Diagnosing pleural effusions using mass spectrometry-based multiplexed targeted proteomics quantitating mid- to high-abundance markers of cancer, infection/inflammation and tuberculosis

• Published in: Scientific reports Vol. 12; no. 1; pp. 3054 - 18
• Main Authors: Robak, Aleksandra, Kistowski, Michał, Wojtas, Grzegorz, Perzanowska, Anna, Targowski, Tomasz, Michalak, Agata, Krasowski, Grzegorz, Dadlez, Michał, Domański, Dominik
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 23.02.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 631/45; 631/45/475; 631/67; 631/67/1612; 692/4028; 692/53; 692/53/2421; 692/699; 692/699/1785; 692/699/255; 692/699/255/1856; Biomarkers; Biomarkers - analysis; Cancer; CXCL10 protein; E-cadherin; Etiology; Gelatinase B; Humanities and Social Sciences; Humans; Infections; Infections - diagnosis; Infections - metabolism; Inflammation; Lung cancer; Lung diseases; Lung Neoplasms - diagnosis; Lung Neoplasms - metabolism; Mass spectrometry; Mass Spectrometry - methods; Mass spectroscopy; multidisciplinary; Pleural cavity; Pleural Cavity - chemistry; Pleural effusion; Pleural Effusion - classification; Pleural Effusion - diagnosis; Pleural Effusion - metabolism; Pneumonia - diagnosis; Pneumonia - metabolism; Proteomics; Proteomics - methods; ROC Curve; Science; Science (multidisciplinary); Scientific imaging; Tuberculosis; Tuberculosis - diagnosis; Tuberculosis - metabolism
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-022-06924-y

Pleural effusion (PE) is excess fluid in the pleural cavity that stems from lung cancer, other diseases like extra-pulmonary tuberculosis (TB) and pneumonia, or from a variety of benign conditions. Diagnosing its cause is often a clinical challenge and we have applied targeted proteomic methods with the aim of aiding the determination of PE etiology. We developed a mass spectrometry (MS)-based multiple reaction monitoring (MRM)-protein-panel assay to precisely quantitate 53 established cancer-markers, TB-markers, and infection/inflammation-markers currently assessed individually in the clinic, as well as potential biomarkers suggested in the literature for PE classification. Since MS-based proteomic assays are on the cusp of entering clinical use, we assessed the merits of such an approach and this marker panel based on a single-center 209 patient cohort with established etiology. We observed groups of infection/inflammation markers (ADA2, WARS, CXCL10, S100A9, VIM, APCS, LGALS1, CRP, MMP9, and LDHA) that specifically discriminate TB-PEs and other-infectious-PEs, and a number of cancer markers (CDH1, MUC1/CA-15-3, THBS4, MSLN, HPX, SVEP1, SPINT1, CK-18, and CK-8) that discriminate cancerous-PEs. Some previously suggested potential biomarkers did not show any significant difference. Using a Decision Tree/Multiclass classification method, we show a very good discrimination ability for classifying PEs into one of four types: cancerous-PEs (AUC: 0.863), tuberculous-PEs (AUC of 0.859), other-infectious-PEs (AUC of 0.863), and benign-PEs (AUC: 0.842). This type of approach and the indicated markers have the potential to assist in clinical diagnosis in the future, and help with the difficult decision on therapy guidance.