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: 8788508
• 负责人: Julia Salzman
• 金额: $ 23.48万
• 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/8788508
• 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.

复发性基因融合和内部串联复制是最具肿瘤特异性的分子