Diagnostic Pathology (Jul 2021)
Evaluation of prognostic histological parameters proposed for pleural mesothelioma in diffuse malignant peritoneal mesothelioma. A short report
Abstract
Abstract Introduction Diffuse malignant peritoneal mesothelioma (DMPM) is a rare malignant neoplasm with poor survival that shares some similarities with the best-known pleural variant, pleural mesothelioma. The recent European Reference Network on Rare Adult Cancers (EURACAN)/International Association for the Study of Lung Cancer (IASLC) proposals attempted to improve the histological diagnosis and patient risk stratification. Herein, we investigated whether the pathology recommendations and suggestions of the pleural proposals were applicable to diffuse malignant peritoneal mesothelioma. Methods Fifty multiple laparoscopic biopsies of DMPM were consecutively collected at the Pathology Unit of the University of Bari. A two-tier system, i.e., low, and high grade, was used to categorize 34 epithelioid DMPMs. Architectural patterns, cytological features and stromal changes were also reported. Immunohistochemistry was performed for BRCA1-associated protein 1 (BAP1), programmed death-ligand 1 (PD-L1), and Ki67, while fluorescence in situ hybridization (FISH) was performed for p16/cyclin-dependent kinase inhibitor 2A (CDKN2A). Results High-grade epithelioid mesothelioma, high Ki67, and p16/CDKN2A deletion were significantly associated with short survival (p = 0.004, p < 0.0001, and p = 0.002, respectively). BAP1 loss and PD-L1 negativity were the most common findings. Multivariate analysis revealed that the nuclear grading system and p16 deletion significantly correlated with survival (p = 0.003 each). Conclusions The present study examined the prognostic significance of several factors proposed for pleural mesothelioma in an extra pleural site. Notably, the introduction of a grading system may provide better risk stratification in epithelioid DMPM. Ki67, BAP1 and p16/CDKN2A should also be measured whenever possible. A detailed report with all supportive data would allow us to collect sufficient information for use in further studies on larger case series.
Keywords