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Reactivity Graph Yields Interpretable IgM Repertoire Signatures as Potential Tumor Biomarkers
Combining adaptive and innate immunity induction modes, the repertoire of immunoglobulin M (IgM) can reflect changes in the internal environment including malignancies. Previously, it was shown that a mimotope library reflecting the public IgM repertoire of healthy donors (IgM IgOme) can be mined fo...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9917253/ https://www.ncbi.nlm.nih.gov/pubmed/36768923 http://dx.doi.org/10.3390/ijms24032597 |
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author | Ferdinandov, Dilyan Kostov, Viktor Hadzhieva, Maya Shivarov, Velizar Petrov, Peter Bussarsky, Assen Pashov, Anastas Dimitrov |
author_facet | Ferdinandov, Dilyan Kostov, Viktor Hadzhieva, Maya Shivarov, Velizar Petrov, Peter Bussarsky, Assen Pashov, Anastas Dimitrov |
author_sort | Ferdinandov, Dilyan |
collection | PubMed |
description | Combining adaptive and innate immunity induction modes, the repertoire of immunoglobulin M (IgM) can reflect changes in the internal environment including malignancies. Previously, it was shown that a mimotope library reflecting the public IgM repertoire of healthy donors (IgM IgOme) can be mined for efficient probes of tumor biomarker antibody reactivities. To better explore the interpretability of this approach for IgM, solid tumor-related profiles of IgM reactivities to linear epitopes of actual tumor antigens and viral epitopes were studied. The probes were designed as oriented planar microarrays of 4526 peptide sequences (as overlapping 15-mers) derived from 24 tumor-associated antigens and 209 cancer-related B cell epitopes from 30 viral antigens. The IgM reactivity in sera from 21 patients with glioblastoma multiforme, brain metastases of other tumors, and non-tumor-bearing neurosurgery patients was thus probed in a proof-of-principle study. A graph representation of the binding data was developed, which mapped the cross-reactivity of the mixture of IgM (poly)specificities, delineating different antibody footprints in the features of the graph—neighborhoods and cliques. The reactivity graph mapped the major features of the IgM repertoire such as the magnitude of the reactivity (titer) and major cross-reactivities, which correlated with blood group reactivity, non-self recognition, and even idiotypic specificities. A correlation between an aspect of this image of the IgM IgOme, namely, small cliques reflecting rare self-reactivities and the capacity of subsets of the epitopes to separate the diagnostic groups studied was found. In this way, the graph representation helped the feature selection in its filtering step and provided reduced feature sets, which, after recursive feature elimination, produced a classifier containing 51 peptide reactivities separating the three diagnostic groups with an unexpected efficiency. Thus, IgM IgOme approaches to repertoire studies is greatly augmented when self/viral antigens are used and the data are represented as a reactivity graph. This approach is most general, and if it is applicable to tumors in immunologically privileged sites, it can be applied to any solid tumors, for instance, breast or lung cancer. |
format | Online Article Text |
id | pubmed-9917253 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99172532023-02-11 Reactivity Graph Yields Interpretable IgM Repertoire Signatures as Potential Tumor Biomarkers Ferdinandov, Dilyan Kostov, Viktor Hadzhieva, Maya Shivarov, Velizar Petrov, Peter Bussarsky, Assen Pashov, Anastas Dimitrov Int J Mol Sci Article Combining adaptive and innate immunity induction modes, the repertoire of immunoglobulin M (IgM) can reflect changes in the internal environment including malignancies. Previously, it was shown that a mimotope library reflecting the public IgM repertoire of healthy donors (IgM IgOme) can be mined for efficient probes of tumor biomarker antibody reactivities. To better explore the interpretability of this approach for IgM, solid tumor-related profiles of IgM reactivities to linear epitopes of actual tumor antigens and viral epitopes were studied. The probes were designed as oriented planar microarrays of 4526 peptide sequences (as overlapping 15-mers) derived from 24 tumor-associated antigens and 209 cancer-related B cell epitopes from 30 viral antigens. The IgM reactivity in sera from 21 patients with glioblastoma multiforme, brain metastases of other tumors, and non-tumor-bearing neurosurgery patients was thus probed in a proof-of-principle study. A graph representation of the binding data was developed, which mapped the cross-reactivity of the mixture of IgM (poly)specificities, delineating different antibody footprints in the features of the graph—neighborhoods and cliques. The reactivity graph mapped the major features of the IgM repertoire such as the magnitude of the reactivity (titer) and major cross-reactivities, which correlated with blood group reactivity, non-self recognition, and even idiotypic specificities. A correlation between an aspect of this image of the IgM IgOme, namely, small cliques reflecting rare self-reactivities and the capacity of subsets of the epitopes to separate the diagnostic groups studied was found. In this way, the graph representation helped the feature selection in its filtering step and provided reduced feature sets, which, after recursive feature elimination, produced a classifier containing 51 peptide reactivities separating the three diagnostic groups with an unexpected efficiency. Thus, IgM IgOme approaches to repertoire studies is greatly augmented when self/viral antigens are used and the data are represented as a reactivity graph. This approach is most general, and if it is applicable to tumors in immunologically privileged sites, it can be applied to any solid tumors, for instance, breast or lung cancer. MDPI 2023-01-30 /pmc/articles/PMC9917253/ /pubmed/36768923 http://dx.doi.org/10.3390/ijms24032597 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ferdinandov, Dilyan Kostov, Viktor Hadzhieva, Maya Shivarov, Velizar Petrov, Peter Bussarsky, Assen Pashov, Anastas Dimitrov Reactivity Graph Yields Interpretable IgM Repertoire Signatures as Potential Tumor Biomarkers |
title | Reactivity Graph Yields Interpretable IgM Repertoire Signatures as Potential Tumor Biomarkers |
title_full | Reactivity Graph Yields Interpretable IgM Repertoire Signatures as Potential Tumor Biomarkers |
title_fullStr | Reactivity Graph Yields Interpretable IgM Repertoire Signatures as Potential Tumor Biomarkers |
title_full_unstemmed | Reactivity Graph Yields Interpretable IgM Repertoire Signatures as Potential Tumor Biomarkers |
title_short | Reactivity Graph Yields Interpretable IgM Repertoire Signatures as Potential Tumor Biomarkers |
title_sort | reactivity graph yields interpretable igm repertoire signatures as potential tumor biomarkers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9917253/ https://www.ncbi.nlm.nih.gov/pubmed/36768923 http://dx.doi.org/10.3390/ijms24032597 |
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