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      DDR2 signaling and mechanosensing orchestrate neuroblastoma cell fate through different transcriptome mechanisms

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          Abstract

          The extracellular matrix (ECM) regulates carcinogenesis by interacting with cancer cells via cell surface receptors. Discoidin Domain Receptor 2 (DDR2) is a collagen‐activated receptor implicated in cell survival, growth, and differentiation. Dysregulated DDR2 expression has been identified in various cancer types, making it as a promising therapeutic target. Additionally, cancer cells exhibit mechanosensing abilities, detecting changes in ECM stiffness, which is particularly important for carcinogenesis given the observed ECM stiffening in numerous cancer types. Despite these, whether collagen‐activated DDR2 signaling and ECM stiffness‐induced mechanosensing exert similar effects on cancer cell behavior and whether they operate through analogous mechanisms remain elusive. To address these questions, we performed bulk RNA sequencing (RNA‐seq) on human SH‐SY5Y neuroblastoma cells cultured on collagen‐coated substrates. Our results show that DDR2 downregulation induces significant changes in the cell transcriptome, with changes in expression of 15% of the genome, specifically affecting the genes associated with cell division and differentiation. We validated the RNA‐seq results by showing that DDR2 knockdown redirects the cell fate from proliferation to senescence. Like DDR2 knockdown, increasing substrate stiffness diminishes cell proliferation. Surprisingly, RNA‐seq indicates that substrate stiffness has no detectable effect on the transcriptome. Furthermore, DDR2 knockdown influences cellular responses to substrate stiffness changes, highlighting a crosstalk between these two ECM‐induced signaling pathways. Based on our results, we propose that the ECM could activate DDR2 signaling and mechanosensing in cancer cells to orchestrate their cell fate through distinct mechanisms, with or without involving gene expression, thus providing novel mechanistic insights into cancer progression.

          Abstract

          The ECM chemical composition and mechanical properties are crucial for tumor development. This study demonstrates that both knocking down the collagen receptor DDR2 and increasing ECM stiffness can reduce neuroblastoma cell proliferation. Surprisingly, RNA sequencing results show that the DDR2 knockdown significantly enhances the expression tumor suppressor genes in neuroblastoma cells, while the ECM stiffness does not.

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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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            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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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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                Author and article information

                Contributors
                szhou@wpi.edu
                qwen@wpi.edu
                Journal
                FEBS Open Bio
                FEBS Open Bio
                10.1002/(ISSN)2211-5463
                FEB4
                FEBS Open Bio
                John Wiley and Sons Inc. (Hoboken )
                2211-5463
                27 March 2024
                May 2024
                : 14
                : 5 ( doiID: 10.1002/feb4.v14.5 )
                : 867-882
                Affiliations
                [ 1 ] Department of Chemical Engineering Worcester Polytechnic Institute MA USA
                [ 2 ] Bancroft School Worcester MA USA
                [ 3 ] Nash Family Department of Neuroscience, Friedman Brain Institute Icahn School of Medicine at Mount Sinai New York NY USA
                [ 4 ] Black Family Stem Cell Institute Icahn School of Medicine at Mount Sinai New York NY USA
                [ 5 ] Department of Biomedical Engineering Wichita State University KS USA
                [ 6 ] Department of Neurobiology University of Massachusetts Medical School Worcester MA USA
                [ 7 ] Department of Pediatrics University of Massachusetts Medical School Worcester MA USA
                [ 8 ] Crnic Institute Boulder Branch, BioFrontiers Institute University of Colorado Boulder CO USA
                [ 9 ] Department of Physics Worcester Polytechnic Institute MA USA
                Author notes
                [*] [* ] Correspondence

                Q. Wen, Department of Physics, Worcester Polytechnic Institute, 100 Institute Rd, Worcester, MA 01609, USA

                E‐mail: qwen@ 123456wpi.edu

                and

                H. S. Zhou, Department of Chemical Engineering, Worcester Polytechnic Institute, 100 Institute Rd Worcester, MA 01609, USA

                E‐mail: szhou@ 123456wpi.edu

                Author information
                https://orcid.org/0000-0002-1344-065X
                https://orcid.org/0000-0001-7098-8251
                Article
                FEB413798 FEBSOPEN-23-0694.R1
                10.1002/2211-5463.13798
                11073507
                38538106
                4e13329d-1ca6-4b87-bc9d-6572ffc15367
                © 2024 The Authors. FEBS Open Bio published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 24 January 2024
                : 12 November 2023
                : 18 March 2024
                Page count
                Figures: 6, Tables: 0, Pages: 16, Words: 10167
                Funding
                Funded by: National Science Foundation , doi 10.13039/100000001;
                Award ID: 2150076
                Categories
                Extracellular Matrix
                Cancer Genetics and Genomics
                Transcriptomics
                Research Article
                Research Articles
                Custom metadata
                2.0
                May 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.2 mode:remove_FC converted:06.05.2024

                ddr2,ecm stiffness,pro‐proliferation,rna‐seq,senescence,transcriptome

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