A Targeted Proteomics Approach for Screening Serum Biomarkers Observed in the Early Stage of Type I Endometrial Cancer
Endometrial cancer (EC) is the most common gynecologic malignancy, and it arises in the inner part of the uterus. Identification of serum biomarkers is essential for diagnosing the disease at an early stage. In this study, we selected 44 healthy controls and 44 type I EC at tumor stage 1, and we use...
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| Format: | Article |
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MDPI AG
2022-08-01
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| Series: | Biomedicines |
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| Online Access: | https://www.mdpi.com/2227-9059/10/8/1857 |
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| author | Blendi Ura Valeria Capaci Michelangelo Aloisio Giovanni Di Lorenzo Federico Romano Giuseppe Ricci Lorenzo Monasta |
| author_facet | Blendi Ura Valeria Capaci Michelangelo Aloisio Giovanni Di Lorenzo Federico Romano Giuseppe Ricci Lorenzo Monasta |
| author_sort | Blendi Ura |
| collection | DOAJ |
| description | Endometrial cancer (EC) is the most common gynecologic malignancy, and it arises in the inner part of the uterus. Identification of serum biomarkers is essential for diagnosing the disease at an early stage. In this study, we selected 44 healthy controls and 44 type I EC at tumor stage 1, and we used the Immuno-oncology panel and the Target 96 Oncology III panel to simultaneously detect the levels of 92 cancer-related proteins in serum, using a proximity extension assay. By applying this methodology, we identified 20 proteins, associated with the outcome at binary logistic regression, with a <i>p</i>-value below 0.01 for the first panel and 24 proteins with a <i>p</i>-value below 0.02 for the second one. The final multivariate logistic regression model, combining proteins from the two panels, generated a model with a sensitivity of 97.67% and a specificity of 83.72%. These results support the use of the proposed algorithm after a validation phase. |
| first_indexed | 2024-03-09T10:00:08Z |
| format | Article |
| id | doaj.art-187683f143d8430e8206dabcdee2d898 |
| institution | Directory Open Access Journal |
| issn | 2227-9059 |
| language | English |
| last_indexed | 2024-03-09T10:00:08Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomedicines |
| spelling | doaj.art-187683f143d8430e8206dabcdee2d8982023-12-01T23:27:28ZengMDPI AGBiomedicines2227-90592022-08-01108185710.3390/biomedicines10081857A Targeted Proteomics Approach for Screening Serum Biomarkers Observed in the Early Stage of Type I Endometrial CancerBlendi Ura0Valeria Capaci1Michelangelo Aloisio2Giovanni Di Lorenzo3Federico Romano4Giuseppe Ricci5Lorenzo Monasta6Institute for Maternal and Child Health—IRCCS Burlo Garofolo, 34137 Trieste, ItalyInstitute for Maternal and Child Health—IRCCS Burlo Garofolo, 34137 Trieste, ItalyInstitute for Maternal and Child Health—IRCCS Burlo Garofolo, 34137 Trieste, ItalyInstitute for Maternal and Child Health—IRCCS Burlo Garofolo, 34137 Trieste, ItalyInstitute for Maternal and Child Health—IRCCS Burlo Garofolo, 34137 Trieste, ItalyInstitute for Maternal and Child Health—IRCCS Burlo Garofolo, 34137 Trieste, ItalyInstitute for Maternal and Child Health—IRCCS Burlo Garofolo, 34137 Trieste, ItalyEndometrial cancer (EC) is the most common gynecologic malignancy, and it arises in the inner part of the uterus. Identification of serum biomarkers is essential for diagnosing the disease at an early stage. In this study, we selected 44 healthy controls and 44 type I EC at tumor stage 1, and we used the Immuno-oncology panel and the Target 96 Oncology III panel to simultaneously detect the levels of 92 cancer-related proteins in serum, using a proximity extension assay. By applying this methodology, we identified 20 proteins, associated with the outcome at binary logistic regression, with a <i>p</i>-value below 0.01 for the first panel and 24 proteins with a <i>p</i>-value below 0.02 for the second one. The final multivariate logistic regression model, combining proteins from the two panels, generated a model with a sensitivity of 97.67% and a specificity of 83.72%. These results support the use of the proposed algorithm after a validation phase.https://www.mdpi.com/2227-9059/10/8/1857biomarkersproteinsendometrial cancertargeted proteomicsPEA |
| spellingShingle | Blendi Ura Valeria Capaci Michelangelo Aloisio Giovanni Di Lorenzo Federico Romano Giuseppe Ricci Lorenzo Monasta A Targeted Proteomics Approach for Screening Serum Biomarkers Observed in the Early Stage of Type I Endometrial Cancer Biomedicines biomarkers proteins endometrial cancer targeted proteomics PEA |
| title | A Targeted Proteomics Approach for Screening Serum Biomarkers Observed in the Early Stage of Type I Endometrial Cancer |
| title_full | A Targeted Proteomics Approach for Screening Serum Biomarkers Observed in the Early Stage of Type I Endometrial Cancer |
| title_fullStr | A Targeted Proteomics Approach for Screening Serum Biomarkers Observed in the Early Stage of Type I Endometrial Cancer |
| title_full_unstemmed | A Targeted Proteomics Approach for Screening Serum Biomarkers Observed in the Early Stage of Type I Endometrial Cancer |
| title_short | A Targeted Proteomics Approach for Screening Serum Biomarkers Observed in the Early Stage of Type I Endometrial Cancer |
| title_sort | targeted proteomics approach for screening serum biomarkers observed in the early stage of type i endometrial cancer |
| topic | biomarkers proteins endometrial cancer targeted proteomics PEA |
| url | https://www.mdpi.com/2227-9059/10/8/1857 |
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