Quantifying patient-specific tumor evolutionary dynamics and resistance mechanisms in HER2-positive breast cancers treated with targeted therapy

量化靶向治疗 HER2 阳性乳腺癌患者特异性肿瘤进化动态和耐药机制

• 批准号: 9757640
• 负责人: Katherine Lee McNamara
• 金额: $ 4.04万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9757640
• 关键词: Address; Affect; Aftercare; Algorithms; Archives; Biological Markers; Biological Models; Breast Cancer Model; Cells; Clinical; Clinical Trials; Computer Simulation; Data; Dedications; Disease; Disease Progression; Disease Resistance; Drug Targeting; Drug resistance; ERBB2 gene; Educational workshop; Evolution; Fellowship; Frequencies; Funding; Future; Gene Expression Profiling; Gene Mutation; Genetic Heterogeneity; Genomics; Growth; Human; Immunologic Markers; In Vitro; In complete remission; Interdisciplinary Study; Journals; Lead; Malignant Neoplasms; Mammary Neoplasms; Mentorship; Messenger RNA; Modeling; Molecular; Monoclonal Antibodies; Mutation; Nature; Neoadjuvant Therapy; Pathologic; Pathology; Patient Care; Patients; Physicians; Population; Proteins; Proteomics; Regimen; Research; Resistance; Resistance development; Resource Development; Role; Running; Sampling; Scientist; Signal Pathway; Solid Neoplasm; Spatial Distribution; Students; Therapeutic Intervention; Time; Tissues; Training; Trastuzumab; Tumor-Derived; Universities; Woman; Work; Writing; base; biomarker development; cancer genomics; career; cohort; effective therapy; faculty mentor; genome sequencing; genomic biomarker; genomic data; genomic profiles; improved; in vivo evaluation; innovation; insight; malignant breast neoplasm; medical schools; multiple omics; novel therapeutics; overtreatment; preclinical study; predicting response; prevent; programs; receptor; resistance gene; resistance mechanism; scaffold; skills; spatiotemporal; symposium; targeted treatment; therapy resistant; transcriptomics; translational cancer research; treatment response; treatment strategy; tumor; tumor growth; tumor progression; whole genome

This proposal addresses the significant clinical and scientific challenge of targeted drug resistance in HER2- positive breast cancer. Breast cancer is the most common cancer in women in the US and HER2-positive disease is particularly aggressive. Trastuzumab, a monoclonal antibody targeted at the HER2 receptor, has revolutionized care for patients with HER2-positive disease, but resistance and subsequent disease progression occur frequently. While there have been multiple attempts to predict response to trastuzumab, previous studies often use bulk expression data from a single time point and do not consider the role of tumor evolution in treatment response. The rich clinical cohort used in this proposal, with longitudinal, multi-region data for each patient, is ideal for studying the spatio-temporal tumor evolutionary dynamics during treatment. We aim to (1) characterize the genomic, transcriptomic, and proteomic changes associated with HER2- targeted therapy and determine if specific alterations are associated with treatment response, (2) use patient genomic data as input to a spatial computational model of breast tumor evolution under targeted treatment to quantify the patient-specific evolutionary dynamics of resistance, and (3) use insights from the evolutionary model to identify drivers of resistance in a unbiased fashion. This proposal addresses the pressing clinical needs of defining biomarkers to predict which patients will respond to HER2-targeted therapy and understanding how and why treatment resistance develops in others. A deeper understanding of how tumors evolve under targeted therapy using HER2-positive breast cancer as a model system will inform more effective treatment strategies that harness tumor evolution to prevent resistance, with applications to other cancers. The fellowship training will take place at the Stanford University School of Medicine, which has unparalleled research, clinical, and student development resources and emphasizes interdisciplinary research and innovation in both the experimental and computational realms. Dr. Christina Curtis is the ideal sponsor for this proposal due to her significant expertise in tumor evolution, cancer genomics, and biomarker development, her federally funded program in modeling therapeutic resistance in breast cancer, as well as her dedication to student mentorship. Dr. Robert West brings expertise in breast cancer pathology, analysis of archival tissue, and physician-scientist career mentorship. Technical and scientific reasoning abilities will be expanded through research, coursework, and faculty mentoring during the training period, facilitating a successful future career in translational cancer research. Attendance at local and national conferences, together with journal clubs and workshops, will also lead to improved writing, presentation, and networking skills.

该提案解决了 HER2-靶向耐药性的重大临床和科学挑战 阳性乳腺癌。乳腺癌是美国女性最常见的癌症，且 HER2 呈阳性 该病特别具有侵袭性。曲妥珠单抗是一种针对 HER2 受体的单克隆抗体， 彻底改变了 HER2 阳性疾病患者的护理，但耐药性和随后的疾病 进展经常发生。虽然已经多次尝试预测曲妥珠单抗的反应， 之前的研究经常使用单个时间点的大量表达数据，并且没有考虑肿瘤的作用 治疗反应的演变。本提案中使用的丰富临床队列，具有纵向、多区域 每个患者的数据非常适合研究治疗期间肿瘤时空进化动态。 我们的目标是 (1) 表征与 HER2-相关的基因组、转录组和蛋白质组变化。 靶向治疗并确定特定改变是否与治疗反应相关，(2) 使用患者 基因组数据作为靶向治疗下乳腺肿瘤进化空间计算模型的输入 量化患者特定的耐药性进化动力学，以及（3）利用进化论的见解 模型以公正的方式识别阻力驱动因素。该提案解决了紧迫的临床问题 需要定义生物标志物来预测哪些患者将对 HER2 靶向治疗产生反应，以及 了解其他人如何以及为何产生治疗耐药性。更深入地了解肿瘤如何 使用 HER2 阳性乳腺癌作为模型系统在靶向治疗下进化将提供更有效的信息 利用肿瘤进化来防止耐药性的治疗策略，并应用于其他癌症。 奖学金培训将在斯坦福大学医学院进行，该学院拥有无与伦比的 研究、临床和学生发展资源，强调跨学科研究和 实验和计算领域的创新。克里斯蒂娜·柯蒂斯博士是本次活动的理想发起人 由于她在肿瘤进化、癌症基因组学和生物标志物开发方面的丰富专业知识，她提出了这一建议 联邦政府资助的乳腺癌治疗耐药性建模项目，以及她对 学生辅导。罗伯特·韦斯特博士带来了乳腺癌病理学、档案组织分析、 以及医师科学家职业指导。技术和科学推理能力将通过以下方式得到扩展： 培训期间的研究、课程作业和教师指导，促进未来职业生涯的成功 转化癌症研究。参加地方和国家会议以及期刊俱乐部和 研讨会还将提高写作、演讲和网络技能。