Discovering genomic rearrangements under selection in serious ovarian cancer

发现严重卵巢癌选择下的基因组重排

• 批准号: 8773658
• 负责人: Julia Salzman
• 金额: $ 24.15万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8773658
• 关键词: Accounting; Award; Bioinformatics; Carcinoma; Cells; Cessation of life; Chromosomal Rearrangement; Clinical; Complex; Cytogenetics; DNA Sequence Rearrangement; Data; Development; Double Minutes; Early Diagnosis; Early identification; Gene Expression Profile; Gene Fusion; Gene Rearrangement; Genomics; High-Throughput Nucleotide Sequencing; Human; Individual; Malignant Neoplasms; Malignant neoplasm of ovary; Mentors; Mentorship; Methods; Phase; RNA; Recurrence; Research Personnel; Serous; Statistical Methods; Symptoms; Techniques; Technology; Testing; Training; Transcript; Woman; analytical method; cancer genome; career development; deep sequencing; design; killings; molecular marker; novel; outcome forecast; pressure; research study; success; therapeutic target; tumor

Recurrent gene fusions and internal tandem duplications are among the most tumor-specific molecular markers known and can provide the potential for therapeutic targets. With a few notable exceptions, however, relatively common recurrent gene fusions have not been identified in commonly occurring carcinomas, which often have multiple, complex chromosomal rearrangements that are difficult to analyze by traditional cytogenetic approaches. Complex tumor karyotpes make it difficult to identify gene fusions using cytogenetics, but suggest the possibility that recurrent rearrangements producing fusions or internal tandem duplications (ITDs) may be prevalent. This proposal aims to use deep sequencing and the novel analytic techniques described to study aspects of the serous ovarian cancer genome and transcriptome which have remained hidden due to limitations in technology or analytical methods, and to test intra-individual and inter-individual selective pressures on tumors. The aspects of this proposal are as follows 1) to further investigate the extent of gene rearrangements in ovarian cancer, focusing on discovering local rearrangements transcribed into RNA; 2) to determine the composition of a group of novel circular transcripts that I have recently found to be expressed at relatively high levels in normal and pathogenic human cells; 3) to characterize double minutes in ovarian cancer, combining bioinformatics to determine rearrangements in their sequence composition and statistical analysis to determine evolutionary pressures on their composition exerted by the tumors. The applicant has a track-record of success in discovering novel gene fusions with ultra-high throughput sequencing (the ESRRA-C11 orf20 fusion), as well as designing original rigorous statistical and bioinformatic methods for ultra-high throughput data. Under the mentorship of Dr. Patrick O. Brown, a pioneer in high throughput genomic technologies and statistical methods for analyzing them, the applicant will continue career development and training. The first aim of this project will be performed during the mentoring phase, and experiments for aims 2 and 3 will be piloted. The K99/R00 award will support the applicant in her development into an independent investigator.

反复的基因融合和内部串联重复是最具肿瘤特异性的分子 已知的标记物可以提供潜在的治疗靶点。除了一些值得注意的例外， 然而，在常见的复发性基因融合中尚未发现相对常见的复发性基因融合。 癌症，通常有多种复杂的染色体重排，难以通过分析来分析 传统的细胞遗传学方法。复杂的肿瘤核型使得利用该技术识别基因融合变得困难 细胞遗传学，但表明反复重排产生融合或内部串联的可能性 重复（ITD）可能很普遍。该提案旨在使用深度测序和新颖的分析方法 所描述的用于研究浆液性卵巢癌基因组和转录组方面的技术 由于技术或分析方法的限制而仍然隐藏，并测试个体内和个体间 对肿瘤的选择性压力。本提案的内容如下： 1）进一步调查 卵巢癌基因重排的程度，重点是发现局部重排 转录成RNA； 2）确定我拥有的一组新颖的循环转录本的组成 最近发现在正常和致病人类细胞中表达水平相对较高； 3）到 描述卵巢癌中双分钟的特征，结合生物信息学来确定重排 它们的序列组成和统计分析以确定对其组成的进化压力 由肿瘤发挥。申请人在发现新型基因融合方面拥有成功记录 超高通量测序（ESRRA-C11 orf20 fusion），以及设计原创严谨 超高通量数据的统计和生物信息学方法。在高通量基因组技术和分析统计方法的先驱 Patrick O. Brown 博士的指导下，申请人将继续职业发展和培训。该项目的第一个目标将在指导阶段实现，目标 2 和 3 的实验将进行试点。 K99/R00 奖将支持申请人发展成为一名独立研究者。