文章：

原发性骨髓纤维化的数据驱动网络模型：CD34+细胞中的转录和转录后改变

A data-driven network model of primary myelofibrosis: transcriptional and post-transcriptional alterations in CD34+ cells

原文发布日期：2016-06-24

DOI: 10.1038/bcj.2016.47

类型: Original Article

开放获取: 是

英文摘要：

microRNAs (miRNAs) are relevant in the pathogenesis of primary myelofibrosis (PMF) but our understanding is limited to specific target genes and the overall systemic scenario islacking. By both knowledge-based and ab initio approaches for comparative analysis of CD34+ cells of PMF patients and healthy controls, we identified the deregulated pathways involving miRNAs and genes and new transcriptional and post-transcriptional regulatory circuits in PMF cells. These converge in a unique and integrated cellular process, in which the role of specific miRNAs is to wire, co-regulate and allow a fine crosstalk between the involved processes. The PMF pathway includes Akt signaling, linked to Rho GTPases, CDC42, PLD2, PTEN crosstalk with the hypoxia response and Calcium-linked cellular processes connected to cyclic AMP signaling. Nested on the depicted transcriptional scenario, predicted circuits are reported, opening new hypotheses. Links between miRNAs (miR-106a-5p, miR-20b-5p, miR-20a-5p, miR-17-5p, miR-19b-3p and let-7d-5p) and key transcription factors (MYCN, ATF, CEBPA, REL, IRF and FOXJ2) and their common target genes tantalizingly suggest new path to approach the disease. The study provides a global overview of transcriptional and post-transcriptional deregulations in PMF, and, unifying consolidated and predicted data, could be helpful to identify new combinatorial therapeutic strategy. Interactive PMF network model: http://compgen.bio.unipd.it/pmf-net/.

摘要翻译： 

microRNAs（miRNAs）在原发性骨髓纤维化（PMF）的发病机制中具有重要作用，但我们的理解仍局限于特定靶基因，且缺乏整体系统性的认识。通过基于知识和从头计算的方法对PMF患者及健康对照者CD34+细胞进行比较分析，我们发现了PMF细胞中涉及miRNAs和基因的失调通路，以及新的转录与转录后调控回路。这些发现汇聚成一个独特而整合的细胞过程，其中特定miRNAs的作用是连接、协同调控并实现相关过程间的精细交互。PMF通路包括Akt信号传导（与Rho GTPases、CDC42、PLD2、PTEN相互关联）、与缺氧反应的串扰，以及与环AMP信号相连的钙相关细胞过程。基于所描述的转录背景，我们报告了预测的调控回路，为新的假设开辟了道路。miRNAs（miR-106a-5p、miR-20b-5p、miR-20a-5p、miR-17-5p、miR-19b-3p和let-7d-5p）与关键转录因子（MYCN、ATF、CEBPA、REL、IRF和FOXJ2）及其共同靶基因之间的关联，暗示了探索该疾病的新途径。本研究提供了PMF中转录和转录后失调的整体概览，并通过整合已验证与预测数据，有助于识别新的组合治疗策略。交互式PMF网络模型：http://compgen.bio.unipd.it/pmf-net/。

原文链接：

A data-driven network model of primary myelofibrosis: transcriptional and post-transcriptional alterations in CD34+ cells