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Analysis of A Disintegrin and Metalloprotease 17 (ADAM17) Expression as a Prognostic Marker in Ovarian Cancer Patients Undergoing First-Line Treatment Plus Bevacizumab
- Source :
- Diagnostics, Vol 12, Iss 9, p 2118 (2022)
- Publication Year :
- 2022
- Publisher :
- MDPI AG, 2022.
-
Abstract
- To find prognostic factors for advanced ovarian cancer patients undergoing first-line therapy with carboplatin, paclitaxel and bevacizumab, we investigated the expression of a disintegrin and metalloprotease 17 (ADAM17) in cancer tissues. ADAM17 has been involved in ovarian cancer development, progression and cell resistance to cisplatin. Tissue microarrays from 309 ovarian cancer patients enrolled in the MITO16A/MANGO-OV2 clinical trial were analyzed by immunohistochemistry for ADAM17 protein expression. Intensity and extent of staining were combined into a semi-quantitative visual grading system (H score) which was related to clinicopathological characteristics of cases and the clinical outcome of patients by univariate and multivariate Cox regression models. ADAM17 immunostaining was detected in most samples, mainly localized in the tumor cells, with variable intensity across the cohort. Kaplan–Meier survival curves, generated according to the best cut-off value for the ADAM17 H score, showed that high ADAM17 expression was associated with worse prognosis for PFS and OS. However, after the application of a shrinkage procedure to adjust for overfitting hazard ratio estimates, the ADAM17 value as prognostic factor was lost. As subgroup analysis suggested that ADAM17 expression could be prognostically relevant in cases with no residual disease at baseline, further studies in this patient category may be worth planning.
Details
- Language :
- English
- ISSN :
- 12092118 and 20754418
- Volume :
- 12
- Issue :
- 9
- Database :
- Directory of Open Access Journals
- Journal :
- Diagnostics
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.3475ee8b2aad49adbddeb11eea2ac3be
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/diagnostics12092118