Adaptive regulation of cancer cell fate following oncogene inhibition

癌基因抑制后癌细胞命运的适应性调节

• 批准号: 10161370
• 负责人: Mohammad Fallahi-Sichani
• 金额: $ 10.5万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-05-01 至 2021-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10161370
• 关键词: Adaptive; regulation; cancer; cell; fate

 DESCRIPTION (provided by applicant): The overall goal of this proposal is to develop a single-cell, and network-level understanding of cell signaling mechanisms involved in adaptive drug responses through the application of engineering and systems biology approaches. I have chosen melanoma and drugs targeting the BRAFV600E oncoprotein, since adaptation is well known to be important in this type of cancer. Treatment of BRAFV600E melanomas with drugs, such as vemurafenib, that inhibit RAF/MEK signaling is effective in the short term, but remission is not durable. Drug resistance is thought to involve short-term adaptive responses that up-regulate compensatory pro-growth and/or anti-apoptotic mechanisms. The discovery and analysis of adaptive responses in melanoma represents a breakthrough in tumor biology and reveals hitherto unsuspected plasticity in signaling biochemistry. However, systematic data comparing BRAFV600E tumor cells is generally lacking and important questions are unanswered. It is not known whether adaptive mechanisms in different cell types are fundamentally similar or they are different from one cell type to the next or even one single cell to the next. Further, it is not clear how different adaptive responses are related to each other, how they are affected by tumor microenvironment, and how they are integrated to determine the fate of an individual cell. Answering these questions is critical for developing single or multi-component biomarkers of drug responsiveness and for designing rational and effective combination therapies to overcome drug adaptation and ultimately drug resistance. Our previous studies show that adaptive responses are diverse across melanomas, involving different combinations of signaling cascades. In particular, we identified an adaptive mechanism involving JNK/c-Jun that diminishes drug efficacy. RAF and JNK inhibitors induce synergistic cell killing in melanoma cells in which c-Jun mediated adaptive response occurs. Single-cell studies show that JNK inhibition enhances suppression of phospho-S6 ribosomal protein, promotes apoptosis in a subset of cells that would otherwise become quiescent and apoptosis-resistant in the presence of vemurafenib alone, and increases drug maximal effect (Emax). This work identified involvement of different pathways in adaptive responses, their diversity with genotype and time, and suggested that it would be critical to examine the diverse phenotypes induced by BRAFV600E inhibition at a single-cell level. Therefore, in this proposal I will couple high-throughput measurement, fixed and live single- cell analysis, and a combination of statistical and mechanistic computational modeling techniques to: (1) identify key molecules (ligands, receptors and transcription factors) linked to JNK/c-Jun mediated adaptive response and crosstalk with other adaptive responses in a set of BRAFV600E melanoma cell lines and primary patient-derived melanoma cells having different genotypes, (2) develop network-level models of adaptive response which discriminate among key adaptive network states observed across different cell types and their association with phenotypic responses and drug sensitivity, (3) assess the diversity and magnitude of adaptive responses across individual cells and determine their association with individual cell phenotypes (proliferation, quiescence, senescence, cell death, etc.), (4) investigate the contribution of other cell types within the tumo microenvironment, in particular tumor-associated macrophages, in drug-induced adaptive and phenotypic responses, and (5) utilize these data to identify mechanism-based biomarkers for different pathway adaptations, use these biomarkers to design and test novel combination therapeutics that take into account malignant cells, the tumor microenvironment, and the dynamics exerted by the treatment itself. The success of these studies is directly linked to the proposed training activities I intend to undertake during the mentored phase of this award. I believe that with my extensive engineering and computational background, being awarded a K99/R00 award will allow me to deepen my understanding of tumor biology (concentrating initially on melanoma) and to obtain advanced training in a highly supportive and innovative training environment of Harvard Medical School. In addition, to support me in my training, and in my transition to the independent phase of my career, I will be benefitting from the mentorship and collaboration with leading experts in the fields I propose studying. This includes my mentor Dr. Peter Sorger (Harvard Medical School), and collaborators Dr. Neal Rosen (Memorial Sloan Kettering Cancer Center), Dr. Nathanael Gray (Dana Farber Cancer Institute), and Dr. Steve Gygi (Harvard Medical School). The skills and knowledge acquired during the mentored phase of this award will be instrumental for the above proposed studies and future studies, and for successfully launching my career as an independent investigator.

 描述(由申请人提供)：本提案的总体目标是通过工程和系统生物学方法的应用，在单细胞和网络水平上理解适应性药物反应中涉及的细胞信号机制。我选择了黑色素瘤和针对BRAFV600E癌蛋白的药物，因为众所周知，适应在这种类型的癌症中很重要。用维莫拉非尼等抑制RAF/MEK信号转导的药物治疗BRAFV600E黑色素瘤短期内有效，但缓解不持久。耐药性被认为涉及短期适应性反应，上调代偿性促生长和/或抗凋亡机制。黑色素瘤适应性反应的发现和分析代表了肿瘤生物学的一项突破，并揭示了信号生物化学中迄今未被怀疑的可塑性。然而，比较BRAFV600E肿瘤细胞的系统数据普遍缺乏，重要的问题也没有答案。目前尚不清楚不同细胞类型中的适应机制是基本相似的，还是从一种细胞类型到另一种细胞类型，甚至是一个细胞到另一个细胞的不同。此外，目前还不清楚不同的适应性反应是如何相互联系的，它们如何受到肿瘤微环境的影响，以及它们如何整合来决定单个细胞的命运。回答这些问题对于开发药物反应性的单组分或多组分生物标志物以及设计合理有效的联合治疗以克服药物适应并最终产生耐药性至关重要。我们之前的研究表明，不同黑色素瘤的适应性反应是不同的，涉及不同的信号级联反应组合。特别是，我们确定了一种涉及jnk/c-jun的适应性机制，它会降低药物疗效。RAF和JNK抑制剂在黑色素瘤细胞中诱导协同杀伤，其中c-jun介导的适应性反应发生。单细胞研究表明，JNK抑制增强了对磷酸化S6核糖体蛋白的抑制，促进了在Vemurafenib单独存在时处于静止和抗凋亡状态的一部分细胞的凋亡，并增加了药物最大效应(Emax)。这项工作确定了不同的途径参与了适应性反应，它们随基因和时间的差异而变化，并表明在单细胞水平上检测BRAFV600E抑制诱导的不同表型是至关重要的。因此，在这项提案中，我将结合高通量测量、固定和活的单细胞分析以及统计和机械计算建模技术的组合来：(1)识别与JNK/c-jun介导的适应性反应有关的关键分子(配体、受体和转录因子)，以及在一组BRAFV600E黑色素瘤细胞系和具有不同基因型别的原发患者来源的黑色素瘤细胞中与其他适应性反应的串扰，(2)建立适应性反应的网络级模型，该模型区分不同细胞类型观察到的关键适应网络状态及其与表型反应和药物敏感性的关联，(3)评估单个细胞适应性反应的多样性和大小，并确定它们与单个细胞表型(增殖、静止、衰老、细胞死亡等)的关系；(4)调查Tumo微环境中其他类型的细胞，尤其是肿瘤相关巨噬细胞，在药物诱导的适应性和表型反应中的贡献，以及(5)利用这些数据来确定不同途径适应的基于机制的生物标记物，使用这些生物标记物设计和测试考虑到恶性细胞、肿瘤微环境和治疗本身所施加的动态的新型联合疗法。这些研究的成功与我打算在该奖项的指导阶段进行的拟议培训活动直接相关。我相信，凭借我广泛的工程和计算背景，获得K99/R00奖将使我加深对肿瘤生物学(最初专注于黑色素瘤)的理解，并在哈佛医学院高度支持和创新的培训环境中获得高级培训。此外，为了支持我的培训，并在我的职业生涯过渡到独立阶段，我将受益于与我提议学习的领域的领先专家的指导和合作。这包括我的导师Peter Sorger博士(哈佛医学院)和合作者Neal Rosen博士(纪念斯隆·凯特琳癌症中心)、Nathanael Gray博士(Dana Farber癌症研究所)和Steve Gygi博士(哈佛医学院)。在该奖项的指导阶段获得的技能和知识将有助于上述拟议的研究和未来的研究，并成功启动我作为独立调查人员的职业生涯。