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    請使用永久網址來引用或連結此文件: https://ir.lib.ncu.edu.tw/handle/987654321/99394


    題名: 成人與青少年皮肌炎轉錄體途徑的生物資訊分析及潛在藥物預測;Bioinformatic Analysis of Transcriptomic Pathways in Adult and Juvenile Dermatomyositis with Potential Drug Prediction
    作者: 蕭朝陽;Hsiao, Chao-Yang
    貢獻者: 跨領域轉譯醫學研究所
    關鍵詞: 皮肌炎;幼年型皮肌炎;差異表達基因;生物資訊學;干擾素訊號;藥物重定位;Dermatomyositis;Juvenile Dermatomyositis;Differential Expressed Gene;Bioinformatics;Interferon Signaling;Drug Repurposing
    日期: 2025-11-18
    上傳時間: 2026-03-06 18:53:08 (UTC+8)
    出版者: 國立中央大學
    摘要: 皮肌炎(Dermatomyositis, DM)與幼年型皮肌炎(Juvenile Dermatomyositis, JDM)為一類罕見的特發性發炎性肌肉病變(Idiopathic Inflammatory Myopathies, IIMs),其特徵為骨骼肌慢性發炎與免疫反應導致的組織損傷。雖然成人與幼年型皮肌炎在臨床表現及病理組織學上有許多相似之處,但近年研究顯示兩者在病生理機轉上也存在差異。本研究目的為使用生物資訊學方法,系統性分析成人與幼年型皮肌炎的共同與特異性轉錄體特徵,並利用藥物篩選平台(drug screening platform)預測潛在的治療候選化合物。
    本研究自 Gene Expression Omnibus (GEO) 資料庫取得肌肉切片微陣列資料集,包括成人皮肌炎 GSE128470、GSE5370、GSE2044 及幼年型皮肌炎 GSE11971、GSE3307。利用 TAC軟體進行批次校正與差異表達基因分析(DEG analysis)。經由 Gene Ontology (GO) 與 Kyoto Encyclopedia of Genes and Genomes (KEGG) 進行功能富集分析,並透過 STRING 與 Cytoscape 建立蛋白質交互作用網路(PPI network)及篩選樞紐基因(hub genes)。候選藥物則以 LINCS L1000CDS2 平台進行預測。
    結果顯示,成人皮肌炎共鑑定出 850 個差異表達基因,主要富集於抗病毒、發炎與免疫相關路徑,包括第一型干擾素反應、MAPK 及 NOD-like receptor 訊號途徑。幼年型皮肌炎共鑑定出 2,544 個差異表達基因,顯示出干擾素驅動的先天免疫活化、細胞黏附、血管新生及 PI3K–Akt 訊號上調。兩組比較後共有 437 個重疊基因,顯示兩者皆具有干擾素介導之「類病毒免疫表現型」;然而,幼年型皮肌炎呈現更明顯的血管重塑與細胞黏附。樞紐基因分析指出 STAT1, DDX58, IFIH1, CXCL10, ISG15, MX1, GBP1, EIF2AK2 為疾病關鍵調控基因。藥物預測結果中,XMD-1150 與 KM 00927 同時被預測為成人與幼年型皮肌炎的共同候選治療化合物。
    綜合而言,本研究以整合轉錄體分析闡明了成人與幼年型皮肌炎之共同與差異的分子機制,指出干擾素介導的免疫活化為兩者共同核心特徵,而血管與細胞黏附訊號的上調則以幼年型皮肌炎較為顯著。所預測之候選藥物提供了後續實驗驗證與精準治療開發的潛在方向,對於難治型皮肌炎具有重要臨床應用價值。
    ;Dermatomyositis (DM) and juvenile dermatomyositis (JDM) are rare idiopathic inflammatory myopathies characterized by chronic muscle inflammation and immune-mediated tissue injury. Despite overlapping clinical and histopathological features, increasing evidence suggests that adult and juvenile DM also possess distinct features of pathogenesis. This study aimed to systematically elucidate the shared and unique transcriptomic landscapes of DM and JDM and to predict potential therapeutic candidates through integrative bioinformatics and drug repurposing approaches.
    Publicly available microarray datasets of muscle biopsy specimens (GSE128470, GSE5370, and GSE2044 for DM; GSE11971 and GSE3307 for JDM) were obtained from the Gene Expression Omnibus (GEO) database. Batch correction and differential expression analyses were conducted using the Transcriptome Analysis Console (TAC) software. Functional enrichment analyses based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to identify key biological pathways, while protein–protein interaction (PPI) networks and hub gene analyses were conducted using STRING and Cytoscape. Candidate compounds were predicted via the LINCS L1000CDS2 platform. In DM, 850 DEGs were identified, predominantly enriched in antiviral, inflammatory, and immune signaling pathways, including type I interferon response, MAPK, and NOD-like receptor signaling. In JDM, 2,544 DEGs were identified, highlighting interferon-driven innate immunity, cell adhesion, angiogenesis, and PI3K–Akt signaling. Comparative analyses revealed 437 overlapping DEGs, underscoring a shared interferon-mediated viral-like immune signature across age groups, while JDM exhibited enhanced vascular remodeling and adhesion-related processes. Hub gene analysis identified STAT1, DDX58, IFIH1, CXCL10, ISG15, MX1, GBP1, EIF2AK2 as central regulators. Drug repurposing predicted XMD-1150 and KM 00927 as potential shared therapeutic candidates for DM and JDM.
    In conclusion, this integrative transcriptomic study delineates both shared and distinct molecular pathways in DM and JDM, highlighting interferon-driven immune activation as a common hallmark and vascular-adhesion signaling as a distinguishing feature in JDM. The predicted compounds provide a foundation for future experimental validation and development of targeted therapies in refractory dermatomyositis.
    顯示於類別:[跨領域轉譯醫學研究所] 博碩士論文

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