Precancer Atlas of Familial Adenomatous Polyposis

家族性腺瘤性息肉病癌前图谱

• 批准号: 10900834
• 负责人: MICHAEL P. SNYDER
• 金额: $ 97.09万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-04 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10900834
• 关键词: 7 year old; APC gene; Achievement; Adenocarcinoma; Affect; Atlases; Automobile Driving; Benign; Biological Models; Biology; Cancer Etiology; Cause of Death; Cessation of life; Child; Colectomy; Collaborations; Collection; Colon; Colon Adenocarcinoma; Colon Carcinoma; Colonic Polyps; Colonoscopy; Colorectal Adenocarcinoma; Colorectal Cancer; Communication; Communities; Computer software; Data; Data Analyses; Data Collection; Development; Diagnostic; Dimensions; Disease; Disease Progression; Disease model; Ensure; Event; Evolution; Familial Adenomatous Polyposis Syndrome; Family; Funding; Gene Mutation; Genes; Genetic; Genomics; Heterogeneity; Human; Image; Imaging technology; Immune System Diseases; Individual; Inherited; Integration Host Factors; Lesion; Life; Link; Malignant Neoplasms; Measures; Medical; Medical Records; Metadata; Methylation; Modeling; Molecular; Mutation; Normal tissue morphology; Operative Surgical Procedures; Patients; Persons; Polyps; Precancerous Polyp; Proteome; Protocols documentation; Research; Research Personnel; Sampling; Serum; Site; Solid Neoplasm; Syndrome; System; Technology; Teleconferences; Therapeutic; Tissue Sample; Tissues; United States; Whole Blood; collaborative approach; colon microbiome; colorectal cancer risk; cytokine; data portal; data visualization; epigenomics; experience; genome sequencing; lifetime risk; meetings; metabolome; microbiome; molecular imaging; multiple omics; outreach; participant enrollment; predictive modeling; premalignant; prophylactic; spatiotemporal; transcriptome; tumor; whole genome

Colorectal cancer (CRC) is the third highest cause of cancer death in the United States. Almost 80% of sporadic colorectal cancers have an APC gene mutation. Familial adenomatous polyposis (FAP), a hereditary colon cancer syndrome, is also caused by mutations in APC and affects children as young as 7 years of age. FAP causes hundreds of colonic polyps in affected individuals and a 100% lifetime risk of CRC. In preliminary efforts we have successfully collected hundreds of pre-cancerous colon polyps from individual FAP patients, applied genomic, epigenomic and other multi-omic analyses and begun to elucidate the impact of multiple types of “omic” alterations on precancerous colon polyp evolution toward CRC. We propose to use an integrated and collaborative approach to develop a PreCancer Atlas for colorectal adenocarcinoma using FAP as the disease model. We will: 1) Establish a biospecimen collection pipeline for procurement of longitudinal tissue samples during surveillance colonoscopy and during prophylactic surgical colectomy, including whole blood, serum, normal colonic tissue, colon microbiome, benign pre-cancerous polyps, dysplastic precancerous polyps and colon adenocarcinomas. The material will be used for our own center and will also be available to the Human Tumor Atlas Network (HTAN). Medical records, longitudinal samples and all relevant metadata will also be collected. 2) Establish a center to characterize the tissue samples with state-of-the-art omics and imaging technologies. These include but are not limited to whole genome sequencing, methylation, transcriptome, proteome, cytokine, metabolome, microbiome, and molecular imaging. 3) Establish an analysis core that analyzes and integrates results from -omics, imaging and medical information, builds a spatiotemporal, multidimensional, integrative multi-omics cancer atlas, and develops longitudinal and predictive models for PreCancer biology and progression, as well as data portal and visualization framework. 4) Establish multi-omics technologies on smaller number of samples. 5) Perform a “multiscale deep data analysis” on a large number of samples (57) from a few people and a fewer number of samples (6) from many people. Use this information to guide additional data collection. 6) Identify factors (e.g. germline genetics, microbiome, immune dysfunction) contributing to polyp heterogeneity between and across individuals. Build disease progression models based on these data. 7) Make all biospecimens, information, protocols and software available to the PCA, HTAN and the general scientific community. We expect our efforts will greatly facilitate understanding CRC at its earliest stages and serve as a model for understanding precancerous lesions of other solid tumor malignancies.

结直肠癌(CRC)是美国第三大癌症死亡原因。几乎80%的 散发性结直肠癌有APC基因突变。遗传性家族性腺瘤性息肉病 结肠癌综合症也是由APC基因突变引起的，影响最小为7岁的儿童。 FAP在受影响的个体中导致数百例结肠息肉，并有100%的终身结直肠癌风险。在预赛中 我们已经成功地从个别FAP患者身上收集了数百例癌前结肠息肉， 应用基因组学、表观基因组学和其他多组学分析，并开始阐明多个 癌前结肠息肉向结直肠癌演变的“基因组”改变类型。我们建议使用一种 使用FAP开发结直肠癌癌前病变图谱的集成和协作方法 作为疾病模型。我们会： 1)建立生物样品收集管道，以便在#年期间采购纵向组织样本 监测结肠镜检查和预防性手术结肠切除术，包括全血、血清、正常 结肠组织，结肠微生物组，良性癌前病变息肉，发育不良癌前病变息肉和结肠 腺癌。这些材料将用于我们自己的中心，也将用于人类肿瘤 阿特拉斯网络(HTAN)。还将收集病历、纵向样本和所有相关元数据。 2)建立一个中心，利用最先进的组学和成像技术对组织样本进行表征。 这些包括但不限于全基因组测序、甲基化、转录组、蛋白质组、 细胞因子、代谢组、微生物组和分子成像。 3)建立分析和整合结果的分析核心-组学、成像和医学 信息，建立时空、多维、一体化的多组学癌症图谱，并开发 癌前生物学和进展的纵向和预测模型，以及数据门户和 可视化框架。 4)在较小样本数量上建立多组学技术。 5)对来自少数人和少数人的大量样本(57个)进行“多尺度深度数据分析” 样本数量(6个)来自多个人。使用此信息来指导其他数据收集。 6)确定导致息肉的因素(如生殖系遗传、微生物群、免疫功能障碍) 个体之间和个体之间的异质性。根据这些数据建立疾病进展模型。 7)将所有生物检疫、信息、协议和软件提供给PCA、HTAN和一般 科学界。 我们希望我们的努力将极大地促进对《儿童权利公约》的早期理解，并成为 了解其他实体肿瘤恶性肿瘤的癌前病变。