Introduction: The aim of this study is to assess the clinical reproducibility and the potential oncological validity of the molecular information provided by the immunohistochemistry (IHC) to properly stratify the endometrial cancer patients. Methods: Retrospective IHC analyses were conducted in a large series of 778 pre-operative uterine-confined ECs, studying the presence/absence of MLH1, MSH2, MSH6 and PMS2 to define the mismatch repair (MMR) stable or instable phenotype; the presence of p53 mutations and other molecular features. The molecular profile was correlated with histological, clinical and prognostic data. Results: Based on IHC assessment, we defined 3 EC populations: stable MMR patients (MMRs), instable patients (MMRi) and p53 mutated patients (p53+). Our result demonstrated that the IHC stratification statistically correlated with the most relevant pathologic-clinical features: FIGO stage (p < 0.001), grading (p < 0.001), histotype (p < 0.001), presence of LVSI (p < 0.001), myometrial invasion and tumor dimension (p = 0.003 for both). These 3 IHC populations statistically reflected the EC risk class ESGO-ESMO-ESP classification 2021 (p < 0.001). These results were also confirmed in the Kaplan-Meier curves in terms of overall survival (OS) and disease-free survival (DFS) (p < 0.0001). The multivariate analyses demonstrated that absence of estrogen receptor (ER) impacted the OS (p = 0.011) and, the Age > 60 years and the ER-status the DFS (p = 0.041 and p = 0.004). Conclusion: In this large series, we demonstrated that the pragmatic and systematic use of IHC may have an important role to properly stratify, in terms of histological features and clinical outcomes, the EC patients.

Perrone, E., De Felice, F., Capasso, I., Distefano, E., Lorusso, D., Nero, C., Arciuolo, D., Zannoni, G. F., Scambia, G., Fanfani, F., The immunohistochemical molecular risk classification in endometrial cancer: A pragmatic and high-reproducibility method, <<GYNECOLOGIC ONCOLOGY>>, 2022; (22): 180-189. [doi:10.1016/j.ygyno.2022.03.009] [http://hdl.handle.net/10807/198483]

The immunohistochemical molecular risk classification in endometrial cancer: A pragmatic and high-reproducibility method

Capasso, Ilaria;Distefano, Ettore;Lorusso, Domenica;Nero, Camilla;Arciuolo, Damiano;Zannoni, Gian Franco;Scambia, Giovanni;Fanfani, Francesco
2022

Abstract

Introduction: The aim of this study is to assess the clinical reproducibility and the potential oncological validity of the molecular information provided by the immunohistochemistry (IHC) to properly stratify the endometrial cancer patients. Methods: Retrospective IHC analyses were conducted in a large series of 778 pre-operative uterine-confined ECs, studying the presence/absence of MLH1, MSH2, MSH6 and PMS2 to define the mismatch repair (MMR) stable or instable phenotype; the presence of p53 mutations and other molecular features. The molecular profile was correlated with histological, clinical and prognostic data. Results: Based on IHC assessment, we defined 3 EC populations: stable MMR patients (MMRs), instable patients (MMRi) and p53 mutated patients (p53+). Our result demonstrated that the IHC stratification statistically correlated with the most relevant pathologic-clinical features: FIGO stage (p < 0.001), grading (p < 0.001), histotype (p < 0.001), presence of LVSI (p < 0.001), myometrial invasion and tumor dimension (p = 0.003 for both). These 3 IHC populations statistically reflected the EC risk class ESGO-ESMO-ESP classification 2021 (p < 0.001). These results were also confirmed in the Kaplan-Meier curves in terms of overall survival (OS) and disease-free survival (DFS) (p < 0.0001). The multivariate analyses demonstrated that absence of estrogen receptor (ER) impacted the OS (p = 0.011) and, the Age > 60 years and the ER-status the DFS (p = 0.041 and p = 0.004). Conclusion: In this large series, we demonstrated that the pragmatic and systematic use of IHC may have an important role to properly stratify, in terms of histological features and clinical outcomes, the EC patients.
eng
Perrone, E., De Felice, F., Capasso, I., Distefano, E., Lorusso, D., Nero, C., Arciuolo, D., Zannoni, G. F., Scambia, G., Fanfani, F., The immunohistochemical molecular risk classification in endometrial cancer: A pragmatic and high-reproducibility method, <>, 2022; (22): 180-189. [doi:10.1016/j.ygyno.2022.03.009] [http://hdl.handle.net/10807/198483]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10807/198483
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