Cancer Genomics Technology Development

我们通过开发适用于福尔马林固定样本、石蜡包埋样本、流动分选原代细胞和细针抽吸物等样本类型的方案，努力扩大可分析样本的范围。我们已经确定，可以从这些固定的组织中获得有用的核酸制剂，并正在继续扩大对这种材料的分析，用于更广泛的基因组技术，特别是测序。事实上，目前的努力主要是针对下一代测序技术的实施和长读测序技术的纳入。这些方法主要依赖于产生一系列DNA分子，这些分子在测序反应期间被顺序成像。我们正在研究使用这些方法对大小RNA进行基因表达谱分析，检测基因组重排、突变，并测量染色质修饰、DNA酶I超敏感部位和转录因子的定位。这项工作的一个主要部分是开发和实施可用于分析由这项工作产生的大量序列数据的软件工具。虽然这是一个具有挑战性的过程，但它最终将产生一个简化的分析流水线，其中基于序列的多个分析将很容易集成，并且没有阵列平台特定的人工产物。我们计算工作的具体目标包括优化管道，以处理染色质分析、染色体重排、基因表达和突变检测的序列数据。我们目前正在寻求新的方法来针对感兴趣的区域进行定向测序工作，例如由基因组成的一小部分基因组或特别感兴趣的基因的子集，以便能够在单个样本中对数千个基因进行测序，或以互补的方式对数百个样本中的几个关键基因进行测序。我们还在开发有效的方法来瞄准基因间和内含子区域，这些区域通常是癌症中重要的结构重排的位置。我们根据需要利用信息模型来测试我们的基因组表征的新方法。最近，我们已经实施了更新的长读技术，并正在应用这些技术来更好地表征基因组重排及其对转录组的影响。这些研究通常利用来自实验室中感兴趣的癌症的细胞系或动物模型。这项工作在基础研究、翻译研究和临床研究中具有广泛的潜在应用。

We have worked to extend the range of analyzable samples by developing protocols suitable for sample types including formalin fixed, paraffin embedded samples, flow sorted primary cells and fine needle aspirates. We have established that useful nucleic acid preparations can be obtained from these fixed tissues and are continuing to extend the analysis of this material for a wider range of genomic technologies, especially for sequencing. Indeed, current efforts have been directed primarily at the implementation of next generation sequencing technologies and the incorporation of long-read sequencing technologies. These methods primarily depend on producing an array of DNA molecules which are sequentially imaged during the sequencing reaction. We are investigating the use of these methods for gene expression profiling for large and small RNAs, for the detection of genome rearrangements, mutations, and for the measurement of chromatin modifications, DNase I hypersensitive sites, and transcription factor localization. A major part of this effort is the development and implementation of software tools can be used to analyze the massive amount of sequence data which is generated by this work. Although this is a challenging process, it ultimately will yield a streamlined analysis pipeline in which multiple sequence-based assays will be easy to integrate and free of array platform specific artifacts. Specific goals of our computational efforts include the optimization of pipelines to process sequence data for chromatin analysis, chromosome rearrangements, gene expression, and mutation detection. We are currently engaged in pursuing new approaches to target sequencing efforts to regions of interest such as the small proportion of the genome composed of genes, or subsets of genes of particular interest in order to be able to sequence thousands of genes in individual samples or in a complementary fashion, to sequence a few key genes in hundreds of samples. We are also developing efficient methods to target intergenic and intronic regions which are often the sites of important structural rearrangements in cancer. We make use of informative models as need to test our novel approaches to genome characterization. Recently, we have implemented newer long read technologies and are applying these to better characterize genome rearrangements and their effects on the transcriptome. These studies typically utilize cell line or animal models derived from cancers of interest in the laboratory. This work has extensive potential applications in basic, translational, and clinical research..