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.

PROJECT NARRATIVE Cancer is a disease that often originates in genomic abnormalities; however, these genome-level defects exert its functional significance at the level of proteins. Coordinating within the Clinical Proteomic Tumor Analysis Consortium, the Proteome Characterization Center at the Pacific Northwest National Laboratory will comprehensively characterize the protein- (including multiple protein modifications such as phosphorylation) and metabolomic-level changes in cancer and healthy states by combing proteome-, metabolome-, and genome-level information. This will contribute to a more unified understanding of cancer biology with translational potential, e.g., development of new cancer diagnostic, prevention, and treatment strategies.