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      Intratumoral Microbiome of Human Primary Liver Cancer

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          Abstract

          Primary liver tumors (PLCs) and liver metastasis currently represent the leading cause of cancer‐related deaths worldwide due to poor outcomes, high incidence, and postsurgical recurrence. Hence, novel diagnostic markers and therapeutic strategies for PLCs are urgently needed. The human microbiome can directly or indirectly impact cancer initiation, progression, and response to therapy, including cancer immunotherapy; however, the roles of the microbiota in the tumor microenvironment are not clear and require more investigation. Here, we investigated intratumoral microbial community profiling on formalin‐fixed paraffin‐embedded tissue samples of patients with PLC by 16S ribosomal RNA using the MiSeq platform. We characterized the microbial communities in different histopathological subtypes and in the different prognoses of patients with PLC. The study revealed microbial population differences not only in carcinoma tissue and the matched adjacent nontumor tissue but in different histopathological subtypes, even in patients with PLC with different prognoses. Interestingly, the abundance of certain bacteria that have antitumor effects at family and genus level, such as Pseudomonadaceae, decreased in tumor tissue and was linearly associated with prognosis of patients with PLC. Conclusion: We provide a potential novel diagnostic biomarker and therapeutic strategy for early clinical diagnosis and treatment of PLC.

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          Most cited references46

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          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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            phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

            Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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              Metagenomic biomarker discovery and explanation

              This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at http://huttenhower.sph.harvard.edu/lefse/.
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                Author and article information

                Contributors
                3145898588@qq.com
                zlyyzhanghe4202@zzu.edu.cn
                Journal
                Hepatol Commun
                Hepatol Commun
                10.1002/(ISSN)2471-254X
                HEP4
                Hepatology Communications
                John Wiley and Sons Inc. (Hoboken )
                2471-254X
                22 February 2022
                July 2022
                : 6
                : 7 ( doiID: 10.1002/hep4.v6.7 )
                : 1741-1752
                Affiliations
                [ 1 ] Department of Pathology Zhengzhou Key Laboratory of Accurate Pathological Diagnosis of Intractable Tumors Henan Medical Key Laboratory of Tumor Pathology and Artificial Intelligence Diagnosis Affiliated Cancer Hospital of Zhengzhou University Zhengzhou China
                [ 2 ] ringgold 26487; School of Life Sciences Northwestern Polytechnical University Xi’an China
                [ 3 ] Medical Service Office Affiliated Cancer Hospital of Zhengzhou University Zhengzhou China
                [ 4 ] ringgold 89667; Department of Pathology Fudan University Shanghai Cancer Center Shanghai China
                Author notes
                [*] [* ] ADDRESS CORRESPONDENCE AND REPRINT REQUESTS TO:

                He Zhang, Ph.D.

                Department of Pathology, Affiliated Cancer Hospital of Zhengzhou University

                127th Dongming Rd., Zhengzhou 450000, Henan, China

                E‐mail: zlyyzhanghe4202@ 123456zzu.edu.cn

                Tel.: +86 0371‐65587018

                Author information
                https://orcid.org/0000-0002-0306-6633
                Article
                HEP41908
                10.1002/hep4.1908
                9234634
                35191218
                f779daa4-f75b-4d5c-8f7d-0c81c75600c3
                © 2022 The Authors. Hepatology Communications published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.

                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
                Page count
                Figures: 6, Tables: 1, Pages: 12, Words: 5757
                Funding
                Funded by: the Doctoral Research Initiation Fund of Affiliated Cancer Hospital of Zhengzhou University
                Award ID: (grants 3101030102 to H.Z.)
                Funded by: the Nursery Scientific Research Foundation of Affiliated Cancer Hospital of Zhengzhou University
                Award ID: (grants to D.D.Q.)
                Funded by: the National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: (grants 31901233 to H.Z.)
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                July 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.7 mode:remove_FC converted:27.06.2022

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