Application of Evolutionary Principles to Maintain Cancer Control (PQ21)

应用进化原理维持癌症控制（PQ21）

• 批准号: 8384513
• 负责人: ROBERT A GATENBY
• 金额: $ 51.22万
• 依托单位: H. LEE MOFFITT CANCER CTR & RES INST
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8384513
• 关键词: Anecdotes; Antineoplastic Agents; Aromatase Inhibitors; Bioluminescence; Breast; Breast Cancer Cell; Breast Cancer Treatment; Cancer Control; Cancer Patient; Cancer cell line; 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 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; Magnetic Resonance Imaging; Maintenance; Malignant Neoplasms; Measures; Metabolic; Metabolism; 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; 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; novel; oncology; pre-clinical; pressure; prevent; research study; resistance mechanism; response; treatment strategy; tumor; tumor progression

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. PUBLIC HEALTH RELEVANCE: Cancer is currently treated with the maximum dose tolerable by the patient, consisting in an "all-out attack" paradigm that ultimately accelerates the emergence of chemoresistance and leads to treatment failure. In this project we explore the Adaptive Therapy approach, which consists of using the minimum dose necessary to maintain the tumor under control, delay emergence of drug resistance by promoting competition between chemosensitive and chemoresistant cells, and maximize the patient's lifespan. Our approach consists of using non-invasive imaging techniques of the tumor metabolism in response to "fake" drugs to estimate both the tumor burden and the levels of chemoresistance, and to feed this data into a computational model which will recommend the drug dosing and combination for the best probability of extended patient survival.

描述（由申请人提供）：在本项目中，我们探讨了自适应疗法概念（AT）的临床前应用，该术语由本赠款的提议者创造。在Shift的情况下，从最大的肿瘤细胞杀伤（“全面攻击”）方法中使用“进化开明的”药物组合来稳定肿瘤负担，从而从最大肿瘤细胞杀伤（“全外攻击”）方法的治疗范例。我们的目标是最大程度地减少多种药物克隆（MDR）出现的可能性，这是当前癌症治疗失败和患者死亡的最终原因。除了促进化学耐药性和化学敏感性肿瘤细胞竞争的原始想法外，作者还提议探索基于进化的方法，从而增加化学耐药性的成本，从而使这些细胞比其化学敏感的对应物的拟合度更低，从而减少了抗体肿瘤的出现可能性。最后，作者提出使用临床上可用的非侵入性代谢成像技术（FDG PET -POSITRON发射断层扫描）来评估肿瘤化学耐药性，并使用此通知临床医生有关肿瘤中耐药细胞的存在和数量。 我们的概念验证肿瘤模型将是乳腺癌。我们将使用体外和小鼠模型，肿瘤负担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，从而最大程度地延长对常规乳腺癌治疗的反应持续时间。作者建议将目前在诊所中使用的三种化学治疗策略结合：（a）激素治疗（他莫昔芬和芳香酶抑制剂），（b）靶向治疗（赫赛汀），以及（c）标准化学疗法（阿霉素和紫杉醇）。在初步实验中，我们将扩展到所有形式的乳腺癌治疗。强化成像以及治疗前和治疗后分子研究将允许评估肿瘤血管和细胞功能，以响应进化治疗。为了改善，我们将检查机制，以利用对检测抗性种群的抵抗成本并抑制其增殖。初步数据表明，表达P-GP泵的乳腺癌细胞系具有加速代谢，并且对葡萄糖剥夺更敏感。这些细胞还显示出在P-gp底物（例如Verapamil，Cyclosporin A，Quinidine和Clarithromycin）下的能量消耗增加，以下毒性水平，使这些候选者用于“假药”，以增加化学疗法时期P-GP细胞的抗药性成本。在存在“假药”的情况下，P-gp表达细胞还显示出增加的葡萄糖摄取。最后，我们还将研究如何使用在治疗间隔中添加雌激素来增加ER+细胞的适应性，从而维持激素疗法 - 敏感细胞的数量。 公共卫生相关性：目前，患者的最大剂量可以治疗癌症，由“全面攻击”范式组成，最终加速了化学耐药性的出现并导致治疗衰竭。在该项目中，我们探索了自适应疗法方法，该方法包括使用所需的最低剂量来维持受到控制的肿瘤，通过促进化学敏感性和化学耐药细胞之间的竞争来延迟耐药性出现，并最大程度地提高患者的寿命。我们的方法包括使用肿瘤代谢的非侵入性成像技术，以响应“假”药物来估计肿瘤负担和化学耐药水平，并将这些数据馈送到计算模型中，该数据将建议使用药物给药和组合，以提高扩展患者存活的最佳可能性。