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The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling
Characterization of the colon cancer immunome and its autoantibody signature from differentially-reactive antigens (DIRAGs) could provide insights into aberrant cellular mechanisms or enriched networks associated with diseases. The purpose of this study was to characterize the antibody profile of pl...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6000238/ https://www.ncbi.nlm.nih.gov/pubmed/29505855 http://dx.doi.org/10.1016/j.gpb.2017.10.002 |
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author | Luna Coronell, Johana A. Sergelen, Khulan Hofer, Philipp Gyurján, István Brezina, Stefanie Hettegger, Peter Leeb, Gernot Mach, Karl Gsur, Andrea Weinhäusel, Andreas |
author_facet | Luna Coronell, Johana A. Sergelen, Khulan Hofer, Philipp Gyurján, István Brezina, Stefanie Hettegger, Peter Leeb, Gernot Mach, Karl Gsur, Andrea Weinhäusel, Andreas |
author_sort | Luna Coronell, Johana A. |
collection | PubMed |
description | Characterization of the colon cancer immunome and its autoantibody signature from differentially-reactive antigens (DIRAGs) could provide insights into aberrant cellular mechanisms or enriched networks associated with diseases. The purpose of this study was to characterize the antibody profile of plasma samples from 32 colorectal cancer (CRC) patients and 32 controls using proteins isolated from 15,417 human cDNA expression clones on microarrays. 671 unique DIRAGs were identified and 632 were more highly reactive in CRC samples. Bioinformatics analyses reveal that compared to control samples, the immunoproteomic IgG profiling of CRC samples is mainly associated with cell death, survival, and proliferation pathways, especially proteins involved in EIF2 and mTOR signaling. Ribosomal proteins (e.g., RPL7, RPL22, and RPL27A) and CRC-related genes such as APC, AXIN1, E2F4, MSH2, PMS2, and TP53 were highly enriched. In addition, differential pathways were observed between the CRC and control samples. Furthermore, 103 DIRAGs were reported in the SEREX antigen database, demonstrating our ability to identify known and new reactive antigens. We also found an overlap of 7 antigens with 48 “CRC genes.” These data indicate that immunomics profiling on protein microarrays is able to reveal the complexity of immune responses in cancerous diseases and faithfully reflects the underlying pathology. |
format | Online Article Text |
id | pubmed-6000238 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-60002382018-06-14 The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling Luna Coronell, Johana A. Sergelen, Khulan Hofer, Philipp Gyurján, István Brezina, Stefanie Hettegger, Peter Leeb, Gernot Mach, Karl Gsur, Andrea Weinhäusel, Andreas Genomics Proteomics Bioinformatics Original Research Characterization of the colon cancer immunome and its autoantibody signature from differentially-reactive antigens (DIRAGs) could provide insights into aberrant cellular mechanisms or enriched networks associated with diseases. The purpose of this study was to characterize the antibody profile of plasma samples from 32 colorectal cancer (CRC) patients and 32 controls using proteins isolated from 15,417 human cDNA expression clones on microarrays. 671 unique DIRAGs were identified and 632 were more highly reactive in CRC samples. Bioinformatics analyses reveal that compared to control samples, the immunoproteomic IgG profiling of CRC samples is mainly associated with cell death, survival, and proliferation pathways, especially proteins involved in EIF2 and mTOR signaling. Ribosomal proteins (e.g., RPL7, RPL22, and RPL27A) and CRC-related genes such as APC, AXIN1, E2F4, MSH2, PMS2, and TP53 were highly enriched. In addition, differential pathways were observed between the CRC and control samples. Furthermore, 103 DIRAGs were reported in the SEREX antigen database, demonstrating our ability to identify known and new reactive antigens. We also found an overlap of 7 antigens with 48 “CRC genes.” These data indicate that immunomics profiling on protein microarrays is able to reveal the complexity of immune responses in cancerous diseases and faithfully reflects the underlying pathology. Elsevier 2018-02 2018-03-02 /pmc/articles/PMC6000238/ /pubmed/29505855 http://dx.doi.org/10.1016/j.gpb.2017.10.002 Text en © 2018 Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Original Research Luna Coronell, Johana A. Sergelen, Khulan Hofer, Philipp Gyurján, István Brezina, Stefanie Hettegger, Peter Leeb, Gernot Mach, Karl Gsur, Andrea Weinhäusel, Andreas The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling |
title | The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling |
title_full | The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling |
title_fullStr | The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling |
title_full_unstemmed | The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling |
title_short | The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling |
title_sort | immunome of colon cancer: functional in silico analysis of antigenic proteins deduced from igg microarray profiling |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6000238/ https://www.ncbi.nlm.nih.gov/pubmed/29505855 http://dx.doi.org/10.1016/j.gpb.2017.10.002 |
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