Edward St John (Presenter)
Bio: I am a breast surgeon and I live and work in London, UK. I qualified from Imperial College School of Medicine in 2006 with a merit in surgery and a 1st class BSc in medical sciences with honours. I became a member of the royal college of surgeons of England in 2009. was appointed to the role of clinical research fellow to Professor the Lord Darzi in April 2014. Professor Zoltan Takats is supervising my PhD research project entitled Rapid Evaporative Ionisation for Examination of Circumferential Surgical Excision Margins in Breast Surgery. In May 2015 I won the BJS (British Journal of Surgery) Prize for the best oral presentation at the Association of Breast Surgeons conference, UK. This was awarded for my initial work on the iKnife in breast cancer. My average week currently consist of time for both clinical and research commitments.
Authorship: Edward St John (1*), April Covington (1*), Emma White (1), Hui-Yu, Ho (1), James McKenzie (1), Francesca Rosini (1), Julia Balog (1 & 2), Ara Darzi (1), Daniel Leff (1), Zoltan Takats (1)
(1) Imperial College London, UK, (2) Waters Corp, Budapest, Hungary, (*) These authors contributed equally to this work.
Rapid Evaporative Ionization Mass Spectrometry (REIMS) measures ionic content of the electrosurgical plume for rapid tissue identification. Key spectral peaks differentiating normal from cancerous breast tissues were identified using univariate analysis of REIMS spectra from a representative sample set of normal and tumour (n=34). 24 significant peaks were identified, with an average 0.5-fold increase in the peaks in the phospholipid region and 5.7-fold decrease in the triglyceride region. These were investigated using REIMS tandem mass spectrometry and compared to lipid databases to identify species. This preliminary study demonstrates that tumour-associated changes in the breast lipidome can be identified by REIMS.
Breast cancer is the most common cancer in females worldwide and accounts for 31% of cancer diagnoses in women in the UK, with 1 in 8 developing breast cancer in their lifetime(1). Rapid Evaporative Ionization Mass Spectrometry (REIMS) uses mass spectrometric analysis of the tissue specific ionic content of the electrosurgical diathermy smoke plume for rapid identification of dissected breast tissues as an intelligent knife (iKnife)(2).
Tissue type differentiation with the iKnife is based upon differences in gross spectral patterns and multivariate analysis of a database of histologically validated spectra (2–5). Ions detected by REIMS are mostly lipid species, and while individual species are not tissue specific, their distribution and abundance allows tissue specific identification by REIMS(4). Dysregulation of lipid metabolism is becoming an increasingly well recognised hallmark of cancer, with up-regulation in de novo fatty acid synthesis occurring early in the development of many cancers in order to meet the increasing metabolic demands of the cell(6,7). Enhanced lipogenesis may confer an early proliferative advantage by protecting cancerous cells from microenvironmental stresses such as hypoxia, and exogenous insults such as chemotherapeutic agents(8,9). Glycerophospholipids have both structural and functional roles with the cell, with properties dependent on the species of glycerophospholipid, as well as the length and degree of saturation of the fatty acid (FA) chains (7,10). Dysregulation of glycerophospholipids has been identified in breast cancer using mass spectrometry techniques(11–20) and has been implicated in mediation of cell survival, proliferation and migration in cancer cells(21).
While lipid changes in breast cancer cells have been studied using other types of MS, these changes have yet to be studied with REIMS. Identifying these lipids may aid in improving the sensitivity and specificity of REIMS tissue detection for application with the iKnife, as well as adding to current knowledge of lipid dysregulation in breast cancer. The aim of this study was to identify lipid ions detected by REIMS that differentiate healthy and cancerous breast tissue, using online lipid databases and tandem mass spectrometry (MS/MS).
Ethical approval was obtained from the Research Ethics Committee. Smoke aerosol produced by electrosurgical diathermy from frozen and fresh ex-vivo breast samples was aspirated into a mass spectrometer via a modified surgical hand-piece. Aerosol was combined with isopropyl alcohol before impact with a heated collision surface and the m/z value of negatively charged ions was analysed by a modified Xevo G2-S instrument. Tissue diagnosis was confirmed by subsequent histopathological validation and spectra were assigned a classification of normal or tumour based upon histopathology. Multivariate statistics – Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) along with leave one patient out cross-validation were used for computational analysis and creation of an ex-vivo classification model.
Spectral data from a representative sample set of normal and tumour breast samples were selected for multi and univariate comparison. Cancer samples were selected by choosing samples containing 90-100% invasive cancer tissue observed on histology, to ensure that the lipid profile was representative of invasive cancer tissue. Normal samples were chosen randomly from samples with good signal intensity using a computerized random number generator. Spectra were aligned and processed for use with MATLAB®(MathWorks, Massachusetts). Peak picking was performed to select spectral peaks from the raw data, with an intensity limit of 30 a.u. to avoid inclusion of noise and low intensity peaks. Univariate analysis using Mann-Whitney U was performed with Benjamini-Hochberg false discovery rate correction.
Statistically significant peaks were selected for further analysis using MS/MS, excluding M+1 and M+2 isotope peaks. Thawed frozen normal and cancerous breast tissue was used for MS/MS data collection with experimental set-up as described above. Tissue was cut with the iKnife hand-piece for 10-15 seconds to allow for collection of sufficient ions and collision energies of 20-40eV for fragmentation. From the subsequent spectra, observed fragments were matched to lipids identified from online lipid databases, METLIN and LIPID MAPS® (22,23).
Data from 34, normal (n=17) and cancerous (n=17) tissues were compared using univariate analysis. The average cancer spectrum demonstrated higher abundance in the phospholipid (600-800 m/z) range, and a decrease in abundance in the triglyceride (800-1000 m/z) range. From this dataset, 35 significant m/z peaks could be identified (p<0.05), of which 11 were excluded as they were isotopes of other significant peaks. Of the 24 remaining significant peaks, 18 were higher in tumour tissue by an average of 0.5 fold increase. 6 peaks were lower in tumour, with an average of 5.7 fold decrease.
REIMS-MS/MS was performed on normal and cancerous tissue in order to analyse the composition of the m/z peaks that were significantly different between tissue types. All peaks selected for tandem mass spectrometry consisted of isobaric and isomeric mixtures of lipid species. For example the following peaks that were upregulated in breast cancer could be attributed to the following lipids: m/z 699.5, PE(16:0/18:1) M-NH3-H, PA(18:1/18:1), PA(18:0/18:2) M-H. m/z 687.5, PA(P-20:0/16:0) M-H and PA(O-18:0/18:1) M-H. m/z 717.51, PA(O-16:0/20:4) M+Cl and PC(16:0/16:0) M-CH3-H.
Overall, 108 lipid species were identified. Phosphatidylethanolamines (PEs) were the most commonly identified species, followed by phosphatidylcholines (PCs), phosphatidic acids (PAs), phosphatidylserines (PSs) and phosphatidylglycerols (PGs) respectively. The most common ion adduct was [M-H], with [M+Cl], [M+OH], [M-H2O-H], [M-CH3-H] and [M-NH3] adducts also identified. Triglycerides with [M+Cl], [M+OH] or [M+CH3COO] adducts were identified from the MS/MS spectra of peaks significantly lower in cancer.
This study demonstrates that it is possible to identify differences in the lipidome of normal and cancerous breast tissue using REIMS, and that these lipids can be interrogated using MS/MS. For the first time, REIMS MS/MS has been used to characterise key lipid species present in normal and cancerous breast tissue. The data shows that phospholipid species increase in cancer tissues compared to normal breast, whereas triglyceride species decrease; a finding which has been reported in other studies of breast tissue using different MS and nuclear magnetic resonance imaging techniques (13,24–26). It is known that triglycerides and glycerophospholipids are synthesised from fatty acids in the cell via the glycerolphosphate pathway. The changes in abundance of species seen in this study and others suggests a shift in this pathway towards phospholipid synthesis and away from storage of FA as triglycerides. Synthesis of phospholipids is increased in order to meet demand for membrane production of these highly proliferating cells(27).
Of the glycerophospholipids, PEs and PCs were most commonly identified, followed by PAs, PSs and PGs. Upregulation of these lipid species has previously been identified by other authors and are thought to confer advantages in cancer cells(11–20,28). For example, phosphatidic acids have been identified to contribute to control of cell survival and proliferation through effects on mTOR and other pathways(29).
Detailed analysis of individual lipids can provide important information about the lipid metabolism in breast cancer tissue(13). Understanding these changes may allow identification of new biomarkers and therapeutic targets. The ability to study lipidomic profiles with REIMS and the iKnife is promising as data collected during surgeries may one day be used to direct research by identifying lipids that are specifically up-regulated in cancer sub-types.
Further work should involve analysis of tissue by liquid chromatography mass spectrometry (LC-MS) which allows separation of lipid compounds, including isomers(30). As many of the m/z peaks identified in this study were mixtures of lipid ions, using REIMS in conjunction with LC-MS/MS would allow individual characterization and quantification of lipid species with greater confidence.
References & Acknowledgements:
Acknowledgements: Edward St John (*) & April Covington (*). *These authors contributed equally to this work. We acknowledge an educational grant provided by Waters Corp for research towards the iKnife. We thank Imperial College Tissue Bank and Imperial College NHS trust breast unit and pathology department. We thank all the patients who have kindly consented for the use of their tissue for research.
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|Grants||yes||Waters Corp provides financial support for the iKnife research. I do not receive a personal grant.|
|Stock||yes||A small amount of my total investments is held within biotech companies - e.g. Thermo and Waters|
IP Royalty: no
|Planning to mention or discuss specific products or technology of the company(ies) listed above:||