An Integrated Systems Approach for Incompletely Penetrant Onco-phenotypes.

项目摘要/摘要 癌细胞的扰动往往导致异质性的结果，因为大多数细胞表现出显性的 表现型，但其余的表现出对扰动的抗性或超敏。如果这样一种外在的 表型遗传不完整，那么要破译上游分子就变得极其困难。 使人口异质性并导致反应多变的事件。通过将量化 使用动态模型进行测量，如果提供核心网络，系统方法应该是有用的 重要的生物分子。令人望而生畏的障碍在于识别与表型相关的调控 在单细胞水平上定义网络通透性的异质性。我们的建议旨在利用 描述上游分子网络的一种新方法，称为随机频率匹配(SFM) 不完全穿透的表型。SFM可识别单细胞异质性并将其参数化-这 在一致的扰动之后，但在可变表型出现之前出现--磨练 与未来外显性相对应的监管状态。对于ErbB不完全触发的肿瘤表型 受体酪氨酸激酶在3D培养的乳腺上皮细胞中的信号转导，我们利用微阵列实现了SFM 发现一个关键的核质调节因子网络。这项提案的目标是应用系统 ErbB核质网络和SFM更广泛地应用于乳腺RNA测序的方法 对癌症患者进行ErbB扩增。根据我们的临时SFM结果，我们假设ErbB 信号异质性地重新配置细胞的核质穿梭状态以确定不完整 肿瘤表型的外显性。目标是：1)确定网络级别的机制，以 不完全穿透性ErbB1：ERBB2表型。2)确定3D中不完全穿透的驱动因素 确定人类癌症的穿梭状态，并促进ErbB2驱动的小鼠乳腺肿瘤。3)顺序 并将HER2+乳腺癌的调节状态异质性参数化，以组装患者特有的网络 穿梭变异性和敏感度模型。不完全外显的驱动因素对理解很重要 肿瘤起始-进展过程中的转变和开发更可靠的治疗干预措施 病人的结果。SFM为癌症系统生物学联盟提供了一种识别驱动器网络的方法 全面性和假设驱动的方式。

PROJECT SUMMARY/ABSTRACT Perturbation of cancer cells often leads to heterogeneous outcomes, in that most cells exhibit a dominant phenotype, but the rest appear resistant or hypersensitive to the perturbation. If the penetrance of such a phenotype is heritably incomplete, then it becomes extremely difficult to decipher the upstream molecular events that heterogenize the population and cause response variability. By combining quantitative measurements with dynamical models, systems approaches should be useful if provided with a core network of important biomolecules. The daunting hurdle lies in identifying phenotype-relevant regulatory heterogeneities that define the network for penetrance at the single-cell level. Our proposal seeks to exploit a new approach, called stochastic frequency matching (SFM), for elaborating the molecular networks upstream of incompletely penetrant phenotypes. SFM identifies and parameterizes single-cell heterogeneities—which emerge after a uniform perturbation but before the appearance of a variable phenotype—to hone in on regulatory states corresponding to future penetrance. For an onco-phenotype incompletely triggered by ErbB receptor tyrosine kinase signaling in 3D cultured breast epithelia, we implemented SFM using microarrays to uncover a network of critical nucleocytoplasmic regulators. The goals of this proposal are to apply systems approaches to the ErbB nucleocytoplasmic network and adapt SFM more broadly to RNA sequencing of breast cancer patients with ErbB amplification. Based on our provisional SFM results, we hypothesize that ErbB signaling heterogeneously reconfigures the nucleocytoplasmic shuttling state of cells to determine incomplete penetrance of the onco-phenotype. The aims are to: 1) Identify network-level mechanisms for the incompletely penetrant ErbB1:ErbB2 phenotype. 2) Determine whether drivers of incomplete penetrance in 3D define shuttling states in human cancers and promote ErbB2-driven mammary tumors in mice. 3) Sequence and parameterize regulatory-state heterogeneity in HER2+ breast cancers to assemble patient-specific network models of shuttling variability and sensitivity. Drivers of incomplete penetrance are important for understanding transitions during tumor initiation-progression and for developing therapeutic interventions with more reliable patient outcomes. SFM gives the Cancer Systems Biology Consortium a means to identify driver networks in a comprehensive and hypothesis-driven way.