U24CA271012

Center for Advanced Multi-Omic Characterization of Cancer - 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 integrate the multi-omic measurements to support improved understanding of the molecular changes that characterize cancer, 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. They have been responsible for comprehensive proteogenomic characterization of high-grade serous ovarian, colon, and endometrial cancers, as well as glioblastoma. The planned PNNL PCC will build on these achievements to extend and advance the CPTAC mission of comprehensive proteogenomic characterization of human cancers to additional cancer types. They aim to meet or exceed 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 the acetylome and ubiquitinome to the phosphoproteome of prospectively collected human tumors. This will better illuminate key biochemical processes related to protein-protein interactions, protein degradation, and signal transduction. They 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, tumor heterogeneity, and microenvironment contributions. This multi-omic analysis strategy will also be applied to preclinical samples, such as cell lines, organoids, and patient-derived xenografts.

PNNL will also develop targeted mass spectrometric assays using input from the CPTAC consortium, particularly the Proteogenomic Data Analysis Centers (PGDACs), to prioritize targets for further exploring important mechanistic proteomic changes in independent cohort(s). Throughout this work, their measurements will benefit from further performance increases, such as 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. They will use 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 platforms, at a throughput of 300 samples per year.

They 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. They will achieve this 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.

Battelle Memorial Institute

TO IMPROVE SCREENING AND EARLY DETECTION STRATEGIES AND TO DEVELOP ACCURATE DIAGNOSTIC TECHNIQUES AND METHODS FOR PREDICTING THE COURSE OF DISEASE IN CANCER PATIENTS. SCREENING AND EARLY DETECTION RESEARCH INCLUDES DEVELOPMENT OF STRATEGIES TO DECREASE CANCER MORTALITY BY FINDING TUMORS EARLY WHEN THEY ARE MORE AMENABLE TO TREATMENT. DIAGNOSIS RESEARCH FOCUSES ON METHODS TO DETERMINE THE PRESENCE OF A SPECIFIC TYPE OF CANCER, TO PREDICT ITS COURSE AND RESPONSE TO THERAPY, BOTH A PARTICULAR THERAPY OR A CLASS OF AGENTS, AND TO MONITOR THE EFFECT OF THE THERAPY AND THE APPEARANCE OF DISEASE RECURRENCE. THESE METHODS INCLUDE DIAGNOSTIC IMAGING AND DIRECT ANALYSES OF SPECIMENS FROM TUMOR OR OTHER TISSUES. SUPPORT IS ALSO PROVIDED FOR ESTABLISHING AND MAINTAINING RESOURCES OF HUMAN TISSUE TO FACILITATE RESEARCH. SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM: TO EXPAND AND IMPROVE THE SBIR PROGRAM, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, TO INCREASE SMALL BUSINESS PARTICIPATION IN FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION. SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM: TO STIMULATE AND FOSTER SCIENTIFIC AND TECHNOLOGICAL INNOVATION THROUGH COOPERATIVE RESEARCH AND DEVELOPMENT CARRIED OUT BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO FOSTER TECHNOLOGY TRANSFER BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION.

93.394 - Cancer Detection and Diagnosis Research

National Cancer Institute (NCI) [HHS - NIH]

Richland, Washington 993520999 United States

Single Zip Code

Proteome Characterization Centers (PCCs) for Clinical Proteomic Tumor Analysis Consortium (U24 Clinical Trial Not Allowed) (RFA-CA-21-023)

Amendment Since initial award the total obligations have increased 335% from $1,240,013 to $5,390,170.