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      Comprehensive bioinformatic analysis of MMP1 in hepatocellular carcinoma and establishment of relevant prognostic model

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          Abstract

          Matrix metalloproteinase 1 (MMP1) encodes endopeptidases associated with degradation of multiple components of the extracellular matrix. This function has increasingly been considered to play a major proteolysis role in tumor invasion and metastasis. However, the relationship between MMP1 gene expression, tumor-immune microenvironment and prognosis in hepatocellular carcinoma patients remains mostly unclear. This study focused on a comprehensive analysis of MMP1 in hepatocellular carcinoma, specifically the prognosis and tumor-immune microenvironment. MMP1 expression was analyzed using TCGA database and clinical samples. MMP1 associated mechanisms, pathways, mutations and prognosis in hepatocellular carcinoma were evaluated. We also analyzed the tumor-immune microenvironment and corresponding treatments. Our research demonstrated that MMP1 expression was upregulated in patients with hepatocellular carcinoma and correlated with poor survival. A prognostic model was established and its performance evaluated. We also found and report various correlations between MMP1 and immune-related cells/genes, as well the potential therapeutic agents. These findings indicate that MMP1 can potentially be a promising prognostic biomarker and indicator of the tumor-immune microenvironment status in hepatocellular carcinoma.

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          Most cited references66

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

            The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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              clusterProfiler: an R package for comparing biological themes among gene clusters.

              Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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                Author and article information

                Contributors
                lucaide@nbu.edu.cn
                yangtze21@sina.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                10 August 2022
                10 August 2022
                2022
                : 12
                : 13639
                Affiliations
                [1 ]GRID grid.203507.3, ISNI 0000 0000 8950 5267, Department of Hepatopancreatobiliary Surgery, , Ningbo Medical Centre Lihuili Hospital, Ningbo University, ; 1111 Jiangnan Road, Ningbo, 315040 Zhejiang China
                [2 ]GRID grid.203507.3, ISNI 0000 0000 8950 5267, Department of Emergency, , Ningbo Medical Centre Lihuili Hospital, Ningbo University, ; Ningbo, 315040 Zhejiang China
                Article
                17954
                10.1038/s41598-022-17954-x
                9365786
                35948625
                62638163-5cb7-42a2-ae49-fefca80999ef
                © The Author(s) 2022

                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/.

                History
                : 18 February 2022
                : 3 August 2022
                Funding
                Funded by: Ningbo Health Branding Subject Fund
                Award ID: PPXK2018-03
                Award ID: PPXK2018-03
                Award ID: PPXK2018-03
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                cancer,computational biology and bioinformatics,genetics,immunology,molecular biology,biomarkers,oncology

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