Systems-level mechanisms of small cell lung cancer dynamics

项目总结 小细胞肺癌(SCLC)是一种起源于神经内分泌的肺癌，其特征是侵袭性生长和 传播很快。小细胞肺癌最初对治疗有反应，几乎总是复发并导致患者死亡。 在两年内。最近的研究表明，小细胞肺癌是一种高度异质性的疾病，包括 肿瘤内对药物治疗表现出不同敏感性的细胞亚型。然而，SCLC的研究 到目前为止，主要集中在两个尚未统一的领域。细胞分子研究揭示了 肿瘤人群中有两种广泛的表型亚型，神经内分泌(NE)和非神经内分泌(非- Ne)。已经发现了受体-配体之间的相互作用，如Notch受体及其配体DLL4之间的相互作用 在诱导这些不同细胞类型之间的转化中发挥作用，例如从NE过渡 细胞转化为非去甲肾上腺素表型。单细胞RNA测序方法已经产生了转录数据 显示在小细胞肺癌肿瘤细胞中活跃的调节通路，这些调节通路驱动细胞向广泛的去甲肾上腺素或非去甲肾上腺素细胞方向发展 流程。虽然细胞信号传递方法和转录方法都提供了有价值的 对SCLC表型亚型分化的洞察，目前尚不清楚亚型的转录调控 与促进肿瘤生长的细胞群体行为有关。小细胞肺癌肿瘤的系统水平图像 如果不了解肿瘤中的细胞间动力学和细胞-细胞信号转导，行为是不可能实现的 直接影响转录激活，以及转录激活如何导致亚型转换 影响这些细胞间的动力学。我提出了一种研究这两种表型机制的方法。 小细胞肺癌的亚型分化，使用种群动力学的计算模型来表征细胞-细胞 与表型亚型有关的相互作用和肿瘤构成，以及布尔逻辑建模 在细胞内表征转录信号通路，以提供有关不同转录的详细信息 各种因素可导致分化为每种表型亚型。我还将研究这两个过程 在实验上，研究破坏每个亚型的稳定并导致抑制肿瘤的方法 增长，同时使用结果进一步完善我的数学模型。在以下背景下研究每个领域 其他研究有望提高人们对肿瘤行为的认识。肿瘤亚型的增强表征 对生长或表型转变的敏感性将导致小细胞肺癌的新治疗策略 这将对改善患者的预后具有极其重要的意义。这个项目将产生一个系统- 肿瘤亚型组成与转录网络对应关系的研究进展 SCLC，揭示了破坏系统稳定的靶向治疗选择。

PROJECT SUMMARY Small cell lung cancer (SCLC) is lung cancer of neuroendocrine origin, characterized by aggressive growth and rapid spread. Initially responsive to treatment, SCLC nearly invariably relapses and leads to patient death within 2 years. Recent work has shown that SCLC is a highly heterogeneous disease comprising multiple cellular subtypes within a tumor that exhibit differential sensitivity to drug treatments. However, SCLC research to date has focused on two major areas, which have not yet been unified. Cell-molecular studies have revealed two broad phenotypic subtypes within a tumor population, neuroendocrine (NE) and non-neuroendocrine (non- NE). Receptor-ligand interactions such as those between Notch receptor and its ligand DLL4 have been found to play a role in inducing transformations between these different cell types, such as the transition from NE cells into a non-NE phenotype. Single-cell RNA sequencing approaches have produced transcriptional data showing regulatory pathways active in SCLC tumor cells, which drive cells towards broadly NE or non-NE cell processes. While both cell-signaling approaches and transcriptional approaches have provided valuable insights into SCLC phenotypic subtype differentiation, it is not clear how transcriptional regulation of subtypes is linked to cell population behaviors that enable tumor growth. A systems-level picture of SCLC tumor behavior is not achievable without understanding how intercellular dynamics and cell-cell signaling in the tumor directly affects transcriptional activation, and how transcriptional activation leading to subtype transitions affects these intercellular dynamics. I present an approach to study both of these mechanisms of phenotypic subtype differentiation in SCLC, using computational modeling of population dynamics to characterize cell-cell interactions and tumor makeup with regard to phenotypic subtypes, and Boolean logic modeling to characterize transcriptional signaling pathways intracellularly to provide detail about how different transcription factors can result in differentiation into each phenotypic subtype. I will also study both of these processes experimentally, investigating means by which to destabilize each subtype and lead to inhibition of tumor growth, while using results to further refine my mathematical models. Studying each area in the context of the other is expected to improve knowledge of tumor behavior. Enhanced characterization of tumor subtype sensitivities with regard to growth or phenotypic transition will lead to new therapeutic strategies for SCLC patients, which will be extremely significant in improving patient outcomes. This project will result in a systems- level understanding of the correspondence between transcriptional networks and tumor subtype composition in SCLC, bringing to light targeted treatment options to destabilize the system.