Literature DB >> 12747745

MUC1-like tandem repeat proteins are broadly immunogenic in cancer patients.

Joseph A Mollick1, F Stephen Hodi, Robert J Soiffer, Lee M Nadler, Glenn Dranoff.   

Abstract

The identification of antigens mediating tumor rejection is an important goal of cancer immunology. The SEREX technology utilizes antibodies from cancer patients to identify candidate antigens from tumor-derived cDNA expression libraries. Using sera from a long-term surviving metastatic melanoma patient vaccinated with irradiated, autologous tumor cells engineered to secrete granulocyte-macrophage colony stimulating factor (GM-CSF), we identified an antigen reported to be a putative opioid growth factor receptor (OGFr). The human immune response to OGFr exhibits three features shared with other tumor antigens. First, the protein is an intracellular antigen found in both nucleus and cytoplasm. Second, part of the antibody response is directed at a putative protein product encoded by an alternative reading frame (ARF). Third, part of the antibody response is directed at a portion of the molecule that bears a striking resemblance to the extracellular domain of MUC1, both with respect to primary structure and size polymorphism. Antibody responses to OGFr and a synthetic peptide representing a putative alternative reading frame product (OGFr-ARF) were frequently found in cancer patients. 11/45 (24%) melanoma patients had antibodies to OGFr and 5/45 (11%) had antibodies to OGFr-ARF. Moreover, 5/24 (21%) lung cancer, 4/25 (16%) prostate cancer, and 5/6 breast or ovarian cancer patients had antibodies to OGFr, the alternative frame product, or both. These data add to the growing list of tumor antigens that appear to be translated in two frames, and suggest that OGFr and OGFr-ARF may be useful targets for vaccination.

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Year:  2003        PMID: 12747745

Source DB:  PubMed          Journal:  Cancer Immun        ISSN: 1424-9634


  11 in total

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10.  Diagnostic peptide discovery: prioritization of pathogen diagnostic markers using multiple features.

Authors:  Santiago J Carmona; Paula A Sartor; María S Leguizamón; Oscar E Campetella; Fernán Agüero
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