Characterization of Cancer Transcriptomes using Next Generation Sequencing

项目摘要/摘要 高通量基因组学技术对个性化药物和新型癌症的影响 治疗最终将由相应地解释数据的能力决定。因此， 申请者的长期目标是翻译基于基因组的知识，通过综合分析高- 通过基因组技术，开发新的诊断、预后和治疗 癌症的治疗策略。作为这一努力的第一步，这项提议侧重于中心假设 常见的癌症隐藏着反复发生的基因融合突变，而这些突变是由非特异性的 像差。我们认为，癌症转录本的下一代测序可能会阐明这些 推动基因融合，因此确定了以下具体目标来实现这一点：(1)使用 基因组学数据的综合分析以检测ETS阴性前列腺癌的新基因融合，(2) 进一步开发生物信息学方法来优先处理随意嵌合体，并将这些方法应用于 黑色素瘤和胰腺癌，以及(3)实现基于测序的基因和外显子水平的表达 异常值分析用于评估公共可获得数据中的流行率，并提名新的基因融合 收藏。总体而言，如果这一应用的目标实现，我们可能会揭示新的病理基因组学靶点。 癌症可以转化为一种靶向治疗的发展。即使成功地发现了一种 单个目标，无论是直接从提议的工作中发现还是由另一个实验室利用 作为这一提议的结果而开发的方法，将对我们如何治疗癌症产生重大影响。 密歇根翻译病理学中心拥有使用生物信息学和 基因组学用于研究基因表达，特别是基因融合，产生大量的生物标记物和 前列腺癌的治疗靶点，因此是支持 申请人。申请人广泛的初步数据可以证明这一点，这导致了多个高 影响第一作者稿件。鉴于Chinnaiyan博士在指导生物统计学家和 当生物信息学家过渡到成功的独立调查人员时，他将提供类似的职业 当前申请者的发展计划。第一个具体目标是在指导阶段完成的， 将专注于检测前列腺癌的基因融合，因此提供关键的综合分析，癌症 生物学和翻译研究培训。独立阶段的焦点将放在序列上 新建立的肿瘤转录组项目中的嵌合体检测和基于RNA-Seq的离群值分析 表达分析以揭示新的治疗靶点，这些靶点将与， 导师对前列腺癌基因融合的研究。总体而言，NIH独立之路奖将是 申请人必须成为一名独立的调查员，在急需的综合领域 癌症生物学将继续将基于基因组的发现转化为广泛采用的临床应用。

PROJECT SUMMARY/ABSTRACT The impact of high-throughput genomics technologies on personalized medicine and novel cancer treatments will ultimately be determined by the ability to interpret the data accordingly. Therefore, the applicant's long-term objective is to translate genome-based knowledge, through integrative analysis of high- throughput genomic technologies, into the development of novel diagnostic, prognostic, and therapeutic strategies in cancer. As an initial step towards this endeavor, this proposal focuses on the central hypothesis that common carcinomas harbor driving recurrent gene fusion mutations that are hidden by non-specific aberrations. We believe that Next Generation Sequencing of cancer transcriptomes may elucidate these driving gene fusions and therefore established the following specific aims to accomplish this: (1) employ integrative analysis of genomics data to detect novel gene fusions in ETS negative prostate tumors, (2) further develop the bioinformatic approaches to prioritize casual chimeras and apply these methods in melanoma and pancreatic cancer, and (3) implement a sequencing based gene- and exon-level expression outlier profile analysis to assess the prevalence, and nominate novel, gene fusions in publicly available data collections. Overall, if the aims of this application are achieved we may reveal novel pathognomomic targets in cancer that can be translated into the development of a targeted therapy. Even the successful discovery of a single target, whether discovered directly from the proposed work or uncovered by another lab leveraging the methodologies developed as a result of this proposal, will have significant impact on how we treat cancer. The Michigan Center for Translational Pathology has in-depth experience using bioinformatics and genomics for studying gene expression, particularly gene fusions, yielding numerous biomarkers and therapeutic targets in prostate cancer and therefore serves as an ideal environment for supporting the applicant. This can be exemplified by the applicant's extensive preliminary data, which has led to multiple high impact first author manuscripts. Given Dr. Chinnaiyan's excellent record of mentoring biostatisticians and bioinformaticians as they transition into successful independent investigators, he will provide a similar career development plan for the current applicant. The first specific aim, to be completed during the Mentored phase, will focus on detecting gene fusions in prostate cancer and therefore offer critical integrative analysis, cancer biology, and translational research training. The focus of the independent phase will be placed on sequence analysis of chimera detection in newly established cancer transcriptome projects and RNA-Seq based outlier expression analysis to reveal novel therapeutic targets, which will have minimal overlap with, but complements, the mentor's research on prostate gene fusions. Overall, an NIH Pathway to Independence Award will be indispensable for the applicant to become an independent investigator in the much needed field of integrative cancer biology to continue translating genome-based discovering into widely adopting clinical applications.