Center for Advanced Multi-Omic Characterization of Cancer

癌症高级多组学表征中心

• 批准号: 10631927
• 负责人: Tao Liu
• 金额: $ 121.53万
• 依托单位: BATTELLE PACIFIC NORTHWEST LABORATORIES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10631927
• 关键词: Achievement; Affinity; Area; Automobile Driving; Basic Science; Biochemical Process; Bioinformatics; Biological Assay; Biological Models; Cancer Biology; Cancer Diagnostics; Catalogs; Cell Line; Cells; Center for Translational Science Activities; Chromatography; Classification; Clinical; Colon Carcinoma; Communities; Complement; Data; Data Analyses; Defect; Development; Disease; Drug Targeting; Endometrial Carcinoma; Genome; Genomics; Genotype; Glioblastoma; Guidelines; Human; Informatics; Infrastructure; International; Label; Laboratories; Link; Liquid Chromatography; Malignant Neoplasms; Malignant neoplasm of ovary; Mass Spectrum Analysis; Measurement; Metabolic; Metabolic Pathway; Metals; Methods; Mission; Molecular; Monitor; Mutation; National Cancer Institute; Organoids; Outcome; Pacific Northwest; Pathway Analysis; Performance; Phenotype; Phosphorylation; Post-Translational Protein Processing; Prevention strategy; Prognostic Marker; Proteins; Proteome; Proteomics; Publishing; Reaction; Role; Route; Sample Size; Sampling; Series; Serous; Signal Pathway; Signal Transduction; Specimen; Technology; The Cancer Genome Atlas; Therapeutic Intervention; Validation; Work; advanced analytics; cancer genome; cancer type; clinical center; cohort; data acquisition; data integration; data quality; diagnostic strategy; expectation; experience; functional status; genomic data; genomic profiles; human genome sequencing; improved; informatics tool; insight; instrumentation; lipidome; meetings; metabolome; metabolomics; multidisciplinary; multiple omics; nanoscale; new technology; patient derived xenograft model; personalized medicine; phenome; pre-clinical; precision oncology; prospective; protein degradation; protein protein interaction; proteogenomics; stable isotope; success; tandem mass spectrometry; technology development; therapeutic target; transcriptomic profiling; translational applications; translational potential; treatment strategy; tumor; tumor behavior; tumor heterogeneity; working group

PROJECT SUMMARY The overall objective of the PNNL Proteome Characterization Center (PCC) is to comprehensively characterize human tumor samples provided by the National Cancer Institute (NCI), and to integrate the multi-omic measurements to support improved understanding of the molecular changes that characterize cancer, and do so in the context of clinical outcome. PNNL has participated in the NCI’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) as a PCC for the past ten years, with responsibility for comprehensive proteogenomic characterization of high-grade serous ovarian, colon, and endometrial cancers, and glioblastoma. The planned PNNL PCC will build on those achievements to extend and advance the CPTAC mission of comprehensive proteogenomic characterization of human cancers to additional cancer types, meeting or exceeding CPTAC key expectations or requirements for sample throughput, coverage, sample size, and data quality. Utilizing an advanced analytical platform, PNNL plans to add analysis of both acetylome and ubiquitinome to the phosphoproteome of prospectively collected human tumors, to betters illuminate key biochemical processes related to protein-protein interactions, protein degradation, and signal transduction. We will also complement the core proteome and post-translational modification (PTM)-ome analysis with global metabolome and lipidome analysis, as well as selected data driven spatial or single-cell proteomics analysis. This will provide additional critical insights on potential metabolic vulnerabilities and tumor heterogeneity as well as microenvironment contributions. This multi-omic analysis strategy will also be applied to preclinical samples, such as cell lines, organoids and patient-derived xenografts. We will also develop targeted mass spectrometric assays using input from the CPTAC consortium, and particularly the Proteogenomic Data Analysis Centers (PGDACs), to prioritize targets for further exploring important mechanistic proteomic changes in independent cohort(s). Throughout this work our measurements will benefit from further performance increases (e.g., sensitivity and throughput) based on refining, validating and implementing developments from both PNNL and the other CPTAC Centers. The PNNL PCC will identify promising cancer signatures and signaling networks through proteomic and metabolomic analysis of human biospecimens and relevant preclinical samples for 2-3 cancer types selected by the CPTAC, using state-of-the-art liquid chromatography-tandem mass spectrometry instrumentation, highly multiplexed isobaric mass-tag labeling (TMT 16-plex), and integrated sample workflows, as well as additional advanced metabolomic, spatial and single-cell proteomic planforms, at a throughput of 300 samples per year. We will also explore mechanistically important proteomic changes in human specimens and model systems using cutting-edge targeted proteomic platforms, analytically validated and highly multiplexed targeted assays, and workflows meeting the CPTAC Tier 2 assay guidelines. Two hundred highly specific, multiplexed targeted proteomics assays will be developed and used for measurements in 300 samples each year. The PNNL PCC will accomplish both unbiased and targeted multi-omic characterization of cancers in conjunction with improving the depth, throughput and quality of both unbiased and targeted data generated by implementing and deploying relevant new technologies, such as nanoscale PTM, metabolomic analysis, and single-cell proteomics analysis. The PNNL PCC will work closely with the other PCCs, PGDACs and PTRCs in the CPTAC network on data integration and bioinformatics analysis, as well as translational applications.

项目总结