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: 10461041
• 负责人: Samuel Achilefu
• 金额: $ 176.77万
• 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 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10461041
• 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