Variability of Cellular Responses to Growth Factors and Drugs During Tumorgenesis

在肿瘤形成过程中，癌细胞和健康细胞都依赖于在肿瘤形成过程中产生的生长因子 以自分泌和旁分泌的方式维持其增殖和分化。因此出现了一场“拔河比赛”。 肿瘤和周围非癌细胞之间的生长因子，以及每个细胞的适合性 每个单元必须由这项比赛在大众层面上定义。重要的是，体内的癌细胞 肿瘤前沿的特点是耐化疗，具有增强的转移潜能和 在形成新肿瘤方面非常有效[6]。 我们已经确定癌细胞和邻近的间质细胞表达高水平的生长因子IL-6 激活的STAT3被认为是肿瘤发生和转移的主要介质 进步。在这项研究中，我们将重点放在黑色素瘤和乳腺癌细胞中的IL-6/pStat3通路， 其增殖和分化关键依赖于pStat3信号。在理解的背景下 肿瘤动力学，特别是在药物治疗期间，克隆内对生长因子的竞争 将对细胞的遗传同源性进行研究。对结果表型的理解 肿瘤细胞的多样性将导致改善根除肿瘤人群的治疗干预措施。 具体地说，我们将(1)表征肿瘤细胞对生长因子的不同反应并有针对性地 抑制物：(2)设计一个数学框架来预测细胞多样性的后果并确定 最大限度地消除肿瘤的机会的最佳治疗干预；以及(3)验证 细胞系和小鼠模型中数学框架的预测。这个项目充分利用了我们的 癌症生物学和临床经验(Bromberg)、单细胞图谱和生化建模方面的专业知识 (Altan-Bonnet)和数学数学建模(Michor)。我们将剖析IL-6途径是如何产生 肿瘤中的表型变异，这推动了肿瘤的进展，并导致对靶向治疗的抵抗[7- 13]。基于我们的模型，我们将识别和测试治疗这些癌症的最佳治疗方案。

During tumorigenesis, cancer cells as well as healthy cells depend upon growth factors produced in an autocrine and paracrine manner to maintain their proliferafion and differenfiafion. Hence there exists a "tug-ofwar" for growth factors between a tumor and the surrounding non-cancer cells, and the fitness of each individual cell must be defined by this competifion at the populafion level. Importantly, cancer cells on the leading edge of tumors are characterized as being chemo-resistant, have enhanced metastatic potential and are extremely efficient at forming new tumors [6]. We have determined that cancer cells and adjacent stromal cells express high levels of the growth factor IL-6 and activated Stat3 which are hypothesized to be the principal mediators of both tumorigenesis and metastafic progression. In this proposal, we focus on the IL-6/pStat3 pathway in melanoma and breast cancer cells, whose proliferation and differenfiafion crifically depends on pStat3 signals. In the context of understanding tumor dynamics, especially during drug treatment, the intraclonal competifion for growth factors within a genefically-idenfical populafion of cells will be investigated. An understanding of the resulfing phenotypic diversity of tumor cells will lead to improved therapeufic intervenfions eradicafing tumor populafions. Specifically, we will (1) characterize the variable response of tumor cells to growth factors and targeted inhibitors: (2) design a mathemafical framework to predict the consequences of cellular diversity and identify the opfimum therapeutic intervenfion that maximizes the chance of eradicafing the tumor; and (3) validate the predictions of the mathemafical framework in cell lines and murine models. This project fully leverages our expertise in cancer biology and clinical experience (Bromberg), single cell profiling and biochemical modeling (Altan-Bonnet), and mathemafical modeling (Michor). We will dissect how the IL-6 pathway can generate phenotypic variability in tumors, which drives their progression and causes resistance to targeted therapies [7- 13]. Based on our models, we will identify and test the opfimal therapeufic protocol for treafing these cancers.