Identification of PRKCQ-AS1 as a Keratinocyte-Derived Exosomal lncRNA That Promotes Th17 Differentiation and IL-17 secretion in Psoriasis Through Bioinformatics, Machine Learning Algorithms, and Cell Experiments

Psoriasis is an immune-mediated skin disease where Th17 cell differentiation and IL-17 secretion play critical roles. This study investigates key exosomal ncRNAs regulating the Th17/IL-17 axis in psoriasis and their mechanisms. We integrated bulk RNA sequencing datasets from the GEO database to cons...

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Bibliographic Details
Published in:Journal of inflammation research Vol. 18; no. Issue 1; pp. 6557 - 6582
Main Authors: Gao, Pengfei, Gao, Xiaolu, Lin, Long, Zhang, Ming, Luo, Dongqiang, Chen, Chuyan, Li, Yujie, He, Yufeng, Liu, Xianmiao, Shi, Chunyu, Yang, Ruisi
Format: Journal Article
Language:English
Published: New Zealand Taylor & Francis Ltd 01.01.2025
Dove
Dove Medical Press
Subjects:
Bioinformatics
Biological products
CD4 antigen
Cell activation
Cell culture
Cell differentiation
Cells
Datasets
Exosomes
Gene set enrichment analysis
Genes
Genome-wide association studies
Helper cells
Immune system
Immunofluorescence
Infiltration
Interleukin 17
Keratinocytes
Learning algorithms
Lymphocytes
Lymphocytes T
Machine learning
MicroRNAs
Non-coding RNA
Original Research
pathogenesis
PRKCQ-AS1
Psoriasis
Ribonucleic acid
RNA
Signal transduction
Skin diseases
Stat3 protein
Th17
Transfection
pathogenesis
Th17
exosomes
psoriasis
bioinformatics
PRKCQ-AS1
ISSN:1178-7031, 1178-7031
Online Access:Get full text
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Summary:Psoriasis is an immune-mediated skin disease where Th17 cell differentiation and IL-17 secretion play critical roles. This study investigates key exosomal ncRNAs regulating the Th17/IL-17 axis in psoriasis and their mechanisms. We integrated bulk RNA sequencing datasets from the GEO database to construct and evaluate exosome-related patterns. Subsequently, exosome-related ncRNAs in psoriasis lesions were identified primarily through weighted gene co-expression network analysis and five machine learning algorithms. Additionally, large-scale integrated single-cell RNA sequencing data and genome-wide association study (GWAS) data were included to investigate the mechanisms of key ncRNA, primarily through immune infiltration analysis, gene set enrichment analysis (GSEA), co-expression analysis, and Mendelian randomization. Finally, the mechanisms of key ncRNA were confirmed primarily through cell co-culture and lentiviral transfection, assessed by immunofluorescence, qRT-PCR, and Western blot. We identified 10 exosome-related ncRNAs, including PRKCQ-AS1, and constructed five machine learning models with excellent diagnostic performance, emphasizing PRKCQ-AS1's significance. Mendelian randomization demonstrated a causal relationship between PRKCQ-AS1 and psoriasis. Immune infiltration analysis and GSEA indicated that PRKCQ-AS1 influences the infiltration pattern of CD4 T cells, promotes Th17 differentiation, and is related to STAT3. The expression distribution in single-cell RNA sequencing data suggested that exosomal PRKCQ-AS1 may originate from keratinocytes, and co-expression analysis supported its role in STAT3 activation within lymphocytes. Co-culture experiments confirmed that keratinocytes in psoriasis models, as well as keratinocytes overexpressing PRKCQ-AS1, can upregulate PRKCQ-AS1 levels in CD4 T cells via exosomes, promoting Th17 cell differentiation and IL-17 secretion. Consistent results and STAT3 signaling pathway activation were detected in CD4 T cells overexpressing PRKCQ-AS1. PRKCQ-AS1 is an exosomal lncRNA from keratinocytes in psoriasis, promoting Th17 differentiation and IL-17 secretion through STAT3 activation. This finding deepens the understanding of psoriasis pathogenesis and provides a basis for targeted therapies.
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ISSN:1178-7031
1178-7031
DOI:10.2147/JIR.S521553