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Serial Analysis of 38 Proteins during the Progression of Human Breast Tumor in Mice Using an Antibody Colocalization Microarray
Proteins in serum or plasma hold great potential for use in disease diagnosis and monitoring. However, the correlation between tumor burden and protein biomarker concentration has not been established. Here, using an antibody colocalization microarray, the protein concentration in serum was measured...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The American Society for Biochemistry and Molecular Biology
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4390249/ https://www.ncbi.nlm.nih.gov/pubmed/25680959 http://dx.doi.org/10.1074/mcp.M114.046516 |
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author | Li, Huiyan Bergeron, Sébastien Annis, Matthew G. Siegel, Peter M. Juncker, David |
author_facet | Li, Huiyan Bergeron, Sébastien Annis, Matthew G. Siegel, Peter M. Juncker, David |
author_sort | Li, Huiyan |
collection | PubMed |
description | Proteins in serum or plasma hold great potential for use in disease diagnosis and monitoring. However, the correlation between tumor burden and protein biomarker concentration has not been established. Here, using an antibody colocalization microarray, the protein concentration in serum was measured and compared with the size of mammary xenograft tumors in 11 individual mice from the time of injection; seven blood samples were collected from each tumor-bearing mouse as well as control mice on a weekly basis. The profiles of 38 proteins detected in sera from these animals were analyzed by clustering, and we identified 10 proteins with the greatest relative increase in serum concentration that correlated with growth of the primary mammary tumor. To evaluate the diagnosis of cancer based on these proteins using either an absolute threshold (i.e. a concentration cutoff) or self-referenced differential threshold based on the increase in concentration before cell injection, receiver operating characteristic curves were produced for 10 proteins with increased concentration, and the area under curve was calculated for each time point based on a single protein or on a panel of proteins, in each case showing a rapid increase of the area under curve. Next, the sensitivity and specificity of individual and optimal protein panels were calculated, showing high accuracy as early as week 2. These results provide a foundation for studies of tumor growth through measuring serial changes of protein concentration in animal models. |
format | Online Article Text |
id | pubmed-4390249 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | The American Society for Biochemistry and Molecular Biology |
record_format | MEDLINE/PubMed |
spelling | pubmed-43902492015-04-17 Serial Analysis of 38 Proteins during the Progression of Human Breast Tumor in Mice Using an Antibody Colocalization Microarray Li, Huiyan Bergeron, Sébastien Annis, Matthew G. Siegel, Peter M. Juncker, David Mol Cell Proteomics Research Proteins in serum or plasma hold great potential for use in disease diagnosis and monitoring. However, the correlation between tumor burden and protein biomarker concentration has not been established. Here, using an antibody colocalization microarray, the protein concentration in serum was measured and compared with the size of mammary xenograft tumors in 11 individual mice from the time of injection; seven blood samples were collected from each tumor-bearing mouse as well as control mice on a weekly basis. The profiles of 38 proteins detected in sera from these animals were analyzed by clustering, and we identified 10 proteins with the greatest relative increase in serum concentration that correlated with growth of the primary mammary tumor. To evaluate the diagnosis of cancer based on these proteins using either an absolute threshold (i.e. a concentration cutoff) or self-referenced differential threshold based on the increase in concentration before cell injection, receiver operating characteristic curves were produced for 10 proteins with increased concentration, and the area under curve was calculated for each time point based on a single protein or on a panel of proteins, in each case showing a rapid increase of the area under curve. Next, the sensitivity and specificity of individual and optimal protein panels were calculated, showing high accuracy as early as week 2. These results provide a foundation for studies of tumor growth through measuring serial changes of protein concentration in animal models. The American Society for Biochemistry and Molecular Biology 2015-04 2015-02-13 /pmc/articles/PMC4390249/ /pubmed/25680959 http://dx.doi.org/10.1074/mcp.M114.046516 Text en © 2015 by The American Society for Biochemistry and Molecular Biology, Inc. Author's Choice—Final version full access. |
spellingShingle | Research Li, Huiyan Bergeron, Sébastien Annis, Matthew G. Siegel, Peter M. Juncker, David Serial Analysis of 38 Proteins during the Progression of Human Breast Tumor in Mice Using an Antibody Colocalization Microarray |
title | Serial Analysis of 38 Proteins during the Progression of Human Breast Tumor in Mice Using an Antibody Colocalization Microarray
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title_full | Serial Analysis of 38 Proteins during the Progression of Human Breast Tumor in Mice Using an Antibody Colocalization Microarray
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title_fullStr | Serial Analysis of 38 Proteins during the Progression of Human Breast Tumor in Mice Using an Antibody Colocalization Microarray
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title_full_unstemmed | Serial Analysis of 38 Proteins during the Progression of Human Breast Tumor in Mice Using an Antibody Colocalization Microarray
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title_short | Serial Analysis of 38 Proteins during the Progression of Human Breast Tumor in Mice Using an Antibody Colocalization Microarray
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title_sort | serial analysis of 38 proteins during the progression of human breast tumor in mice using an antibody colocalization microarray |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4390249/ https://www.ncbi.nlm.nih.gov/pubmed/25680959 http://dx.doi.org/10.1074/mcp.M114.046516 |
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