Time-Frequency Analysis of Peptide Microarray Data: Application to XXXX Immunosignatures.

@entity1 @entity1313 @entity5 @entity3689 @entity463
One of the gravest dangers facing @entity5 @entity1 is an extended symptom-free lull between @entity5 initiation and the first diagnosis. Detection of @entity5 is critical for effective intervention. Using the body's immune system to detect and amplify @entity5 -specific signals may enable detection of @entity5 using an inexpensive immunoassay. Immunosignatures are one such assay: they provide a map of antibody interactions with random-sequence peptides. They enable detection of disease-specific patterns using classic train/test methods. However, to date, very little effort has gone into extracting information from the sequence of peptides that interact with disease-specific antibodies. Because it is difficult to represent all possible antigen peptides in a microarray format, we chose to synthesize only 330,000 peptides on a single immunosignature microarray. The 330,000 random-sequence peptides on the microarray represent 83% of all tetramers and 27% of all pentamers, creating an unbiased but substantial gap in the coverage of total sequence space. We therefore chose to examine many relatively short motifs from these random-sequence peptides. Time-variant analysis of recurrent subsequences provided a means to dissect @entity3689 sequences from the peptides while simultaneously retaining the antibody-peptide binding intensities. We first used a simple experiment in which monoclonal antibodies with known linear epitopes were exposed to these random-sequence peptides, and their binding intensities were used to create our algorithm. We then demonstrated the performance of the proposed algorithm by examining immunosignatures from @entity1 with @entity463 multiformae (GBM), an aggressive form of @entity1313 . Eight different frameshift targets were identified from the random-sequence peptides using this technique. If immune-reactive antigens can be identified using a relatively simple immune assay, it might enable a diagnostic test with sufficient sensitivity to detect @entity5 in a clinically useful way.
