Characterization of Cancer Transcriptomes using Next Generation Sequencing

描述(由申请人提供)：高通量基因组学技术对个性化医学和新型癌症治疗的影响最终将取决于相应地解释数据的能力。因此，申请者的长期目标是通过高通量基因组技术的综合分析，将基于基因组的知识转化为癌症新的诊断、预后和治疗策略的开发。作为这一努力的第一步，这一建议侧重于中心假设，即常见癌症存在驱动通过非特异性异常隐藏的反复发生的基因融合突变。我们相信，下一代癌症转录本测序可能会阐明这些驱动基因融合的原因，并因此建立了以下具体目标来实现这一目标：(1)利用基因组数据的综合分析来检测ETS阴性前列腺癌中的新基因融合，(2)进一步发展生物信息学方法来优先考虑随意嵌合体，并将这些方法应用于黑色素瘤和胰腺癌，以及(3)实施基于测序的基因和外显子水平表达异常值分析，以评估公共可用数据集中的新基因融合的发生率，并提名新的基因融合。总体而言，如果这项应用的目标得以实现，我们可能会揭示癌症的新病因学靶点，这些靶点可以转化为靶向治疗的开发。即使成功地发现了一个单一的靶点，无论是从拟议的工作中直接发现的，还是由另一个利用该提议开发的方法发现的实验室发现的，都将对我们治疗癌症的方式产生重大影响。 密歇根翻译病理学中心在使用生物信息学和基因组学研究基因表达，特别是基因融合方面拥有深入的经验，在前列腺癌中产生了大量的生物标记物和治疗靶点，因此是支持申请者的理想环境。申请人广泛的初步数据可以证明这一点，这导致了多个影响很大的第一作者手稿。鉴于奇奈扬博士在指导生物统计学家和生物信息学家转变为成功的独立调查人员方面的出色记录，他将为目前的申请者提供类似的职业发展计划。第一个具体目标将在指导阶段完成，重点是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。独立阶段的重点将放在新建立的癌症转录组项目中嵌合体检测的序列分析和基于RNA-Seq的异常表达分析，以揭示新的治疗靶点，这些靶点将与导师关于前列腺癌基因融合的研究有最小的重叠，但却是补充。总体而言，NIH独立之路奖对于申请者成为整合癌症生物学领域的独立研究员是不可或缺的，以继续将基于基因组的发现转化为广泛采用的临床应用。 公共卫生相关性：癌症关键基因异常的特征是开发早期诊断标记物和有效治疗靶点的关键。因此，这项提案寻求利用人类肿瘤的下一代转录组测序来检测新的、反复发生的基因融合的资金。由于其癌症特异性表达，新型基因融合是理想的治疗靶点，可能对我们如何分类和治疗癌症产生重大影响，最终将导致改善患者护理。

DESCRIPTION (provided by applicant): 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 pathogenomic 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. PUBLIC HEALTH RELEVANCE: Characterization of key genetic aberrations in cancers holds the key to the development of early diagnostic markers and effective therapeutic targets. Therefore this proposal seeks funding to detecting novel, recurrent gene fusions using Next Generation transcriptome sequencing of human tumors. Due to their cancer-specific expression, novel gene fusions serve as ideal therapeutic targets that could have a significant impact on how we classify and treat cancer which will ultimately lead to improved patient care.