Literature DB >> 32950480

Systematic Transcriptional Profiling of Responses to STAT1- and STAT3-Activating Cytokines in Different Cancer Types.

Mélanie Kirchmeyer1, Florence Servais1, Aurélien Ginolhac1, Petr V Nazarov2, Christiane Margue1, Demetra Philippidou1, Nathalie Nicot2, Iris Behrmann1, Claude Haan1, Stephanie Kreis3.   

Abstract

Cytokines orchestrate responses to pathogens and in inflammatory processes, but they also play an important role in cancer by shaping the expression levels of cytokine response genes. Here, we conducted a large profiling study comparing miRNome and mRNA transcriptome data generated following different cytokine stimulations. Transcriptomic responses to STAT1- (IFNγ, IL-27) and STAT3-activating cytokines (IL6, OSM) were systematically compared in nine cancerous and non-neoplastic cell lines of different tissue origins (skin, liver and colon). The largest variation in our datasets was seen between cell lines of the three different tissues rather than stimuli. Notably, the variability in miRNome datasets was a lot more pronounced than in mRNA data. Our data also revealed that cells of skin, liver and colon tissues respond very differently to cytokines and that the cell signaling networks activated or silenced in response to STAT1- or STAT3-activating cytokines are specific to the tissue and the type of cytokine. However, globally, STAT1-activating cytokines had stronger effects than STAT3-inducing cytokines with most significant responses in liver cells, showing more genes upregulated and with higher fold change. A more detailed analysis of gene regulations upon cytokine stimulation in these cells provided insights into STAT1- versus STAT3-driven processes in hepatocarcinogenesis. Finally, independent component analysis revealed interconnected transcriptional networks distinct between cancer cells and their healthy counterparts.
Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Cancer; Cytokines; Profiling; Signaling; Transcriptome

Year:  2020        PMID: 32950480     DOI: 10.1016/j.jmb.2020.09.011

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  2 in total

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Authors:  Lei Guo; Jiali Sun; Changjun Wang; Yang Wang; Ya Wang; Dong Li; Yuliang Li
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Review 2.  JAK-STAT core cancer pathway: An integrative cancer interactome analysis.

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Journal:  J Cell Mol Med       Date:  2022-03-01       Impact factor: 5.310

  2 in total

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