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: 8332792
• 负责人: LAURA ROZEK
• 金额: $ 47.68万
• 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 2016-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8332792
• 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; carcinogenesis; chemical carcinogenesis; clinically relevant; 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; non-genetic; non-smoker; novel; outcome forecast; patient population; 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）中的分子机制之间存在差异与与烟草癌相关的分子机制之间存在差异。目前，头颈SCC（HNSCC）的治疗不是基于HPV状态。扁桃体和舌癌的发病率每年增加，许多人含有高风险HPV。重要的是要了解HPV（+）和HPV（ - ）HNSCC中癌变的不同因素以开发个性化的治疗方法。为此，需要更多了解驱动肿瘤行为的分子机制，并在HPV（+）与HPV（ - ）SCC中对治疗的反应。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，但是要欣赏这些差异，必须考虑它们的基因表达和其他体细胞变化。我们建议使用基因表达，DNA甲基化和组蛋白修饰，以及拷贝数的变化，以识别定义和区分癌变诱导的HNSCC的HPV诱导的HPV的分子机制。该提案的总体目的是了解导致HPV（+）和HPV（ - ）HNSCC的异常分子途径的差异，并考虑了吸烟和其他流行病学因素。我们的中心假设是，通过使用HPV+和HPV-肿瘤细胞的基因组和表观基因组谱的先进的生物信息学方法，我们将能够将HPV+和HPV-肿瘤细分为高和低风险亚群。我们的长期目标是基于吸烟，分子因素和本研究中确定的新目标，准确预测和应用最合适的治疗方案，以对单个HPV+和HPV-HNSCCS进行精确预测和应用。在第一个目标中，将对HPV+和HPV-口咽细胞系以及来自HPV+吸烟者，HPV+非Smokers以及HPV-有没有吸烟者，吸烟者，吸烟者，吸烟者，HPV+的原发性口服/口腔/口咽（OPSCC）肿瘤进行全基因组分析。以及相关的正常细胞，以定义和区分每个病因的异常分子途径。 AIM 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，以根据临床相关性来确定结果，通过开发，验证和应用整合方法来分析多方面的深层测序数据。 AIM 3将在较大的原发性肿瘤样品样本中识别并验证顶部优先级的发现。这将证实临床上重要的生物标志物，并确定与临床标本中肿瘤细胞中病因学，复发或存活相关的异常变化。从高通量技术到患者人群的验证以及创新的生物信息学方法，我们的分层方法将为理解和利用躯体差异以实现最佳治疗应用铺平道路。总的来说，我们拟议的研究将使我们更接近OPSCC的个性化治疗方案，并为研究社区提供有价值的，可访问的工具，以综合分析和对深层测序数据的解释。