Abstract
Recent years have witnessed a dramatic rise in interest towards cancer epitopes in general and particularly neoepitopes, antigens that are encoded by somatic mutations that arise as a consequence of tumorigenesis. There is also an interest in the specific T cell and B cell receptors recognizing these epitopes, as they have therapeutic applications. They can also aid in basic studies to infer the specificity of T cells or B cells characterized in bulk and single-cell sequencing data. The resurgence of interest in T cell and B cell epitopes emphasizes the need to catalog all cancer epitope-related data linked to the biological, immunological, and clinical contexts, and most importantly, making this information freely available to the scientific community in a user-friendly format. In parallel, there is also a need to develop resources for epitope prediction and analysis tools that provide researchers access to predictive strategies and provide objective evaluations of their performance. For example, such tools should enable researchers to identify epitopes that can be effectively used for immunotherapy or in defining biomarkers to predict the outcome of checkpoint blockade therapies. We present here a detailed vision, blueprint, and work plan for the development of a new resource, the Cancer Epitope Database and Analysis Resource (CEDAR). CEDAR will provide a freely accessible, comprehensive collection of cancer epitope and receptor data curated from the literature and provide easily accessible epitope and T cell/B cell target prediction and analysis tools. The curated cancer epitope data will provide a transparent benchmark dataset that can be used to assess how well prediction tools perform and to develop new prediction tools relevant to the cancer research community.
Highlights
Recent years have witnessed a dramatic rise in interest towards cancer epitopes, studies that have been greatly facilitated by the dramatic decrease in the cost of whole-exome and transcriptome sequencing, as well as advances in mass spectrometry that has resulted in the generation of large datasets of candidate T cell epitopes that are naturally processed and presented [1]
Following initial interviews with cancer experts, we identified the elements relating to an epitope that should be captured in Cancer Epitope Database and Analysis Resource (CEDAR) (Figure 1), including seven main “field groups”, namely [1] related to the structure of the epitope, [2] the protein/antigen source from which the epitope is derived, [3] the host associated with the identified epitope responses, [4] the features of the tumor sample, isolate or model, [5] the effectors of the immune responses
In the case of non-peptidic epitopes, such as, for example, CHO epitopes recognized by antibody responses or ceramides used to expand natural killer (NK) T cells, the structures are captured following the format of ChEBI [12] and PubChem [13] resources
Summary
Recent years have witnessed a dramatic rise in interest towards cancer epitopes, studies that have been greatly facilitated by the dramatic decrease in the cost of whole-exome and transcriptome sequencing, as well as advances in mass spectrometry that has resulted in the generation of large datasets of candidate T cell epitopes that are naturally processed and presented [1] This resurgence of interest is linked to the exceptional success of immune checkpoint blockade therapies that disengage immune suppressive mechanisms and enable cancer antigen-specific T cells to recognize and attack tumor cells expressing those antigens [2,3,4]. The general curation processes are described in detail in previous publications [30, 32,33,34] and have been continuously adapted as new assay types are established, as has been done to capture receptor data from high throughput sequencing [35]
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