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非霍奇金B细胞淋巴瘤的联合二次转录组分析预测对与细胞外基质相关途径的依赖性及强大的诊断生物标志物。

Joint Secondary Transcriptomic Analysis of Non-Hodgkin's B-Cell Lymphomas Predicts Reliance on Pathways Associated with the Extracellular Matrix and Robust Diagnostic Biomarkers.

作者信息

Rapier-Sharman Naomi, Clancy Jeffrey, Pickett Brett E

机构信息

Department of Microbiology and Molecular Biology, Brigham Young University, Provo, UT 84602, USA.

出版信息

J Bioinform Syst Biol. 2022;5(4):119-135. doi: 10.26502/jbsb.5107040. Epub 2022 Sep 27.

Abstract

Approximately 450,000 cases of Non-Hodgkin's lymphoma are annually diagnosed worldwide, resulting in ~240,000 deaths. An augmented understanding of the common mechanisms of pathology among larger numbers of B-cell Non-Hodgkin's Lymphoma (BCNHL) patients is sorely needed. We consequently performed a large joint secondary transcriptomic analysis of the available BCNHL RNA-sequencing projects from GEO, consisting of 322 relevant samples across ten distinct public studies, to find common underlying mechanisms and biomarkers across multiple BCNHL subtypes and patient subpopulations; limitations may include lack of diversity in certain ethnicities and age groups and limited clinical subtype diversity due to sample availability. We found ~10,400 significant differentially expressed genes (FDR-adjusted p-value < 0.05) and 33 significantly modulated pathways (Bonferroni-adjusted p-value < 0.05) when comparing BCNHL samples to non-diseased B-cell samples. Our findings included a significant class of proteoglycans not previously associated with lymphomas as well as significant modulation of genes that code for extracellular matrix-associated proteins. Our drug repurposing analysis predicted new candidates for repurposed drugs including ocriplasmin and collagenase. We also used a machine learning approach to identify robust BCNHL biomarkers that include YES1, FERMT2, and FAM98B, which have not previously been associated with BCNHL in the literature, but together provide ~99.9% combined specificity and sensitivity for differentiating lymphoma cells from healthy B-cells based on measurement of transcript expression levels in B-cells. This analysis supports past findings and validates existing knowledge while providing novel insights into the inner workings and mechanisms of transformed B-cell lymphomas that could give rise to improved diagnostics and/or therapeutics.

摘要

全球每年约有45万例非霍奇金淋巴瘤被诊断出来,导致约24万人死亡。目前迫切需要加深对大量B细胞非霍奇金淋巴瘤(BCNHL)患者病理共同机制的理解。因此,我们对来自基因表达综合数据库(GEO)的现有BCNHL RNA测序项目进行了大规模联合二次转录组分析,该分析涵盖十项不同的公共研究中的322个相关样本,以寻找多种BCNHL亚型和患者亚群的共同潜在机制和生物标志物;局限性可能包括某些种族和年龄组缺乏多样性,以及由于样本可用性导致临床亚型多样性有限。在将BCNHL样本与未患病的B细胞样本进行比较时,我们发现了约10400个显著差异表达基因(FDR校正p值<0.05)和33条显著调节的通路(Bonferroni校正p值<0.05)。我们的研究结果包括一类以前与淋巴瘤无关的重要蛋白聚糖,以及编码细胞外基质相关蛋白的基因的显著调节。我们的药物重新利用分析预测了包括ocriplasmin和胶原酶在内的重新利用药物的新候选物。我们还使用机器学习方法来识别强大的BCNHL生物标志物,包括YES1、FERMT2和FAM98B,这些标志物在文献中以前未与BCNHL相关联,但基于B细胞中转录本表达水平的测量,它们共同提供了约99.9%的联合特异性和敏感性,用于区分淋巴瘤细胞与健康B细胞。该分析支持了过去的研究结果,验证了现有知识,同时为转化型B细胞淋巴瘤的内在运作和机制提供了新的见解,这可能会带来更好的诊断和/或治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a41/9980876/acb7950e441d/nihms-1870914-f0001.jpg

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