Imperial College London

DrJamesMcKenzie

Faculty of MedicineDepartment of Metabolism, Digestion and Reproduction

Research Associate
 
 
 
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j.mckenzie

 
 
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E311Burlington DanesHammersmith Campus

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Summary

 

Publications

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44 results found

Abbassi-Ghadi N, Antonowicz SS, McKenzie JS, Kumar S, Huang J, Jones EA, Strittmatter N, Petts G, Kudo H, Court S, Hoare JM, Veselkov K, Goldin R, Takáts Z, Hanna GBet al., 2023, Data from <i>De Novo</i> Lipogenesis Alters the Phospholipidome of Esophageal Adenocarcinoma

<jats:p>&lt;div&gt;Abstract&lt;p&gt;The incidence of esophageal adenocarcinoma is rising, survival remains poor, and new tools to improve early diagnosis and precise treatment are needed. Cancer phospholipidomes quantified with mass spectrometry imaging (MSI) can support objective diagnosis in minutes using a routine frozen tissue section. However, whether MSI can objectively identify primary esophageal adenocarcinoma is currently unknown and represents a significant challenge, as this microenvironment is complex with phenotypically similar tissue-types. Here, we used desorption electrospray ionization-MSI (DESI-MSI) and bespoke chemometrics to assess the phospholipidomes of esophageal adenocarcinoma and relevant control tissues. Multivariate models derived from phospholipid profiles of 117 patients were highly discriminant for esophageal adenocarcinoma both in discovery (AUC = 0.97) and validation cohorts (AUC = 1). Among many other changes, esophageal adenocarcinoma samples were markedly enriched for polyunsaturated phosphatidylglycerols with longer acyl chains, with stepwise enrichment in premalignant tissues. Expression of fatty acid and glycerophospholipid synthesis genes was significantly upregulated, and characteristics of fatty acid acyls matched glycerophospholipid acyls. Mechanistically, silencing the carbon switch &lt;i&gt;ACLY&lt;/i&gt; in esophageal adenocarcinoma cells shortened glycerophospholipid chains, linking &lt;i&gt;de novo&lt;/i&gt; lipogenesis to the phospholipidome. Thus, DESI-MSI can objectively identify invasive esophageal adenocarcinoma from a number of premalignant tissues and unveils mechanisms of phospholipidomic reprogramming.&lt;/p&gt;Significance:&lt;p&gt;These results call for accelerated diagnosis studies using DESI-MSI in the upper gastrointestinal endoscopy suite, as well as functional studies to determine how polyunsaturated phosphatidylglycerols contribute to

Other

Abbassi-Ghadi N, Antonowicz SS, McKenzie JS, Kumar S, Huang J, Jones EA, Strittmatter N, Petts G, Kudo H, Court S, Hoare JM, Veselkov K, Goldin R, Takáts Z, Hanna GBet al., 2023, Data from &lt;i&gt;De Novo&lt;/i&gt; Lipogenesis Alters the Phospholipidome of Esophageal Adenocarcinoma

<jats:p>&lt;div&gt;Abstract&lt;p&gt;The incidence of esophageal adenocarcinoma is rising, survival remains poor, and new tools to improve early diagnosis and precise treatment are needed. Cancer phospholipidomes quantified with mass spectrometry imaging (MSI) can support objective diagnosis in minutes using a routine frozen tissue section. However, whether MSI can objectively identify primary esophageal adenocarcinoma is currently unknown and represents a significant challenge, as this microenvironment is complex with phenotypically similar tissue-types. Here, we used desorption electrospray ionization-MSI (DESI-MSI) and bespoke chemometrics to assess the phospholipidomes of esophageal adenocarcinoma and relevant control tissues. Multivariate models derived from phospholipid profiles of 117 patients were highly discriminant for esophageal adenocarcinoma both in discovery (AUC = 0.97) and validation cohorts (AUC = 1). Among many other changes, esophageal adenocarcinoma samples were markedly enriched for polyunsaturated phosphatidylglycerols with longer acyl chains, with stepwise enrichment in premalignant tissues. Expression of fatty acid and glycerophospholipid synthesis genes was significantly upregulated, and characteristics of fatty acid acyls matched glycerophospholipid acyls. Mechanistically, silencing the carbon switch &lt;i&gt;ACLY&lt;/i&gt; in esophageal adenocarcinoma cells shortened glycerophospholipid chains, linking &lt;i&gt;de novo&lt;/i&gt; lipogenesis to the phospholipidome. Thus, DESI-MSI can objectively identify invasive esophageal adenocarcinoma from a number of premalignant tissues and unveils mechanisms of phospholipidomic reprogramming.&lt;/p&gt;Significance:&lt;p&gt;These results call for accelerated diagnosis studies using DESI-MSI in the upper gastrointestinal endoscopy suite, as well as functional studies to determine how polyunsaturated phosphatidylglycerols contribute to

Other

Abbassi-Ghadi N, Antonowicz SS, McKenzie JS, Kumar S, Huang J, Jones EA, Strittmatter N, Petts G, Kudo H, Court S, Hoare JM, Veselkov K, Goldin R, Takáts Z, Hanna GBet al., 2023, Supplementary Data from &lt;i&gt;De Novo&lt;/i&gt; Lipogenesis Alters the Phospholipidome of Esophageal Adenocarcinoma

<jats:p>&lt;p&gt;The Supplementary information file contains: (i) Supplementary Methods, concerning PCR primers, antibodies and explanation of the chemometric approach. (ii) Supplementary Figures 1-4, which provide extended data for the multivariable models of Figure 2 and 3, MS/MS analyses, and further gene expression data supporting Figure 5. (iii) Supplementary Tables 1-4, which provide demographics of the cohorts and univariate lipid analyses from Cohort 1 and 2.&lt;/p&gt;</jats:p>

Other

Abbassi-Ghadi N, Antonowicz SS, McKenzie JS, Kumar S, Huang J, Jones EA, Strittmatter N, Petts G, Kudo H, Court S, Hoare JM, Veselkov K, Goldin R, Takáts Z, Hanna GBet al., 2023, Supplementary Data from &lt;i&gt;De Novo&lt;/i&gt; Lipogenesis Alters the Phospholipidome of Esophageal Adenocarcinoma

<jats:p>&lt;p&gt;The Supplementary information file contains: (i) Supplementary Methods, concerning PCR primers, antibodies and explanation of the chemometric approach. (ii) Supplementary Figures 1-4, which provide extended data for the multivariable models of Figure 2 and 3, MS/MS analyses, and further gene expression data supporting Figure 5. (iii) Supplementary Tables 1-4, which provide demographics of the cohorts and univariate lipid analyses from Cohort 1 and 2.&lt;/p&gt;</jats:p>

Other

Dannhorn A, Doria ML, McKenzie J, Inglese P, Swales JGG, Hamm G, Strittmatter N, Maglennon G, Ghaem-Maghami S, Goodwin RJA, Takats Zet al., 2023, Targeted Desorption Electrospray Ionization Mass Spectrometry Imaging for Drug Distribution, Toxicity, and Tissue Classification Studies, METABOLITES, Vol: 13

Journal article

Ford L, Chalau V, Naguleswaran A, McKenzie J, Mason S, Manoli E, Goldin R, Takats Z, Elson D, Kinross Jet al., 2023, Feasibility Analysis of iEndoscope for Real-Time Data Driven Pathology Using Novel MS and Optical Technology, Mass Spectrometry and Advances in the Clinical Lab

Conference paper

Marcus D, Phelps DL, Savage A, Balog J, Kudo H, Dina R, Bodai Z, Rosini F, Ip J, Amgheib A, Abda J, Manoli E, McKenzie J, Yazbek J, Takats Z, Ghaem-Maghami Set al., 2022, Point-of-care diagnosis of endometrial cancer using the surgical intelligent knife (iknife)-a prospective pilot study of diagnostic accuracy, Cancers, Vol: 14, Pages: 1-14, ISSN: 2072-6694

Introduction: Delays in the diagnosis and treatment of endometrial cancer negatively impact patient survival. The aim of this study was to establish whether rapid evaporative ionisation mass spectrometry using the iKnife can accurately distinguish between normal and malignant endometrial biopsy tissue samples in real time, enabling point-of-care (POC) diagnoses. Methods: Pipelle biopsy samples were obtained from consecutive women needing biopsies for clinical reasons. A Waters G2-XS Xevo Q-Tof mass spectrometer was used in conjunction with a modified handheld diathermy (collectively called the ‘iKnife’). Each tissue sample was processed with diathermy, and the resultant surgical aerosol containing ionic lipid species was then analysed, producing spectra. Principal component analyses and linear discriminant analyses were performed to determine variance in spectral signatures. Leave-one-patient-out cross-validation was used to test the diagnostic accuracy. Results: One hundred and fifty patients provided Pipelle biopsy samples (85 normal, 59 malignant, 4 hyperplasia and 2 insufficient), yielding 453 spectra. The iKnife differentiated between normal and malignant endometrial tissues on the basis of differential phospholipid spectra. Cross-validation revealed a diagnostic accuracy of 89% with sensitivity, specificity, positive predictive value and negative predictive value of 85%, 93%, 94% and 85%, respectively. Conclusions: This study is the first to use the iKnife to identify cancer in endometrial Pipelle biopsy samples. These results are highly encouraging and suggest that the iKnife could be used in the clinic to provide a POC diagnosis.

Journal article

Wu V, Tillner J, Jones E, McKenzie JS, Gurung D, Mroz A, Poynter L, Simon D, Grau C, Altafaj X, Dumas M-E, Gilmore I, Bunch J, Takats Zet al., 2022, High resolution ambient MS imaging of biological samples by desorption electro-flow focussing ionization, Analytical Chemistry, Vol: 94, Pages: 10035-10044, ISSN: 0003-2700

In this study, we examine the suitability of desorption electro-flow focusing ionization (DEFFI) for mass spectrometry imaging (MSI) of biological tissue. We also compare the performance of desorption electrospray ionization (DESI) with and without the flow focusing setup. The main potential advantages of applying the flow focusing mechanism in DESI is its rotationally symmetric electrospray jet, higher intensity, more controllable parameters, and better portability due to the robustness of the sprayer. The parameters for DEFFI have therefore been thoroughly optimized, primarily for spatial resolution but also for intensity. Once the parameters have been optimized, DEFFI produces similar images to the existing DESI. MS images for mouse brain samples, acquired at a nominal pixel size of 50 μm, are comparable for both DESI setups, albeit the new sprayer design yields better sensitivity. Furthermore, the two methods are compared with regard to spectral intensity as well as the area of the desorbed crater on rhodamine-coated slides. Overall, the implementation of a flow focusing mechanism in DESI is shown to be highly suitable for imaging biological tissue and has potential to overcome some of the shortcomings experienced with the current geometrical design of DESI.

Journal article

Sani M, Ford L, Simon D, Xiang Y, McKenzie J, Stavrakaki SM, Paizs P, Huq T, Higginson J, Alexander J, Takats Z, Kinross Jet al., 2022, A prospective pilot study of desorption electrospray ionisation mass spectrometry (DESI-MS) for the early detection of colorectal adenoma., Annual Meeting of the American-Association-for-Cancer-Research (AACR), Publisher: AMER ASSOC CANCER RESEARCH, ISSN: 0008-5472

Conference paper

Isberg OG, Giunchiglia V, McKenzie JS, Takats Z, Jonasson JG, Bodvarsdottir SK, Thorsteinsdottir M, Xiang Yet al., 2022, Automated Cancer Diagnostics via Analysis of Optical and Chemical Images by Deep and Shallow Learning, METABOLITES, Vol: 12

Journal article

Ford L, Chalau V, McKenzie J, Mason S, Manoli E, Goldin R, Takats Z, Elson D, Kinross Jet al., 2022, Comparison of Mass Spectrometry and Optical Spectroscopy for novel real time diagnosis of colorectal cancer, United European Gastroenterology Week

Conference paper

Mason SE, Manoli E, Alexander JL, Poynter L, Ford L, Paizs P, Adebesin A, McKenzie JS, Rosini F, Goldin R, Darzi A, Takats Z, Kinross JMet al., 2021, Lipidomic profiling of colorectal lesions for real-time tissue recognition and risk-stratification using rapid evaporative ionisation mass spectrometry., Annals of Surgery, Vol: 00, ISSN: 0003-4932

OBJECTIVE: Rapid Evaporative Ionisation Mass Spectrometry (REIMS) is a metabolomic technique analysing tissue metabolites, which can be applied intra-operatively in real-time. The objective of this study was to profile the lipid composition of colorectal tissues using REIMS, assessing its accuracy for real-time tissue recognition and risk-stratification. SUMMARY BACKGROUND DATA: Metabolic dysregulation is a hallmark feature of carcinogenesis, however it remains unknown if this can be leveraged for real-time clinical applications in colorectal disease. METHODS: Patients undergoing colorectal resection were included, with carcinoma, adenoma and paired-normal mucosa sampled. Ex vivo analysis with REIMS was conducted using monopolar diathermy, with the aerosol aspirated into a Xevo G2S QToF mass spectrometer. Negatively charged ions over 600-1000m/z were used for univariate and multivariate functions including linear discriminant analysis. RESULTS: 161 patients were included, generating 1013 spectra. Unique lipidomic profiles exist for each tissue type, with REIMS differentiating samples of carcinoma, adenoma and normal mucosa with 93 1% accuracy and 96 1% negative predictive value for carcinoma. Neoplasia (carcinoma or adenoma) could be predicted with 96 0% accuracy and 91 8% negative predictive value. Adenomas can be risk-stratified by grade of dysplasia with 93 5% accuracy, but not histological subtype. The structure of 61 lipid metabolites was identified, revealing that during colorectal carcinogenesis there is progressive increase in relative abundance of phosphatidylglycerols, sphingomyelins and mono-unsaturated fatty acid containing phospholipids. CONCLUSIONS: The colorectal lipidome can be sampled by REIMS and leveraged for accurate real-time tissue recognition, in addition to risk-stratification of colorectal adenomas. Unique lipidomic features associated with carcinogenesis are described.

Journal article

Dorado E, Doria ML, Nagelkerke A, McKenzie JS, Maneta-Stavrakaki S, Ion C, Whittaker T, Nicholson J, Stevens MM, Coombes RC, Takats Zet al., 2021, Lipidomic analysis of extracellular vesicles and its potential for the identification of body fluid-based biomarkers for breast cancer diagnosis., Annual Meeting of the American-Association-for-Cancer-Research (AACR), Publisher: AMER ASSOC CANCER RESEARCH, ISSN: 0008-5472

Conference paper

Capece D, D'Andrea D, Begalli F, Goracci L, Tornatore L, Alexander JL, Di Veroli A, Leow S-C, Vaiyapuri TS, Ellis JK, Verzella D, Bennett J, Savino L, Ma Y, McKenzie JS, Doria ML, Mason SE, Chng KR, Keun HC, Frost G, Tergaonkar V, Broniowska K, Stunkel W, Takats Z, Kinross JM, Cruciani G, Franzoso Get al., 2021, Enhanced triacylglycerol catabolism by Carboxylesterase 1 promotes aggressive colorectal carcinoma., Journal of Clinical Investigation, ISSN: 0021-9738

The ability to adapt to low-nutrient microenvironments is essential for tumor-cell survival and progression in solid cancers, such as colorectal carcinoma (CRC). Signaling by the NF-κB transcription-factor pathway associates with advanced disease stages and shorter survival in CRC patients. NF-κB has been shown to drive tumor-promoting inflammation, cancer-cell survival and intestinal epithelial cell (IEC) dedifferentiation in mouse models of CRC. However, whether NF-κB affects the metabolic adaptations that fuel aggressive disease in CRC patients is unknown. Here, we identified carboxylesterase 1 (CES1) as an essential NF-κB-regulated lipase linking obesity-associated inflammation with fat metabolism and adaptation to energy stress in aggressive CRC. CES1 promoted CRC-cell survival via cell-autonomous mechanisms that fuel fatty-acid oxidation (FAO) and prevent the toxic build-up of triacylglycerols. We found that elevated CES1 expression correlated with worse outcomes in overweight CRC patients. Accordingly, NF-κB drove CES1 expression in CRC consensus molecular subtype (CMS)4, associated with obesity, stemness and inflammation. CES1 was also upregulated by gene amplifications of its transcriptional regulator, HNF4A, in CMS2 tumors, reinforcing its clinical relevance as a driver of CRC. This subtype-based distribution and unfavourable prognostic correlation distinguished CES1 from other intracellular triacylglycerol lipases and suggest CES1 could provide a route to treat aggressive CRC.

Journal article

Kazanc E, Karali E, Wu V, Inglese P, McKenzie J, Tripp A, Koundouros N, Tsalikis T, Kudo H, Poulogiannis G, Takats Zet al., 2020, A multimodal analysis in breast cancer: Revealing metabolic heterogeneity using DESI-MS imaging with Laser-microdissection coupled transcriptome approach., AACR Virtual Special Conference on Tumor Heterogeneity - From Single Cells to Clinical Impact, Publisher: AMER ASSOC CANCER RESEARCH, ISSN: 0008-5472

Conference paper

Tzafetas M, Mitra A, Paraskevaidi M, Bodai Z, Kalliala I, Bowden S, Lathouras K, Rosini F, Szasz M, Savage A, Manoli E, Balog J, McKenzie J, Lyons D, Bennett P, MacIntyre D, Ghaem-Maghami S, Takats Z, Kyrgiou Met al., 2020, The intelligent knife (iKnife) and its intraoperative diagnostic advantage for the treatment of cervical disease (vol 117, pg 7338, 2020), PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 117, Pages: 18892-18892, ISSN: 0027-8424

Journal article

Abbassi-Ghadi N, Antonowicz S, McKenzie J, Kumar S, Huang J, Jones E, Strittmatter N, Petts G, Kudo H, court S, Hoare J, Veselkov K, Goldin R, Takats Z, Hanna Get al., 2020, De novo lipogenesis alters the phospholipidome of esophageal adenocarcinoma, Cancer Research, Vol: 80, Pages: 2764-2774, ISSN: 0008-5472

The incidence of esophageal adenocarcinoma is rising, survival remains poor, and new tools to improve early diagnosis and precise treatment are needed. Cancer phospholipidomes quantified with mass spectrometry imaging can support objective diagnosis in minutes using a routine frozen tissue section. However, whether mass spectrometry imaging can objectively identify primary esophageal adenocarcinoma is currently unknown and represents a significant challenge, as this microenvironment is complex with phenotypically similar tissue-types. Here we used desorption electrospray ionisation mass spectrometry imaging (DESI-MSI) and bespoke chemometrics to assess the phospholipidomes of esophageal adenocarcinoma and relevant control tissues. Multivariable models derived from phospholipid profiles of 117 patients were highly discriminant for esophageal adenocarcinoma both in discovery (area-under-curve = 0.97) and validation cohorts (AUC = 1). Among many other changes, esophageal adenocarcinoma samples were markedly enriched for polyunsaturated phosphatidylglycerols with longer acyl chains, with stepwise enrichment in pre-malignant tissues. Expression of fatty acid and glycerophospholipid synthesis genes was significantly upregulated, and characteristics of fatty acid acyls matched glycerophospholipid acyls. Mechanistically, silencing the carbon switch ACLY in esophageal adenocarcinoma cells shortened GPL chains, linking de novo lipogenesis to the phospholipidome. Thus, DESI-MSI can objectively identify invasive esophageal adenocarcinoma from a number of pre-malignant tissues and unveils mechanisms of phospholipidomic reprogramming. These results call for accelerated diagnosis studies using DESI-MSI in the upper gastrointestinal endoscopy suite as well as functional studies to determine how polyunsaturated phosphatidylglycerols contribute to esophageal carcinogenesis.

Journal article

Tzafetas M, Mitra A, Paraskevaidi M, Bodai Z, Kalliala I, Bowden S, Lathouras K, Rosini F, Szasz M, Savage A, Balog J, McKenzie J, Lyons D, Bennett P, MacIntyre D, Ghaem-Maghami S, Takats Z, Kyrgiou Met al., 2020, The intelligent-Knife (i-Knife) and its intraoperative diagnostic advantage for the treatment of cervical disease, Proceedings of the National Academy of Sciences of USA, Vol: 117, Pages: 7338-7346, ISSN: 0027-8424

Clearance of surgical margins in cervical cancer prevents the need for adjuvant chemoradiation and allows fertility preservation. In this study, we determined the capacity of the rapid evaporative ionization mass spectrometry (REIMS), also known as intelligent knife (iKnife), to discriminate between healthy, preinvasive, and invasive cervical tissue. Cervical tissue samples were collected from women with healthy, human papilloma virus (HPV) ± cervical intraepithelial neoplasia (CIN), or cervical cancer. A handheld diathermy device generated surgical aerosol, which was transferred into a mass spectrometer for subsequent chemical analysis. Combination of principal component and linear discriminant analysis and least absolute shrinkage and selection operator was employed to study the spectral differences between groups. Significance of discriminatory m/z features was tested using univariate statistics and tandem MS performed to elucidate the structure of the significant peaks allowing separation of the two classes. We analyzed 87 samples (normal = 16, HPV ± CIN = 50, cancer = 21 patients). The iKnife discriminated with 100% accuracy normal (100%) vs. HPV ± CIN (100%) vs. cancer (100%) when compared to histology as the gold standard. When comparing normal vs. cancer samples, the accuracy was 100% with a sensitivity of 100% (95% CI 83.9 to 100) and specificity 100% (79.4 to 100). Univariate analysis revealed significant MS peaks in the cancer-to-normal separation belonging to various classes of complex lipids. The iKnife discriminates healthy from premalignant and invasive cervical lesions with high accuracy and can improve oncological outcomes and fertility preservation of women treated surgically for cervical cancer. Larger in vivo research cohorts are required to validate these findings.

Journal article

Brusberg-Kiermeier S, McKenzie J, Schaebler D, 2019, Fear and Anxiety in Contemporary Drama and Performance: An Introduction, JOURNAL OF CONTEMPORARY DRAMA IN ENGLISH, Vol: 7, Pages: 1-11, ISSN: 2195-0156

Journal article

Poynter LR, Mirnezami R, Soares R, McKenzie J, Patel P, Peppa N, Mirnezami A, Kinross J, Darzi A, Takats Zet al., 2018, Modulation of cellular phospholipids correlates with tumor regression grade and radio resistance in rectal cancer, Annual Meeting of the American-Association-for-Cancer-Research (AACR), Publisher: AMER ASSOC CANCER RESEARCH, ISSN: 0008-5472

Conference paper

Phelps DL, Balog J, Gildea LF, Bodai Z, El-Bahrawy MA, Speller AVM, Rosini F, Kudo H, McKenzie JS, Brown R, Takats Z, Ghaem-Maghami Set al., 2018, The surgical intelligent knife distinguishes normal, borderline and malignant gynaecological tissues using rapid evaporative ionisation mass spectrometry (REIMS), British Journal of Cancer, Vol: 118, Pages: 1349-1358, ISSN: 0007-0920

BackgroundSurvival from ovarian cancer (OC) is improved with surgery, but surgery can be complex and tumour identification, especially for borderline ovarian tumours (BOT), is challenging. The Rapid Evaporative Ionisation Mass Spectrometric (REIMS) technique reports tissue histology in real-time by analysing aerosolised tissue during electrosurgical dissection.MethodsAerosol produced during diathermy of tissues was sampled with the REIMS interface. Histological diagnosis and mass spectra featuring complex lipid species populated a reference database on which principal component, linear discriminant and leave-one-patient-out cross-validation analyses were performed.ResultsA total of 198 patients provided 335 tissue samples, yielding 3384 spectra. Cross-validated OC classification vs separate normal tissues was high (97·4% sensitivity, 100% specificity). BOT were readily distinguishable from OC (sensitivity 90.5%, specificity 89.7%). Validation with fresh tissue lead to excellent OC detection (100% accuracy). Histological agreement between iKnife and histopathologist was very good (kappa 0.84, P < 0.001, z = 3.3). Five predominantly phosphatidic acid (PA(36:2)) and phosphatidyl-ethanolamine (PE(34:2)) lipid species were identified as being significantly more abundant in OC compared to normal tissue or BOT (P < 0.001, q < 0.001).ConclusionsThe REIMS iKnife distinguishes gynaecological tissues by analysing mass-spectrometry-derived lipidomes from tissue diathermy aerosols. Rapid intra-operative gynaecological tissue diagnosis may improve surgical care when histology is unknown, leading to personalised operations tailored to the individual.

Journal article

Bergholt MS, Serio A, McKenzie JS, Boyd A, Soares RF, Tillner J, Chiappini C, Wu V, Dannhorn A, Takats Z, Williams A, Stevens MMet al., 2017, Correlated heterospectral lipidomics for biomolecular profiling of remyelination in multiple sclerosis, ACS Central Science, Vol: 4, Pages: 39-51, ISSN: 2374-7943

Analyzing lipid composition and distribution within the brain is important to study white matter pathologies that present focal demyelination lesions, such as multiple sclerosis. Some lesions can endogenously re-form myelin sheaths. Therapies aim to enhance this repair process in order to reduce neurodegeneration and disability progression in patients. In this context, a lipidomic analysis providing both precise molecular classification and well-defined localization is crucial to detect changes in myelin lipid content. Here we develop a correlated heterospectral lipidomic (HSL) approach based on coregistered Raman spectroscopy, desorption electrospray ionization mass spectrometry (DESI-MS), and immunofluorescence imaging. We employ HSL to study the structural and compositional lipid profile of demyelination and remyelination in an induced focal demyelination mouse model and in multiple sclerosis lesions from patients ex vivo. Pixelwise coregistration of Raman spectroscopy and DESI-MS imaging generated a heterospectral map used to interrelate biomolecular structure and composition of myelin. Multivariate regression analysis enabled Raman-based assessment of highly specific lipid subtypes in complex tissue for the first time. This method revealed the temporal dynamics of remyelination and provided the first indication that newly formed myelin has a different lipid composition compared to normal myelin. HSL enables detailed molecular myelin characterization that can substantially improve upon the current understanding of remyelination in multiple sclerosis and provides a strategy to assess remyelination treatments in animal models.

Journal article

Tillner J, Wu V, Jones EA, Pringle SD, Karancsi T, Dannhorn A, Veselkov K, McKenzie JS, Takats Zet al., 2017, Faster, more reproducible DESI-MS for biological tissue imaging, Journal of The American Society for Mass Spectrometry, Vol: 28, Pages: 2090-2098, ISSN: 1044-0305

A new, more robust sprayer for desorption electrospray ionization (DESI) mass spectrometry imaging is presented. The main source of variability in DESI is thought to be the uncontrolled variability of various geometric parameters of the sprayer, primarily the position of the solvent capillary, or more specifically, its positioning within the gas capillary or nozzle. If the solvent capillary is off-center, the sprayer becomes asymmetrical, making the geometry difficult to control and compromising reproducibility. If the stiffness, tip quality, and positioning of the capillary are improved, sprayer reproducibility can be improved by an order of magnitude. The quality of the improved sprayer and its potential for high spatial resolution imaging are demonstrated on human colorectal tissue samples by acquisition of images at pixel sizes of 100, 50, and 20 μm, which corresponds to a lateral resolution of 40-60 μm, similar to the best values published in the literature. The high sensitivity of the sprayer also allows combination with a fast scanning quadrupole time-of-flight mass spectrometer. This provides up to 30 times faster DESI acquisition, reducing the overall acquisition time for a 10 mm × 10 mm rat brain sample to approximately 1 h. Although some spectral information is lost with increasing analysis speed, the resulting data can still be used to classify tissue types on the basis of a previously constructed model. This is particularly interesting for clinical applications, where fast, reliable diagnosis is required. Graphical Abstract ᅟ.

Journal article

St John ERC, Leff D, takats Z, Darzi Aet al., 2017, Rapid Evaporative Ionisation Mass Spectrometry of Electrosurgical Vapours for the Identification of Breast Pathology: Towards an Intelligent Knife for Breast Cancer Surgery, Breast Cancer Research, Vol: 19, ISSN: 1465-542X

Background:Re-operation for positive resection margins following breast-conserving surgery occurs frequently (average = 20–25%), is cost-inefficient, and leads to physical and psychological morbidity. Current margin assessment techniques are slow and labour intensive. Rapid evaporative ionisation mass spectrometry (REIMS) rapidly identifies dissected tissues by determination of tissue structural lipid profiles through on-line chemical analysis of electrosurgical aerosol toward real-time margin assessment.Methods:Electrosurgical aerosol produced from ex-vivo and in-vivo breast samples was aspirated into a mass spectrometer (MS) using a monopolar hand-piece. Tissue identification results obtained by multivariate statistical analysis of MS data were validated by histopathology. Ex-vivo classification models were constructed from a mass spectral database of normal and tumour breast samples. Univariate and tandem MS analysis of significant peaks was conducted to identify biochemical differences between normal and cancerous tissues. An ex-vivo classification model was used in combination with bespoke recognition software, as an intelligent knife (iKnife), to predict the diagnosis for an ex-vivo validation set. Intraoperative REIMS data were acquired during breast surgery and time-synchronized to operative videos.Results:A classification model using histologically validated spectral data acquired from 932 sampling points in normal tissue and 226 in tumour tissue provided 93.4% sensitivity and 94.9% specificity. Tandem MS identified 63 phospholipids and 6 triglyceride species responsible for 24 spectral differences between tissue types. iKnife recognition accuracy with 260 newly acquired fresh and frozen breast tissue specimens (normal n = 161, tumour n = 99) provided sensitivity of 90.9% and specificity of 98.8%. The ex-vivo and intra-operative method produced visually comparable high intensity spectra. iKnife interpretation

Journal article

Inglese P, McKenzie JS, Mroz A, Kinross J, Veselkov K, Holmes E, Takats Z, Nicholson JK, Glen RCet al., 2017, Deep learning and 3D-DESI imaging reveal the hidden metabolic heterogeneity of cancer, Chemical Science, Vol: 8, Pages: 3500-3511, ISSN: 2041-6539

Visual inspection of tumour tissues does not reveal the complex metabolic changes that differentiate cancer and its sub-types from healthy tissues. Mass spectrometry imaging, which quantifies the underlying chemistry, represents a powerful tool for the molecular exploration of tumour tissues. A 3-dimensional topological description of the chemical properties of the tumour permits the formulation of hypotheses about the biological composition and interactions and the possible causes of its heterogeneous structure. The large amount of information contained in such datasets requires powerful tools for its analysis, visualisation and interpretation. Linear methods for unsupervised dimensionality reduction, such as PCA, are inadequate to capture the complex non-linear relationships present in these data. For this reason, a deep unsupervised neural network based technique, parametric t-SNE, is adopted to map a 3D-DESI-MS dataset from a human colorectal adenocarcinoma biopsy onto a 2-dimensional manifold. This technique allows the identification of clusters not visible with linear methods. The unsupervised clustering of the tumour tissue results in the identification of sub-regions characterised by the abundance of identified metabolites, making possible the formulation of hypotheses to account for their significance and the underlying biological heterogeneity in the tumour.

Journal article

Takats Z, Strittmatter N, McKenzie JS, 2017, Ambient Mass Spectrometry in Cancer Research, APPLICATIONS OF MASS SPECTROMETRY IMAGING TO CANCER, Editors: Drake, McDonnell, Publisher: ELSEVIER ACADEMIC PRESS INC, Pages: 231-256, ISBN: 978-0-12-805249-5

Book chapter

Doria ML, McKenzie JS, Mroz A, Phelps DL, Speller A, Rosini F, Strittmatter N, Golf O, Veselkov K, Brown R, Ghaem-Maghami S, Takats Zet al., 2016, Epithelial ovarian carcinoma diagnosis by desorption electrospray ionization mass spectrometry imaging, Scientific Reports, Vol: 6, ISSN: 2045-2322

Ovarian cancer is highly prevalent among European women, and is the leading cause of gynaecological cancer death. Current histopathological diagnoses of tumour severity are based on interpretation of, for example, immunohistochemical staining. Desorption electrospray mass spectrometry imaging (DESI-MSI) generates spatially resolved metabolic profiles of tissues and supports an objective investigation of tumour biology. In this study, various ovarian tissue types were analysed by DESI-MSI and co-registered with their corresponding haematoxylin and eosin (H&E) stained images. The mass spectral data reveal tissue type-dependent lipid profiles which are consistent across the n = 110 samples (n = 107 patients) used in this study. Multivariate statistical methods were used to classify samples and identify molecular features discriminating between tissue types. Three main groups of samples (epithelial ovarian carcinoma, borderline ovarian tumours, normal ovarian stroma) were compared as were the carcinoma histotypes (serous, endometrioid, clear cell). Classification rates >84% were achieved for all analyses, and variables differing statistically between groups were determined and putatively identified. The changes noted in various lipid types help to provide a context in terms of tumour biochemistry. The classification of unseen samples demonstrates the capability of DESI-MSI to characterise ovarian samples and to overcome existing limitations in classical histopathology.

Journal article

Veselkov KA, Inglese, Galea D, McKenzie JS, Nicholson JKet al., 2016, Statistical Tools for Molecular Covariance Spectroscopy, Encyclopedia of Spectroscopy and Spectrometry, Editors: Lindon, Tranter, Koppenaal, Publisher: Elsevier B.V., Pages: 243-249, ISBN: 978-0-12-803224-4

One major application of modern spectroscopic and spectrometric techniques is to measure hundreds to thousands of molecules in biological specimens as part of a process of metabolic phenotyping. Statistical spectroscopy covers a range of techniques used for the recovery of correlated intensity patterns within and between molecules. This plays an essential role in the annotation of molecular features of potential biological or diagnostic significance. The article introduces a variety of univariate and multivariate statistical tools for molecular covariance spectroscopy.

Book chapter

Cauet E, Laponogov I, McKenzie J, Veselkov K, Takats Zet al., 2016, Computer assisted identification of metabolite mass spectra: How can machine learning and quantum mechanics help?, AMERICAN CHEMICAL SOCIETY, Publisher: AMER CHEMICAL SOC, ISSN: 0065-7727

Conference paper

Alexander J, Gildea L, Balog J, Speller A, McKenzie J, Muirhead L, Scott A, Kontovounisios C, Rasheed S, Teare J, Hoare J, Veselkov K, Goldin R, Tekkis P, Darzi A, Nicholson J, Kinross J, Takats Zet al., 2016, A novel methodology for in vivo endoscopic phenotyping of colorectal cancer based on real-time analysis of the mucosal lipidome: a prospective observational study of the iKnife, Surgical Endoscopy and Other Interventional Techniques, Vol: 31, Pages: 1361-1370, ISSN: 1432-2218

Background:This pilot study assessed the diagnostic accuracy of rapid evaporative ionization mass spectrometry (REIMS) in colorectal cancer (CRC) and colonic adenomas.Methods:Patients undergoing elective surgical resection for CRC were recruited at St. Mary’s Hospital London and The Royal Marsden Hospital, UK. Ex vivo analysis was performed using a standard electrosurgery handpiece with aspiration of the electrosurgical aerosol to a Xevo G2-S iKnife QTof mass spectrometer (Waters Corporation). Histological examination was performed for validation purposes. Multivariate analysis was performed using principal component analysis and linear discriminant analysis in Matlab 2015a (Mathworks, Natick, MA). A modified REIMS endoscopic snare was developed (Medwork) and used prospectively in five patients to assess its feasibility during hot snare polypectomy.Results:Twenty-eight patients were recruited (12 males, median age 71, range 35–89). REIMS was able to reliably distinguish between cancer and normal adjacent mucosa (NAM) (AUC 0.96) and between NAM and adenoma (AUC 0.99). It had an overall accuracy of 94.4 % for the detection of cancer versus adenoma and an adenoma sensitivity of 78.6 % and specificity of 97.3 % (AUC 0.99) versus cancer. Long-chain phosphatidylserines (e.g., PS 22:0) and bacterial phosphatidylglycerols were over-expressed on cancer samples, while NAM was defined by raised plasmalogens and triacylglycerols expression and adenomas demonstrated an over-expression of ceramides. REIMS was able to classify samples according to tumor differentiation, tumor budding, lymphovascular invasion, extramural vascular invasion and lymph node micrometastases (AUC’s 0.88, 0.87, 0.83, 0.81 and 0.81, respectively). During endoscopic deployment, colonoscopic REIMS was able to detect target lipid species such as ceramides during hot snare polypectomy.Conclusion:REIMS demonstrates high diagnostic accuracy for tumor type and for established histological featur

Journal article

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