Application of Evolutionary Principles to Maintain Cancer Control (PQ21)

应用进化原理维持癌症控制（PQ21）

基本信息

批准号：
8862176
负责人：
ROBERT A GATENBY
金额：
$ 52.89万
依托单位：
H. LEE MOFFITT CANCER CTR & RES INST
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-09-01 至 2017-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8862176
关键词：
Anecdotes Antineoplastic Agents Aromatase Inhibitors Bioluminescence Breast Breast Cancer Patient Breast Cancer Treatment Breast Cancer cell line Breast Cancer therapy Cancer Control Cell Line Cell physiology Cells Cellularity Cessation of life Clarithromycin Clinic Clinical Clinical Trials Coin Computer Simulation Cyclosporine DNA Repair Pathway Data Dose Doxorubicin Drug Combinations Drug Delivery Systems Drug Targeting Drug resistance Drug-sensitive ERBB2 gene Epithelial Estrogen Antagonists Estrogens Evolution Exemestane Exhibits Glucose Goals Grant Growth Head Image Imaging Techniques In Vitro Longevity MCF7 cell MDA MB 231 Magnetic Resonance Imaging Maintenance Malignant Neoplasms Measures Metabolic Metabolism Metastatic breast cancer Modeling Molecular Monitor Multi-Drug Resistance Mutation Oncologist Paclitaxel Pathway interactions Patients Pharmaceutical Preparations Phenotype Population Positron-Emission Tomography Probability Protocols documentation Pump Quinidine Regimen Reproduction Research Personnel Resistance Resources Roche brand of trastuzumab Sequence Analysis Stable Populations Tamoxifen Testing Thinking Time Treatment Failure Tumor Burden Ultrasonography Up-Regulation Verapamil Xenobiotics Xenograft Model angiogenesis base cancer therapy cell killing chemotherapy clinical application cost cytotoxic deprivation design exome sequencing feeding fitness glucose uptake hormone therapy improved in vivo inhibitor/antagonist life history malignant breast neoplasm mathematical model member migration mouse model multidisciplinary neoplastic cell non-invasive imaging novel oncology personalized medicine pre-clinical pressure prevent research study resistance mechanism response targeted treatment treatment strategy tumor tumor metabolism tumor progression

项目摘要

DESCRIPTION (provided by applicant): In this project we explore the pre-clinical application of the concept of Adaptive Therapy (AT), a term coined by the proposers of this grant. AT shifts the treatment paradigm of currently incurable cancers from the maximum tumor cell killing ("all-out attack") approach to the use of "evolutionarily enlightened" drug combinations to stabilize the tumor burden. Our goal is to minimize the probability of emergence of multi drug resistant clones (MDR), which are the ultimate cause of current cancer treatment failure and patient death. In addition to the original AT idea of promoting competition of chemoresistant and chemosensitive tumor cells, the authors propose to explore evolutionary-based approaches that increase the cost of chemoresistance, making these cells less fit than their chemosensitive counterpart, and thus reducing the likeliness of emergence of a resistant tumor. Finally, the authors propose the use of clinically available non-invasive metabolic imaging techniques (FdG PET -Positron Emission Tomography) to assess tumor chemoresistance, and use this to inform the clinicians about the presence and number of resistant cells within the tumor. Our proof-of-concept tumor model will be in breast cancer. We will use in vitro and mouse models, non- invasive imaging of tumor burden and metabolism, and computational evolutionary models of tumor progression and drug response. These approaches will be used to detect and measure tumor resistance and suggest the optimal treatment strategy that maximally prolongs the duration of response to conventional breast cancer therapy. The authors propose to combine three chemotherapeutic strategies currently used in the clinic: (a) hormonal therapy (tamoxifen and aromatase inhibitors), (b) targeted therapy (herceptin), and (c) standard chemotherapy (doxorubicin and taxol). In preliminary experiments we will extend AT to all forms of breast cancer therapy. Intensive imaging and pre and post therapy molecular studies will allow assessment of tumor vascularity and cell function in response to evolutionary therapy. To improve AT we will examine mechanisms to exploit the cost of resistance to both detect resistant populations and suppress their proliferation. Preliminary data has shown that breast cancer cell lines expressing P-gp pumps have accelerated metabolism and are more sensitive to glucose deprivation than their parental cell line. These cells also show increased energy depletion in presence of P-gp substrates, such as Verapamil, Cyclosporin A, Quinidine and Clarithromycin at sub-toxic levels, making these candidates for "fake drugs", to be used to increase the cost of resistance of P-gp cells between periods of chemotherapy. P-gp expressing cells also show increased glucose uptake in presence of "fake drugs". Finally, we will also study how the addition of estrogen during therapy intervals can be used to increase the fitness of ER+ cells and thus maintain the number of hormonal therapy- sensitive cells.

描述（由申请人提供）：在这个项目中，我们探索适应性治疗（AT）概念的临床前应用，该术语是由本次资助的提案者创造的。 AT 将目前无法治愈的癌症的治疗模式从最大程度地杀死肿瘤细胞（“全面攻击”）方法转变为使用“进化启发”的药物组合来稳定肿瘤负荷。我们的目标是最大限度地减少多重耐药克隆（MDR）出现的可能性，多重耐药克隆是当前癌症治疗失败和患者死亡的最终原因。除了促进化学抗性和化学敏感性肿瘤细胞竞争的原始 AT 想法之外，作者还建议探索基于进化的方法，以增加化学抗性的成本，使这些细胞不如化学敏感的对应细胞适应，从而降低出现的可能性耐药肿瘤。最后，作者建议使用临床上可用的非侵入性代谢成像技术（FdG PET - 正电子发射断层扫描）来评估肿瘤化疗耐药性，并用它来告知临床医生肿瘤内耐药细胞的存在和数量。我们的概念验证肿瘤模型将用于乳腺癌。我们将使用体外和小鼠模型、肿瘤负荷和代谢的非侵入性成像以及肿瘤进展和药物反应的计算进化模型。这些方法将用于检测和测量肿瘤耐药性，并提出最佳治疗策略，最大限度地延长传统乳腺癌治疗的反应持续时间。作者建议结合目前临床上使用的三种化疗策略：(a) 激素治疗（他莫昔芬和芳香酶抑制剂）、(b) 靶向治疗（赫赛汀）和 (c) 标准化疗（阿霉素和紫杉醇）。在初步实验中，我们将把 AT 扩展到所有形式的乳腺癌治疗。强化成像以及治疗前后的分子研究将能够评估肿瘤血管分布和细胞功能对进化治疗的反应。为了改进 AT，我们将研究利用耐药成本来检测耐药群体并抑制其扩散的机制。初步数据表明，表达 P-gp 泵的乳腺癌细胞系比其亲代细胞系加速了新陈代谢，并且对葡萄糖剥夺更敏感。这些细胞在存在 P-gp 底物（例如亚毒水平的维拉帕米、环孢素 A、奎尼丁和克拉霉素）时也表现出能量消耗增加，使这些细胞成为“假药”的候选者，用于增加耐药性成本化疗期间的 P-gp 细胞。 P-gp 表达细胞在存在“假药”的情况下也表现出葡萄糖摄取增加。最后，我们还将研究如何在治疗间隔期间添加雌激素来增加 ER+ 细胞的适应性，从而维持激素治疗敏感细胞的数量。