Project 2: Dissection of clonal architecture and evolution in solid tumors

标题 项目2：实体肿瘤克隆结构和进化的解剖 摘要 越来越多的实体肿瘤证据表明，耐药性和治疗失败是由 病程中抗性亚克隆的自然选择。肿瘤内异质性与肿瘤 亚克隆多样性是肿瘤药物相对于其他医学药物失败率高的关键驱动力 将药物应用于稳定的体细胞基因组而不是在 人类癌症。在这项提案中，我们关注的是一种最无法治愈、基因异质性最强的肿瘤。 (人类胶质母细胞瘤)，为了预测和验证标志着开始的司机改变的景观，方正 患者个体内的进化和治疗适应。我们将开发和应用新技术，以 恶性胶质瘤组织内单个细胞的高通量转录和基因组分析。我们的 目前的系统能够捕获单细胞mRNA，进行cDNA条形码编码，以及芯片上扩增，生成 将扩增产物直接转化为标准的混合测序文库。我们将对相同的设备进行改装 大规模并行、芯片上捕获单个细胞的基因组DNA，用于全基因组扩增和 外显子捕获。接下来，我们将从功能上验证单细胞胶质瘤模型在原位小鼠和 体外和体内的人体系统。这项提议的成功结果将是提供一个完整的 计算-实验流水线，将能够预测任何固体即将到来的进化运动 肿瘤在一组确定的选择压力下。这一信息将具有无价的意义。 以破译不断演变的肿瘤相关性，并提供最准确的治疗预测。

TITLE Project 2: Dissection of clonal architecture and evolution in solid tumors ABSTRACT Increasing evidence in solid tumors suggests that drug resistance and therapeutic failure results from natural selection of resistant subclones during the disease course. Intra-tumor heterogeneity and cancer subclonal diversity is the key driving force of the high failure rate of oncology drugs relative to other medical specialties where drugs are applied to stable somatic genomes rather than the unstable genomes found in human cancer. In this proposal, we focus on one of the most incurable and genetically heterogeneous tumors (human glioblastoma), to predict and validate the landscape of driver alterations that mark initiation, founder evolution, and therapy adaptation within individual patients. We will develop and apply novel technologies for high-throughput transcription and genomic analysis of individual cells within malignant glioma tissues. Our current system is capable of single cell mRNA capture, cDNA barcoding, and on-chip amplification, generating amplicons for direct conversion into a standard, pooled sequencing library. We will adapt the same device for massively parallel, on-chip capture of genomic DNA from individual cells for whole genome amplification and exome capture. Next, we will functionally validate the single-cell glioma models in orthotopic mouse and human systems in vitro and in vivo. The successful outcome of this proposal will be to deliver an integrated computational-experimental pipeline that will be able to predict the forthcoming evolutionary moves of any solid tumor in the presence of a defined set of selective pressures. This information will be of invaluable significance to decipher evolving tumor dependencies and provide the most accurate therapeutic predictions.