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      Comparative analysis of basal and etoposide-induced alterations in gene expression by DNA-PKcs kinase activity

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          Abstract

          Background: Maintenance of the genome is essential for cell survival, and impairment of the DNA damage response is associated with multiple pathologies including cancer and neurological abnormalities. DNA-PKcs is a DNA repair protein and a core component of the classical nonhomologous end-joining pathway, but it also has roles in modulating gene expression and thus, the overall cellular response to DNA damage.

          Methods: Using cells producing either wild-type (WT) or kinase-inactive (KR) DNA-PKcs, we assessed global alterations in gene expression in the absence or presence of DNA damage. We evaluated differential gene expression in untreated cells and observed differences in genes associated with cellular adhesion, cell cycle regulation, and inflammation-related pathways. Following exposure to etoposide, we compared how KR versus WT cells responded transcriptionally to DNA damage.

          Results: Downregulated genes were mostly involved in protein, sugar, and nucleic acid biosynthesis pathways in both genotypes, but enriched biological pathways were divergent, again with KR cells manifesting a more robust inflammatory response compared to WT cells. To determine what major transcriptional regulators are controlling the differences in gene expression noted, we used pathway analysis and found that many master regulators of histone modifications, proinflammatory pathways, cell cycle regulation, Wnt/β-catenin signaling, and cellular development and differentiation were impacted by DNA-PKcs status. Finally, we have used qPCR to validate selected genes among the differentially regulated pathways to validate RNA sequence data.

          Conclusion: Overall, our results indicate that DNA-PKcs, in a kinase-dependent fashion, decreases proinflammatory signaling following genotoxic insult. As multiple DNA-PK kinase inhibitors are in clinical trials as cancer therapeutics utilized in combination with DNA damaging agents, understanding the transcriptional response when DNA-PKcs cannot phosphorylate downstream targets will inform the overall patient response to combined treatment.

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          Most cited references81

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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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            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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              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
                URI : https://loop.frontiersin.org/people/1049519/overviewRole: Role: Role:
                Role: Role: Role: Role: Role:
                Role: Role: Role:
                URI : https://loop.frontiersin.org/people/2407683/overviewRole: Role: Role: Role:
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                URI : https://loop.frontiersin.org/people/2041601/overview
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                21 March 2024
                2024
                : 15
                : 1276365
                Affiliations
                [1] 1 Department of Chemistry and Biochemistry , New Mexico State University , Las Cruces, NM, United States
                [2] 2 National Center for Genome Resources , Santa Fe, NM, United States
                Author notes

                Edited by: Ata Abbas, Case Western Reserve University, United States

                Reviewed by: Atrayee Bhattacharya, Dana–Farber Cancer Institute, United States

                Waldemar Wagner, Polish Academy of Sciences, Poland

                Anthony J. Davis, University of Texas Southwestern Medical Center, United States

                *Correspondence: Amanda K. Ashley, ashleyak@ 123456nmsu.edu
                Article
                1276365
                10.3389/fgene.2024.1276365
                10991847
                38577247
                8d1509b7-30ab-43db-b1c5-4df217646652
                Copyright © 2024 Ali, Najaf-Panah, Pyper, Lujan, Sena and Ashley.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 11 August 2023
                : 29 January 2024
                Funding
                Funded by: National Institute of General Medical Sciences , doi 10.13039/100000057;
                The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. Research reported in this publication was supported by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under grant number P20GM103451.
                Categories
                Genetics
                Original Research
                Custom metadata
                Cancer Genetics and Oncogenomics

                Genetics
                dna-pkcs,dna damage repair,non-homologous end-joining,etoposide,gene expression,transcriptome
                Genetics
                dna-pkcs, dna damage repair, non-homologous end-joining, etoposide, gene expression, transcriptome

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