Computer methods in biomechanics and biomedical engineering · 2024
Identification of exosome-related gene features in psoriasis and construction of a diagnostic model via integrated bioinformatics analysis.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Chen Lifen, Zhu Shuangmei, Zhao Lu, Ye Wenxia
Аннотация
BACKGROUND: Psoriasis, a chronic inflammatory dermatosis, profoundly affects patients' well-being. Although exosomes are key in disease etiology, diagnostic potentials of associated genes are unclear. Our research targeted bioinformatics-based characterization of exosome-related genes and the development of a diagnostic model for psoriasis.
METHODS: Within GSE30999 dataset, an exosome-centric diagnostic model was formulated. Its diagnostic capability was appraised in GSE30999 and GSE14905 cohorts. Human keratinocytes (HaCaT) were used to construct psoriasis cell model. qRT-PCR was used to detect expression of diagnostic genes in the model. Construction of a protein-protein interaction network was undertaken, complemented by enrichment analyses. Comparative evaluation of immunological microenvironments between healthy controls and disease cohort was executed. Prospective miRNAs and transcription factors (TFs) were prognosticated using online prediction tools.
RESULTS: A distinctive diagnostic model with superior diagnostic performance, evidenced by an AUC value greater than 0.88, was unveiled. The model featured seven exosome-related biomarker genes (CCNA2, NDC80, CCNB1, CDCA8, KIF11, CENPF, and ASPM) interwoven in a complex network and chiefly linked in the regulation of Cell Cycle and Cellular Senescence. These genes were significantly overexpressed in psoriasis cell models. Immune infiltration analysis distinguished profound discrepancies (p < 0.05) in immunological microenvironment between disease and control groups with enrichment of T cells CD4 memory activated, Macrophages M1, and Neutrophils in the disease group. 11 miRNAs and 27 TFs were identified.
CONCLUSION: The study introduces a new and potent diagnostic model for psoriasis, with selection of credible exosome-associated biomarker genes. These discoveries aid in clinical diagnostics and research on exosome involvement in psoriasis.
METHODS: Within GSE30999 dataset, an exosome-centric diagnostic model was formulated. Its diagnostic capability was appraised in GSE30999 and GSE14905 cohorts. Human keratinocytes (HaCaT) were used to construct psoriasis cell model. qRT-PCR was used to detect expression of diagnostic genes in the model. Construction of a protein-protein interaction network was undertaken, complemented by enrichment analyses. Comparative evaluation of immunological microenvironments between healthy controls and disease cohort was executed. Prospective miRNAs and transcription factors (TFs) were prognosticated using online prediction tools.
RESULTS: A distinctive diagnostic model with superior diagnostic performance, evidenced by an AUC value greater than 0.88, was unveiled. The model featured seven exosome-related biomarker genes (CCNA2, NDC80, CCNB1, CDCA8, KIF11, CENPF, and ASPM) interwoven in a complex network and chiefly linked in the regulation of Cell Cycle and Cellular Senescence. These genes were significantly overexpressed in psoriasis cell models. Immune infiltration analysis distinguished profound discrepancies (p < 0.05) in immunological microenvironment between disease and control groups with enrichment of T cells CD4 memory activated, Macrophages M1, and Neutrophils in the disease group. 11 miRNAs and 27 TFs were identified.
CONCLUSION: The study introduces a new and potent diagnostic model for psoriasis, with selection of credible exosome-associated biomarker genes. These discoveries aid in clinical diagnostics and research on exosome involvement in psoriasis.