RATIONALE: Malignant pleural mesothelioma is an extremely aggressive and incurable malignancy associated with prior exposure to asbestos fibres. Difficulties remain in relation to early diagnosis, notably due to impeded identification of asbestos in lung tissue. This study describes a novel laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) imaging approach to identify asbestos within mesothelioma models with clinical significance. METHODS: Human mesothelioma cells were exposed to different types of asbestos fibres and prepared on plastic slides for LA-ICP-MS analysis. No further sample preparation was required prior to analysis, which was performed using an NWR Image 266 nm laser ablation system coupled to an Element XR sector-field ICP mass spectrometer, with a lateral resolution of 2 μm. Data was processed using LA-ICP-MS ImageTool v1.7 with the final graphic production made using DPlot software. RESULTS: Four different mineral fibres were successfully identified within the mesothelioma samples based on some of the most abundant elements that make up these fibres (Si, Mg and Fe). Using LA-ICP-MS as an imaging tool provided information on the spatial distribution of the fibres at cellular level, which is essential in asbestos detection within tissue samples. Based on the metal counts generated by the different types of asbestos, different fibres can be identified based on shape, size, and elemental composition. Detection of Ca was attempted but requires further optimisation. CONCLUSIONS: Detection of asbestos fibres in lung tissues is very useful, if not necessary, to complete the pathological dt9iagnosis of asbestos-related malignancies in the medicolegal field. For the first time, this study demonstrates the successful application of LA-ICP-MS imaging to identify asbestos fibres and other mineral fibres within mesothelioma samples. Ultimately, high-resolution, fast-speed LA-ICP-MS analysis has the potential to be integrated into clinical workflow to aid earlier detection and stratification of mesothelioma patient samples.
RATIONALE: Malignant pleural mesothelioma is an extremely aggressive and incurable malignancy associated with prior exposure to asbestos fibres. Difficulties remain in relation to early diagnosis, notably due to impeded identification of asbestos in lung tissue. This study describes a novel laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) imaging approach to identify asbestos within mesothelioma models with clinical significance. METHODS:Humanmesothelioma cells were exposed to different types of asbestos fibres and prepared on plastic slides for LA-ICP-MS analysis. No further sample preparation was required prior to analysis, which was performed using an NWR Image 266 nm laser ablation system coupled to an Element XR sector-field ICP mass spectrometer, with a lateral resolution of 2 μm. Data was processed using LA-ICP-MS ImageTool v1.7 with the final graphic production made using DPlot software. RESULTS: Four different mineral fibres were successfully identified within the mesothelioma samples based on some of the most abundant elements that make up these fibres (Si, Mg and Fe). Using LA-ICP-MS as an imaging tool provided information on the spatial distribution of the fibres at cellular level, which is essential in asbestos detection within tissue samples. Based on the metal counts generated by the different types of asbestos, different fibres can be identified based on shape, size, and elemental composition. Detection of Ca was attempted but requires further optimisation. CONCLUSIONS: Detection of asbestos fibres in lung tissues is very useful, if not necessary, to complete the pathological dt9iagnosis of asbestos-related malignancies in the medicolegal field. For the first time, this study demonstrates the successful application of LA-ICP-MS imaging to identify asbestos fibres and other mineral fibres within mesothelioma samples. Ultimately, high-resolution, fast-speed LA-ICP-MS analysis has the potential to be integrated into clinical workflow to aid earlier detection and stratification of mesotheliomapatient samples.
Authors: Anna Schoeberl; Michael Gutmann; Sarah Theiner; Martin Schaier; Andreas Schweikert; Walter Berger; Gunda Koellensperger Journal: Anal Chem Date: 2021-11-30 Impact factor: 6.986
Authors: Oana M Voloaca; Malcolm R Clench; Gunda Koellensperger; Laura M Cole; Sarah L Haywood-Small; Sarah Theiner Journal: Anal Chem Date: 2022-01-24 Impact factor: 6.986