尖端和茎部细胞行为的计算机筛选提出Apelin信号传导在肿瘤进展中的作用
Computational Screening of Tip and Stalk Cell Behavior Proposes a Role for Apelin Signaling in Sprout Progression
摘要：
血管生成涉及通过现有血管的发芽或分裂形成新血管。在发芽过程中，一种高度活跃的内皮细胞，称为尖端细胞，从血管中迁移出来，随后是茎细胞，一种形成芽体的内皮细胞类型。为了更深入地了解尖端细胞如何促进血管生成，我们扩展了现有的计算模型的血管网络形成的基础上的细胞Potts模型与尖端和茎分化，而不作先验假设尖端细胞和茎细胞之间的差异。为了预测潜在的差异，我们寻找参数值，使尖端细胞（a）移动到芽尖，（b）改变血管生成网络的形态。筛选预测，如果尖端细胞对内皮化学引诱物的反应不如柄细胞有效，它们会移动到芽的尖端，这会影响网络的形态。将该模型预测与尖端和柄细胞中差异表达的基因进行比较，发现内皮化学引诱物Apelin及其受体APJ可能与模型预测相匹配。为了测试模型预测，我们在我们的模型和血管生成发芽的\emph{in vitro}模型中抑制爱帕琳信号传导，并且发现在两种情况下抑制爱帕琳或其受体APJ减少发芽。基于计算模型的预测，我们提出Apelin和APJ的差异表达产生了一个“自生”的梯度机制，加速了芽的延伸。
英文摘要：
Angiogenesis involves the formation of new blood vessels by sprouting or splitting of existing blood vessels. During sprouting, a highly motile type of endothelial cell, called the tip cell, migrates from the blood vessels followed by stalk cells, an endothelial cell type that forms the body of the sprout. To get more insight into how tip cells contribute to angiogenesis, we extended an existing computational model of vascular network formation based on the cellular Potts model with tip and stalk differentiation, without making a priori assumptions about the differences between tip cells and stalk cells. To predict potential differences, we looked for parameter values that make tip cells (a) move to the sprout tip, and (b) change the morphology of the angiogenic networks. The screening predicted that if tip cells respond less effectively to an endothelial chemoattractant than stalk cells, they move to the tips of the sprouts, which impacts the morphology of the networks. A comparison of this model prediction with genes expressed differentially in tip and stalk cells revealed that the endothelial chemoattractant Apelin and its receptor APJ may match the model prediction. To test the model prediction we inhibited Apelin signaling in our model and in an \emph{in vitro} model of angiogenic sprouting, and found that in both cases inhibition of Apelin or of its receptor APJ reduces sprouting. Based on the prediction of the computational model, we propose that the differential expression of Apelin and APJ yields a "self-generated" gradient mechanisms that accelerates the extension of the sprout.
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