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，其发病率正在增加，尤其是。用于预后不良且更常见于非裔美国人的侵袭性、未充分研究的肿瘤 (AA) 是所有癌症中生存差异最大的癌症之一：AA 的死亡率比其他癌症高 2 倍以上。考虑到分期、组织学、合并症和治疗后，差异仍然存在。侵袭性肿瘤的病因学和两倍的生存差异是癌症领域的巨大知识空白。基因组图谱 (TCGA) 在利用外显子组序列阐明子宫内膜肿瘤生物学方面取得了里程碑式的进展。根据数据，TCGA 定义了 4 种具有预后意义的新肿瘤亚型，并表明这些数据可以细化但 TCGA 主要使用预后良好的子宫内膜样肿瘤的亚型分类。 (>90%) 和白人女性肿瘤（只有 46 种 AA）来定义这些亚型。这些稀疏数据中的非 AA 肿瘤表明 AA 更经常具有提示较差的突变特征我们追求 AA 与非 AA 肿瘤的体细胞差异可能有助于解释高生存率。在这里，我们将使用迄今为止最大、最多样化的群体——包括 1,011 名 AA 和 2,043 名非 AA。子宫内膜癌流行病学联盟 (E2C2) 中的病例——研究跨子宫内膜癌的基因组变异全谱子宫内膜肿瘤、不同肿瘤类型的不同危险因素概况以及潜在的作用肿瘤生物学导致两倍的生存差异我们将：定义突变格局和新颖性。使用 3,054 个子宫内膜肿瘤的全外显子组序列数据确定肿瘤亚型，并在 AA 与非 AA 病例这将使用点突变、插入缺失和拷贝数的详尽基因组分析。接下来，我们将确定肿瘤分子亚型的危险因素关联的差异。 3,054 例病例和 3,054 例匹配对照尽管存在许多已知的 EC 风险因素，但 TCGA 的设计初衷并非如此。我们将结合病例的肿瘤分析数据和相关信息来研究这些。病例和对照中已知的种系遗传和流行病学危险因素，以研究不同的危险因素概况最后，我们将3）确定肿瘤分子亚型解释的程度。 AA 和非 AA 病例的生存率差异为 2 倍：在描述了肿瘤基因组特征后，我们将使用中介分析以确定 AA 和非 AA 中的肿瘤分子谱在多大程度上解释了利用 E2C2 资源和合作，我们将描述生物学和风险的特征。 EC 组成亚型的概况，包括侵袭性肿瘤，以及驱动肿瘤的体细胞差异从长远来看，这可以导致风险预测工具的完善，提高疾病的针对性。我们的研究将探讨预防和治疗以及减少长期存在的种族差异的策略。还建立了一个独特的平台，在该平台上进行未来基于人群的 EC 组学研究。