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An incoherent regulatory network architecture that orchestrates B cell diversification in response to antigen signaling.一个不连贯的调控网络架构,协调 B 细胞多样化以响应抗原信号。
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Inactivating mutations of acetyltransferase genes in B-cell lymphoma.B 细胞淋巴瘤中乙酰转移酶基因的失活突变。
Nature. 2011 Mar 10;471(7337):189-95. doi: 10.1038/nature09730.
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BLIMP1 is a tumor suppressor gene frequently disrupted in activated B cell-like diffuse large B cell lymphoma.BLIMP1 是一个抑癌基因,在活化 B 细胞样弥漫性大 B 细胞淋巴瘤中经常被破坏。
Cancer Cell. 2010 Dec 14;18(6):568-79. doi: 10.1016/j.ccr.2010.10.030.
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Bach2 represses plasma cell gene regulatory network in B cells to promote antibody class switch.Bach2 抑制 B 细胞中的浆细胞基因调控网络以促进抗体类别转换。
EMBO J. 2010 Dec 1;29(23):4048-61. doi: 10.1038/emboj.2010.257. Epub 2010 Oct 15.
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Chronic active B-cell-receptor signalling in diffuse large B-cell lymphoma.弥漫性大 B 细胞淋巴瘤中慢性活性 B 细胞受体信号转导。
Nature. 2010 Jan 7;463(7277):88-92. doi: 10.1038/nature08638.
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Mutations of multiple genes cause deregulation of NF-kappaB in diffuse large B-cell lymphoma.多个基因的突变导致弥漫性大B细胞淋巴瘤中NF-κB的失调。
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Molecular subtypes of diffuse large B-cell lymphoma arise by distinct genetic pathways.弥漫性大B细胞淋巴瘤的分子亚型通过不同的遗传途径产生。
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IRF4 addiction in multiple myeloma.多发性骨髓瘤中的IRF4成瘾
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Oncogenic CARD11 mutations in human diffuse large B cell lymphoma.人类弥漫性大B细胞淋巴瘤中的致癌性CARD11突变。
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B 细胞终末分化的定量建模与淋巴瘤发生机制。

Quantitative modeling of the terminal differentiation of B cells and mechanisms of lymphomagenesis.

机构信息

Joint Center for Systems Biology, Columbia University, New York, NY 10032, USA.

出版信息

Proc Natl Acad Sci U S A. 2012 Feb 14;109(7):2672-7. doi: 10.1073/pnas.1113019109. Epub 2012 Jan 30.

DOI:10.1073/pnas.1113019109
PMID:22308355
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3289327/
Abstract

Mature B-cell exit from germinal centers is controlled by a transcriptional regulatory module that integrates antigen and T-cell signals and, ultimately, leads to terminal differentiation into memory B cells or plasma cells. Despite a compact structure, the module dynamics are highly complex because of the presence of several feedback loops and self-regulatory interactions, and understanding its dysregulation, frequently associated with lymphomagenesis, requires robust dynamical modeling techniques. We present a quantitative kinetic model of three key gene regulators, BCL6, IRF4, and BLIMP, and use gene expression profile data from mature human B cells to determine appropriate model parameters. The model predicts the existence of two different hysteresis cycles that direct B cells through an irreversible transition toward a differentiated cellular state. By synthetically perturbing the interactions in this network, we can elucidate known mechanisms of lymphomagenesis and suggest candidate tumorigenic alterations, indicating that the model is a valuable quantitative tool to simulate B-cell exit from the germinal center under a variety of physiological and pathological conditions.

摘要

成熟 B 细胞从生发中心的退出受转录调控模块的控制,该模块整合抗原和 T 细胞信号,并最终导致终末分化为记忆 B 细胞或浆细胞。尽管结构紧凑,但由于存在多个反馈回路和自我调节相互作用,模块动力学非常复杂,理解其失调(常与淋巴瘤发生有关)需要强大的动态建模技术。我们提出了三个关键基因调节剂(BCL6、IRF4 和 BLIMP)的定量动力学模型,并使用成熟人 B 细胞的基因表达谱数据来确定合适的模型参数。该模型预测存在两个不同的滞后循环,可指导 B 细胞不可逆地向分化细胞状态转变。通过对该网络中的相互作用进行合成扰动,我们可以阐明淋巴瘤发生的已知机制,并提出候选的致瘤性改变,表明该模型是一种有价值的定量工具,可模拟各种生理和病理条件下生发中心的 B 细胞退出。