A high throughput method for identifying personalized tumor-associated antigens

Circulating autoantibodies against tumor-associated antigens (TAAs) and their pattern of glycosylation can be used as diagnostic indicators of cancer. Using random peptide library screening, we identified patient-specific sets of peptides recognized by colon cancer patients' serum IgG and IgM antibodies. We demonstrate a strategy for analyzing BLAST search results for identifying tumor-associated antigens represented by peptides that mimic sequential epitopes. Statistical analysis of the frequency with which the proteins are retrieved by BLAST homology searching and an estimation of the probability of a match by chance can identify the proteins that are the real targets of the immune response against tumors. In addition, we observed an over-expression of the mRNA for the match-producing protein only in the corresponding tumor sample, out of fourteen tumor and normal samples analyzed. This observation confirms that personalized tumor-associated antigens can be identified by BLAST homology search following random peptide library screening on cancer patient's serum antibodies.