U24CA271075
Cooperative Agreement
Overview
Grant Description
Center for Comprehensive Proteogenomic Data Analysis - Project Summary
Proteogenomics involves the integrative multi-omic analysis of genomic, transcriptomic, proteomic, and post-translational modification data produced by next-generation sequencing and mass spectrometry-based proteomics. Several publications by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and others have highlighted the impact of proteogenomics in enabling deeper insight into the biology of cancer and identification of potential drug targets.
Integrative analysis of multi-omic data requires the deployment of complex algorithms and data processing techniques, which are generally inaccessible to scientists without a background in bioinformatics and computational biology. Our proposed Center for Comprehensive Proteogenomic Data Analysis will encapsulate a comprehensive set of analysis methods in a platform that will be:
(I) Simple to use
(II) Flexible
(III) Automated, facilitating the routine application to all CPTAC proteogenomic datasets as they become available
(IV) Able to incorporate new methods with minimal effort.
We will leverage Panoply, a cloud-based platform for automated and reproducible proteogenomic data analysis, as the foundation, with specific, carefully chosen algorithms targeted for addition to provide an expansive set of analysis capabilities that can be easily harnessed to provide a rapid and extensive baseline analysis for proteogenomic studies. This will lead to many disease-specific hypotheses that can be explored further using additional computational and wet-lab experiments.
Our collection of tools, algorithms, and interactive reports will enable unprecedented, automated, and integrative systems-biology level analyses of proteome, post-translational modification, and metabolomic data combined with genomic data for individual disease cohorts and pan-cancer analysis across cohorts. This will lead to a deeper understanding of cancer biology and enable the identification of therapeutic targets and disease/prognostic biomarkers.
Proteogenomics involves the integrative multi-omic analysis of genomic, transcriptomic, proteomic, and post-translational modification data produced by next-generation sequencing and mass spectrometry-based proteomics. Several publications by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and others have highlighted the impact of proteogenomics in enabling deeper insight into the biology of cancer and identification of potential drug targets.
Integrative analysis of multi-omic data requires the deployment of complex algorithms and data processing techniques, which are generally inaccessible to scientists without a background in bioinformatics and computational biology. Our proposed Center for Comprehensive Proteogenomic Data Analysis will encapsulate a comprehensive set of analysis methods in a platform that will be:
(I) Simple to use
(II) Flexible
(III) Automated, facilitating the routine application to all CPTAC proteogenomic datasets as they become available
(IV) Able to incorporate new methods with minimal effort.
We will leverage Panoply, a cloud-based platform for automated and reproducible proteogenomic data analysis, as the foundation, with specific, carefully chosen algorithms targeted for addition to provide an expansive set of analysis capabilities that can be easily harnessed to provide a rapid and extensive baseline analysis for proteogenomic studies. This will lead to many disease-specific hypotheses that can be explored further using additional computational and wet-lab experiments.
Our collection of tools, algorithms, and interactive reports will enable unprecedented, automated, and integrative systems-biology level analyses of proteome, post-translational modification, and metabolomic data combined with genomic data for individual disease cohorts and pan-cancer analysis across cohorts. This will lead to a deeper understanding of cancer biology and enable the identification of therapeutic targets and disease/prognostic biomarkers.
Awardee
Funding Goals
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.
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Cambridge,
Massachusetts
021421027
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 293% from $791,128 to $3,109,133.
The Broad Institute was awarded
Center for comprehensive proteogenomic data analysis
Cooperative Agreement U24CA271075
worth $3,109,133
from National Cancer Institute in June 2022 with work to be completed primarily in Cambridge Massachusetts United States.
The grant
has a duration of 5 years and
was awarded through assistance program 93.394 Cancer Detection and Diagnosis Research.
The Cooperative Agreement was awarded through grant opportunity Proteogenomic Data Analysis Centers (PGDACs) for Clinical Proteomic Tumor Analysis Consortium (U24 Clinical Trial Not Allowed).
Status
(Ongoing)
Last Modified 6/5/25
Period of Performance
6/15/22
Start Date
5/31/27
End Date
Funding Split
$3.1M
Federal Obligation
$0.0
Non-Federal Obligation
$3.1M
Total Obligated
Activity Timeline
Transaction History
Modifications to U24CA271075
Additional Detail
Award ID FAIN
U24CA271075
SAI Number
U24CA271075-1251600639
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Nonprofit With 501(c)(3) IRS Status (Other Than An Institution Of Higher Education)
Awarding Office
75NC00 NIH National Cancer Institute
Funding Office
75NC00 NIH National Cancer Institute
Awardee UEI
H5G9NWEFHXN4
Awardee CAGE
5BP51
Performance District
MA-07
Senators
Edward Markey
Elizabeth Warren
Elizabeth Warren
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| National Cancer Institute, National Institutes of Health, Health and Human Services (075-0849) | Health research and training | Grants, subsidies, and contributions (41.0) | $1,566,434 | 100% |
Modified: 6/5/25