The Breath Analysis For Early Detection Of Malignant Pleural Mesothelioma (Mpm) and Management Of Asbestos Exposure Subjects 

Authors: Di Gilio A. (1,2), Palmisani J. (1,2), Nisi M.R. (1,2)*, Varesano N. (3), Catino A. (3), Galetta D. (3), de Gennaro G. (1,2)

Affiliations: (1) Department of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Bari, Italy, (2) Apulian Regional Centre for the Breath Analysis, Istituto Tumori ‘Giovanni Paolo II’, Bari, Italy, (3) Thoracic Oncology Unit, Istituto Tumori ‘Giovanni Paolo II’, Bari, Italy

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Abstract:

Introduction Malignant Pleural Mesothelioma (MPM) is a rare neoplasm cancer with still a poor prognosis and mainly caused by previous both occupational and environmental asbestos exposure. The management of MPM is challenging due to the long latency period between the exposure and the diagnosis and due to symptoms appearing only at an advanced stage [1]. Recently, the chemical characterization of Volatile Organic Compounds (VOCs) in human breath has been recognized as non-invasive and promising approach for the early detection of neoplastic diseases. Therefore, this study aimed to explore the breath analysis potentialities in early detection of MPM and the identification of metabolic alterations in subjects with previous asbestos exposure. Methods A cross-sectional observational study was carried out, enrolling a total of 136 individuals matched for age and gender. The breath samples were collected from: 55 patients affected by MPM, 60 healthy controls (HC) and 21 asymptomatic asbestos-exposed individuals (EXP). For each volunteer, an end-tidal exhaled breath sample and an ambient air (AA) sample were collected on two sorbent tube (Biomonitoring steel tubes, Markes International) by an automated sampling system (Mistral – Predict srl). Breath and AA samples (n. 272) were thermally desorbed (Unity Ultra-xr Markes) and analyzed by Gas Chromatography/Mass Spectrometry (GC Agilent 7890/MS Agilent 5975). Results A total of 84 VOCs were detected in breath samples but only 35 compounds showed levels significatively different respect to AA. Nonparametric test as Wilcoxon signed rank tests allowed to identify the seven most weighting variables able to discriminate between end-tidal breath samples of patients with MPM and of HCs (variables with p-values < 0.05). A promising multivariate data mining approach incorporating only selected variables showing p-values lower than 0.05 was developed and cross-validated providing a prediction accuracy equal to 90% in identifying between groups, i.e. MPM and HC. Moreover, to explore the potentiality of the developed model in detection of metabolic alterations linked to previous asbestos exposure, a more extensive data set including asbestos exposed participants (EXP) has been processed by means Linear Discriminant Analysis (LDA) (R version 3.5.1 – MASS package). Two discriminating functions LD1 and LD2 explained 99% of the total variance of the data (accounting 58% and 41%, respectively) and leave-one-out cross validation resulted in four out of 21 EXP subjects misclassified as MPM. Hence, it could be useful a further and more frequent clinical surveillance for the follow up of these subjects. Furthermore, eleven breath samples collected from MPM patients in follow up (FU), after first-line chemotherapy, were exploratively analyzed, processed by the validated statistical method as blinded samples and classified as MPM. Good agreement was found with patients’ outcomes because the eleven MPM–FU subjects were in disease progression. Conclusions Despite the promising results, the size and the homogeneity of the sample population deserves further investigation to validate breath analysis as a helpful tool in the screening and clinical management of MPM. References [1] Catino A. et al., 2019. Cancers, 11, 831.