Cancer Therapeutics through Theory and Experiment: From Cell Lines to Canine Tumors Grown on the Back of Mice

成人多细胞生物（如人）的细胞数量受到严格控制，在正常情况下，新细胞产生和细胞死亡之间保持平衡。粗略地说，当细胞数量控制系统出现一些故障，导致细胞分裂过度或细胞死亡减少时，癌症就会发生。一种可能的癌症治疗方法是快速而有力地诱导癌细胞死亡，早期的工作已经使用工程方法来解释治疗分子戏剧性地成功诱导人类癌细胞死亡背后的基本原理。我们的目标是将这些结果扩展到犬类癌症领域，首先对它们进行建模，然后在小鼠背部生长的犬类肿瘤上进行治疗实验。由于这项工作的目标是改善癌症治疗，因此该项目的潜在社会效益可能是巨大的。该项目将在德克萨斯农工大学的生物信息学和基因组系统工程中心（CBGSE）进行，在那里广泛传播研究成果，向研究生传授真正跨学科的实践教育，并有利于少数民族和少数民族机构，是重中之重。细胞周期控制系统的故障是癌症的一个基本特征，可归因于信号通路中许多不同位置的不同信号中断。因此，适当的癌症治疗设计应该首先尝试确定途径中功能障碍的位置和类型，然后得出特别适合它的药物组合。不幸的是，除了最近对靶向免疫疗法的尝试之外，大多数癌症治疗方法都没有遵循这样一个系统的程序。因此，对于大多数癌症来说，迫切需要精确地识别通路中的失效点，希望能带来更有针对性的治疗，并有更大的成功可能性。迄今为止，许多癌症疗法主要集中在阻断细胞增殖的关键途径上。然而，通常情况下，即使药物最初成功地治疗了癌症，这种成功通常是短暂的，因为癌细胞可以激活药物无法靶向的其他途径。另一种治疗癌症的方法是使用能够诱导细胞死亡的药物。靶向细胞死亡的化疗药物也表现出耐药性，当癌细胞找到逃避药物诱导细胞死亡活性的机制时，就会出现耐药性。然而，如果人们能够在细胞死亡途径中识别出在确保细胞死亡中起决定性作用的分子，而不考虑上游信号的破坏，那么用药物靶向这些分子将为治疗癌症提供一种强有力的策略。在最近的工作中，研究小组利用数学模型和实验证明了在人类乳腺癌、胰腺癌和黑色素瘤细胞系中实现强大的细胞杀伤方面取得了显著的成功。这是通过使用含有隐丹参酮（一种传统中药衍生物）的药物组合鸡尾酒来调节一种名为STAT3的基因来实现的。在这一初步成功的激励下，我们的目标是在兽医实验室中对骨肉瘤进行类似的建模，并证明在细胞系和小鼠上移植犬癌异种移植物的治疗成功。后者的成功可能会使结果更接近临床应用的药物开发领域。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The number of cells in an adult multicellular organism such as a human being is under very tight control and, under normal circumstances, there is a balance between new cell production and cell death. Roughly speaking, cancer results when there is excessive cell division or reduced cell death due to some malfunctioning in the cell number control system. A possible approach to cancer therapy is to quickly and robustly induce the death of cancer cells, and earlier work has used an engineering approach to explain the rationale behind the dramatically successful induction of human cancer cell death by a therapeutic molecule. The goal here is to extend these results to the domain of canine cancers by first modeling them and then conducting therapeutic experiments on canine tumors grown on the backs of mice. Since the work is driven by the goal of improving cancer treatment, the potential societal benefits of this project could be enormous. The project will be carried out at the Center for Bioinformatics and Genomic Systems Engineering (CBGSE) at Texas A & M University, where widespread dissemination of the research results, imparting truly interdisciplinary hands-on education to graduate students, and beneficially targeting minorities and minority institutions, are top priorities. The malfunctioning of the cell-cycle control system, an essential characteristic of cancer, can be attributed to different signaling breakdowns at many different locations in a signaling pathway. As a result, a proper design of cancer therapy should first attempt to identify the location and type of malfunction in the pathway and then arrive at a drug combination that is particularly well suited for it. Unfortunately, with the notable exception of the recent attempts at targeted immunotherapy, most of the approaches to cancer therapy do not follow such a systematic procedure. Thus, for most of cancers, there is a critical need for precisely identifying the failure point(s) in the pathway, hopefully leading to a more targeted therapy with a better likelihood of success. Many of the cancer therapies to date have mostly focused on blocking the pathways essential to cell proliferation. However, often, even if the drugs are initially successful in treating the cancer, the success is usually short lived as the cancer cell can activate some other pathways not targeted by the drug. An alternative approach to treat cancer would be to use drugs that are capable of inducing cell death. Chemotherapeutic drugs targeting cell death also display drug resistance which occurs when the cancer cells figure out mechanisms to evade the cell death inducing activity of the drug. If, however, one could identify molecules along the cell death pathway that can play a decisive role in ensuring cell death, regardless of the upstream signaling breakdown(s), then targeting such molecules with drugs would provide a robust strategy for treating cancer. In very recent work, the research team has utilized mathematical modeling and experimentation to demonstrate remarkable success in achieving robust cell killing for human breast cancer, pancreatic cancer and melanoma cell lines. This was done via the modulation of a gene called STAT3 using drug combination cocktails containing Cryptotanshinone, a traditional Chinese herb derivative. Motivated by this preliminary success, the goal here is to carry out similar modeling for osteosarcoma and demonstrate therapeutic success on cell lines and mice implanted canine cancer xenografts in a veterinarian's lab. Success with the latter is likely to move the results closer to the domain of drug development for clinical applications.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.