Author of

• 35273

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  P25 - Mesothelioma, Thymoma and Other Thoracic Malignancies - Mesothelioma Preclinical, Prognostic and Predictive Factors (ID 139)

  • Event: WCLC 2020
  • Type: Posters
  • Track: Mesothelioma, Thymoma and Other Thoracic Malignancies
  • Presentations: 1
  • Moderators:
  • Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall

  • 35276

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    P25.03 - Novel Diagnosis Technique for Identification of Asbestos Fibres in Mesothelioma Samples using LA-ICP-MS Imaging (ID 1797)

    00:00 - 00:00  |  Presenting Author(s): Oana Maria Voloaca
    • Abstract

    Introduction
    

    Malignant mesothelioma (MM) is an aggressive cancer of the mesothelium associated with occupational and environmental exposure to asbestos and other mineral fibres (MF). There is an urgent need to develop methods to clearly identify and quantify the MF within biological samples. The aim of the current project is to identify MF based on their metal content within MM in vitro models as well as patient samples using laser ablation-inductively coupled plasma-mass spectrometry imaging (LA-ICP-MSI).

    Methods
    

    MM models were developed using immortalised cell lines prepared as both 2D cytospins and 3D cell pellets. For the 2D samples, cells were exposed to 3 µg/ mL MF solution (actinolite, amosite, wollastonite, crocidolite and chrysotile) for 24h and then harvested and cytospun plastic slides. For the 3D cell pellets, 1 x 10⁷ cells were harvested, centrifuged and treated with 100 µl MF before embedding in HMPC/ PVP media (3:1 ratio) and flash frozen in liquid nitrogen. The 3D models were cryosectioned onto plastic slides in 12 µm thick sections. Patient tissue samples were obtained from MesobanK. LA-ICP-MS images were acquired using Thermo Scientific™ Element™ XR sector field ICP-MS Series instrumentation in standard measurement. Data processing was performed using LA-ICP-MS ImageTool v1.7.

    Results
    

    Preliminary data has been acquired using LA-ICP-MSI, confirming that this analytical method has high potential in identifying the MF at cellular level. Moreover, data acquired in 2D models suggests that different MF can be identified based on shape, size and elemental composition. The MF were detected based on the high magnesium, iron and silicon content. Detection of calcium was attempted but requires further optimisation. Spatial distribution of the MF was also investigated in 3D models of MM by LA-ICP-MSI. Based on these findings, analysis on patient tissue will be performed to further validate this new approach in a clinical setting.

    

    Conclusion
    

    For the first time, this research has developed an imaging method using LA-ICP-MSI to identify MF within MM samples. High-resolution and high-speed analysis suggests that LA-ICP-MSI has the potential to be ultimately be integrated in the clinical flow to aid early diagnosis of mesothelioma and higher overall survival rates.