Renata Soares (Presenter)
Imperial College London
Bio: I have been working as a Research Associate in imaging mass spectrometry since 2015 in Prof. Zoltan Takats research lab. My role consists in managing the lab and the research DESI-imaging team. I have been involved in improving the DESI setup as well as developing/implementing different applications for DESI-MS.
Authorship: Renata Soares (1), Luisa Doria (1), James McKenzie (1), Anna Mroz (1), Francesca Rossini (1), Zoltan Takats (1)
(1) Mass Spectrometry Lab, Department of Surgery & Cancer, Imperial College London
| Short Abstract Desorption Electrospray Ionisation Mass Spectrometry Imaging (DESI-MSI) has been extensively used for the analysis of cancer samples. One major advantage of DESI-MSI is that spatial distribution of molecules can be obtained, which can allow for the further investigation of cancer environment. Eicosanoids are considered inflammatory molecules that play an important role in cancer. In this work, cancerous samples have been analysed by DESI-MSI and the spatial distribution of eicosanoid classes was assessed in different types of tissues. It was observed that different classes of eicosanoids are present depending on the tissue type. Hence, highlighting another usage of this ambient imaging technique. |
Long Abstract
Desorption Electrospray Ionisation (DESI) is an ambient ionisation technique that uses a charged-solvent droplets guided by nitrogen gas to desorb molecules of interest from sample surfaces generating secondary ions, which in turn will be analysed by mass spectrometry. For the past decade DESI-MSI has extensively been used as an imaging mass spectrometry technique (DESI-MSI). DESI-MSI allows the spatial distribution molecules to be determined.
The analysis of tissue samples has been extensively done using DESI-MSI. In particular, in the detection of phospholipids, where several phospholipid classes could be determined, such as phosphatidic acid (PA), Phosphatidylethanolamine (PE), Phosphatidylglycerol (PG), phosphatidylinositol (PI), phosphatidylserines (PS) and Phosphatidylcholines (PC). It has been extensively shown that different tissue types, for example healthy and cancer tissue, have different phospholipid distribution hence allowing for the different identification of different tissue types.
This technique has been of particular interest in the field of diagnosis, in particular cancer. As a diagnosis tool, DESI-MSI would allow cancer diagnosis to be quicker, more precise, and more accurately compared to routinely used methodologies in histo-pathology laboratories. The routinely used methodology in histo-pathology laboratories can take approximately 10 working days. This is mainly due to the fact that there are multiple sample processing steps, as well as multiple assays which are usually necessary until the final diagnosis can be provided. With the DESI-MSI approach, the analysis of a tissue sample can take approximately 3 working days. DESI-MSI sample preparation requirements are minimal as the sample needs only to be cryosectioned. After this the sample is analysed by DESI-MSI and the collected mass spectra are interrogated using a statistical programme where tissue-specific phospholipid profiles are interrogated. Most-importantly, because the mass spectra contain x and y coordinates for every spectra obtained it is possible to obtain spatial information of the different tissue types and as this tissue classification / identification is based on biochemical information it can prevent miss-diagnosis.
One important aspect of cancer, is to understand tumour microenvironment. One particular aspect of this topic is to try and understand the role of eicosanoids in cancer. It has been know that this reactive lipid species is involved in inflammation and cancer.
Fresh frozen colorectal, ovarian tissue samples containing healthy and cancerous tissue were cryosectioned into 10 µm thickness and mounted onto glass slides. The samples were kept at -80 oC until analysis. The DESI-MSI analysis was performed using a 2D DESI stage coupled to a QToF mass spectrometer (Xevo G2-XS, Waters), a flow rate of 1.5 µl/min 95:5 v/v methanol: water as ionisation solvent and 0.001 µg/ml of raffinose as a lockmass compound. The DESI-MSI scan rate was set to 4 scans per second and analysis was performed in positive and negative ion modes. After this, the DESI-MSI analysed section of stained with hematoxylin and eosin (H&E). The stained imaged was digitalised with an optical scanner. The optical image and the DESI-MSI image of the samples analysed were aligned using an in house developed imaging toolbox and the areas of interest were annotated by a classified histopathologist.
The spatial distribution of eicosanoids was enquired using an in house toolbox and statistical analysis were performed between the different types of samples. Putative identification of eicosanoids were obtained using Metlin (https://metlin.scripps.edu/index.php) and were based high mass accuracy measurements. The presence of eicosanoids was as expected more abundant and more homogenous in cancerous tissue than in healthy tissue. Is was also observed that areas around the tumour contained specific eicosanoids, where “hot regions” were observed. No difference in eicosanoid classes were detected in positive or negative ion mode for the same type of samples. Cancer samples and healthy samples were compared prostaglandins were the main eicosanoid class detected for both sample types. Leukotrines seemed to be less abundant in tumour samples and in addition other classes of eicosanoids seemed to be only present in cancerous tissues, such as lipoxins and isoprostanes.
In conclusion, DESI-MSI can be utilised for the spatial determination of eicosanoids in tissue samples, highlighting another usage of this imaging technique. In addition, proving further understanding of the role of these mediators in inflammation.
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