(PQD1) Clonal heterogeneity and targeted therapy resistance in melanoma

项目摘要 PQD1：黑色素瘤的克隆异质性和靶向治疗耐药性 癌细胞的分子不稳定性产生了多样性，反过来又使肿瘤演变成为可能。一个强大 来自靶向治疗的选择性压力可以提供显著的临床反应， 进化以产生快速的耐药性肿瘤生长。为了有效地应对现代社会的这一关键挑战， 因此，为了更好地了解肿瘤耐药演变的基本机制， 患者体内。我们假设，晚期乳腺癌患者对靶向治疗的临床耐药性的发展 癌症是显著的肿瘤异质性和克隆选择的函数，而不是细胞适应性的函数。 治疗压力我们的建议将通过靶向抑制致癌BRAF来验证这一假设， 黑色素瘤作为模型系统。为了实现这一目标，我们将采用一种高度创新的方法， 直接从石蜡包埋的实体瘤临床样品中分选肿瘤细胞核的细胞计数法 与下一代测序，提供了一个独特的机会，利用广泛的马约诊所资源 存档的临床注释的黑色素瘤组织。在这些实验中获得的基因组序列数据 从一系列患者匹配的敏感和耐药组织中分选的不同克隆肿瘤群体 将用于定义克隆肿瘤谱系和与抗性相关的相应分子事件。我们 还将利用我们的站起来对抗癌症（SU2C）黑色素瘤的新的和强大的信息学资源， 梦之队努力在本提案中对基因组数据进行临床相关解释。最后，我们将探讨 以独特的、高度临床化的方式调节患者体内产生的抗性的发展的方法 相关动物模型系统。使用来自患者匹配的治疗前（敏感）和 复发（耐药）组织，我们将测试改变药物剂量和时间的影响，并探索合理的 基于来自配对组织的基因组数据的组合治疗。本提案所涉及的关键问题 不仅与黑色素瘤有关，而且与一般的实体瘤有关。我们的研究成果 有可能显着影响我们对耐药性的理解和临床发展， 这一点特别重要，因为许多有针对性的制剂正在达到 诊所

PROJECT SUMMARY PQD1: Clonal heterogeneity and targeted therapy resistance in melanoma Molecular instability of cancer cells generates diversity that, in turn, enables tumor evolution. A strong selective pressure from targeted therapies can provide dramatic clinical responses but also drive such evolution to yield rapid drug resistant tumor growth. To effectively address this key challenge of modern day oncology, it is imperative to better understand the basic mechanisms underlying evolution of resistance in patients in vivo. We hypothesize that development of clinical resistance to targeted therapy in advanced cancers is a function of marked tumor heterogeneity and clonal selection rather than cellular adaptation to therapeutic pressure. Our proposal will test this hypothesis using targeted inhibition of oncogenic BRAF in melanoma as a model system. To achieve this we will employ a highly innovative approach that combines flow cytometry-based sorting of tumor nuclei directly from solid tumor archived paraffin-embedded clinical samples with next generation sequencing, providing a unique opportunity to exploit the extensive Mayo Clinic resources of archived clinically annotated melanoma tissues. Genomic sequence data obtained in these experiments from distinct clonal tumor populations sorted from a series of patient matched sensitive and resistant tissues will be used to define clonal tumor lineages and respective molecular events associated with resistance. We will also leverage the novel and robust informatics resources of our Stand Up To Cancer (SU2C) Melanoma Dream Team effort for clinically relevant interpretation of genomic data in this proposal. Finally, we will explore approaches to modulate development of resistance arising in patients in vivo in a unique, highly clinically relevant animal model system. Using tumorgrafts derived from patient's matched pre-treatment (sensitive) and relapsed (resistant) tissues, we will test the effects of altering drug dose and timing and explore rational combination treatments based on genomic data from paired tissues. The key issue addressed in this proposal holds relevance not only to melanoma but solid tumors in general. The outcomes of our proposed research have potential to significantly impact our understanding of drug resistance and the development of clinically relevant approaches to overcome it, which is of particular relevance as numerous targeted agents are reaching the clinic.