U24CA248138
Cooperative Agreement
Overview
Grant Description
The Cancer Epitope Database and Analysis Resource - Abstract
Recent years have witnessed a dramatic rise in interest towards cancer epitopes in general, and neoepitopes that encompass mutations arising in a given tumor in particular. Current lines of research examine how the epitope load in a given tumor relates to the success of checkpoint blockade treatments, and how to utilize epitope-based vaccines and adoptive transfer of epitope-specific T cells for personalized therapies.
For these purposes, neoepitopes that are recurrently recognized in different individuals are of particular interest, which has also re-ignited interest in epitopes identified in classic tumor-associated antigens. Along with the interest in cancer epitopes, there is also interest in the TCRs and BCRs specifically recognizing them, as these have the potential to be used in therapeutic approaches, and they can aid in basic studies to infer the specificity of T cells or B cells characterized in single cell sequencing data.
This resurgence of interest in epitopes has created a need to catalog and make accessible to the scientific community all epitope data, also linked to the biological, immunological, and clinical contexts. The ultimate goal is to come "full circle" and link epitope recognition and immunological readouts to clinical outcomes and treatment strategies alike.
In parallel, there is an urgent need to develop resources for epitope prediction and analysis tools that provide access to predictive strategies and provide objective evaluations of their performance in the relevant biological, immunological, and clinical contexts. Recent years have also witnessed the publication of multiple original methodologies that reported sometimes impressive gains in the predictions of cancer epitopes. However, several of these studies were difficult to evaluate because the methodologies and/or datasets were not fully available in a format that was readily executable. As a result, their performance could not be properly benchmarked on independent datasets. This is also because effective benchmarking on independent datasets requires the assembly of novel datasets of sufficient size and diversity.
To overcome all of these information technology challenges, we propose to design and implement the Cancer Epitope Database and Analysis Resource (CEDAR), which will provide a freely accessible, comprehensive collection of cancer epitope and receptor data curated from the literature, and provide easily accessible epitope and TCR/BCR target prediction and analysis tools. As the cancer epitope data are curated, they will be used as a transparent benchmark of how well prediction tools perform and also to develop new prediction tools for the analysis resource component of CEDAR.
CEDAR will leverage our expertise from developing the Immune Epitope Database and Analysis Resource (IEDB), which is fully operational and widely used by researchers globally. CEDAR will directly complement other projects currently funded through the NIH ITCR program that provide resources and tools related to cancer omics data. Finally, we will engage in outreach activities to improve functions, user interfaces, and interoperability with other ITCR tools and promote the use of CEDAR in cancer research.
Recent years have witnessed a dramatic rise in interest towards cancer epitopes in general, and neoepitopes that encompass mutations arising in a given tumor in particular. Current lines of research examine how the epitope load in a given tumor relates to the success of checkpoint blockade treatments, and how to utilize epitope-based vaccines and adoptive transfer of epitope-specific T cells for personalized therapies.
For these purposes, neoepitopes that are recurrently recognized in different individuals are of particular interest, which has also re-ignited interest in epitopes identified in classic tumor-associated antigens. Along with the interest in cancer epitopes, there is also interest in the TCRs and BCRs specifically recognizing them, as these have the potential to be used in therapeutic approaches, and they can aid in basic studies to infer the specificity of T cells or B cells characterized in single cell sequencing data.
This resurgence of interest in epitopes has created a need to catalog and make accessible to the scientific community all epitope data, also linked to the biological, immunological, and clinical contexts. The ultimate goal is to come "full circle" and link epitope recognition and immunological readouts to clinical outcomes and treatment strategies alike.
In parallel, there is an urgent need to develop resources for epitope prediction and analysis tools that provide access to predictive strategies and provide objective evaluations of their performance in the relevant biological, immunological, and clinical contexts. Recent years have also witnessed the publication of multiple original methodologies that reported sometimes impressive gains in the predictions of cancer epitopes. However, several of these studies were difficult to evaluate because the methodologies and/or datasets were not fully available in a format that was readily executable. As a result, their performance could not be properly benchmarked on independent datasets. This is also because effective benchmarking on independent datasets requires the assembly of novel datasets of sufficient size and diversity.
To overcome all of these information technology challenges, we propose to design and implement the Cancer Epitope Database and Analysis Resource (CEDAR), which will provide a freely accessible, comprehensive collection of cancer epitope and receptor data curated from the literature, and provide easily accessible epitope and TCR/BCR target prediction and analysis tools. As the cancer epitope data are curated, they will be used as a transparent benchmark of how well prediction tools perform and also to develop new prediction tools for the analysis resource component of CEDAR.
CEDAR will leverage our expertise from developing the Immune Epitope Database and Analysis Resource (IEDB), which is fully operational and widely used by researchers globally. CEDAR will directly complement other projects currently funded through the NIH ITCR program that provide resources and tools related to cancer omics data. Finally, we will engage in outreach activities to improve functions, user interfaces, and interoperability with other ITCR tools and promote the use of CEDAR in cancer research.
Funding Goals
TO PROVIDE FUNDAMENTAL INFORMATION ON THE CAUSE AND NATURE OF CANCER IN PEOPLE, WITH THE EXPECTATION THAT THIS WILL RESULT IN BETTER METHODS OF PREVENTION, DETECTION AND DIAGNOSIS, AND TREATMENT OF NEOPLASTIC DISEASES. CANCER BIOLOGY RESEARCH INCLUDES THE FOLLOWING RESEARCH PROGRAMS: CANCER CELL BIOLOGY, CANCER IMMUNOLOGY, HEMATOLOGY AND ETIOLOGY, DNA AND CHROMOSOMAL ABERRATIONS, TUMOR BIOLOGY AND METASTASIS, AND STRUCTURAL BIOLOGY AND MOLECULAR APPLICATIONS.
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
La Jolla,
California
92037
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 442% from $839,852 to $4,550,196.
LA Jolla Institute For Immunology was awarded
THE CANCER EPITOPE DATABASE AND ANALYSIS RESOURCE
Cooperative Agreement U24CA248138
worth $4,550,196
from National Cancer Institute in May 2021 with work to be completed primarily in La Jolla California United States.
The grant
has a duration of 5 years and
was awarded through assistance program 93.396 Cancer Biology Research.
The Cooperative Agreement was awarded through grant opportunity Advanced Development of Informatics Technologies for Cancer Research and Management (U24 Clinical Trial Optional).
Status
(Ongoing)
Last Modified 8/20/25
Period of Performance
5/5/21
Start Date
4/30/26
End Date
Funding Split
$4.6M
Federal Obligation
$0.0
Non-Federal Obligation
$4.6M
Total Obligated
Activity Timeline
Subgrant Awards
Disclosed subgrants for U24CA248138
Transaction History
Modifications to U24CA248138
Additional Detail
Award ID FAIN
U24CA248138
SAI Number
U24CA248138-3948193510
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
ZPAUY3FQMM26
Awardee CAGE
1WRP4
Performance District
CA-50
Senators
Dianne Feinstein
Alejandro Padilla
Alejandro Padilla
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) | $1,679,709 | 82% |
| Office of the Director, National Institutes of Health, Health and Human Services (075-0846) | Health research and training | Grants, subsidies, and contributions (41.0) | $366,000 | 18% |
Modified: 8/20/25