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Identification immune response genes in psoriasis after treatment with secukinumab

BACKGROUND: Secukinumab is a fully human IgG1κ MoAb that selectively binds to IL-17A with high affinity, and it has been proven effective for the treatment of psoriasis. However, the immune response pathways and mechanisms during the treatment are still masked. Therefore, the current study was desig...

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Autores principales: Wang, Jing, Liu, Yufang, Zhang, Yuxin, Wang, Shiyan, Kang, Shaomei, Mi, Ningyu, Li, Ruxin, Zou, Yulin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10082531/
https://www.ncbi.nlm.nih.gov/pubmed/37029373
http://dx.doi.org/10.1186/s12920-023-01507-w
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author Wang, Jing
Liu, Yufang
Zhang, Yuxin
Wang, Shiyan
Kang, Shaomei
Mi, Ningyu
Li, Ruxin
Zou, Yulin
author_facet Wang, Jing
Liu, Yufang
Zhang, Yuxin
Wang, Shiyan
Kang, Shaomei
Mi, Ningyu
Li, Ruxin
Zou, Yulin
author_sort Wang, Jing
collection PubMed
description BACKGROUND: Secukinumab is a fully human IgG1κ MoAb that selectively binds to IL-17A with high affinity, and it has been proven effective for the treatment of psoriasis. However, the immune response pathways and mechanisms during the treatment are still masked. Therefore, the current study was designed to investigate the potential immune response genes via bioinformatics approaches. METHODS: Gene expression data of severe plaque-type psoriasis was retrieved from the GEO database. Quantification of immune infiltration by ssGSEA and identification of differentially infiltrated immune cells were conducted to validate the treatment effect of secukinumab. After data processing, differentially expressed genes were identified between the treatment and untreated group. TC-seq was employed to analyze the trend of gene expression and clustering analysis. IL-17 therapeutic immune response genes were selected by taking the intersection of the genes inside the key cluster set and the MAD3-PSO geneset. Based on these therapeutic response genes, protein–protein interaction networks were built for key hub gene selection. These hub genes would work as potential immune response genes, and be validated via an external dataset. RESULTS: Enrichment scores calculated by ssGSEA illustrated that the immune infiltration level of T cells had a strong difference before and after medication, which validated the treatment effect of Secukinumab. 1525 genes that have significantly different expression patterns before and after treatment were extracted for further analysis, and the enrichment result shows that these genes have the function related to epidermal development, differentiation, and keratinocytes differentiation. After overlapping candidate genes with MAD3-PSO gene set, 695 genes were defined as anti-IL7A treatment immune response genes, which were mainly enriched in receptor signaling and IL-17 signaling pathways. Hub gene were pinpointed from the PPI network constructed by anti-IL7A treatment immune response genes, their expression pattern fits TC-seq gene expression pattern. CONCLUSION: Our study revealed the potential anti-IL7A treatment immune response genes, and the central hub genes, which may act critical roles in Secukinumab, induced immune response. This would open up a novel and effective avenue for the treatment of psoriasis.
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spelling pubmed-100825312023-04-09 Identification immune response genes in psoriasis after treatment with secukinumab Wang, Jing Liu, Yufang Zhang, Yuxin Wang, Shiyan Kang, Shaomei Mi, Ningyu Li, Ruxin Zou, Yulin BMC Med Genomics Research BACKGROUND: Secukinumab is a fully human IgG1κ MoAb that selectively binds to IL-17A with high affinity, and it has been proven effective for the treatment of psoriasis. However, the immune response pathways and mechanisms during the treatment are still masked. Therefore, the current study was designed to investigate the potential immune response genes via bioinformatics approaches. METHODS: Gene expression data of severe plaque-type psoriasis was retrieved from the GEO database. Quantification of immune infiltration by ssGSEA and identification of differentially infiltrated immune cells were conducted to validate the treatment effect of secukinumab. After data processing, differentially expressed genes were identified between the treatment and untreated group. TC-seq was employed to analyze the trend of gene expression and clustering analysis. IL-17 therapeutic immune response genes were selected by taking the intersection of the genes inside the key cluster set and the MAD3-PSO geneset. Based on these therapeutic response genes, protein–protein interaction networks were built for key hub gene selection. These hub genes would work as potential immune response genes, and be validated via an external dataset. RESULTS: Enrichment scores calculated by ssGSEA illustrated that the immune infiltration level of T cells had a strong difference before and after medication, which validated the treatment effect of Secukinumab. 1525 genes that have significantly different expression patterns before and after treatment were extracted for further analysis, and the enrichment result shows that these genes have the function related to epidermal development, differentiation, and keratinocytes differentiation. After overlapping candidate genes with MAD3-PSO gene set, 695 genes were defined as anti-IL7A treatment immune response genes, which were mainly enriched in receptor signaling and IL-17 signaling pathways. Hub gene were pinpointed from the PPI network constructed by anti-IL7A treatment immune response genes, their expression pattern fits TC-seq gene expression pattern. CONCLUSION: Our study revealed the potential anti-IL7A treatment immune response genes, and the central hub genes, which may act critical roles in Secukinumab, induced immune response. This would open up a novel and effective avenue for the treatment of psoriasis. BioMed Central 2023-04-07 /pmc/articles/PMC10082531/ /pubmed/37029373 http://dx.doi.org/10.1186/s12920-023-01507-w 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
Wang, Jing
Liu, Yufang
Zhang, Yuxin
Wang, Shiyan
Kang, Shaomei
Mi, Ningyu
Li, Ruxin
Zou, Yulin
Identification immune response genes in psoriasis after treatment with secukinumab
title Identification immune response genes in psoriasis after treatment with secukinumab
title_full Identification immune response genes in psoriasis after treatment with secukinumab
title_fullStr Identification immune response genes in psoriasis after treatment with secukinumab
title_full_unstemmed Identification immune response genes in psoriasis after treatment with secukinumab
title_short Identification immune response genes in psoriasis after treatment with secukinumab
title_sort identification immune response genes in psoriasis after treatment with secukinumab
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10082531/
https://www.ncbi.nlm.nih.gov/pubmed/37029373
http://dx.doi.org/10.1186/s12920-023-01507-w
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