Identification of cancer-specific motifs in mimotope profiles of serum antibody repertoire
| Autor: | Ion I. Mandoiu, Alexander Zelikovsky, Ekaterina Nenastyeva, Yurij Ionov |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Phage display Peptide Computational biology Peptide motifs Biology lcsh:Computer applications to medicine. Medical informatics 01 natural sciences Biochemistry Epitope Epitopes Mimotope profile 010104 statistics & probability 03 medical and health sciences Antigen Peptide Library Structural Biology Neoplasms medicine Biomarkers Tumor Humans Immune response 0101 mathematics Panning (camera) lcsh:QH301-705.5 Molecular Biology Early Detection of Cancer Autoantibodies chemistry.chemical_classification Mimotope Repertoire Research Applied Mathematics Cancer Computational Biology Random peptide phage display library Early cancer detection medicine.disease Molecular biology Computer Science Applications 030104 developmental biology lcsh:Biology (General) chemistry Proteome biology.protein lcsh:R858-859.7 Identification (biology) Antibody DNA microarray |
| Zdroj: | BMC Bioinformatics, Vol 18, Iss S8, Pp 1-6 (2017) BMC Bioinformatics ICCABS |
| ISSN: | 1471-2105 |
| DOI: | 10.1186/s12859-017-1661-5 |
| Popis: | Background For fighting cancer, earlier detection is crucial. Circulating auto-antibodies produced by the patient’s own immune system after exposure to cancer proteins are promising bio-markers for the early detection of cancer. Since an antibody recognizes not the whole antigen but 4–7 critical amino acids within the antigenic determinant (epitope), the whole proteome can be represented by a random peptide phage display library. This opens the possibility to develop an early cancer detection test based on a set of peptide sequences identified by comparing cancer patients’ and healthy donors’ global peptide profiles of antibody specificities. Results Due to the enormously large number of peptide sequences contained in global peptide profiles generated by next generation sequencing, the large number of cancer and control sera is required to identify cancer-specific peptides with high degree of statistical significance. To decrease the number of peptides in profiles generated by nextgen sequencing without losing cancer-specific sequences we used for generation of profiles the phage library enriched by panning on the pool of cancer sera. To further decrease the complexity of profiles we used computational methods for transforming a list of peptides constituting the mimotope profiles to the list motifs formed by similar peptide sequences. Conclusion We have shown that the amino-acid order is meaningful in mimotope motifs since they contain significantly more peptides than motifs among peptides where amino-acids are randomly permuted. Also the single sample motifs significantly differ from motifs in peptides drawn from multiple samples. Finally, multiple cancer-specific motifs have been identified. |
| Databáze: | OpenAIRE |
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