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)：在这个项目中，我们探索了适应性治疗(AT)的概念在临床前的应用，这是一个由本基金的提出者创造的术语。AT改变了目前无法治愈的癌症的治疗模式，从最大限度地杀灭肿瘤细胞(“全力以赴”)的方法转变为使用“进化启蒙的”药物组合来稳定肿瘤负担。我们的目标是将出现多药耐药克隆(MDR)的可能性降至最低，MDR是当前癌症治疗失败和患者死亡的最终原因。除了最初的AT促进化疗耐药和化疗敏感肿瘤细胞竞争的想法外，作者还建议探索基于进化的方法，增加化疗耐药的成本，使这些细胞比化疗敏感的细胞更不适合，从而降低出现耐药肿瘤的可能性。最后，作者建议使用临床可用的非侵入性代谢成像技术(FDGPET-正电子发射断层扫描)来评估肿瘤的化疗耐药性，并利用这一技术向临床医生通报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。这些方法将被用来检测和测量肿瘤耐药性，并建议最优的治疗策略，最大限度地延长对传统乳腺癌治疗的反应时间。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。密集的成像和治疗前和治疗后的分子研究将允许评估肿瘤血管和细胞功能对进化治疗的反应。为了改善AT，我们将研究利用耐药性成本来检测耐药群体和抑制其增殖的机制。初步数据显示，表达P-gp泵的乳腺癌细胞系比其亲代细胞系代谢加快，对葡萄糖剥夺更敏感。这些细胞还表现出在亚毒性水平存在P-gp底物时能量消耗增加，如维拉帕米、环孢素A、奎尼丁和克拉霉素，使这些候选的“假药”被用来在化疗期间增加P-gp细胞的耐药性成本。表达P-gp的细胞在“假药”存在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期间添加雌激素来增加ER+细胞的适合性，从而保持激素治疗敏感细胞的数量。 与公共卫生相关：目前癌症的治疗剂量是患者可以承受的最大剂量，即“全力以赴”的治疗模式，最终会加速化疗耐药的出现并导致治疗失败。在这个项目中，我们探索适应性治疗方法，它包括使用必要的最小剂量来维持肿瘤的控制，通过促进化疗敏感细胞和化疗耐药细胞之间的竞争来延迟耐药的出现，并最大化患者的寿命。我们的方法包括使用非侵入性的肿瘤新陈代谢成像技术来响应“假”药物，以估计肿瘤负担和化疗耐药水平，并将这些数据输入到计算模型中，该模型将推荐药物剂量和组合，以获得延长患者生存的最佳概率。