Washington University Human Tumor Atlas Research Center

华盛顿大学人类肿瘤图谱研究中心

• 批准号: 10242181
• 负责人: Samuel Achilefu
• 金额: $ 177.19万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10242181
• 关键词: 3-Dimensional; Affect; Anatomy; Archives; Area; Atlases; Biopsy; Biopsy Specimen; Cancer Biology; Cancer Center; Cancer Model; Cancer Patient; Cataloging; Cells; Clinical; Clinical Oncology; Clinical Research; Clinical Treatment; Clinical Trials; Clonal Evolution; Clonality; Collaborations; Communities; Comprehensive Cancer Center; Cytometry; DNA; Data; Data Analyses; Data Set; Dimensions; Discipline; Disease; Drug resistance; Ecosystem; Ensure; Evolution; FAIR principles; Fostering; Foundations; Future; Generations; Genes; Genome; Genomics; Glioblastoma; Goals; Histopathology; Human; Image; Immune; Immunofluorescence Immunologic; Individual; Infrastructure; Institutes; Knowledge; Link; Location; Magnetic Resonance Imaging; Malignant Neoplasms; Measures; Medicine; Methodology; Minority Groups; Modeling; Molecular; Mutate; Mutation; Neoplasm Metastasis; Organ; Pancreatic Ductal Adenocarcinoma; Pathology; Pathway Analysis; Pathway interactions; Patient Recruitments; Patients; Phase; Phenotype; Physicians; Pilot Projects; Positron-Emission Tomography; Process; Prognosis; Proteins; Proteome; Proteomics; Recurrence; Reporting; Research; Research Personnel; Resistance; Sampling; Series; Site; Slice; Solid Neoplasm; Spatial Distribution; Specimen; Structure; Time; Tissues; Translational Research; United States National Institutes of Health; Universities; Validation; Washington; analysis pipeline; anticancer research; biomarker discovery; cancer cell; cancer therapy; cancer type; cell type; chemotherapy; clinical application; clinical care; clinical imaging; cohesion; data integration; density; diverse data; drug development; exome sequencing; experience; genome sequencing; imaging informatics; improved; in vivo; innovation; liquid chromatography mass spectrometry; malignant breast neoplasm; medical schools; metabolome; metabolomics; multidisciplinary; neoplastic cell; new technology; new therapeutic target; patient population; relational database; response; single-cell RNA sequencing; synergism; therapeutic development; therapy resistant; three dimensional structure; three-dimensional modeling; tool; transcriptome sequencing; triple-negative invasive breast carcinoma; tumor; tumor progression; whole genome

Project Summary/Abstract: Overall Diverse areas of cancer research have progressed to the point that it is now feasible to meaningfully integrate research data and clinical information across the molecular, cellular, and tissue realms into a larger, more detailed picture of the onco-dynamics of cancer, including spatial-temporal details during cancer treatment and progression. Physicians and researchers at Washington University School of Medicine (WUSM) and the Siteman Cancer Center (WUSM-SCC) are longtime leaders in the allied sub-disciplines of cancer, including genomics, proteomics, imaging, functional characterization, pathology, clinical trials, and clinical care. WUSM- SCC is an NCI-designated Comprehensive Cancer Center, which sees ~9,000 new cancer patients annually. Building on our expertise, established infrastructure, large patient population, and extraordinary institutional commitment, we propose to develop the Washington University Human Tumor Atlas Research Center (WU- HTARC) within the NIH Human Tumor Analysis Network (HTAN). We will focus on generating organ-specific human tumor atlases for three high priority cancer types associated with exceptionally poor prognosis: the triple negative breast cancer (TNBC), glioblastoma (GBM), and pancreatic ductal adenocarcinoma (PDAC). Collectively, we will analyze ~1,600-2000 samples collected from spatially separated locations and at different time points along the clinical treatment course from 300-375 patients (selected from ~750 recruited patients) for the duration of the project. In addition to standard histopathological analyses, bulk DNA/RNA sequencing, proteomics, and clinical imaging, etc., we will conduct cutting-edge, comprehensive analyses, including single cell RNA-Seq (scRNA-Seq), multiplexed immunofluorescent protein localization (MxIF), mass cytometry/Cytometry by Time of Flight (CyTOF) cellular characterization, metabolomics analysis, innovative imaging, and 3-D modeling. We have established infrastructure covering the aforementioned areas, from specimen procurement (Biospecimen Unit), to multidisciplinary analyses modules (Characterization Unit), and to analysis pipelines (Data Analysis Unit). Data generated from this study will be valuable for revealing the clonal evolution of the tumor cells from longitudinally collected specimens and to reconstruct the tumor ecosystem involving non- cancer cells and acellular structures. Our atlases will have comprehensive data integration at the 3D level over time, providing unprecedented 4D models for the 3 selected cancer types. Our established infrastructure and continuous efforts in incorporating new technologies in omics, imaging, and informatics, will help ensure our atlases will be the state-of-the-art, taking full advantage of the latest progress in these fields and will continue to evolve beyond the pilot phase to facilitate cancer research and improve clinical care. The proposed atlases target a set of critically important clinical questions, including tumor resistance that has long been a challenge for GBM treatment and also an important clinical problem in BRCA/TNBC and PDAC, in which minority populations are disproportionately affected. Other emphases are BRCA response/resistance to chemotherapy, PDAC metastasis, and GBM local recurrence in conjunction with resistance to therapy. These atlases can cross reference each other for pan-cancer analyses. We will also seek to cooperate with any Pre- Cancer Atlas (PCA) centers studying these disease types to maximize the temporal continuity of research on these cancers. The similarities and differences among the three selected cancer types will provide synergy among the three atlases and will also allow us to accumulate valuable knowledge in atlas building for other cancer types. The data, specimens, and experience gained by our center will be shared with HTAN and the broader research community to foster the next important discoveries in personalized cancer medicine.

项目摘要/摘要：总体 癌症研究的不同领域已经取得进展，现在可以有意义地整合 将分子、细胞和组织领域的研究数据和临床信息转化为更大、更广泛的信息 癌症动态的详细图片，包括癌症治疗期间的时空细节和 进展。华盛顿大学医学院 (WUSM) 的医生和研究人员以及 斯特曼癌症中心 (WUSM-SCC) 是癌症相关分支学科的长期领导者，包括 基因组学、蛋白质组学、成像、功能表征、病理学、临​​床试验和临床护理。 WUSM- SCC 是 NCI 指定的综合癌症中心，每年收治约 9,000 名新癌症患者。 建立在我们的专业知识、成熟的基础设施、庞大的患者群体和卓越的机构基础上 承诺，我们建议发展华盛顿大学人类肿瘤图谱研究中心（WU- HTARC）属于 NIH 人类肿瘤分析网络 (HTAN)。 我们将专注于为三种相关的高优先级癌症类型生成器官特异性人类肿瘤图谱 预后极差：三阴性乳腺癌（TNBC）、胶质母细胞瘤（GBM）和 胰腺导管腺癌（PDAC）。我们将共同分析从以下地点收集的约 1,600-2000 个样本： 临床治疗过程中的空间分离位置和不同时间点（300-375） 项目期间的患者（从大约 750 名招募的患者中选出）。除了标准的 组织病理学分析、大量DNA/RNA测序、蛋白质组学和临床影像等，我们将进行 尖端的综合分析，包括单细胞 RNA-Seq (scRNA-Seq)、多重分析 免疫荧光蛋白定位 (MxIF)、质谱流式细胞术/飞行时间流式细胞术 (CyTOF) 细胞 表征、代谢组学分析、创新成像和 3D 建模。 我们已经建立了覆盖上述领域的基础设施，从标本采购 （生物样本单元）、多学科分析模块（表征单元）以及分析管道 （数据分析单元）。这项研究产生的数据对于揭示克隆进化非常有价值 从纵向收集的标本中提取肿瘤细胞并重建涉及非 癌细胞和非细胞结构。我们的地图集将在 3D 级别上进行全面的数据集成 时间，为 3 种选定的癌症类型提供前所未有的 4D 模型。我们已建立的基础设施和 不断努力整合组学、成像和信息学方面的新技术，将有助于确保我们的 地图集将是最先进的，充分利用这些领域的最新进展，并将继续 超越试验阶段，促进癌症研究并改善临床护理。 拟议的图谱针对一系列至关重要的临床问题，包括已发生的肿瘤耐药性 长期以来一直是GBM治疗的挑战，也是BRCA/TNBC和PDAC的重要临床问题。 其中少数民族人口受到的影响尤为严重。其他重点是 BRCA 反应/抵抗 化疗、PDAC 转移和 GBM 局部复发以及耐药性。这些 图谱可以相互参考以进行泛癌分析。我们还将寻求与任何预 癌症图谱 (PCA) 中心研究这些疾病类型，以最大限度地提高研究的时间连续性 这些癌症。三种选定癌症类型之间的异同将提供协同作用 三个地图集之间的关系，也将使我们能够积累有关为其他地图集构建地图集的宝贵知识。 癌症类型。我们中心获得的数据、标本和经验将与HTAN和 更广泛的研究界，以促进个性化癌症医学的下一个重要发现。