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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

Authors :
Marina Fabbi
Delfina Costa
Daniela Russo
Laura Arenare
Gabriele Gaggero
Simona Signoriello
Giovanni Scambia
Carmela Pisano
Nicoletta Colombo
Nunzia Simona Losito
Gilberto Filaci
Anna Spina
Daniela Califano
Giosuè Scognamiglio
Angiolo Gadducci
Delia Mezzanzanica
Marina Bagnoli
Silvano Ferrini
Vincenzo Canzonieri
Paolo Chiodini
Francesco Perrone
Sandro Pignata
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