Transcriptomic landscaping of core genes and pathways of mild and severe psoriasis vulgaris

Choudhary, Saumya; Anand, R Pream; Pradhan, Dibyabhaba; Bastia, Banajit; Kumar, Sandeep; Singh, Harpreet; Puri, Poonam; Thomas, George; Jain, Arun K.

doi:10.3892/ijmm.2020.4771

Cited by 27 publications

(15 citation statements)

References 65 publications

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“…13,32 Indeed, Choudhary et al even demonstrated that CCNB1 is one of the central targets of severe psoriasis. 14 However, to date, the potential pathological mechanisms of CCNB1 and CCNB2 in psoriasis remain unclear.…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…12,13 Bioinformatics analyses by Choudhary and Melero showed that CCNB1 is a core target in the onset mechanism of psoriasis and may contribute to the transformation of mild to severe psoriasis. 14,15 Furthermore, Li et al showed that CCNB2 expression ameliorates the symptoms of psoriasis patients. 16 Indeed, bioinformatics analyses by Zou et al further showed that CCNB1 and CCNB2 levels are correlated with several immune cell types, including CD4 þ T cells, CD8 þ T cells, B cells, neutrophils, and macrophages.…”

Section: Introductionmentioning

confidence: 99%

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CCNB1 and CCNB2 involvement in the pathogenesis of psoriasis: a bioinformatics study

Chen

Chen³

et al. 2022

J Int Med Res

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Objective The cell cycle-related proteins cyclin B1 (CCNB1) and cyclin B2 (CCNB2) are potentially involved in the underlying mechanisms of psoriasis. The present study aimed to explore this possibility using bioinformatics approaches. Methods CCNB1 and CCNB2 protein levels were evaluated in 14 psoriasis patients and five healthy controls by enzyme-linked immunosorbent assays, and their mRNA levels were evaluated using data from four publicly available datasets (GSE53552, GSE41664, GSE14905, and GSE13355). Comparison of high- and low-expressing groups were performed to reveal CCNB1- and CCNB2-related differentially expressed genes, which were then assessed based on gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses. Correlation analyses between CCNB1 and CCNB2 levels and immune infiltration, as well as typical targets of psoriasis, were also performed. Results Overall, 12 CCNB1 and CCNB2 common immune-related targets potentially involved in psoriasis were identified. These could regulate the cell cycle of through multiple pathways. In addition, CCNB1 and CCNB2 were found to potentially support the release of key molecular targets of psoriasis through the regulation of mast cell activation and macrophage polarization. Conclusions These findings suggest that CCNB1 and CCNB2 may represent valuable molecular biomarkers of psoriasis, contributing to its onset and progression.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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CCNB1 and CCNB2 involvement in the pathogenesis of psoriasis: a bioinformatics study

Chen

Chen³

et al. 2022

J Int Med Res

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“…A recent study has shown that Ps deregulated genes were found. These genes are involving cytokine-cytokine receptor interaction, cell cycle and cell adhesion molecules and these candidate genes regulating important immune pathways can be new therapeutic targets in Ps [96]. There are more than 50 genetic susceptible biomarkers associated with the risk of Ps.…”

Section: Immune Molecules As Biomarkers In Psoriasismentioning

confidence: 99%

Immune Markers in Psoriasis

Surcel¹,

Munteanu²,

Constantin³

et al. 2022

Psoriasis - New Research

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Psoriasis is a chronic inflammatory skin disorder with high immunological background caused by a complex interplay between an altered immune system, genetic factors, autoantigens, lifestyle, and environmental factors. Extensive literature in recent years highlighted the crucial role played by the immune system in the pathogenesis of this pathology. Although it is unequivocally accepted that psoriasis is a T-cell mediated autoimmune condition, both innate and specific immune cells are highly involved in the pathogenesis of psoriasis. The aberrant interactions between immune cells and resident hyper-proliferative keratinocytes are mediated by immune and non-immune related molecules which lead to amplification of the local immune responses, that maintain the chronic inflammatory status. In this chapter, we will highlight the immune molecules resident in the psoriatic tissue or appending to the blood circulation that can indicate the prognosis of this systemic autoimmune disease. Moreover, we will focus on immune cells resident or circulating ones that can pinpoint the clinical evolution of the psoriatic disease. All these data can be developed in immune markers patterns that aid psoriasis diagnosis and/or future (immune)therapies.

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“…In recent years, new insights into the molecular mechanisms and therapeutic targets of psoriasis have been provided by bioinformatics analysis ( 10 ). A pooled analysis of DEGs in psoriasis will remind us of the etiology of the disease, as these DEGs may reflect the common skin reactions that occur in many skin diseases in the absence of common causal mechanisms, and prognostic analyses have no evidence of significant differences between patients treated with guselkumab ( 11 , 12 ).…”

Section: Introductionmentioning

confidence: 99%

Based on Gene Expression Analysis: Low-Density Neutrophil Expression Is a Characteristic of the Fast Responders Treated With Guselkumab for Psoriasis

Wang

Liu

et al. 2022

Front. Immunol.

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Psoriasis is a worldwide chronic inflammatory skin disease. The treatment of disease is usually designed according to its severity. In this research, RNA-seq was performed on 37 patients with psoriasis treated with guselkumab before and after treatment, and the patients were divided into fast responder and slow responder according to PASI score to analyze the differentially expressed genes (DEGs) between them. Moreover, The biological mechanism of psoriasis was explored by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Gene Ontology (GO) analysis, and Gene Set Enrichment Analysis (GSEA) analysis. And then, this protein-protein interaction network was constructed and 17 DEGs including IL-1β, CXCL8, S100A12 and MMP9 were analyzed by GSVA. DEGs were detected by GO and KEGG analysis of target genes, which were primarily associated with immune response, neutrophil activation, neutrophil degranulation. GSEA reminded that fast responders were mainly involved in low-density neutrophils and abundant NK cells. And the GSVA showed that the DEGs were down-regulated after the early stage of the fast responder and the reverse in the slow responder by GSVA analysis. On the whole, these results indicated that these DEGs may serve as a psoriasis potential diagnostic and predictive biomarkers after been treated by guselkumab.

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Transcriptomic landscaping of core genes and pathways of mild and severe psoriasis vulgaris

Cited by 27 publications

References 65 publications

CCNB1 and CCNB2 involvement in the pathogenesis of psoriasis: a bioinformatics study

CCNB1 and CCNB2 involvement in the pathogenesis of psoriasis: a bioinformatics study

Immune Markers in Psoriasis

Based on Gene Expression Analysis: Low-Density Neutrophil Expression Is a Characteristic of the Fast Responders Treated With Guselkumab for Psoriasis

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