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Targeted Selected Reaction Monitoring Verifies Histology Specific Peptide Signatures in Epithelial Ovarian Cancer
SIMPLE SUMMARY: Ovarian cancer is a lethal disease due to its late phase discovery. Any steps towards improving early diagnostics will dramatically increase survival rates. To identify new ovarian cancer biomarker panels, we need to focus on early-stage disease and all histologic subtypes. In this s...
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/PMC8616310/ https://www.ncbi.nlm.nih.gov/pubmed/34830868 http://dx.doi.org/10.3390/cancers13225713 |
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author | Liljedahl, Leena Malmström, Johan Kristjansdottir, Björg Waldemarson, Sofia Sundfeldt, Karin |
author_facet | Liljedahl, Leena Malmström, Johan Kristjansdottir, Björg Waldemarson, Sofia Sundfeldt, Karin |
author_sort | Liljedahl, Leena |
collection | PubMed |
description | SIMPLE SUMMARY: Ovarian cancer is a lethal disease due to its late phase discovery. Any steps towards improving early diagnostics will dramatically increase survival rates. To identify new ovarian cancer biomarker panels, we need to focus on early-stage disease and all histologic subtypes. In this study we have, based on prior discoveries, constructed a multiplexed targeted selected-reaction-monitoring assay to detect peptides from 177 proteins in only 20 µL of plasma. The assay was evaluated in patients with a focus on early-stages and all ovarian cancer histologies in separate groups. With multivariate analysis, we found the highest predictive value in the benign vs. low-grade serous (Q2 = 0.615) and mucinous (Q2 = 0.611) early stage compared to all malignant (Q2 = 0.226) or late stage (Q2 = 0.43) ovarian cancers. The results show that each ovarian cancer histology subgroup can be identified by a unique panel of proteins. ABSTRACT: Epithelial ovarian cancer (OC) is a disease with high mortality due to vague early clinical symptoms. Benign ovarian cysts are common and accurate diagnosis remains a challenge because of the molecular heterogeneity of OC. We set out to investigate whether the disease diversity seen in ovarian cyst fluids and tumor tissue could be detected in plasma. Using existing mass spectrometry (MS)-based proteomics data, we constructed a selected reaction monitoring (SRM) assay targeting peptides from 177 cancer-related and classical proteins associated with OC. Plasma from benign, borderline, and malignant ovarian tumors were used to verify expression (n = 74). Unsupervised and supervised multivariate analyses were used for comparisons. The peptide signatures revealed by the supervised multivariate analysis contained 55 to 77 peptides each. The predictive (Q2) values were higher for benign vs. low-grade serous Q2 = 0.615, mucinous Q2 = 0.611, endometrioid Q2 = 0.428 and high-grade serous Q2 = 0.375 (stage I–II Q2 = 0.515; stage III Q2 = 0.43) OC compared to benign vs. all malignant Q2 = 0.226. With targeted SRM MS we constructed a multiplexed assay for simultaneous detection and relative quantification of 185 peptides from 177 proteins in only 20 µL of plasma. With the approach of histology-specific peptide patterns, derived from pre-selected proteins, we may be able to detect not only high-grade serous OC but also the less common OC subtypes. |
format | Online Article Text |
id | pubmed-8616310 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86163102021-11-26 Targeted Selected Reaction Monitoring Verifies Histology Specific Peptide Signatures in Epithelial Ovarian Cancer Liljedahl, Leena Malmström, Johan Kristjansdottir, Björg Waldemarson, Sofia Sundfeldt, Karin Cancers (Basel) Article SIMPLE SUMMARY: Ovarian cancer is a lethal disease due to its late phase discovery. Any steps towards improving early diagnostics will dramatically increase survival rates. To identify new ovarian cancer biomarker panels, we need to focus on early-stage disease and all histologic subtypes. In this study we have, based on prior discoveries, constructed a multiplexed targeted selected-reaction-monitoring assay to detect peptides from 177 proteins in only 20 µL of plasma. The assay was evaluated in patients with a focus on early-stages and all ovarian cancer histologies in separate groups. With multivariate analysis, we found the highest predictive value in the benign vs. low-grade serous (Q2 = 0.615) and mucinous (Q2 = 0.611) early stage compared to all malignant (Q2 = 0.226) or late stage (Q2 = 0.43) ovarian cancers. The results show that each ovarian cancer histology subgroup can be identified by a unique panel of proteins. ABSTRACT: Epithelial ovarian cancer (OC) is a disease with high mortality due to vague early clinical symptoms. Benign ovarian cysts are common and accurate diagnosis remains a challenge because of the molecular heterogeneity of OC. We set out to investigate whether the disease diversity seen in ovarian cyst fluids and tumor tissue could be detected in plasma. Using existing mass spectrometry (MS)-based proteomics data, we constructed a selected reaction monitoring (SRM) assay targeting peptides from 177 cancer-related and classical proteins associated with OC. Plasma from benign, borderline, and malignant ovarian tumors were used to verify expression (n = 74). Unsupervised and supervised multivariate analyses were used for comparisons. The peptide signatures revealed by the supervised multivariate analysis contained 55 to 77 peptides each. The predictive (Q2) values were higher for benign vs. low-grade serous Q2 = 0.615, mucinous Q2 = 0.611, endometrioid Q2 = 0.428 and high-grade serous Q2 = 0.375 (stage I–II Q2 = 0.515; stage III Q2 = 0.43) OC compared to benign vs. all malignant Q2 = 0.226. With targeted SRM MS we constructed a multiplexed assay for simultaneous detection and relative quantification of 185 peptides from 177 proteins in only 20 µL of plasma. With the approach of histology-specific peptide patterns, derived from pre-selected proteins, we may be able to detect not only high-grade serous OC but also the less common OC subtypes. MDPI 2021-11-15 /pmc/articles/PMC8616310/ /pubmed/34830868 http://dx.doi.org/10.3390/cancers13225713 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 Liljedahl, Leena Malmström, Johan Kristjansdottir, Björg Waldemarson, Sofia Sundfeldt, Karin Targeted Selected Reaction Monitoring Verifies Histology Specific Peptide Signatures in Epithelial Ovarian Cancer |
title | Targeted Selected Reaction Monitoring Verifies Histology Specific Peptide Signatures in Epithelial Ovarian Cancer |
title_full | Targeted Selected Reaction Monitoring Verifies Histology Specific Peptide Signatures in Epithelial Ovarian Cancer |
title_fullStr | Targeted Selected Reaction Monitoring Verifies Histology Specific Peptide Signatures in Epithelial Ovarian Cancer |
title_full_unstemmed | Targeted Selected Reaction Monitoring Verifies Histology Specific Peptide Signatures in Epithelial Ovarian Cancer |
title_short | Targeted Selected Reaction Monitoring Verifies Histology Specific Peptide Signatures in Epithelial Ovarian Cancer |
title_sort | targeted selected reaction monitoring verifies histology specific peptide signatures in epithelial ovarian cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8616310/ https://www.ncbi.nlm.nih.gov/pubmed/34830868 http://dx.doi.org/10.3390/cancers13225713 |
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