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Two Dimensional-Difference in Gel Electrophoresis (2D-DIGE) Proteomic Approach for the Identification of Biomarkers in Endometrial Cancer Serum
SIMPLE SUMMARY: Endometrial cancer is the most common gynecologic malignancy arising from the endometrium. Identification of serum biomarkers could be beneficial for its early diagnosis. This study compared the serum proteins of 15 patients with endometrial cancer and 15 non-cancer subjects, identif...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8305989/ https://www.ncbi.nlm.nih.gov/pubmed/34298850 http://dx.doi.org/10.3390/cancers13143639 |
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author | Ura, Blendi Biffi, Stefania Monasta, Lorenzo Arrigoni, Giorgio Battisti, Ilaria Di Lorenzo, Giovanni Romano, Federico Aloisio, Michelangelo Celsi, Fulvio Addobbati, Riccardo Valle, Francesco Rampazzo, Enrico Brucale, Marco Ridolfi, Andrea Licastro, Danilo Ricci, Giuseppe |
author_facet | Ura, Blendi Biffi, Stefania Monasta, Lorenzo Arrigoni, Giorgio Battisti, Ilaria Di Lorenzo, Giovanni Romano, Federico Aloisio, Michelangelo Celsi, Fulvio Addobbati, Riccardo Valle, Francesco Rampazzo, Enrico Brucale, Marco Ridolfi, Andrea Licastro, Danilo Ricci, Giuseppe |
author_sort | Ura, Blendi |
collection | PubMed |
description | SIMPLE SUMMARY: Endometrial cancer is the most common gynecologic malignancy arising from the endometrium. Identification of serum biomarkers could be beneficial for its early diagnosis. This study compared the serum proteins of 15 patients with endometrial cancer and 15 non-cancer subjects, identifying 16 proteins with diagnostic potential. Quantification of protein expression revealed the upregulation of CLU, ITIH4, SERPINC1, and C1RL in endometrial cancer samples compared to the sera of control subjects. We built a mathematical model based on this set of proteins that detects cancer samples with excellent sensitivity and specificity levels. After a validation phase our findings support the potential to use the proposed algorithm as a diagnostic tool in the clinical stage. ABSTRACT: Endometrial cancer is the most common gynecologic malignancy arising from the endometrium. Identification of serum biomarkers could be beneficial for its early diagnosis. We have used 2D-Difference In Gel Electrophoresis (2D-DIGE) coupled with Mass Spectrometry (MS) procedures to investigate the serum proteome of 15 patients with endometrial cancer and 15 non-cancer subjects. We have identified 16 proteins with diagnostic potential, considering only spots with a fold change in %V ≥ 1.5 or ≤0.6 in intensity, which were statistically significant (p < 0.05). Western blotting data analysis confirmed the upregulation of CLU, ITIH4, SERPINC1, and C1RL in endometrial and exosome cancer sera compared to those of control subjects. The application of the logistic regression constructed based on the abundance of these four proteins separated the controls from the cancers with excellent levels of sensitivity and specificity. After a validation phase, our findings support the potential of using the proposed algorithm as a diagnostic tool in the clinical stage. |
format | Online Article Text |
id | pubmed-8305989 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83059892021-07-25 Two Dimensional-Difference in Gel Electrophoresis (2D-DIGE) Proteomic Approach for the Identification of Biomarkers in Endometrial Cancer Serum Ura, Blendi Biffi, Stefania Monasta, Lorenzo Arrigoni, Giorgio Battisti, Ilaria Di Lorenzo, Giovanni Romano, Federico Aloisio, Michelangelo Celsi, Fulvio Addobbati, Riccardo Valle, Francesco Rampazzo, Enrico Brucale, Marco Ridolfi, Andrea Licastro, Danilo Ricci, Giuseppe Cancers (Basel) Article SIMPLE SUMMARY: Endometrial cancer is the most common gynecologic malignancy arising from the endometrium. Identification of serum biomarkers could be beneficial for its early diagnosis. This study compared the serum proteins of 15 patients with endometrial cancer and 15 non-cancer subjects, identifying 16 proteins with diagnostic potential. Quantification of protein expression revealed the upregulation of CLU, ITIH4, SERPINC1, and C1RL in endometrial cancer samples compared to the sera of control subjects. We built a mathematical model based on this set of proteins that detects cancer samples with excellent sensitivity and specificity levels. After a validation phase our findings support the potential to use the proposed algorithm as a diagnostic tool in the clinical stage. ABSTRACT: Endometrial cancer is the most common gynecologic malignancy arising from the endometrium. Identification of serum biomarkers could be beneficial for its early diagnosis. We have used 2D-Difference In Gel Electrophoresis (2D-DIGE) coupled with Mass Spectrometry (MS) procedures to investigate the serum proteome of 15 patients with endometrial cancer and 15 non-cancer subjects. We have identified 16 proteins with diagnostic potential, considering only spots with a fold change in %V ≥ 1.5 or ≤0.6 in intensity, which were statistically significant (p < 0.05). Western blotting data analysis confirmed the upregulation of CLU, ITIH4, SERPINC1, and C1RL in endometrial and exosome cancer sera compared to those of control subjects. The application of the logistic regression constructed based on the abundance of these four proteins separated the controls from the cancers with excellent levels of sensitivity and specificity. After a validation phase, our findings support the potential of using the proposed algorithm as a diagnostic tool in the clinical stage. MDPI 2021-07-20 /pmc/articles/PMC8305989/ /pubmed/34298850 http://dx.doi.org/10.3390/cancers13143639 Text en © 2021 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 Ura, Blendi Biffi, Stefania Monasta, Lorenzo Arrigoni, Giorgio Battisti, Ilaria Di Lorenzo, Giovanni Romano, Federico Aloisio, Michelangelo Celsi, Fulvio Addobbati, Riccardo Valle, Francesco Rampazzo, Enrico Brucale, Marco Ridolfi, Andrea Licastro, Danilo Ricci, Giuseppe Two Dimensional-Difference in Gel Electrophoresis (2D-DIGE) Proteomic Approach for the Identification of Biomarkers in Endometrial Cancer Serum |
title | Two Dimensional-Difference in Gel Electrophoresis (2D-DIGE) Proteomic Approach for the Identification of Biomarkers in Endometrial Cancer Serum |
title_full | Two Dimensional-Difference in Gel Electrophoresis (2D-DIGE) Proteomic Approach for the Identification of Biomarkers in Endometrial Cancer Serum |
title_fullStr | Two Dimensional-Difference in Gel Electrophoresis (2D-DIGE) Proteomic Approach for the Identification of Biomarkers in Endometrial Cancer Serum |
title_full_unstemmed | Two Dimensional-Difference in Gel Electrophoresis (2D-DIGE) Proteomic Approach for the Identification of Biomarkers in Endometrial Cancer Serum |
title_short | Two Dimensional-Difference in Gel Electrophoresis (2D-DIGE) Proteomic Approach for the Identification of Biomarkers in Endometrial Cancer Serum |
title_sort | two dimensional-difference in gel electrophoresis (2d-dige) proteomic approach for the identification of biomarkers in endometrial cancer serum |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8305989/ https://www.ncbi.nlm.nih.gov/pubmed/34298850 http://dx.doi.org/10.3390/cancers13143639 |
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