弥漫性大b细胞淋巴瘤(DLBCL)和系统性红斑狼疮(SLE)之间共同基因和分子通路的评估:系统生物学方法。

Q2 Medicine
Medical Journal of the Islamic Republic of Iran Pub Date : 2024-11-06 eCollection Date: 2024-01-01 DOI:10.47176/mjiri.38.129
Alireza Hejrati, Reza Maddah, Sadaf Parvin, Abbas Gholami, Lina Hejrati, Bahareh Shateri Amiri, Anousheh Haghighi
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引用次数: 0

摘要

背景:弥漫性大b细胞淋巴瘤(DLBL)和系统性红斑狼疮(SLE)是复杂的自身免疫性疾病,具有独特的临床挑战。尽管这些疾病表现不同,但它们可能具有共同的潜在遗传和信号通路。揭示这些共性可以为疾病发病机制提供宝贵的见解,为更有针对性和更有效的治疗干预铺平道路。本研究对SLE和DLBL之间的共同基因和信号通路进行了全面的研究。方法:研究人员搜索基因表达Omnibus数据库,精心收集SLE (GSE61635)和DLBL (GSE56315)的微阵列数据集。进行差异表达分析,使研究小组能够确定在这两种自身免疫性疾病中普遍失调的基因。为了深入挖掘这些共享基因的生物学意义,研究人员进行了功能富集分析、网络分析和核心基因鉴定。值得注意的是,已确定的枢纽基因的诊断潜力是使用尖端的神经网络模型进行评估的。结果:数据分析显示SLE和DLBL共有146个基因,其中111个基因上调,45个基因下调。功能富集分析揭示了这些共享基因在重要的免疫系统相关过程中的参与,如对病毒的防御反应、干扰素信号传导和更广泛的免疫系统途径。网络分析确定了5个中心基因(IFIT3、IFIT1、DDX58、CCL2和OASL)作为中心基因出现,表现出高度的中心性,并预计在潜在的分子机制中发挥关键作用。值得注意的是,神经网络模型仅基于这些中枢基因的表达模式,在区分疾病状态(DLBL和SLE)方面表现出卓越的诊断准确性。结论:已鉴定的枢纽基因及其相关通路具有巨大的诊断生物标志物潜力,并可能成为未来治疗探索的有价值靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of Genes and Molecular Pathways Common between Diffuse Large B-cell Lymphoma (DLBCL) and Systemic Lupus Erythematosus (SLE): A Systems Biology Approach.

Background: Diffuse large B-cell lymphoma (DLBL) and systemic lupus erythematosus (SLE) are complex autoimmune disorders that present unique clinical challenges. These conditions may share underlying genetic and signaling pathways despite their distinct manifestations. Uncovering these commonalities could offer invaluable insights into disease pathogenesis, paving the way for more targeted and effective therapeutic interventions. This study embarks on a comprehensive investigation of the common genes and signaling pathways between SLE and DLBL.

Methods: The researchers scoured the Gene Expression Omnibus database, meticulously gathering microarray datasets for SLE (GSE61635) and DLBL (GSE56315). Differential expression analysis was performed, allowing the team to identify the genes that were commonly dysregulated across these 2 autoimmune conditions. To delve deeper into the biological significance of these shared genes, the researchers conducted functional enrichment analysis, network analysis, and core gene identification. Notably, the diagnostic potential of the identified hub genes was assessed using a cutting-edge neural network model.

Results: The data analysis revealed a remarkable 146 genes that were shared between SLE and DLBL, of which 111 were upregulated and 45 downregulated. Functional enrichment analysis unveiled the involvement of these shared genes in vital immune system-related processes-such as defense response to viruses, interferon signaling, and broader immune system pathways. Network analysis pinpointed 5 hub genes (IFIT3, IFIT1, DDX58, CCL2, and OASL) that emerged as central players, exhibiting a high degree of centrality and predicted to hold crucial roles in the underlying molecular mechanisms. Remarkably, the neural network model demonstrated exceptional diagnostic accuracy in distinguishing between the disease states (DLBL and SLE) based solely on the expression patterns of these hub genes.

Conclusion: The identified hub genes and their associated pathways hold immense potential as diagnostic biomarkers and may serve as valuable targets for future therapeutic explorations.

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CiteScore
2.40
自引率
0.00%
发文量
90
审稿时长
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