Open AccessA gene‑expression‑based test can outperform bap1 and p16 analyses in the differential diagnosis of pleural mesothelial proliferations
Author(s) -
Greta Alì,
Rossella Bruno,
Anello Marcello Poma,
Agnese Proietti,
Stefano Ricci,
Antonio Chella,
Franca Melfi,
Marcello Carlo Ambrogi,
Marco Lucchi,
Gabriella Fontanini
Publication year - 2019
Publication title -
oncology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.766
H-Index - 54
eISSN - 1792-1082
pISSN - 1792-1074
DOI - 10.3892/ol.2019.11174
Subject(s) - bap1 , differential diagnosis , context (archaeology) , mesothelioma , pathology , immunohistochemistry , receiver operating characteristic , medicine , cancer research , biology , paleontology
The demonstration of tissue invasion by histology is an essential criterion for the differential diagnosis of benign and malignant mesothelial proliferations. When tissue invasion cannot be identified, the use of ancillary tests is sometimes necessary. Among investigated markers, the loss of BRCA1 associated protein 1 (BAP1) protein expression and the homozygous deletion of p16 have shown 100% specificity in separating benign and malignant mesothelial lesions. However, beyond the excellent specificity of these two markers, their low sensitivity limits their clinical utility. In this context, a previous study developed and tested a novel tool for use in the differential diagnosis of malignant pleural mesothelioma (MPM) using the NanoString System and a classification algorithm. In the current study, the performance of gene classifiers were compared using BAP1 and p16 testing. p16 FISH and BAP1 immunohistochemistry were performed on the same series of 34 epithelioid MPM and 20 benign pleural lesions, which were previously analyzed by the system. The diagnostic performance of p16 , BAP1 and our classification models were compared using ROC analysis. It was observed that BAP1 loss and p16 deletion were highly specific for MPM, since they were not detected in benign lesions. However, their AUC values were not completely satisfying (BAP1: 0.8235; p16 : 0.7647) particularly due to their low sensitivities. As expected, combining BAP1 and p16 tests increased the diagnostic sensitivity, thus improving the AUC (0.8824). In the same series of cases, our MPM tool outperformed BAP1 and p16 tests using the 22 and 40-gene classification models (AUC 22-gene model: 0.9996; AUC 40-gene model: 0.9990). In conclusion, the present gene-expression-based classification exhibited great potential and further validation is required to support these findings in a prospective fashion, in order to provide a solid alternative for pleural proliferation diagnosis.