Spain
                [7 ]GRID grid.510933.d, ISNI 0000 0004 8339 0058, Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), ; Madrid, Spain
                [8 ]GRID grid.29172.3f, ISNI 0000 0001 2194 6418, Université de Lorraine, UAR2008 IBSLor CNRS-UL-INSERM, Biopôle UL, ; 9, Avenue de La Forêt de Haye, 54505 Vandoeuvre-Les-Nancy, France
                [9 ]GRID grid.4711.3, ISNI 0000 0001 2183 4846, Bioinformatics Unit, Cancer Research Center (CIC-IBMCC, CSIC/USAL), , Consejo Superior de Investigaciones Científicas (CSIC) and University of Salamanca (USAL), ; 37007 Salamanca, Spain
                [10 ]GRID grid.429289.c, Josep Carreras Leukaemia Research Institute (IJC), Badalona, ; 08916 Barcelona, Catalonia Spain
                [11 ]Germans Trias I Pujol Health Science Research Institute, Badalona, 08916 Barcelona, Catalonia Spain
                [12 ]GRID grid.414269.c, ISNI 0000 0001 0667 6181, Department of Pathology, , Basurto University Hospital, ; 48013 Bilbao, Spain
                [13 ]GRID grid.414269.c, ISNI 0000 0001 0667 6181, Department of Urology, , Basurto University Hospital, ; 48013 Bilbao, Spain
                [14 ]GRID grid.452310.1, Traslational Prostate Cancer Research Lab, CIC bioGUNE-Basurto, Biocruces Bizkaia Health Research Institute, ; Avenida Montevideo 18, 48013 Bilbao, Spain
                [15 ]Carlos III Networked Proteomics Platform (ProteoRed-ISCIII), Madrid, Spain
                [16 ]GRID grid.452371.6, ISNI 0000 0004 5930 4607, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), ; Madrid, Spain
                [17 ]GRID grid.7719.8, ISNI 0000 0000 8700 1153, Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), ; 28029 Madrid, Spain
                [18 ]GRID grid.11762.33, ISNI 0000 0001 2180 1817, Servicio de Transgénesis, Nucleus, Universidad de Salamanca, ; 37007 Salamanca, Spain
                [19 ]GRID grid.29172.3f, ISNI 0000 0001 2194 6418, Université de Lorraine, UMR7365 IMoPA CNRS-UL, Biopôle UL, ; 9, Avenue de La Forêt de Haye, 54505 Vandoeuvre-Les-Nancy, France
                [20 ]GRID grid.5802.f, ISNI 0000 0001 1941 7111, Institute of Pharmaceutical and Biomedical Sciences, , Johannes Gutenberg-University Mainz, ; Mainz, Germany
                [21 ]GRID grid.7605.4, ISNI 0000 0001 2336 6580, Molecular Biotechnology Center (MBC), Department of Molecular Biotechnology and Health Sciences, , University of Turin, ; 10126 Turin, TO Italy
                [22 ]GRID grid.298261.6, ISNI 0000 0000 8685 5368, William N. Pennington Cancer Center, Renown Health, Nevada System of Higher Education, ; Reno, NV 89502 USA
                [23 ]GRID grid.11480.3c, ISNI 0000000121671098, Biochemistry and Molecular Biology Department, , University of the Basque Country (UPV/EHU), ; P. O. Box 644, 48080 Bilbao, Spain
                Article
                1809
                10.1186/s12943-023-01809-8
                10386714
                37516825
                72926536-7f82-40ba-8ce0-c40c95ffdda9
                © 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 3 August 2022
                : 17 June 2023
                Funding
                Funded by: Consejo Superior de Investigaciones Cientificas (CSIC)
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2023

                Oncology & Radiotherapy
                epitranscriptome,rna modifications,prostate cancer,7-methylguanosine,trna fragments,tumour microenvironment (tme),interferon,immune checkpoint blockade

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