Citations

PurposeStudies have demonstrated that the generation of immunity to tumor antigens is associated with improved prognosis for many cancers. A candidate antigen is the folate receptor alpha (FRα), which is overexpressed in breast and ovarian cancers. Our goal in this study was to attain a better understanding of the extent of endogenous FRα immunity.MethodsUsing a CD4+T cell epitope prediction algorithm, we predicted promiscuous epitopes of FRα, and tested for immunity in 30 breast (n = 17) or ovarian (n = 13) cancer patients and 18 healthy donors using enzyme-linked immunospot analysis.ResultsFourteen peptides were predicted, seven each from the carboxy- and amino-terminus halves of the protein. More than 70% of patients demonstrated immunity to at least one FRα peptide. Patients responded to an average of 3 ± 0.5 peptides, whereas healthy donors responded to 1 ± 0.4 peptides (P = .004). Five peptides were recognized by more than 25% of patients. Responses to three peptides were higher (P < .05) in patients than in healthy donors, suggesting augmented immunity. Compared with healthy individuals, patients developed higher immunity to the amino-terminus half of the receptor (P = .03). There was no difference between each group in the responses to nonspecific (P = .2) and viral stimuli (P = .5). Lastly, patients demonstrated elevated levels of FRα antibodies consistent with a coordinated immune response.ConclusionThese findings demonstrate that the FRα is a target of the immune system in breast and ovarian cancer patients. Understanding which antigens are targeted by the immune system may be important for prognosis or immune-based therapies.

The National Center for Biomedical Ontology is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists, funded by the National Institutes of Health (NIH) Roadmap, to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create new software tools so that scientists can use ontologies to annotate and analyze biomedical data, (3) to provide a national resource for the ongoing evaluation, integration, and evolution of biomedical ontologies and associated tools and theories in the context of driving biomedical projects (DBPs), and (4) to disseminate the tools and resources of the Center and to identify, evaluate, and communicate best practices of ontology development to the biomedical community. Through the research activities within the Center, collaborations with the DBPs, and interactions with the biomedical community, our goal is to help scientists to work more effectively in the e-science paradigm, enhancing experiment design, experiment execution, data analysis, information synthesis, hypothesis generation and testing, and understand human disease. This paper is part of the special issue of OMICS on data standards.