Title |
Platelet protein biomarker panel for ovarian cancer diagnosis
|
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Published in |
Biomarker Research, January 2018
|
DOI | 10.1186/s40364-018-0118-y |
Pubmed ID | |
Authors |
Marta Lomnytska, Rui Pinto, Susanne Becker, Ulla Engström, Sonja Gustafsson, Christina Björklund, Markus Templin, Jan Bergstrand, Lei Xu, Jerker Widengren, Elisabeth Epstein, Bo Franzén, Gert Auer |
Abstract |
Platelets support cancer growth and spread making platelet proteins candidates in the search for biomarkers. Two-dimensional (2D) gel electrophoresis, Partial Least Squares Discriminant Analysis (PLS-DA), Western blot, DigiWest. PLS-DA of platelet protein expression in 2D gels suggested differences between the International Federation of Gynaecology and Obstetrics (FIGO) stages III-IV of ovarian cancer, compared to benign adnexal lesions with a sensitivity of 96% and a specificity of 88%. A PLS-DA-based model correctly predicted 7 out of 8 cases of FIGO stages I-II of ovarian cancer after verification by western blot. Receiver-operator curve (ROC) analysis indicated a sensitivity of 83% and specificity of 76% at cut-off >0.5 (area under the curve (AUC) = 0.831, p < 0.0001) for detecting these cases. Validation on an independent set of samples by DigiWest with PLS-DA differentiated benign adnexal lesions and ovarian cancer, FIGO stages III-IV, with a sensitivity of 70% and a specificity of 83%. We identified a group of platelet protein biomarker candidates that can quantify the differential expression between ovarian cancer cases as compared to benign adnexal lesions. |
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Geographical breakdown
Country | Count | As % |
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Unknown | 62 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 12 | 19% |
Student > Bachelor | 11 | 18% |
Student > Master | 7 | 11% |
Student > Doctoral Student | 6 | 10% |
Researcher | 5 | 8% |
Other | 7 | 11% |
Unknown | 14 | 23% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 5 | 8% |
Pharmacology, Toxicology and Pharmaceutical Science | 4 | 6% |
Nursing and Health Professions | 2 | 3% |
Other | 6 | 10% |
Unknown | 17 | 27% |