Determining the clinical utility of a breath test for screening an asbestos-exposed population for pleural mesothelioma: baseline results.

Pleural mesothelioma (PM) is an aggressive cancer of the serosal lining of the thoracic cavity, predominantly caused by asbestos exposure. Due to nonspecific symptoms, PM is characterized by an advanced-stage diagnosis, resulting in a dismal prognosis. However, early diagnosis improves patient outcome. Currently, no diagnostic biomarkers or screening tools are available. Therefore, exhaled breath was explored as this can easily be obtained and contains volatile organic compounds, which are considered biomarkers for multiple (patho)physiological processes. A breath test, which differentiates asbestos-exposed (AEx) individuals from PM patients with 87% accuracy, was developed. However, before being implemented as a screening tool, the clinical utility of the test must be determined. Occupational AEx individuals underwent annual breath tests using multicapillary column/ion mobility spectrometry. A baseline breath test was taken and their individual risk of PM was estimated. PM patients were included as controls. In total, 112 AEx individuals and six PM patients were included in the first of four screening rounds. All six PM patients were correctly classified as having mesothelioma (100% sensitivity) and out of 112 AEx individuals 78 were classified by the breath-based model as PM patients (30% specificity). Given the large false positive outcome, the breath test will be repeated annually for three more consecutive years to adhere to the 'test, re-test' principle and improve the false positivity rate. A low-dose computed tomography scan in those with two consecutive positive tests will correlate test positives with radiological findings and the possible growth of a pleural tumor. Finally, the evaluation of the clinical value of a breath-based prediction model may lead to the initiation of a screening program for early detection of PM in Aex individuals, which is currently lacking. This clinical study received approval from the Antwerp University Hospital Ethics Committee (B300201837007).

External Validation of a Breath-Based Prediction Model for Malignant Pleural Mesothelioma.

During the past decade, volatile organic compounds (VOCs) in exhaled breath have emerged as promising biomarkers for malignant pleural mesothelioma (MPM). However, as these biomarkers lack external validation, no breath test for MPM has been implemented in clinical practice. To address this issue, we performed the first external validation of a VOC-based prediction model for MPM. The external validation cohort was prospectively recruited, consisting of 47 MPM patients and 76 asbestos-exposed (AEx) controls. The predictive performance of the previously developed model was assessed by determining the degree of agreement between the predicted and actual outcome of the participants (patient/control). Additionally, to optimise the performance, the model was updated by refitting it to the validation cohort. External validation revealed a poor performance of the original model as the accuracy was estimated at only 41%, indicating poor generalisability. However, subsequent updating of the model improved the differentiation between MPM patients and AEx controls significantly (73% accuracy, 92% sensitivity, and 92% negative predictive value), substantiating the validity of the original predictors. This updated model will be more generalisable to the target population and exhibits key characteristics of a potential screening test for MPM, which could significantly impact MPM management.

Headspace Volatile Organic Compound Profiling of Pleural Mesothelioma and Lung Cancer Cell Lines as Translational Bridge for Breath Research.

Introduction: Malignant pleural mesothelioma (MPM) is a lethal cancer for which early-stage diagnosis remains a major challenge. Volatile organic compounds (VOCs) in breath proved to be potential biomarkers for MPM diagnosis, but translational studies are needed to elucidate which VOCs originate from the tumor itself and thus are specifically related to MPM cell metabolism. Methods: An in vitro model was set-up to characterize the headspace VOC profiles of six MPM and two lung cancer cell lines using thermal desorption-gas chromatography-mass spectrometry. A comparative analysis was carried out to identify VOCs that could discriminate between MPM and lung cancer, as well as between the histological subtypes within MPM (epithelioid, sarcomatoid and biphasic). Results: VOC profiles were identified capable of distinguishing MPM (subtypes) and lung cancer cells with high accuracy. Alkanes, aldehydes, ketones and alcohols represented many of the discriminating VOCs. Discrepancies with clinical findings were observed, supporting the need for studies examining breath and tumor cells of the same patients and studying metabolization and kinetics of in vitro discovered VOCs in a clinical setting. Conclusion: While the relationship between in vitro and in vivo VOCs is yet to be established, both could complement each other in generating a clinically useful breath model for MPM.

Prolyl Carboxypeptidase Mediates the C-Terminal Cleavage of (Pyr)-Apelin-13 in Human Umbilical Vein and Aortic Endothelial Cells.

The aim of this study was to investigate the C-terminal cleavage of (pyr)-apelin-13 in human endothelial cells with respect to the role and subcellular location of prolyl carboxypeptidase (PRCP). Human umbilical vein and aortic endothelial cells, pre-treated with prolyl carboxypeptidase-inhibitor compound 8o and/or angiotensin converting enzyme 2 (ACE2)-inhibitor DX600, were incubated with (pyr)-apelin-13 for different time periods. Cleavage products of (pyr)-apelin-13 in the supernatant were identified by mass spectrometry. The subcellular location of PRCP was examined via immunocytochemistry. In addition, PRCP activity was measured in supernatants and cell lysates of LPS-, TNFα-, and IL-1ß-stimulated cells. PRCP cleaved (pyr)-apelin-13 in human umbilical vein and aortic endothelial cells, while ACE2 only contributed to this cleavage in aortic endothelial cells. PRCP was found in endothelial cell lysosomes. Pro-inflammatory stimulation induced the secretion of PRCP in the extracellular environment of endothelial cells, while its intracellular level remained intact. In conclusion, PRCP, observed in endothelial lysosomes, is responsible for the C-terminal cleavage of (pyr)-apelin-13 in human umbilical vein endothelial cells, while in aortic endothelial cells ACE2 also contributes to this cleavage. These results pave the way to further elucidate the relevance of the C-terminal Phe of (pyr)-apelin-13.

Volatile organic compounds in human matrices as lung cancer biomarkers: a systematic review.

Volatile organic compounds (VOCs) have shown potential as non-invasive breath biomarkers for lung cancer, but their unclear biological origin currently limits clinical applications. This systematic review explores headspace analysis of VOCs in patient-derived body fluids and lung cancer cell lines to pinpoint lung cancer-specific VOCs and uncover their biological origin. A search was performed in the databases MEDLINE and Web of Science. Twenty-two articles were included in this systematic review. Since there is no standardised approach to analyse VOCs, a plethora of techniques and matrices/cell lines were explored, which is reflected in the various VOCs identified. However, comparing VOCs in the headspace of urine, blood and pleural effusions from patients and lung cancer cell lines showed some overlapping VOCs, indicating their potential use in lung cancer diagnosis. This review demonstrates that VOCs are promising biomarkers for lung cancer. However, due to lack of inter-matrix consensus, standardised prospective trials will have to be conducted to validate clinically relevant biomarkers.

Fast and flexible X-ray tomography using the ASTRA toolbox.

Object reconstruction from a series of projection images, such as in computed tomography (CT), is a popular tool in many different application fields. Existing commercial software typically provides sufficiently accurate and convenient-to-use reconstruction tools to the end-user. However, in applications where a non-standard acquisition protocol is used, or where advanced reconstruction methods are required, the standard software tools often are incapable of computing accurate reconstruction images. This article introduces the ASTRA Toolbox. Aimed at researchers across multiple tomographic application fields, the ASTRA Toolbox provides a highly efficient and highly flexible open source set of tools for tomographic projection and reconstruction. The main features of the ASTRA Toolbox are discussed and several use cases are presented.