High Definition Clonal Analyses of Archival Pancreatic Adenocarcinoma Samples

描述(申请人提供)：基因组不稳定性似乎与达尔文的选择合作，通过加速发生基因组异常的过程促进癌症的形成，而那些提供选择性生长优势的改变导致克隆进化和扩张。因此，癌症中的基因组异常模式可能会有很大的不同，即使是发生在同一器官部位的肿瘤也是如此。当前癌症基因组工作的一个基本假设是，根据每个样本中存在的选定异常及其靶向途径，肿瘤细胞对可用的临床干预措施变得不同地耐药或敏感。因此，在患者样本中识别选定的异常将有助于开发新的治疗靶点，这些靶点可以被推进，以改进更个性化的癌症治疗方法。基因组技术的最新进展为感兴趣的样本提供了非常详细的分析。例如，寡核苷酸CGH阵列可以在基因内图谱分辨率下区分整个基因组的单拷贝变化，探针错误率为5%。研究复杂组织的一个挑战是细胞混合物的存在和人类肿瘤的多克隆性质。此外，除了掩盖关键的基因组异常外，活检组织中肿瘤细胞群体的克隆性混合物的存在使得辨别哪些基因组异常同时发生和全面定义患者样本的基因组环境变得令人望而却步。福尔马林固定石蜡包埋(FFPE)组织是临床注释样本的巨大来源，具有患者随访数据，包括诊断和治疗结果。因此，这些样本是高清晰度基因组学应用的高度可取和信息丰富的材料，可以改善患者管理，并为选择个性化治疗方法提供分子基础。然而，到目前为止，使用这些样本进行高分辨率基因组分析的一个主要限制是从感兴趣的样本中提取的DNA的质量高度可变。利用客观可量化的标记物，流式细胞术已经被用来从各种组织的初级活检组织中识别和分离肿瘤克隆。一旦确定，单个种群可以流动纯化到95%以上的纯度，用于后续的分子分析。我们最近开发了一种方法，使新鲜冰冻样本的单参数流式细胞术适用于胰腺癌的高清晰度克隆性aCGH分析。该应用程序的总体目标是通过开发和验证与高清晰度阵列CGH分析和下一代临床样本测序兼容的多参数流式细胞术分析来扩展这些方法。这将包括来自胰腺癌配方固定石蜡包埋(FFPE)样本的二倍体和非整倍体细胞群。

DESCRIPTION (provided by applicant): Genomic instability appears to cooperate with Darwinian selection to promote cancer formation through a process in which genomic aberrations occur at accelerated rates, and those alterations that provide a selective growth advantage lead to clonal evolution and expansion. Consequently the patterns of genomic aberrations in cancers can vary extensively, even in tumors arising in the same organ site. A fundamental hypothesis of current cancer genome efforts is that tumor cells become differentially resistant or sensitive to available clinical interventions according to selected aberrations present in each sample and the pathways that they target. Thus the identification of selected aberrations in patient samples will help develop novel therapeutic targets that can be advanced for improved more personalized approach to the treatment of cancer. Recent advances in genomic technologies provide highly detailed analyses of samples of interest. For example oligonucleotide CGH arrays can distinguish single copy changes across an entire genome at intragenic mapping resolution with probe error rates of <5%. A challenge in studying complex tissues is the presence of admixtures of cells and the polyclonal nature of human neoplasias. Furthermore, in addition to masking critical genomic aberrations, the presence of clonal mixtures of neoplastic cell populations in biopsies makes it prohibitively difficult to discern which genomic aberrations occur concurrently and to comprehensively define the genomic contexts of patient samples. Formalin fixed paraffin embedded (FFPE) tissues are a vast resource of clinically annotated samples with patient follow-up data including diagnostic and therapeutic outcomes. As such, these samples represent highly desirable and informative materials for the application of high definition genomics that could improve patient management and provide the molecular basis for the selection of personalized therapeutics. However a major limitation to the use of these samples for high resolution genomic analyses to date is the highly variable quality of the DNA extracted from samples of interest. Flow cytometry has been used to identify and isolate neoplastic clones from primary biopsies in a variety of tissues using objective quantifiable markers. Once identified individual populations can be flow purified to greater than 95% purity for subsequent molecular analyses. We have recently developed methods that adapt single parameter flow cytometry of fresh frozen samples to high definition clonal aCGH analyses of pancreatic cancer. The overall objective of this application is to extend these methods by developing and validating multiparameter flow cytometry assays that are compatible with high definition array CGH analyses and next generation sequencing of clinical samples. These will include diploid and aneuploid cell populations from formulin fixed paraffin embedded (FFPE) samples of pancreatic adenocarcinomas.