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Bioinformatics analyses of combined databases identify shared differentially expressed genes in cancer and autoimmune disease

BACKGROUND: Inadequate immunity caused by poor immune surveillance leads to tumorigenesis, while excessive immunity due to breakdown of immune tolerance causes autoimmune genesis. Although the function of immunity during the onset of these two processes appears to be distinct, the underlying mechani...

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Autores principales: Sui, Yuan, Li, Shuping, Fu, Xue-Qi, Zhao, Zhizhuang Joe, Xing, Shu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921081/
https://www.ncbi.nlm.nih.gov/pubmed/36765396
http://dx.doi.org/10.1186/s12967-023-03943-9
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author Sui, Yuan
Li, Shuping
Fu, Xue-Qi
Zhao, Zhizhuang Joe
Xing, Shu
author_facet Sui, Yuan
Li, Shuping
Fu, Xue-Qi
Zhao, Zhizhuang Joe
Xing, Shu
author_sort Sui, Yuan
collection PubMed
description BACKGROUND: Inadequate immunity caused by poor immune surveillance leads to tumorigenesis, while excessive immunity due to breakdown of immune tolerance causes autoimmune genesis. Although the function of immunity during the onset of these two processes appears to be distinct, the underlying mechanism is shared. To date, gene expression data for large bodies of clinical samples are available, but the resemblances of tumorigenesis and autoimmune genesis in terms of immune responses remains to be summed up. METHODS: Considering the high disease prevalence, we chose invasive ductal carcinoma (IDC) and systemic lupus erythematosus (SLE) to study the potential commonalities of immune responses. We obtained gene expression data of IDC/SLE patients and normal controls from five IDC databases (GSE29044, GSE21422, GSE22840, GSE15852, and GSE9309) and five SLE databases (GSE154851, GSE99967, GSE61635, GSE50635, and GSE17755). We intended to identify genes differentially expressed in both IDC and SLE by using three bioinformatics tools including GEO2R, the limma R package, and Weighted Gene Co-expression Network Analysis (WGCNA) to perform function enrichment, protein-protein network, and signaling pathway analyses. RESULTS: The mRNA levels of signal transducer and activator of transcription 1 (STAT1), 2'-5'-oligoadenylate synthetase 1 (OAS1), 2'-5'-oligoadenylate synthetase like (OASL), and PML nuclear body scaffold (PML) were found to be differentially expressed in both IDC and SLE by using three different bioinformatics tools of GEO2R, the limma R package and WGCNA. From the combined databases in this study, the mRNA levels of STAT1 and OAS1 were increased in IDC while reduced in SLE. And the mRNA levels of OASL and PML were elevated in both IDC and SLE. Based on Kyoto Encyclopedia of Genes and Genomes pathway analysis and QIAGEN Ingenuity Pathway Analysis, both IDC and SLE were correlated with the changes of multiple components involved in the Interferon (IFN)-Janus kinase (JAK)-signal transducer and activator of transcription (STAT) signaling pathway. CONCLUSION: The expression levels of STAT1 and OAS1 manifest the opposite expression tendency across cancer and autoimmune disease. They are components in the IFN-JAK-STAT signaling pathway related to both tumorigenesis and autoimmune genesis. STAT1 and OAS1-associated IFN-JAK-STAT signaling could explain the commonalities during tumorigenesis and autoimmune genesis and render significant information for more precise treatment from the point of immune homeostasis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-03943-9.
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spelling pubmed-99210812023-02-12 Bioinformatics analyses of combined databases identify shared differentially expressed genes in cancer and autoimmune disease Sui, Yuan Li, Shuping Fu, Xue-Qi Zhao, Zhizhuang Joe Xing, Shu J Transl Med Research BACKGROUND: Inadequate immunity caused by poor immune surveillance leads to tumorigenesis, while excessive immunity due to breakdown of immune tolerance causes autoimmune genesis. Although the function of immunity during the onset of these two processes appears to be distinct, the underlying mechanism is shared. To date, gene expression data for large bodies of clinical samples are available, but the resemblances of tumorigenesis and autoimmune genesis in terms of immune responses remains to be summed up. METHODS: Considering the high disease prevalence, we chose invasive ductal carcinoma (IDC) and systemic lupus erythematosus (SLE) to study the potential commonalities of immune responses. We obtained gene expression data of IDC/SLE patients and normal controls from five IDC databases (GSE29044, GSE21422, GSE22840, GSE15852, and GSE9309) and five SLE databases (GSE154851, GSE99967, GSE61635, GSE50635, and GSE17755). We intended to identify genes differentially expressed in both IDC and SLE by using three bioinformatics tools including GEO2R, the limma R package, and Weighted Gene Co-expression Network Analysis (WGCNA) to perform function enrichment, protein-protein network, and signaling pathway analyses. RESULTS: The mRNA levels of signal transducer and activator of transcription 1 (STAT1), 2'-5'-oligoadenylate synthetase 1 (OAS1), 2'-5'-oligoadenylate synthetase like (OASL), and PML nuclear body scaffold (PML) were found to be differentially expressed in both IDC and SLE by using three different bioinformatics tools of GEO2R, the limma R package and WGCNA. From the combined databases in this study, the mRNA levels of STAT1 and OAS1 were increased in IDC while reduced in SLE. And the mRNA levels of OASL and PML were elevated in both IDC and SLE. Based on Kyoto Encyclopedia of Genes and Genomes pathway analysis and QIAGEN Ingenuity Pathway Analysis, both IDC and SLE were correlated with the changes of multiple components involved in the Interferon (IFN)-Janus kinase (JAK)-signal transducer and activator of transcription (STAT) signaling pathway. CONCLUSION: The expression levels of STAT1 and OAS1 manifest the opposite expression tendency across cancer and autoimmune disease. They are components in the IFN-JAK-STAT signaling pathway related to both tumorigenesis and autoimmune genesis. STAT1 and OAS1-associated IFN-JAK-STAT signaling could explain the commonalities during tumorigenesis and autoimmune genesis and render significant information for more precise treatment from the point of immune homeostasis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-03943-9. BioMed Central 2023-02-10 /pmc/articles/PMC9921081/ /pubmed/36765396 http://dx.doi.org/10.1186/s12967-023-03943-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Sui, Yuan
Li, Shuping
Fu, Xue-Qi
Zhao, Zhizhuang Joe
Xing, Shu
Bioinformatics analyses of combined databases identify shared differentially expressed genes in cancer and autoimmune disease
title Bioinformatics analyses of combined databases identify shared differentially expressed genes in cancer and autoimmune disease
title_full Bioinformatics analyses of combined databases identify shared differentially expressed genes in cancer and autoimmune disease
title_fullStr Bioinformatics analyses of combined databases identify shared differentially expressed genes in cancer and autoimmune disease
title_full_unstemmed Bioinformatics analyses of combined databases identify shared differentially expressed genes in cancer and autoimmune disease
title_short Bioinformatics analyses of combined databases identify shared differentially expressed genes in cancer and autoimmune disease
title_sort bioinformatics analyses of combined databases identify shared differentially expressed genes in cancer and autoimmune disease
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921081/
https://www.ncbi.nlm.nih.gov/pubmed/36765396
http://dx.doi.org/10.1186/s12967-023-03943-9
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