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

(PQ #4) Single cell barcoding for studies of study clonal evolution in glioblastoma
(PQ
批准号:
9353234
负责人:
Erik Sulman
金额:
$33.2万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-01-01 至 2018-08-31

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项目成果

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中文摘要
翻译
描述(申请人提供):胶质母细胞瘤(GBM)是最常见和最具侵袭性的成人脑肿瘤类型。尽管有标准的护理、伴随的放射治疗和基于替莫唑胺的化疗,但对大多数患者来说,疾病复发通常在一年内发生。最近发现的肿瘤内区域差异可能导致治疗抵抗,突显了这种疾病的复杂性。通过使用shRNA条形码对单个GBM细胞进行高通量测序和标记,可以在不同的环境下研究肿瘤细胞混合物的异质性。这笔赠款的第一个目标是将这一方法应用于在小鼠体内培养基底膜,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化疗和放射治疗的敏感性,我们将对小鼠异种移植瘤应用标准治疗方案,并分析由此产生的肿瘤的细胞多样性。这笔赠款的第二个目的是评估是否可以使用治疗学来调节肿瘤的复杂性,以及这种特性是否在形成治疗耐药性方面发挥作用。通过计算和数学方法,基因组异常图谱可以被分析来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,例如来自诊断肿瘤和匹配的治疗后肿瘤活检,克隆进化的模式可以被揭示。这些可能与患者的特征有关,如预后,但也与肿瘤生物学特征有关,如特定基因组变化的存在。这笔赠款的最终目标是构建THA GBM为逃避治疗和导致复发而采取的进化道路。综上所述,通过评估单个细胞在正常生长特性下、治疗压力下和患者肿瘤中的克隆进化模式,该建议旨在提高我们对GBM为什么对治疗的毒性效应具有如此抵抗力的理解。
英文摘要
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.
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K12 Training for Clinical and Translational Oncology Researchers
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(PQ #4) Single cell barcoding for studies of study clonal evolution in glioblasto
(PQ #4) Single cell barcoding for studies of study clonal evolution in glioblasto
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