Antibody repertoire analysis in sera of breast cancer patients using a random peptide microarray differentiates cases from controls with high specificity and sensitivity

• Published in: The Journal of immunology (1950) 2017-05, Vol.198 (1_Supplement), p.76-76.19
• Main Authors: Chapoval, Andrei I, Podlesknyh, Stepan, Kolosova, Evgenia, Anisimov, Daniil, Ryzanov, Mikhail, Petrova, Valentina, Shcherbakov, Dmitry, Johnston, Stephen, Lazarev, Aleksander
• Format: Article
• Language: English
• ISSN: 0022-1767; 1550-6606
• DOI: 10.4049/jimmunol.198.Supp.76.19

Breast cancer (BC) is the most common malignancy and the second most common cause of cancer-related mortality in women. Early detection of BC using different biomarkers is a key factor for successful BC therapy. Many studies have shown that serum antibodies (Ab) against tumor-associated antigens (TAAs) could be used as potential biomarkers in the detection of BC. However in some cases the most of informative TAAs for circulating Ab detection, at early stages of BC, might be unknown. Even if informative Ab targets are currently unknown it is possible to analyze Ab repertoire (immunosignature) using random peptide arrays. In the present study, we probe a custom 330,000 random 12-mer peptide microarray with sera from 42 BC cases and 41 controls to develop a diagnostic signature. We determined that differentiation of BC cases from controls with high sensitivity and specificity requires a panel of at least 100–150 peptides. Basic Local Alignment Search Tool (BLAST) searches suggest that the identified peptides have no similarity with known TAAs. However, despite the random nature of the amino acid sequence that were used in microchip design, common amino acid motif is present in the groups of peptides that react with sera Ab from patients with BC but not healthy control. Thus the evaluation of Ab repertoire (immunosignature) using microarray containing peptides with random amino acid sequences has a potential value in the early diagnosis of cancer.