Title |
Aurora Kinase A expression predicts platinum-resistance and adverse outcome in high-grade serous ovarian carcinoma patients
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Published in |
Journal of Ovarian Research, May 2016
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DOI | 10.1186/s13048-016-0238-7 |
Pubmed ID | |
Authors |
Chiara Mignogna, Nicoletta Staropoli, Cirino Botta, Carmela De Marco, Antonia Rizzuto, Michele Morelli, Annalisa Di Cello, Renato Franco, Caterina Camastra, Ivan Presta, Natalia Malara, Angela Salvino, Pierfrancesco Tassone, Pierosandro Tagliaferri, Tullio Barni, Giuseppe Donato, Anna Di Vito |
Abstract |
High-Grade Serous Ovarian Carcinoma (HGSOC) is the predominant histotype of epithelial ovarian cancer (EOC), characterized by advanced stage at diagnosis, frequent TP53 mutation, rapid progression, and high responsiveness to platinum-based-chemotherapy. To date, standard first-line-chemotherapy in advanced EOC includes platinum salts and paclitaxel with or without bevacizumab. The major prognostic factor is the response duration from the end of the platinum-based treatment (platinum-free interval) and about 10-0 % of EOC patients bear a platinum-refractory disease or develop early resistance (platinum-free interval shorter than 6 months). On these bases, a careful selection of patients who could benefit from chemotherapy is recommended to avoid unnecessary side effects and for a better disease outcome. In this retrospective study, an immunohistochemical evaluation of Aurora Kinase A (AURKA) was performed on 41 cases of HGSOC according to platinum-status. Taking into account the number and intensity of AURKA positive cells we built a predictive score able to discriminate with high accuracy platinum-sensitive patients from platinum-resistant patients (p < 0.001). Furthermore, we observed that AURKA overexpression correlates to worse overall survival (p = 0.001; HR 0.14). We here suggest AURKA as new effective tool to predict the biological behavior of HGSOC. Particularly, our results indicate that AURKA has a role both as predictor of platinum-resistance and as prognostic factor, that deserves further investigation in prospective clinical trials. Indeed, in the era of personalized medicine, AURKA could assist the clinicians in selecting the best treatment and represent, at the same time, a promising new therapeutic target in EOC treatment. |
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Unknown | 1 | 100% |
Demographic breakdown
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 33 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Bachelor | 6 | 18% |
Other | 4 | 12% |
Student > Master | 3 | 9% |
Researcher | 3 | 9% |
Student > Ph. D. Student | 3 | 9% |
Other | 5 | 15% |
Unknown | 9 | 27% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 11 | 33% |
Biochemistry, Genetics and Molecular Biology | 4 | 12% |
Agricultural and Biological Sciences | 3 | 9% |
Psychology | 3 | 9% |
Business, Management and Accounting | 1 | 3% |
Other | 1 | 3% |
Unknown | 10 | 30% |