Precancer Atlas of Familial Adenomatous Polyposis

项目摘要 我们正在从家族性腺瘤性息肉病建立结直肠癌前病变图谱。 (FAP)患者。我们已经建立了一个生物库，其中包含来自78个捐赠者的数千份样本。我们 已应用基因组学、表观基因组学、蛋白质组学、脂体学、代谢学、转录学和 空间分析，以表征分子变化发生在从 从正常粘膜到癌症。我们建议使用综合方法来进一步发展我们的 癌症前地图集。通过对同一患者的多个息肉进行分析，我们的癌前病变图谱使 描述导致结直肠癌的早期事件。我们会： 1)在监测期间完成从100名捐赠者那里采购纵向组织样本 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 结肠腺癌。这些材料将用于我们自己的中心，也将用于 提供给人类肿瘤图集网络(Htan)。医疗记录，纵向样本 还将收集所有相关的元数据。 2)用最先进的组学和成像技术对组织样本进行表征。 3)整合组学、影像和医学信息的成果，构建时空、 多维、集成的多组学癌症图谱，并开发纵向和预测性的 癌前生物学和进展的模型。 4)完成我们的多组学技术的建立，完成我们的法典，SnRNA-seq 和器官侧写。 5)完成我们对大量样本的《多尺度深度数据分析》的发布 从几个人那里。使用此信息指导其他数据收集，包括我们的以下内容- UP SNRNA-SEQ实验和我们在有机物模型中的假设检验实验。 6)确定导致息肉的因素(如生殖系遗传、免疫功能障碍) 异质性，并基于这些数据建立疾病进展模型。 7)使所有生物检疫剂、信息、协议和软件可供PCA、Htan和 普通科学界。

Project Summary We are building a Precancer Atlas of colorectal cancer from Familial Adenomatous Polyposis (FAP) patients. We have built a biobank containing thousands of samples from 78 donors. We have applied genomic, epigenomic, proteomic, lipidomic, metabolomic, transcriptomic, and spatial assays to characterize the molecular changes occurring during the progression from normal mucosa to cancer. We propose to use an integrated approach to further develop our Precancer Atlas. By profiling multiple polyps from the same patient, our Precancer Atlas enables characterization of the early events driving colorectal cancer. We will: 1) Complete procurement of longitudinal tissue samples from 100 donors 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) Characterize the tissue samples with state-of-the-art omics and imaging technologies. 3) Integrate results from -omics, imaging and medical information, to build a spatiotemporal, multidimensional, integrative multi-omics cancer atlas, and develop longitudinal and predictive models for PreCancer biology and progression. 4) Complete our establishment of multi-omics technologies, finishing our CODEX, snRNA-seq and organoid profiling. 5) Complete the publication of our “multiscale deep data analysis” on a large number of samples from a few people. Use this information to guide additional data collection, including our follow- up snRNA-seq experiments and our hypothesis-testing experiments in organoid models. 6) Identify factors (e.g. germline genetics, immune dysfunction) contributing to polyp heterogeneity and 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.