Integrative epigenomic/genomic profiling and biomarker discovery in HPV+ and HPV-

HPV 和 HPV- 的综合表观基因组/基因组分析和生物标志物发现

• 批准号: 9093942
• 负责人: LAURA ROZEK
• 金额: $ 18.55万
• 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: 2011-09-14 至 2017-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9093942
• 关键词: Accounting; Automobile Driving; Behavior; Benchmarking; Bioinformatics; Biological Markers; Carcinogens; Cell Line; Cervical Squamous Cell Carcinoma; Clinical; Clinical Trials; Communities; Complex; DNA Methylation; DNA Modification Process; Data; Development; Employee Strikes; Epidemiological Factors; Epigenetic Process; Etiology; Excision; Gene Expression; Genome; Genomics; Goals; HPV-High Risk; Head and Neck Cancer; Head and Neck Neoplasms; Head and Neck Squamous Cell Carcinoma; Head and neck structure; Human Papillomavirus; Incidence; Individual; Knowledge; Life; Light; Link; Malignant Epithelial Cell; Malignant Neoplasms; Methods; Michigan; Molecular; Molecular Epidemiology of Cancer; National Center for Integrative Biomedical Informatics; Normal Cell; Oral; Oropharyngeal; Oropharyngeal Squamous Cell Carcinoma; Pathway interactions; Patients; Persons; Population Sciences; Primary Neoplasm; Recurrence; Research; Risk; Risk Factors; Role; Sampling; Site; Smoker; Smoking; Specialized Program of Research Excellence; Specimen; Squamous cell carcinoma; Survival Rate; The Cancer Genome Atlas; Therapeutic; Tobacco; Tobacco-Associated Carcinogen; Translational Research; Tumor Cell Line; Universities; Validation; advanced disease; base; behavioral response; carcinogenesis; chemical carcinogenesis; clinically relevant; deep sequencing; epigenomics; experience; functional genomics; genome-wide; high throughput technology; histone modification; improved; innovation; keratinocyte; malignant oropharynx neoplasm; malignant tongue neoplasm; malignant tonsil neoplasm; neoplastic cell; next generation sequencing; non-genetic; non-smoker; novel; outcome forecast; patient population; personalized medicine; protein expression; response; tool; transcriptomics; tumor

DESCRIPTION (provided by applicant): It is clear that differences exist between the molecular mechanisms in HPV-induced squamous cell carcinomas (SCCs) and those linked to tobacco carcinogens. Currently, treatment of head and neck SCC (HNSCC) is not based on HPV status. The incidence of tonsil and tongue cancers have been increasing annually and many contain high risk HPV. It is important to understand differing factors of carcinogenesis in HPV(+) and HPV(-) HNSCC to develop personalized treatment approaches. To do this requires more knowledge of the molecular mechanisms that drive tumor behavior and response to therapy in HPV(+) vs HPV(-) SCCs. Our preliminary data indicate that there are striking epigenetic differences between HPV+ and HPV- tumors, but to appreciate these differences, they must be considered in light of gene expression and other somatic changes. We propose to use gene expression, DNA methylation and histone modifications, and copy number changes to identify molecular mechanisms that define and differentiate HPV-induced from carcinogen-induced HNSCC. The overall objective of this proposal is to understand the differences in the aberrant molecular pathways leading to carcinogenesis in HPV(+) and HPV(-) HNSCCs taking into account smoking and additional epidemiological factors. Our central hypothesis is that by using advanced, integrative bioinformatics methods on the genomic and epigenomic profiles of HPV+ and HPV- tumor cells, we will be able to subdivide HPV+ and HPV- tumors into high and low risk subsets. Our long term goal is to accurately predict and apply the most appropriate treatment regimes for individual HPV+ and HPV- HNSCCs based on smoking, molecular factors and new targets identified in this study. In the first aim, whole-genome analyses will be performed on a well-characterized panel of HPV+ and HPV- oropharyngeal cell lines and primary oral/oropharyngeal (OPSCC) tumors from HPV+ smokers, HPV+ non-smokers, and HPV- ever smokers, and relevant normal cells to define and distinguish aberrant molecular pathways for each etiology. Aim 2 will integrate and characterize genomic, epigenomic and corresponding gene expression changes to prioritize results based on clinical relevancy by developing, validating, and applying integrative methods for the analysis of multifaceted deep sequencing data. Aim 3 will identify and validate top prioritized findings in a larger sample of primary tumor samples. This will confirm clinically important biomarkers and identify aberrant changes associated with etiology, recurrence, or survival in tumor cells from clinical specimens. Our tiered approach from high-throughput technologies to validation in a patient population together with innovative bioinformatics approaches will pave the way to understanding and exploiting somatic differences for optimal therapeutic application. Collectively, our proposed studies will bring us closer to personalized treatment regimes for OPSCCs, as well as provide valuable, accessible tools to the research community for integrative analysis and interpretation of deep sequencing data.

描述（由申请人提供）：很明显，HPV诱导的鳞状细胞癌（SCC）的分子机制与烟草致癌物相关的分子机制存在差异。目前，头颈部鳞状细胞癌（HNSCC）的治疗不是基于HPV状态。扁桃体癌和舌癌的发病率每年都在增加，其中许多含有高危HPV。了解HPV（+）和HPV（-）HNSCC中致癌的不同因素对制定个性化治疗方法至关重要。要做到这一点，需要更多地了解HPV（+）与HPV（-）SCC中驱动肿瘤行为和治疗反应的分子机制。我们的初步数据表明，HPV+和HPV-肿瘤之间存在显着的表观遗传差异，但要理解这些差异，必须根据基因表达和其他体细胞变化来考虑。我们建议使用基因表达，DNA甲基化和组蛋白修饰，和拷贝数的变化，以确定定义和区分HPV诱导的致癌物诱导的HNSCC的分子机制。本提案的总体目标是了解导致HPV（+）和HPV（-）HNSCC致癌的异常分子途径的差异，同时考虑吸烟和其他流行病学因素。我们的中心假设是，通过对HPV+和HPV-肿瘤细胞的基因组和表观基因组图谱使用先进的综合生物信息学方法，我们将能够将HPV+和HPV-肿瘤细分为高风险和低风险子集。我们的长期目标是根据吸烟、分子因素和本研究中确定的新靶点，准确预测并应用最适合个体HPV+和HPV-HNSCC的治疗方案。在第一个目标中，将对一组充分表征的HPV+和HPV-口咽细胞系和来自HPV+吸烟者、HPV+非吸烟者和HPV-曾经吸烟者的原发性口腔/口咽（OPSCC）肿瘤以及相关正常细胞进行全基因组分析，以定义和区分每种病因的异常分子途径。目标2将整合和表征基因组、表观基因组和相应的基因表达变化，通过开发、验证和应用分析多方面深度测序数据的综合方法，根据临床相关性对结果进行优先排序。目标3将在更大的原发性肿瘤样本中识别和验证最优先的发现。这将确认临床上重要的生物标志物，并识别与临床标本中肿瘤细胞的病因、复发或存活相关的异常变化。我们从高通量技术到患者群体验证的分层方法以及创新的生物信息学方法将为理解和利用体细胞差异以实现最佳治疗应用铺平道路。总的来说，我们提出的研究将使我们更接近OPSCC的个性化治疗方案，并为研究界提供有价值的，可访问的工具，用于深度测序数据的综合分析和解释。