(PQ #4) Single cell barcoding for studies of study clonal evolution in glioblastoma

描述（由申请人提供）：胶质母细胞瘤（GBM）是成人脑肿瘤中最常见和最具侵袭性的类型。尽管有标准的护理、伴随的放射和基于替莫唑胺的化疗治疗，大多数患者的疾病复发通常在一年内发生。最近发现肿瘤内的区域差异可能导致治疗耐药性，这强调了疾病的复杂性。通过使用shRNA条形码对单个GBM细胞进行高通量测序和标记，可以在不同情况下研究肿瘤细胞混合物的异质性。这项资助的第一个目标是在小鼠中生长GBM时应用这种方法，以评估在没有治疗挑战的情况下增殖后的复杂程度。为了研究肿瘤细胞混合物的异质性是否有助于对化疗和放疗的敏感性，我们将对小鼠异种移植物应用标准治疗方案，并分析所得肿瘤的细胞多样性。这项资助的第二个目的是评估是否可以使用治疗方法调节肿瘤的复杂性，以及这种特性是否在产生治疗抗性中发挥作用。通过计算和数学方法，可以分析基因组异常谱以推断克隆和亚克隆细胞群体。当应用于多个相关的基因组图谱时，例如来自诊断性肿瘤和匹配的治疗后肿瘤活检，可以揭示克隆进化的模式。这些可能与患者特征（如结果）有关，但也与肿瘤生物学特征（如存在特定基因组改变）有关。这项资助的最终目的是构建GBM逃避治疗并导致复发的进化路径。总之，通过评估正常生长特性下、治疗应激下和患者肿瘤中单细胞的克隆进化模式，该提案旨在提高我们对GBM为何对治疗的毒性作用如此耐受的理解。

DESCRIPTION (provided by applicant): Glioblastomas (GBM) are the most common and aggressive type of adult brain tumors. Despite the standard of care, concomitant radiation and temozolomide based chemotherapy treatment, disease relapse typically occurs within a year for most patients. The complexity of the disease is underlined by recent discoveries of regional differences within the tumor that may contribute to therapy resistance. Through high throughput sequencing and tagging of individual GBM cells using shRNA barcodes, the heterogeneity of the tumor cell mix can be investigated under variable circumstances. The first goal of this grant is to apply this methodology when growing GBMs in mice, to evaluate the degree of complexity after proliferation in absence of therapeutic challenges. To study whether the heterogeneity of the tumor cell mix contributes to the sensitivity to chemo- and radio-therapy, we will apply standard treatment protocols to mouse xenografts and analyze the cellular diversity of the resulting tumors. The second aim of this grant is to evaluate whether tumor complexity can be modulated using therapeutics and whether this property plays a role in developing treatment resistance. Through computational and mathematical approaches, the genomic abnormality profile can be analyzed to infer clonal and subclonal cell populations. When applied to multiple related genomic profiles, such as from diagnostic tumors and matching post-treatment tumor biopsies, patterns of clonal evolution can be uncovered. These can be related to patient features such as outcome, but also to tumor biology characteristics such as the presence of specific genomic alterations. The final aim of this grant is to construct the evolutionary path tha GBM take to escape treatment and result in recurrence. In summary, by evaluating the patterns of clonal evolution of single cells under normal growth properties, under the stress of treatment and in patient tumors, this proposal aims to improve our understanding of why GBM are so resistant to the toxic effects of therapy.