Comprehensive molecular characterization of endometrial cancer, etiologic heterogeneity, and racial disparities

子宫内膜癌的综合分子特征、病因异质性和种族差异

基本信息

批准号：
10156374
负责人：
Immaculata De Vivo
金额：
$ 112.51万
依托单位：
BRIGHAM AND WOMEN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-02-05 至 2026-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10156374
关键词：
Accounting African American Algorithms Automobile Driving Bioinformatics Biology Blood Cancer Etiology Cancer Patient Carcinoma Cessation of life Classification Clear Cell Clinical Collaborations Data Development Diagnosis Diagnostic Endometrial Carcinoma Endometrial Neoplasms Endometrioid Tumor Epidemiology Ethnic group Etiology Foundations Frequencies Funding Future Genetic Genomics Genotype Hereditary Disease Heterogeneity Histology Incidence Informatics Intervention Knowledge Lead Letters Life Style Malignant Female Reproductive System Neoplasm Malignant Neoplasms Maps Mediation Molecular Molecular Profiling Mutation Oncogenes Outcome Patient Selection Patients Point Mutation Population Population Heterogeneity Prevention strategy Process Prognosis Research Resources Risk Risk Factors Role Sampling Sequence Analysis Serous Somatic Mutation Statistical Data Interpretation Suggestion Techniques Testing The Cancer Genome Atlas Time Tumor Biology Tumor Subtype Tumor stage Variant Woman anticancer research base cancer genome cancer health disparity cancer subtypes carcinogenicity case control comorbidity cost disorder prevention epidemiology study exhaustion exome exome sequencing experience genetic risk factor genomic variation high risk improved insertion/deletion mutation insight molecular subtypes mortality mortality disparity novel population based prognostic significance racial and ethnic racial difference racial disparity racial diversity reproductive risk prediction sample collection sociodemographics survival disparity tool treatment strategy tumor

项目摘要

ABSTRACT Endometrial cancer (EC) is the most common gynecologic cancer in the US. Incidence is increasing, especially for aggressive, understudied tumors that confer poor prognosis and are more often seen in African Americans (AAs). EC has one of the largest survival disparities of all cancers: AAs have >2-fold higher mortality vs. other racial/ethnic groups. The disparity remains after accounting for stage, histology, comorbidities, and treatment. The etiology of aggressive tumors and 2-fold survival disparity are large knowledge gaps in EC. The Cancer Genome Atlas (TCGA) achieved milestones in clarifying endometrial tumor biology. Using exome sequence data, TCGA defined 4 new tumor subtypes with prognostic significance and showed these data can refine subtype classification beyond classic histology. But TCGA used mostly good prognosis endometrioid tumors (>90%) and tumors in white women—with only 46 AAs—to define these subtypes. Our pilot analysis of AA vs. non-AA tumors in these sparse data suggested AAs more often had mutational features suggestive of poor outcomes. We hypothesize somatic differences in AA vs. non-AA tumors may help explain the large survival disparity. Here, we will use the largest, most diverse population to date—including 1,011 AA and 2,043 non-AA cases in the Epidemiology of Endometrial Cancer Consortium (E2C2)—to study genomic variation across the full spectrum of endometrial tumors, distinct risk factor profiles across tumor types, and the role of underlying tumor biology in driving the 2-fold survival disparity. We will: define the mutational landscape and novel tumor subtypes using whole-exome sequence data in 3,054 endometrial tumors and compare these in AA vs. non-AA cases. This will use exhaustive genomic profiling of point mutations, indels, and copy number alterations. Next, we will identify differences in risk factor associations by tumor molecular subtypes in 3,054 cases and 3,054 matched controls. Despite many known EC risk factors, TCGA was not designed to study these in concert with somatic changes. We will combine tumor profiling data in cases with information on known germline genetic and epidemiologic risk factors in cases and controls to study distinct risk factor profiles by tumor subtypes. Finally, we will 3) determine the extent to which tumor molecular subtypes explain the 2-fold survival disparity in AA and non-AA cases: Having characterized tumor genomes, we will use mediation analysis to determine the extent to which tumor molecular profiles in AAs and non-AAs explain the survival disparity. Leveraging E2C2 resources and collaborations, we will characterize the biology and risk profiles of the component subtypes of EC, including aggressive tumors, and somatic differences that drive the survival disparity. Long-term this can lead to refined risk prediction tools, improved targeting of disease prevention and treatment, and strategies to reduce longstanding racial disparities in mortality. Our study will also build a unique platform on which to perform future population-based -omics studies of EC.

抽象的子宫内膜癌（EC）是美国最常见的妇科癌症。事件正在增加，尤其是为了激进，理解的肿瘤，会议预后不佳，并且在非裔美国人中经常看到（AAS）。 EC是所有癌症中最大的生存差异之一：AA具有高于2倍的死亡率，而其他癌症则是其他癌症。种族/族裔。考虑阶段，组织学，合并症和治疗后，差异仍然存在。侵略性肿瘤和2倍生存差异的病因是EC中的较大知识差距。癌症基因组地图集（TCGA）实现了子宫内膜肿瘤生物学的里程碑。使用外显子序列数据，TCGA定义了4种具有预后意义的新肿瘤亚型，并显示这些数据可以完善亚型分类超出了经典组织学。但是TCGA主要使用了良好的预后子宫内膜肿瘤（> 90％）和白人妇女的肿瘤（只有46个AA）来定义这些亚型。我们对AA VS的试点分析这些稀疏数据中的非AA肿瘤表明AAS更多的突变特征表明较差结果。我们假设AA与非AA肿瘤的体细胞差异可能有助于解释较大的生存差距。在这里，我们将使用迄今为止最大的，最大的潜水员人口 - 包括1,011 AA和2,043个非AA 子宫内膜癌联盟流行病学的病例（E2C2） - 研究跨整个基因组变异全子宫内膜肿瘤，各种肿瘤类型的不同危险因素剖面以及潜在的作用肿瘤生物学在驱动2倍生存差异方面。我们将：定义突变景观和新颖肿瘤亚型使用3,054个子宫内膜肿瘤中的全外例序列数据，并将其比较 AA与非AA案件。这将使用点突变，indels和拷贝数的详尽基因组分析改变。接下来，我们将确定肿瘤分子亚型的危险因素关联差异 3,054例和3,054个匹配对照。尽管有许多已知的EC风险因素，但TCGA并未设计为研究这些与躯体变化一起研究。在情况下，我们将结合肿瘤分析数据以及有关在病例和对照中，已知的种系遗传和流行病学风险因素研究不同的风险因素概况通过肿瘤亚型。最后，我们将3）确定肿瘤分子亚型解释的程度在AA和非AA病例中的2倍生存差异：具有表征肿瘤基因组，我们将使用调解分析以确定AAS和NON-AAS中的肿瘤分子谱的程度解释了生存差异。利用E2C2资源和合作，我们将表征生物学和风险 EC的组分亚型的曲线，包括侵袭性肿瘤和驱动的体细胞差异生存差异。长期这可以导致精致的风险预测工具，改善疾病的靶向预防和治疗，以及减少死亡率长期种族差异的策略。我们的研究愿意还建立了一个独特的平台，可以在该平台上进行基于人群的ec的未来基础研究。