Identification of Highly Sensitive Pleural Effusion Protein Biomarkers for Malignant Pleural Mesothelioma by Affinity-Based Quantitative Proteomics

SIMPLE SUMMARY: The development of malignant pleural mesothelioma, a rare and often aggressive cancer associated with asbestos exposure, can take decades to develop. The existing methods for diagnosis are insufficient, hence, better detection methods are required. Given that pleural effusions are close to the tumor and reasonably accessible, it is believed that pleural effusion contains biomarkers that can provide insight into the disease. As part of our explorative analysis of pleural effusion, we applied a novel mass spectrometry-based method, and as a result, we have identified several proteins with diagnostic potential as markers for malignant pleural mesothelioma. The research into the potential use of pleural effusion biomarkers as a viable future diagnostic tool for malignant pleural mesothelioma will be advanced with the addition of the knowledge gained from our study. ABSTRACT: Malignant pleural mesothelioma (MPM) is an asbestos-associated, highly aggressive cancer characterized by late-stage diagnosis and poor prognosis. Gold standards for diagnosis are pleural biopsy and cytology of pleural effusion (PE), both of which are limited by low sensitivity and markedly inter-observer variations. Therefore, the assessment of PE biomarkers is considered a viable and objective diagnostic tool for MPM diagnosis. We applied a novel affinity-enrichment mass spectrometry-based proteomics method for explorative analysis of pleural effusions from a prospective cohort of 84 patients referred for thoracoscopy due to clinical suspicion of MPM. Protein biomarkers with a high capability to discriminate MPM from non-MPM patients were identified, and a Random Forest algorithm was applied for building classification models. Immunohistology of pleural biopsies confirmed MPM in 40 patients and ruled out MPM in 44 patients. Proteomic analysis of pleural effusions identified panels of proteins with excellent diagnostic properties (90–100% sensitivities, 89–98% specificities, and AUC 0.97–0.99) depending on the specific protein combination. Diagnostic proteins associated with cancer growth included galactin-3 binding protein, testican-2, haptoglobin, Beta ig-h3, and protein AMBP. Moreover, we also confirmed previously reported diagnostic accuracies of the MPM markers fibulin-3 and mesothelin measured by two complementary mass spectrometry-based methods. In conclusion, a novel affinity-enrichment mass spectrometry-based proteomics identified panels of proteins in pleural effusion with extraordinary diagnostic accuracies, which are described here for the first time as biomarkers for MPM.