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      Waterpipe smoke condensate influences epithelial to mesenchymal transition and interferes with the cytotoxic immune response in non-small cell lung cancer cell lines

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          Abstract

          Waterpipe tobacco smoking (WPS) continues to spread globally and presents serious health hazards. The aim of the present study was to investigate the effects of treatment with WPS condensate (WPSC) on lung cell proliferation and plasticity as well as tumor cell recognition and killing by natural killer (NK) cells using cytotoxicity assays. The results indicated that exposure of normal and cancer lung cell lines to WPSC resulted in a decrease in their in vitro growth in a dose-dependent manner and it induced tumor senescence. In addition, WPSC selectively caused DNA damage as revealed by an increase in γH2AX and 53BP1 in tumor lung cells. To gain further insight into the molecular mechanisms altered by WPSC, we conducted a global comprehensive transcriptome analysis of WPSC-treated tumor cells. Data analysis identified an expression profile of genes that best distinguished treated and non-treated cells involving several pathways. Of these pathways, we focused on those involved in epithelial to mesenchymal transition (EMT) and stemness. Results showed that WPSC induced an increase in SNAI2 expression associated with EMT, ACTA2 and SERPINE2 were involved in invasion and CD44 was associated with stemness. Furthermore, WPSC exposure increased the expression of inflammatory response genes including CASP1, IL1B, IL6 and CCL2. While immune synapse formation between NK and WPSC-treated lung cancer target cells was not affected, the capacity of NK cells to kill these target cells was reduced. The data reported in the present study are, to the best of our knowledge, the first in vitro demonstration of WPSC effects on lung cellular parameters providing evidence of its potential involvement in tumor physiology and development.

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          Most cited references56

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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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            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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              The Molecular Signatures Database (MSigDB) hallmark gene set collection.

              The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.
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                Author and article information

                Journal
                Oncol Rep
                Oncol Rep
                Oncology Reports
                D.A. Spandidos
                1021-335X
                1791-2431
                March 2021
                18 January 2021
                18 January 2021
                : 45
                : 3
                : 879-890
                Affiliations
                [1 ]Thumbay Research Institute for Precision Medicine, Gulf Medical University, Ajman 4184, UAE
                [2 ]INSERM UMR 1186, Integrative Tumour Immunology and Immunotherapy, Gustave Roussy, Faculty of Medicine - University of Paris-Sud, University of Paris-Saclay, F-94805 Villejuif, France
                [3 ]Department of Biology, Chemistry and Environmental Sciences (BCE), American University of Sharjah, Sharjah 26666, UAE
                Author notes
                Correspondence to: Dr Rania Faouzi Zaarour, Thumbay Research Institute for Precision Medicine, Gulf Medical University, P.O. Box 4148, Ajman 4184, UAE, E-mail: dr.rania@ 123456gmu.ac.ae
                Article
                or-45-03-0879
                10.3892/or.2021.7938
                7859923
                33469682
                c0d03beb-3b35-4766-8987-0fe8c323fbae
                Copyright: © Zaarour et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 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
                : 13 March 2020
                : 12 October 2020
                Funding
                Funded by: Al Jalila Foundation
                Award ID: AJF 2018009
                Funded by: Research and Graduate Studies at the American University of Sharjah
                Award ID: FRG19-L-S11
                The present study was supported by Al Jalila Foundation (AJF 2018009) to Zaarour. The smoke sampling and analysis research were funded by the office of Research and Graduate Studies at the American University of Sharjah (FRG19-L-S11).
                Categories
                Articles

                waterpipe smoke,lung cancer,epithelial to mesenchymal transition,cancer stem cells,inflammation,tumor microenvironment,natural killer-mediated cytotoxicity

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