关键词: biomarkers differentially expressed drug repurposing mantle cell lymphoma non-Hodgkin lymphoma stages

Mesh : Lymphoma, Mantle-Cell / diagnosis drug therapy genetics metabolism pathology Humans Drug Repositioning / methods Gene Expression Regulation, Neoplastic / drug effects Gene Regulatory Networks / drug effects Osteonectin / metabolism genetics Vascular Endothelial Growth Factor A / metabolism genetics Transcriptome Gene Expression Profiling / methods Biomarkers, Tumor / metabolism Signal Transduction / drug effects Antineoplastic Agents / therapeutic use pharmacology

来  源:   DOI:10.3390/ijms25137298   PDF(Pubmed)

Abstract:
Mantle cell lymphoma (MCL) is a rare, incurable, and aggressive B-cell non-Hodgkin lymphoma (NHL). Early MCL diagnosis and treatment is critical and puzzling due to inter/intra-tumoral heterogeneity and limited understanding of the underlying molecular mechanisms. We developed and applied a multifaceted analysis of selected publicly available transcriptomic data of well-defined MCL stages, integrating network-based methods for pathway enrichment analysis, co-expression module alignment, drug repurposing, and prediction of effective drug combinations. We demonstrate the \"butterfly effect\" emerging from a small set of initially differentially expressed genes, rapidly expanding into numerous deregulated cellular processes, signaling pathways, and core machineries as MCL becomes aggressive. We explore pathogenicity-related signaling circuits by detecting common co-expression modules in MCL stages, pointing out, among others, the role of VEGFA and SPARC proteins in MCL progression and recommend further study of precise drug combinations. Our findings highlight the benefit that can be leveraged by such an approach for better understanding pathobiology and identifying high-priority novel diagnostic and prognostic biomarkers, drug targets, and efficacious combination therapies against MCL that should be further validated for their clinical impact.
摘要:
套细胞淋巴瘤(MCL)是一种罕见的,无法治愈,和侵袭性B细胞非霍奇金淋巴瘤(NHL)。由于肿瘤间/肿瘤内异质性和对潜在分子机制的有限理解,早期MCL诊断和治疗至关重要且令人困惑。我们开发并应用了对明确定义的MCL阶段的选定公开可用转录组数据的多方面分析,整合基于网络的路径富集分析方法,共表达模块对齐,药物再利用,和有效药物组合的预测。我们证明了从一小组最初差异表达的基因中出现的“蝴蝶效应”,迅速扩展到许多失调的细胞过程,信号通路,和核心机械随着MCL变得咄咄逼人。我们通过检测MCL分期中常见的共表达模块来探索致病性相关的信号通路,指出,其中,VEGFA和SPARC蛋白在MCL进展中的作用,并建议进一步研究精确的药物组合。我们的发现强调了通过这种方法可以更好地理解病理生物学并确定高优先级新型诊断和预后生物标志物的益处。药物靶标,以及针对MCL的有效联合疗法,应进一步验证其临床影响。
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