Identifying Mutational Drivers of Late Stage Colon Cancer

该提案旨在确定与重要的临床和病理学相关的癌症特异性基因突变， 结肠癌（CC）的流行病学特征。“驱动”基因突变与临床 几乎所有癌症中的行为。然而，驱动CC进展的突变，从容易治愈的 疾病晚期不治之症，尚待确定。我们小组和我们的 合作者已经在CC中确定了140个候选癌症基因（CAN基因）。我们还发现， 在转移性CC中发现的CAN基因突变也在先前的原发癌中发现。这 令人惊讶的结果使我们有机会在多种临床环境中探索CAN基因突变。到 使这些研究，我们已经建立了一个大型的生物储存库，其中含有来自接受治疗的患者的CC， 在过去的20年里，大型医疗中心。这些标本大部分是福尔马林固定石蜡 嵌入式[FFPE]。我们已经开发出先进的方法来提高提取的DNA的效用 从FFPE材料。这些包括可靠地提取大的DNA片段。我们还开发了 “DNA捕获”靶向外显子片段并鉴定FFPE突变的技术和过程 使用“下一代”测序仪。我们建立了基础设施和知识库， 支持高通量组织处理和测序。我们建议使用这些方法来识别 CAN基因突变仅出现在晚期CC中。此外，我们还将从功能上剖析这些 使用细胞系和异种移植小鼠模型的基因。由于CC是具有显著差异的癌症之一， 归因于种族和性别相关的病因因素，我们将比较CC CAN基因突变之间的差异。 非裔美国人和白色患者以及女性和男性患者之间，癌症分期相似， 结果。我们利用一种遗传信息标记- SNP，为前面的研究提供了便利 患者的分类将被直接纳入DNA测序分析。我们的建议 有可能显著推进对癌症转移生物学基础的理解 并深入了解CC患者中基于种族/性别的病因学和结局差异。

This proposal seeks to identify cancer specific gene mutations that are linked with important clinical and epidemiological characteristics of colon cancer (CC). 'Driver' gene mutations are directly related to clinical behavior in virtually all cancers. However, mutations that drive CC progression, from the eady curable disease to late stage incurable disease, are yet to be identified. Recent studies by our group and our collaborators have identified 140 candidate cancer genes (CAN genes) in CC. We also found that virtually all the CAN gene mutations found in metastatic CCs are also found in the antecedent primary cancer. This surprising result gives us an opportunity to explore CAN gene mutations in multiple clinical settings. To enable these studies, we have constructed a large biorepository containing CCs from patients treated at a large medical center over the last 20 years. The majority of these specimens are formalin-fixed paraffin embedded [FFPE]. We have developed sophisticated approaches to enhance the utility of DNA extracted from FFPE materials. These include reliable extraction of large DNA fragments. We also developed the technologies and processes to 'DNA capture' targeted exonal fragments and identify mutations from FFPE material using a 'next generation' sequencer. We have developed an infrastructure and knowledge base to support high throughput tissue processing and sequencing. We propose to use these methods to identify CAN gene mutations which appear only in late stage CCs. Also we will functionally dissect the role of these genes using cell line and xenograft mouse models. As CC is one of the cancers with significant disparities attributed to race and gender associated etiologic factors, we will compare CC CAN gene mutations between African American and white patients and between females and male patients, of similar cancer stage and outcome. The former studies will be facilitated by our use of an Ancestry Informative Marker- SNP classification of patients which will be incorporated directly into the DNA sequencing analyses. Our proposals have the potential to significantly advance the understanding of the biological basis for cancer metastasis and to gain insights into racial/gender based differences in etiology and outcomes among CC patients.