Discovering genomic rearrangements under selection in serious ovarian cancer

描述（由申请人提供）：复发性基因融合和内部串联重复是已知的最具肿瘤特异性的分子标志物之一，可以提供治疗靶点的潜力。然而，除了少数值得注意的例外，在常见的癌症中还没有发现相对常见的复发性基因融合，这些癌症通常具有难以通过传统细胞遗传学方法分析的多个复杂的染色体重排。复杂的肿瘤核型使得难以使用细胞遗传学鉴定基因融合，但表明产生融合或内部串联重复（ITDs）的经常性重排可能是普遍的。该提案旨在使用深度测序和所描述的新分析技术来研究由于技术或分析方法的限制而仍然隐藏的浆液性卵巢癌基因组和转录组的方面，并测试个体内和个体间对肿瘤的选择性压力。该建议的方面如下：1）进一步研究卵巢癌中基因重排的程度，重点是发现转录成RNA的局部重排; 2）确定一组新的环状转录物的组成，我最近发现这些转录物在正常和致病性人类细胞中以相对高的水平表达; 3）表征卵巢癌中的双微体，结合生物信息学以确定其序列组成中的重排和统计分析以确定肿瘤对其组成施加的进化压力。 申请人在发现具有超高通量测序的新型基因融合（ESRRA-C11 orf 20融合）以及为超高通量数据设计原始严格的统计和生物信息学方法方面取得了成功。在帕特里克奥博士的指导下， 布朗，在高通量基因组技术和分析它们的统计方法的先驱，申请人将继续职业发展和培训。该项目的第一个目标将在辅导阶段实现，目标2和3的实验将进行试点。K99/R 00奖将支持申请人发展成为一名独立的研究者，结合统计和实验方法研究癌症遗传学。 公共卫生相关性： 据估计，卵巢癌每年导致超过14万名妇女死亡，一旦出现临床症状，预后就很差。发现真正的肿瘤特异性分子标志物或鉴定早期和选择性扩增可能是有效的早期诊断所必需的。 浆液性肿瘤的检测，这占卵巢癌死亡的大多数。虽然这项建议的重点是卵巢癌，但这些方法适用于任何癌症，因此具有广泛的意义。 该提案的整合主题是使用深度测序和所描述的新分析技术来研究由于技术或分析方法的限制而仍然隐藏的浆液性卵巢癌基因组和转录组的各个方面。开发的实验和分析方法将适用于所有肿瘤类型，因此与癌症研究具有广泛的相关性。

DESCRIPTION (provided by applicant): 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-C11orf20 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 who combines statistical and experimental approaches to study cancer genetics. PUBLIC HEALTH RELEVANCE: Ovarian cancer is estimated to kill more than 140,000 women every year and has a poor prognosis once it presents with clinical symptoms. Discovery of truly tumor- specific molecular markers or identification of early and selected amplifications may be essential for effective early detection of serous tumors, which account for the majority of ovarian cancer deaths. While this proposal is focused on ovarian cancer, the methods are applicable to any cancer, and thus have broad significance. The consolidating theme of this proposal is 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. The experimental and analytical methods developed will be applicable to all tumor types and hence of broad relevance to the study of cancer.