High Throughput Transcriptome Sequencing for Systematic Detection of Recurrent Tr

用于系统检测复发性 Tr 的高通量转录组测序

• 批准号: 8250350
• 负责人: Chandan Kumar-Sinha
• 金额: $ 16.91万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-01 至 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8250350
• 关键词: ABL1 gene; Address; Amino Acids; Aneuploidy; Apoptosis; Area; Bioinformatics; Biological Assay; Cancer Etiology; Cancer cell line; Candidate Disease Gene; Cells; Cessation of life; Chimera organism; Chromosome abnormality; Chromosomes; Chronic Myeloid Leukemia; Clinical; Code; Communities; Complex; Data; Data Quality; Detection; Development; Diagnostic; ERBB2 gene; Early Diagnosis; Economic Burden; Epidermal Growth Factor Receptor; Epithelial Cells; Face; Fluorescent in Situ Hybridization; Funding; Future; Gastrointestinal Stromal Tumors; Gene Expression; Gene Expression Profile; Gene Fusion; Gene Targeting; Genes; Genetic; Genome; Genome Components; Genomics; Germ-Line Mutation; Goals; Housing; Human; Length; Libraries; Malignant Neoplasms; Malignant neoplasm of lung; Malignant neoplasm of pancreas; Malignant neoplasm of prostate; Maps; Medical Research; Methods; Michigan; Molecular; Molecular Profiling; Mus; Mutation; Normal tissue morphology; Nucleotides; Oncogenes; PDGFRB gene; Pancreas; Pancreatic Adenocarcinoma; Pharmaceutical Preparations; Polyploidy; Prognostic Marker; Protein Isoforms; Protocols documentation; Public Health; RNA; RNA Splicing; Reading; Recurrence; Running; Sample Size; Sampling; Sequence Analysis; Structure; System; TMPRSS2 gene; Techniques; Testing; Therapeutic Intervention; Tissue Microarray; Tissues; Transcript; United States; Universities; Variant; Xenograft procedure; anticancer research; base; cancer genome; cancer genomics; cohort; genome sequencing; genome-wide; improved; in vivo; indexing; inhibitor/antagonist; interest; malignant breast neoplasm; next generation; novel; novel therapeutics; outcome forecast; pancreatic cancer cells; public health relevance; small molecule; socioeconomics; success; therapeutic target; tool; transcriptomics; tumor; tumor xenograft

DESCRIPTION (provided by applicant): Cancer continues to exact a massive socio-economic burden on the United States and world community and early detection and targeted therapy remain the core dual-goals of all cancer research. Cancer results from accumulated somatic and/ or germline mutations, and several genomic aberrations have emerged as successful diagnostic/ prognostic markers and therapeutic targets such as the BCR-ABL1 gene fusion in Chronic Myeloid Leukemia, PDGFR mutation in gastrointestinal stromal tumors, ERBB2 amplification in breast cancers, and EGFR mutations in lung cancers etc. In order to systematically discover key genetic aberrations in cancers, genome-wide sequencing of candidate genes has been undertaken(1-5) and based on these global molecular analyses, it has been argued that key cancer genes act in concert with a battery of other diverse genomic aberrations(6). The recent advent of next-generation sequencing platforms (7) has made it possible to address the ambitious goal of delineating the landscape of cancer genome aberrations (8, 9). While whole genome sequencing throughput continues to evolve, cancer genomic studies that often need analysis of scores, if not hundreds, of samples still face practical bottlenecks. Basically, cancer genome is often highly aneuploid (aberrant chromosome numbers) or polyploid (with aberrant sets of chromosomes), and almost always highly rearranged, with several areas of gains and losses (10). To adequately analyze these complex sequences, requires extra deep coverage of the genome that is not yet routinely feasible (or economical) over large sample sizes. Therefore, we have considered a complementary approach of focusing on the 'expressed' component of the genome, namely the transcriptome. Sequencing the transcriptome provides an in depth coverage of the genomic coding sequences, as well as serves as a direct readout of gene expression, alternatively spliced isoforms, chimeric transcripts and mutations, thus enriching the data for 'functional' aberrations. We have recently applied transcriptome sequencing to discover multiple novel gene fusions and RNA chimeras in prostate cancer, including the discovery of a recurrent chimera, SLC45A3-ELK4 in a subset of prostate cancer tissues (11). Subsequently, in a proof of concept study we have improved our technique by developing the method of 'paired end transcriptome sequencing' to systematically identify gene fusions and chimeric transcripts in cancers (12). We are now focused on applying transcriptome sequencing to discover recurrent gene fusions and other transcript aberrations in pancreatic cancer, the 4th most common cause of cancer related deaths in the US, with the worst prognosis of all major malignancies (5 year survival < 3%), making it a major public health concern and an exquisitely challenging bio-medical research problem(13). The aim of this proposal is to discover novel cancer-specific, recurrent gene fusions and other signature genetic/ transcriptomic aberrations in pancreatic cancer that could be characterized further to develop early diagnostic markers and therapeutic targets. The specific aims are to 1. Generate high throughput transcriptome sequencing data from pancreatic cancer cell lines, pancreatic adenocarcinomas and matching normal tissues. 2. Bioinformatically identify cancer-specific, recurrent gene fusions, chimeric transcripts, non synonymous coding mutations, and gene expression signatures in pancreatic cancer; validate candidate aberrations and screen larger sample cohorts to determine recurrence and to 3. Functionally validate novel, recurrent or potentially driver aberrations with clinical implications. Overall, we envision discovering a pathognomonic gene fusion or other transcript aberrations in pancreatic cancers a la BCR-ABL1 in CML or TMPRSS2-ERG in prostate cancers, and provide a general roadmap for similar discoveries in other common cancers. PUBLIC HEALTH RELEVANCE: Characterization of key genetic aberrations in cancers holds the key to the development of early diagnostic markers and effective therapeutic targets. High throughput whole genome sequencing applications represent the most powerful tools to address this problem, but are limited by logistical and analytical considerations. Therefore this proposal seeks funding to adapt the high throughput next generation sequencing applications to develop a complementary approach of 'transcriptome' sequencing analyses to identify novel, recurrent gene fusions and other transcript aberrations in cancer that can be further characterized to develop early diagnostic markers and novel therapeutic candidates. As a test case, we propose to analyze pancreatic cancer, which is the 4th most common cause of cancer related deaths in the US, with the worst prognosis of all major malignancies (5 year survival < 3%).

描述（由申请人提供）：癌症继续在美国和世界社区中确定巨大的社会经济负担，以及早期发现和靶向疗法仍然是所有癌症研究的核心双重目标。 Cancer results from accumulated somatic and/ or germline mutations, and several genomic aberrations have emerged as successful diagnostic/ prognostic markers and therapeutic targets such as the BCR-ABL1 gene fusion in Chronic Myeloid Leukemia, PDGFR mutation in gastrointestinal stromal tumors, ERBB2 amplification in breast cancers, and EGFR mutations in lung cancers etc. In order to系统地发现了癌症中的关键遗传畸变，已经进行了候选基因的全基因组测序（1-5），并基于这些全球分子分析，人们认为，关键的癌症基因与其他多样的基因组畸变作用（6）。下一代测序平台（7）的最近出现使得解决了描述癌症基因组畸变景观的雄心勃勃的目标（8、9）。尽管整个基因组测序吞吐量继续发展，但通常需要分析得分（即使不是数百个样本）的癌症基因组研究仍然面临实用的瓶颈。基本上，癌症基因组通常是高度非整倍体（异常的染色体数）或多倍体（具有异常的染色体），几乎总是高度重排，有几个领域的增长和损失（10）。为了充分分析这些复杂的序列，需要对大型样本量尚不可行（或经济）的基因组进行额外的深层覆盖。因此，我们考虑了一种互补的方法，即关注基因组的“表达”成分，即转录组。测序转录组提供了基因组编码序列的深度覆盖范围，并作为基因表达的直接读数，替代剪接的同工型，嵌合转录本和突变，从而丰富了“功能性”畸变的数据。我们最近应用了转录组测序，以在前列腺癌中发现多个新型基因融合和RNA嵌合体，包括在前列腺癌组织中发现复发性嵌合体，SLC45A3-ELK4（11）。随后，在一项概念验证研究中，我们通过开发“配对最终转录组测序”的方法来改进我们的技术，以系统地识别癌症中的基因融合和嵌合转录本（12）。现在，我们专注于应用转录组测序，以发现胰腺癌的复发基因融合和其他转录畸变，这是美国与癌症相关死亡的第四个最常见原因，所有主要的恶性肿瘤的预后最差（5年生存率<3％），这是一个主要的公共卫生问题，这是一个重大的公共健康问题，这是一个重大的挑战性挑战性的生物生物研究（13）。该提案的目的是发现胰腺癌中新型的癌症特异性，复发基因融合和其他特征性的遗传/转录组畸变，这些遗传/转录组畸变可以进一步发展以发展早期诊断标记和治疗靶标。具体目的是1。从胰腺癌细胞系，胰腺腺癌和匹配正常组织匹配的高吞吐量转录组测序数据。 2。生物信息上鉴定胰腺癌中的癌症特异性，复发基因融合，嵌合式转录本，非同义编码突变和基因表达特征。验证候选畸变和筛查较大样本队列以确定复发，并对3。在功能上验证具有临床意义的新颖，经常性或潜在的驱动器像差。总体而言，我们设想在胰腺癌或前列腺癌中发现胰腺癌或TMPRSS2-erg中的胰腺癌中发现病理学基因融合或其他转录畸变，并为其他常见癌症中的类似发现提供一般的路线图。 公共卫生相关性：癌症中关键遗传畸变的表征是早期诊断标记和有效治疗靶标的开发的关键。高吞吐量整个基因组测序应用是解决此问题的最强大工具，但受到后勤和分析考虑的限制。因此，该提案寻求资金来适应高吞吐量的下一代测序应用，以开发“转录组”测序分析的补充方法，以鉴定癌症中新型，经常性的基因融合和其他转录物畸变，这些方法可以进一步表征，以开发早期诊断标记和新型治疗候选者。作为测试案例，我们建议分析胰腺癌，这是美国与癌症相关的第四个最常见原因，所有主要恶性肿瘤的预后最差（5年生存率<3％）。