The cancer epitope database and analysis resource

The National Cancer Institute awarded La Jolla Institute for Immunology $785,938 on August 14, 2026, under the Cancer Biology Research program (CFDA 93.396) to develop and maintain the Cancer Epitope Database and Analysis Resource (CEDAR), a comprehensive database that integrates cancer epitope information with immunological, clinical, and biological context to support precision diagnostics, vaccine development, and immunotherapy design.

The award funds creation of a unified, accessible resource linking cancer epitopes to T-cell and B-cell receptors that recognize them, patient characteristics, structural features, and clinical outcomes. CEDAR addresses fragmentation across existing databases by consolidating epitope data with clinical and biological depth, enabling researchers to explore and apply cancer epitope information to improve cancer diagnosis, monitoring, and therapeutic approaches.

The five-year award runs through July 31, 2031, with work performed in La Jolla, California. The Cancer Biology Research program supports fundamental research on cancer cause and nature with the aim of advancing prevention, detection, diagnosis, and treatment methods.

Abstract

Cancer epitopes are unique molecular signatures expressed by tumor cells and recognized by the immune system. They play a central role in understanding the mechanisms underlying tumorigenesis and offer exceptional opportunities to advance precision diagnostics, vaccine development, and immunotherapies. Detailed information on cancer epitopes, along with their associated immunological, clinical, and biological contexts, is essential for developing predictive algorithms and pipelines that can significantly and rapidly contribute to advances in clinical oncology. While epitopes have been identified in all disease categories, studies focused on cancer-derived epitopes are particularly valuable because these antigenic determinants act as tumor- specific molecular signatures, and reveal how anti-cancer immune cells identify and respond to tumors. These features can be leveraged to develop targeted diagnostics and harness patients' tumor-reactive cells (i.e., t cells and b cells) to design tailored, tumor-directed therapies. Thus, there has been a recent resurgence in interest in cancer epitopes and the specific t-cell and b-cell receptors that recognize them. The distinctive molecular fingerprints of cancer epitopes underscore the transformative value of unified databases equipped with advanced analysis tools to streamline their translational application. A comprehensive, reliable, and accessible resource linking cancer epitopes to their recognizing receptors, structural features, patient characteristics, and clinical outcomes would enable researchers to better explore, compare, and apply these data to improve cancer diagnosis, monitoring, and therapy. Existing databases capture portions of this information, but are often fragmented, incomplete, or lack clinical and biological depth. To address this GAP, in 2021, we established the cancer epitope database and analysis resource (cedar), a single, fully integrated, and continuously updated platform. We developed epitope analysis tools that give researchers access to predictive strategies and offer objective evaluations of their performance. Having completed the initial development phase and demonstrated cedar's potential to transform cancer research, our next phase will focus on expanding its capabilities to enhance the acquisition, management, analysis, and dissemination of cancer epitope knowledge across the scientific community. Our specific aims are to curate immune epitope data relevant to cancer immunology, as reported in the literature (aim 1), strengthen the cedar database, its ontology, and query and reporting functionalities (aim 2), provide a validated set of cancer epitope prediction and analysis tools (aim 3), and implement a multifaceted outreach program to engage the cancer research community (aim 4). Our efforts will consolidate scattered and incomplete datasets into a continually updated platform that links cancer epitopes with their recognizing receptors, structural details, patient-specific factors, and clinical outcomes. This integration will enable researchers to see the "full picture" by connecting molecular targets to immune recognition and real-world patient responses, thus making discoveries and therapy development faster, more accurate, and effective.