Identifying Mutational Drivers of Late Stage Colon Cancer

这项建议寻求确定癌症特异性基因突变，这些突变与重要的临床和 结肠癌的流行病学特征。“驾驶员”基因突变与临床直接相关 几乎所有癌症的行为。然而，推动CC进展的突变是可以治愈的 疾病到晚期不治之症，尚待查明。我们团队和我们的团队最近的研究 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，几乎所有的 在转移性CCS中发现的CaN基因突变也在先前的原发癌中发现。这 令人惊讶的结果为我们提供了在多种临床环境中探索CAN基因突变的机会。至 使这些研究成为可能，我们已经构建了一个大型生物信息库，其中包含来自接受治疗的患者的CC 在过去的20年里是一个大型医疗中心。这些标本大部分是福尔马林固定的石蜡标本。 嵌入式[FFPE]。我们已经开发了复杂的方法来提高提取的DNA的实用性 来自FFPE材料。其中包括可靠地提取大的DNA片段。我们还开发了 DNA捕获目标外显子片段并从FFPE中识别突变的技术和过程 使用“下一代”测序仪的材料。我们开发了基础设施和知识库，以 支持高通量的组织处理和测序。我们建议使用这些方法来识别 仅出现在晚期CCS的CaN基因突变。此外，我们还将从功能上剖析这些角色 使用细胞系和异种移植小鼠模型的基因。由于CC是差异显著的癌症之一 由于种族和性别相关的病因因素，我们将比较CC CAN基因突变在 非洲裔美国人和白人患者以及女性和男性患者之间，癌症分期相似和 结果。前面的研究将通过我们使用的祖先信息标记-SNP来促进 将直接纳入DNA测序分析的患者分类。我们的建议 有可能显著提高对癌症转移生物学基础的理解 并深入了解CC患者在病因和预后方面基于种族/性别的差异。

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.