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Maitra I, Morais CLM, Lima KMG, Ashton KM, Bury D, Date RS, Martin FL. Attenuated Total Reflection Fourier-Transform Infrared Spectral Discrimination in Human Tissue of Oesophageal Transformation to Adenocarcinoma. J Pers Med 2023; 13:1277. [PMID: 37623527 PMCID: PMC10455976 DOI: 10.3390/jpm13081277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 08/11/2023] [Accepted: 08/17/2023] [Indexed: 08/26/2023] Open
Abstract
This study presents ATR-FTIR (attenuated total reflectance Fourier-transform infrared) spectral analysis of ex vivo oesophageal tissue including all classifications to oesophageal adenocarcinoma (OAC). The article adds further validation to previous human tissue studies identifying the potential for ATR-FTIR spectroscopy in differentiating among all classes of oesophageal transformation to OAC. Tissue spectral analysis used principal component analysis quadratic discriminant analysis (PCA-QDA), successive projection algorithm quadratic discriminant analysis (SPA-QDA), and genetic algorithm quadratic discriminant analysis (GA-QDA) algorithms for variable selection and classification. The variables selected by SPA-QDA and GA-QDA discriminated tissue samples from Barrett's oesophagus (BO) to OAC with 100% accuracy on the basis of unique spectral "fingerprints" of their biochemical composition. Accuracy test results including sensitivity and specificity were determined. The best results were obtained with PCA-QDA, where tissues ranging from normal to OAC were correctly classified with 90.9% overall accuracy (71.4-100% sensitivity and 89.5-100% specificity), including the discrimination between normal and inflammatory tissue, which failed in SPA-QDA and GA-QDA. All the models revealed excellent results for distinguishing among BO, low-grade dysplasia (LGD), high-grade dysplasia (HGD), and OAC tissues (100% sensitivities and specificities). This study highlights the need for further work identifying potential biochemical markers using ATR-FTIR in tissue that could be utilised as an adjunct to histopathological diagnosis for early detection of neoplastic changes in susceptible epithelium.
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Affiliation(s)
- Ishaan Maitra
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - Camilo L. M. Morais
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil; (C.L.M.M.); (K.M.G.L.)
- Center for Education, Science and Technology of the Inhamuns Region, State University of Ceará, Tauá 63660-000, Brazil
| | - Kássio M. G. Lima
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil; (C.L.M.M.); (K.M.G.L.)
| | - Katherine M. Ashton
- Lancashire Teaching Hospitals NHS Foundation Trust, Royal Preston Hospital, Preston PR2 9HT, UK; (K.M.A.); (R.S.D.)
| | - Danielle Bury
- Department of Cellular Pathology, Blackpool Teaching Hospitals NHS Foundation Trust, Blackpool FY3 8NR, UK;
| | - Ravindra S. Date
- Lancashire Teaching Hospitals NHS Foundation Trust, Royal Preston Hospital, Preston PR2 9HT, UK; (K.M.A.); (R.S.D.)
| | - Francis L. Martin
- Department of Cellular Pathology, Blackpool Teaching Hospitals NHS Foundation Trust, Blackpool FY3 8NR, UK;
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Lilo T, Morais CLM, Ashton KM, Davis C, Dawson TP, Martin FL, Alder J, Roberts G, Ray A, Gurusinghe N. Raman hyperspectral imaging coupled to three-dimensional discriminant analysis: Classification of meningiomas brain tumour grades. Spectrochim Acta A Mol Biomol Spectrosc 2022; 273:121018. [PMID: 35189493 DOI: 10.1016/j.saa.2022.121018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Revised: 02/04/2022] [Accepted: 02/06/2022] [Indexed: 06/14/2023]
Abstract
Meningiomas remains a clinical dilemma. They are the commonest "benign" types of brain tumours and, although being typically benign, they are divided into three WHO grades categories (I, II and III) which are associated with the tumour growth rate and likelihood of recurrence. Recurrence depends on extend of surgery as well as histopathological diagnosis. There is a marked variation amongst surgeons in the follow-up arrangements for their patients even within the same unit which has a significant clinical, and financial implication. Knowing the tumour grade rapidly is an important factor to predict surgical outcomes and adequate patient treatment. Clinical follow up sometimes is haphazard and not based on clear evidence. Spectrochemical techniques are a powerful tool for cancer diagnostics. Raman hyperspectral imaging is able to generate spatially-distributed spectrochemical signatures with great sensitivity. Using this technique, 95 brain tissue samples (66 meningiomas WHO grade I, 24 meningiomas WHO grade II and 5 meningiomas that reoccurred) were analysed in order to discriminate grade I and grade II samples. Newly-developed three-dimensional discriminant analysis algorithms were used to process the hyperspectral imaging data in a 3D fashion. Three-dimensional principal component analysis quadratic discriminant analysis (3D-PCA-QDA) was able to distinguish grade I and grade II meningioma samples with 96% test accuracy (100% sensitivity and 95% specificity). This technique is here shown to be a high-throughput, reagent-free, non-destructive, and can give accurate predictive information regarding the meningioma tumour grade, hence, having enormous clinical potential with regards to being developed for intra-operative real-time assessment of disease.
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Affiliation(s)
- Taha Lilo
- Department of Neurosurgery, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, UK; School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK.
| | - Camilo L M Morais
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - Katherine M Ashton
- Department of Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, UK
| | - Charles Davis
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - Timothy P Dawson
- Department of Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, UK
| | | | - Jane Alder
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - Gareth Roberts
- Department of Neurosurgery, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, UK
| | - Arup Ray
- Department of Neurosurgery, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, UK
| | - Nihal Gurusinghe
- Department of Neurosurgery, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, UK
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Pangeni RP, Olivaries I, Huen D, Buzatto VC, Dawson TP, Ashton KM, Davis C, Brodbelt AR, Jenkinson MD, Bièche I, Yang L, Latif F, Darling JL, Warr TJ, Morris MR. Genome-wide methylation analyses identifies Non-coding RNA genes dysregulated in breast tumours that metastasise to the brain. Sci Rep 2022; 12:1102. [PMID: 35058523 PMCID: PMC8776809 DOI: 10.1038/s41598-022-05050-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 12/08/2021] [Indexed: 02/06/2023] Open
Abstract
Brain metastases comprise 40% of all metastatic tumours and breast tumours are among the tumours that most commonly metastasise to the brain, the role that epigenetic gene dysregulation plays in this process is not well understood. We carried out 450 K methylation array analysis to investigate epigenetically dysregulated genes in breast to brain metastases (BBM) compared to normal breast tissues (BN) and primary breast tumours (BP). For this, we referenced 450 K methylation data for BBM tumours prepared in our laboratory with BN and BP from The Cancer Genome Atlas. Experimental validation on our initially identified genes, in an independent cohort of BP and in BBM and their originating primary breast tumours using Combined Bisulphite and Restriction Analysis (CoBRA) and Methylation Specific PCR identified three genes (RP11-713P17.4, MIR124-2, NUS1P3) that are hypermethylated and three genes (MIR3193, CTD-2023M8.1 and MTND6P4) that are hypomethylated in breast to brain metastases. In addition, methylation differences in candidate genes between BBM tumours and originating primary tumours shows dysregulation of DNA methylation occurs either at an early stage of tumour evolution (in the primary tumour) or at a later evolutionary stage (where the epigenetic change is only observed in the brain metastasis). Epigentic changes identified could also be found when analysing tumour free circulating DNA (tfcDNA) in patient’s serum taken during BBM biopsies. Epigenetic dysregulation of RP11-713P17.4, MIR3193, MTND6P4 are early events suggesting a potential use for these genes as prognostic markers.
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Giamougiannis P, Morais CLM, Grabowska R, Ashton KM, Wood NJ, Martin-Hirsch PL, Martin FL. A comparative analysis of different biofluids towards ovarian cancer diagnosis using Raman microspectroscopy. Anal Bioanal Chem 2020; 413:911-922. [PMID: 33242117 PMCID: PMC7808972 DOI: 10.1007/s00216-020-03045-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Revised: 10/24/2020] [Accepted: 11/03/2020] [Indexed: 12/31/2022]
Abstract
Biofluids, such as blood plasma or serum, are currently being evaluated for cancer detection using vibrational spectroscopy. These fluids contain information of key biomolecules, such as proteins, lipids, carbohydrates and nucleic acids, that comprise spectrochemical patterns to differentiate samples. Raman is a water-free and practically non-destructive vibrational spectroscopy technique, capable of recording spectrochemical fingerprints of biofluids with minimum or no sample preparation. Herein, we compare the performance of these two common biofluids (blood plasma and serum) together with ascitic fluid, towards ovarian cancer detection using Raman microspectroscopy. Samples from thirty-eight patients were analysed (n = 18 ovarian cancer patients, n = 20 benign controls) through different spectral pre-processing and discriminant analysis techniques. Ascitic fluid provided the best class separation in both unsupervised and supervised discrimination approaches, where classification accuracies, sensitivities and specificities above 80% were obtained, in comparison to 60–73% with plasma or serum. Ascitic fluid appears to be rich in collagen information responsible for distinguishing ovarian cancer samples, where collagen-signalling bands at 1004 cm−1 (phenylalanine), 1334 cm−1 (CH3CH2 wagging vibration), 1448 cm−1 (CH2 deformation) and 1657 cm−1 (Amide I) exhibited high statistical significance for class differentiation (P < 0.001). The efficacy of vibrational spectroscopy, in particular Raman spectroscopy, combined with ascitic fluid analysis, suggests a potential diagnostic method for ovarian cancer. Raman microspectroscopy analysis of ascitic fluid allows for discrimination of patients with benign gynaecological conditions or ovarian cancer. ![]()
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Affiliation(s)
- Panagiotis Giamougiannis
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, PR2 9HT, UK.,School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK
| | - Camilo L M Morais
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK
| | - Rita Grabowska
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK
| | - Katherine M Ashton
- Department of Pathology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, PR2 9HT, UK
| | - Nicholas J Wood
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, PR2 9HT, UK
| | - Pierre L Martin-Hirsch
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, PR2 9HT, UK
| | - Francis L Martin
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK. .,Biocel Ltd, Hull, HU10 7TS, UK.
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Sala A, Spalding KE, Ashton KM, Board R, Butler HJ, Dawson TP, Harris DA, Hughes CS, Jenkins CA, Jenkinson MD, Palmer DS, Smith BR, Thornton CA, Baker MJ. Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and "digital drying". J Biophotonics 2020; 13:e202000118. [PMID: 32506784 DOI: 10.1002/jbio.202000118] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 05/28/2020] [Accepted: 05/30/2020] [Indexed: 06/11/2023]
Abstract
In recent years, the diagnosis of brain tumors has been investigated with attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy on dried human serum samples to eliminate spectral interferences of the water component, with promising results. This research evaluates ATR-FTIR on both liquid and air-dried samples to investigate "digital drying" as an alternative approach for the analysis of spectra obtained from liquid samples. Digital drying approaches, consisting of water subtraction and least-squares method, have demonstrated a greater random forest (RF) classification performance than the air-dried spectra approach when discriminating cancer vs control samples, reaching sensitivity values higher than 93.0% and specificity values higher than 83.0%. Moreover, quantum cascade laser infrared (QCL-IR) based spectroscopic imaging is utilized on liquid samples to assess the implications of a deep-penetration light source on disease classification. The RF classification of QCL-IR data has provided sensitivity and specificity amounting to 85.1% and 75.3% respectively.
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Affiliation(s)
- Alexandra Sala
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, Glasgow, UK
| | - Katie E Spalding
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, Glasgow, UK
| | - Katherine M Ashton
- Neuropathology, Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Preston, UK
| | - Ruth Board
- Rosemere Cancer Centre, Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Preston, UK
| | - Holly J Butler
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, Glasgow, UK
| | - Timothy P Dawson
- Neuropathology, Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Preston, UK
| | - Dean A Harris
- Swansea Bay University Local Health Board, Singleton Hospital, Swansea, UK
| | - Caryn S Hughes
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, Glasgow, UK
| | - Cerys A Jenkins
- Department of Physics, College of Science, Swansea University, Swansea, UK
| | - Michael D Jenkinson
- University of Liverpool & The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - David S Palmer
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow, UK
| | - Benjamin R Smith
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, Glasgow, UK
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow, UK
| | - Catherine A Thornton
- Institute of Life Science, Swansea University Medical School, Swansea University, Swansea, UK
| | - Matthew J Baker
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, Glasgow, UK
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Maitra I, Morais CLM, Lima KMG, Ashton KM, Date RS, Martin FL. Raman spectral discrimination in human liquid biopsies of oesophageal transformation to adenocarcinoma. J Biophotonics 2020; 13:e201960132. [PMID: 31794123 DOI: 10.1002/jbio.201960132] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 11/27/2019] [Accepted: 11/30/2019] [Indexed: 06/10/2023]
Abstract
The aim of this study was to determine whether Raman spectroscopy combined with chemometric analysis can be applied to interrogate biofluids (plasma, serum, saliva and urine) towards detecting oesophageal stages through to oesophageal adenocarcinoma [normal/squamous epithelium, inflammatory, Barrett's, low-grade dysplasia, high-grade dysplasia and oesophageal adenocarcinoma (OAC)]. The chemometric analysis of the spectral data was performed using principal component analysis, successive projections algorithm or genetic algorithm (GA) followed by quadratic discriminant analysis (QDA). The genetic algorithm quadratic discriminant analysis (GA-QDA) model using a few selected wavenumbers for saliva and urine samples achieved 100% classification for all classes. For plasma and serum, the GA-QDA model achieved excellent accuracy in all oesophageal stages (>90%). The main GA-QDA features responsible for sample discrimination were: 1012 cm-1 (C─O stretching of ribose), 1336 cm-1 (Amide III and CH2 wagging vibrations from glycine backbone), 1450 cm-1 (methylene deformation) and 1660 cm-1 (Amide I). The results of this study are promising and support the concept that Raman on biofluids may become a useful and objective diagnostic tool to identify oesophageal disease stages from squamous epithelium to OAC.
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Affiliation(s)
- Ishaan Maitra
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Camilo L M Morais
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Kássio M G Lima
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
- Biological Chemistry and Chemometrics, Institute of Chemistry, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Katherine M Ashton
- Lancashire Teaching Hospitals NHS Foundation Trust, Royal Preston Hospital, Preston, UK
| | - Ravindra S Date
- Lancashire Teaching Hospitals NHS Foundation Trust, Royal Preston Hospital, Preston, UK
| | - Francis L Martin
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
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7
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Lilo T, Morais CLM, Ashton KM, Pardilho A, Davis C, Dawson TP, Gurusinghe N, Martin FL. Spectrochemical differentiation of meningioma tumours based on attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy. Anal Bioanal Chem 2019; 412:1077-1086. [PMID: 31865413 PMCID: PMC7007428 DOI: 10.1007/s00216-019-02332-w] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 11/11/2019] [Accepted: 12/05/2019] [Indexed: 12/11/2022]
Abstract
Meningiomas are the commonest types of tumours in the central nervous system (CNS). It is a benign type of tumour divided into three WHO grades (I, II and III) associated with tumour growth rate and likelihood of recurrence, where surgical outcomes and patient treatments are dependent on the meningioma grade and histological subtype. The development of alternative approaches based on attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy could aid meningioma grade determination and its biospectrochemical profiling in an automated fashion. Herein, ATR-FTIR in combination with chemometric techniques is employed to distinguish grade I, grade II and grade I meningiomas that re-occurred. Ninety-nine patients were investigated in this study where their formalin-fixed paraffin-embedded (FFPE) brain tissue samples were analysed by ATR-FTIR spectroscopy. Subsequent classification was performed via principal component analysis plus linear discriminant analysis (PCA-LDA) and partial least squares plus discriminant analysis (PLS-DA). PLS-DA gave the best results where grade I and grade II meningiomas were discriminated with 79% accuracy, 80% sensitivity and 73% specificity, while grade I versus grade I recurrence and grade II versus grade I recurrence were discriminated with 94% accuracy (94% sensitivity and specificity) and 97% accuracy (97% sensitivity and 100% specificity), respectively. Several wavenumbers were identified as possible biomarkers towards tumour differentiation. The majority of these were associated with lipids, protein, DNA/RNA and carbohydrate alterations. These findings demonstrate the potential of ATR-FTIR spectroscopy towards meningioma grade discrimination as a fast, low-cost, non-destructive and sensitive tool for clinical settings. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy was used to discriminate meningioma WHO grade I, grade II and grade I recurrence tumours. ![]()
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Affiliation(s)
- Taha Lilo
- Department of Neurosurgery, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston, PR2 9HT, UK.,School of Pharmacy and Biomedical Sciences, UCLan, Preston, PR1 2HE, UK
| | - Camilo L M Morais
- School of Pharmacy and Biomedical Sciences, UCLan, Preston, PR1 2HE, UK
| | - Katherine M Ashton
- Department of Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston, PR2 9HT, UK
| | - Ana Pardilho
- Department of Neurosurgery, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston, PR2 9HT, UK
| | - Charles Davis
- School of Pharmacy and Biomedical Sciences, UCLan, Preston, PR1 2HE, UK
| | - Timothy P Dawson
- Department of Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston, PR2 9HT, UK
| | - Nihal Gurusinghe
- Department of Neurosurgery, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston, PR2 9HT, UK
| | - Francis L Martin
- School of Pharmacy and Biomedical Sciences, UCLan, Preston, PR1 2HE, UK.
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Bury D, Morais CLM, Martin FL, Lima KMG, Ashton KM, Baker MJ, Dawson TP. Discrimination of fresh frozen non-tumour and tumour brain tissue using spectrochemical analyses and a classification model. Br J Neurosurg 2019; 34:40-45. [PMID: 31642351 DOI: 10.1080/02688697.2019.1679352] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Introduction: In order for brain tumours to be successfully treated, maximal resection is beneficial. A method to detect infiltrative tumour edges intraoperatively, improving on current methods would be clinically useful. Vibrational spectroscopy offers the potential to provide a handheld, reagent-free method for tumour detection.Purpose: This study was designed to determine the ability of both Raman and Fourier-transform infrared (FTIR) spectroscopy towards differentiating between normal brain tissue, glioma or meningioma.Method: Unfixed brain tissue, which had previously only been frozen, comprising normal, glioma or meningioma tissue was placed onto calcium fluoride slides for analysis using Raman and attenuated total reflection (ATR)-FTIR spectroscopy. Matched haematoxylin and eosin slides were used to confirm tumour areas. Analyses were then conducted to generate a classification model.Results: This study demonstrates the ability of both Raman and ATR-FTIR spectroscopy to discriminate tumour from non-tumour fresh frozen brain tissue with 94% and 97.2% of cases correctly classified, with sensitivities of 98.8% and 100%, respectively. This decreases when spectroscopy is used to determine tumour type.Conclusion: The study demonstrates the ability of both Raman and ATR-FTIR spectroscopy to detect tumour tissue from non-tumour brain tissue with a high degree of accuracy. This demonstrates the ability of spectroscopy when targeted for a cancer diagnosis. However, further improvement would be required for a classification model to determine tumour type using this technology, in order to make this tool clinically viable.
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Affiliation(s)
- Danielle Bury
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Camilo L M Morais
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Francis L Martin
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Kássio M G Lima
- Biological Chemistry and Chemometrics, Institute of Chemistry, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Katherine M Ashton
- Department of Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston, UK
| | - Matthew J Baker
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, Glasgow, UK
| | - Timothy P Dawson
- Department of Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston, UK
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Bury D, Morais CLM, Ashton KM, Dawson TP, Martin FL. Ex Vivo Raman Spectrochemical Analysis Using a Handheld Probe Demonstrates High Predictive Capability of Brain Tumour Status. Biosensors (Basel) 2019; 9:E49. [PMID: 30934999 PMCID: PMC6627213 DOI: 10.3390/bios9020049] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Revised: 03/25/2019] [Accepted: 03/29/2019] [Indexed: 12/18/2022]
Abstract
With brain tumour incidence increasing, there is an urgent need for better diagnostic tools. Intraoperatively, brain tumours are diagnosed using a smear preparation reported by a neuropathologist. These have many limitations, including the time taken for the specimen to reach the pathology department and for results to be communicated to the surgeon. There is also a need to assist with resection rates and identifying infiltrative tumour edges intraoperatively to improve clearance. We present a novel study using a handheld Raman probe in conjunction with gold nanoparticles, to detect primary and metastatic brain tumours from fresh brain tissue sent for intraoperative smear diagnosis. Fresh brain tissue samples sent for intraoperative smear diagnosis were tested using the handheld Raman probe after application of gold nanoparticles. Derived Raman spectra were inputted into forward feature extraction algorithms to build a predictive model for sensitivity and specificity of outcome. These results demonstrate an ability to detect primary from metastatic tumours (especially for normal and low grade lesions), in which accuracy, sensitivity and specificity were respectively equal to 98.6%, 94.4% and 99.5% for normal brain tissue; 96.1%, 92.2% and 97.0% for low grade glial tumours; 90.3%, 89.7% and 90.6% for high grade glial tumours; 94.8%, 63.9% and 97.1% for meningiomas; 95.4%, 79.2% and 98.8% for metastases; and 99.6%, 88.9% and 100% for lymphoma, based on smear samples (κ = 0.87). Similar results were observed when compared to the final formalin-fixed paraffin embedded tissue diagnosis (κ = 0.85). Overall, our results have demonstrated the ability of Raman spectroscopy to match results provided by intraoperative smear diagnosis and raise the possibility of use intraoperatively to aid surgeons by providing faster diagnosis. Moving this technology into theatre will allow it to develop further and thus reach its potential in the clinical arena.
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Affiliation(s)
- Danielle Bury
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK.
| | - Camilo L M Morais
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK.
| | - Katherine M Ashton
- Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Sharoe Green Lane, Preston PR2 9HT, UK.
| | - Timothy P Dawson
- Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Sharoe Green Lane, Preston PR2 9HT, UK.
| | - Francis L Martin
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK.
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Paraskevaidi M, Morais CLM, Lima KMG, Ashton KM, Stringfellow HF, Martin-Hirsch PL, Martin FL. Potential of mid-infrared spectroscopy as a non-invasive diagnostic test in urine for endometrial or ovarian cancer. Analyst 2019; 143:3156-3163. [PMID: 29878018 DOI: 10.1039/c8an00027a] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The current lack of an accurate, cost-effective and non-invasive test that would allow for screening and diagnosis of gynaecological carcinomas, such as endometrial and ovarian cancer, signals the necessity for alternative approaches. The potential of spectroscopic techniques in disease investigation and diagnosis has been previously demonstrated. Here, we used attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy to analyse urine samples from women with endometrial (n = 10) and ovarian cancer (n = 10), as well as from healthy individuals (n = 10). After applying multivariate analysis and classification algorithms, biomarkers of disease were pointed out and high levels of accuracy were achieved for both endometrial (95% sensitivity, 100% specificity; accuracy: 95%) and ovarian cancer (100% sensitivity, 96.3% specificity; accuracy 100%). The efficacy of this approach, in combination with the non-invasive method for urine collection, suggest a potential diagnostic tool for endometrial and ovarian cancers.
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Affiliation(s)
- Maria Paraskevaidi
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK.
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Bury D, Morais CLM, Paraskevaidi M, Ashton KM, Dawson TP, Martin FL. Spectral classification for diagnosis involving numerous pathologies in a complex clinical setting: A neuro-oncology example. Spectrochim Acta A Mol Biomol Spectrosc 2019; 206:89-96. [PMID: 30086451 DOI: 10.1016/j.saa.2018.07.078] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Revised: 07/26/2018] [Accepted: 07/27/2018] [Indexed: 06/08/2023]
Abstract
Much effort is currently being placed into developing new blood tests for cancer diagnosis in the hope of moving cancer diagnosis earlier and by less invasive means than current techniques, e.g., biopsy. Current methods are expected to diagnose and begin treatment of cancer within 62 days of patient presentation, though due to high volume and pressures within the NHS in the UK any technique that can reduce time to diagnosis would allow reduction in the time to treat for patients. The use of vibrational spectroscopy, notably infrared (IR) spectroscopy, has been under investigation for many years with varying success. This technique holds promise as is would combine a generally well accepted test (a blood test) with analysis that is reagent free and cheap to run. It has been demonstrated that, when asked simple clinical questions (i.e., cancer vs. no cancer), results from spectroscopic studies are promising. However, in order to become a clinically useful tool, it is important that the test differentiates a variety of cancer types from healthy patients. This study has analysed plasma samples with attenuated total reflection Fourier-transform IR spectroscopy (ATR-FTIR), to establish if the technique is able to distinguish normal from primary or metastatic brain tumours. We have shown that when asked specific questions, i.e., high-grade glioma vs. low-grade glioma, the results show a significantly high accuracy (100%). Crucially, when combined with meningiomas and metastatic lesions, the accuracy remains high (88-100%) with only minimal overlap between the two metastatic adenocarcinoma groups. Therefore in a clinical setting, this novel technique demonstrates potential benefit when used in conjuction with existing diagnostic methods.
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Affiliation(s)
- Danielle Bury
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - Camilo L M Morais
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - Maria Paraskevaidi
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - Katherine M Ashton
- Department of Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, UK
| | - Timothy P Dawson
- Department of Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, UK
| | - Francis L Martin
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK.
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Maitra I, Morais CLM, Lima KMG, Ashton KM, Date RS, Martin FL. Attenuated total reflection Fourier-transform infrared spectral discrimination in human bodily fluids of oesophageal transformation to adenocarcinoma. Analyst 2019; 144:7447-7456. [DOI: 10.1039/c9an01749f] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) of biofluids was used to detect oesophageal stages through to oesophageal adenocarcinoma.
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Affiliation(s)
- Ishaan Maitra
- School of Pharmacy and Biomedical Sciences
- University of Central Lancashire
- Preston PR1 2HE
- UK
| | - Camilo L. M. Morais
- School of Pharmacy and Biomedical Sciences
- University of Central Lancashire
- Preston PR1 2HE
- UK
| | - Kássio M. G. Lima
- School of Pharmacy and Biomedical Sciences
- University of Central Lancashire
- Preston PR1 2HE
- UK
- Institute of Chemistry
| | - Katherine M. Ashton
- Lancashire Teaching Hospitals NHS Foundation Trust
- Royal Preston Hospital
- Preston PR2 9HT
- UK
| | - Ravindra S. Date
- Lancashire Teaching Hospitals NHS Foundation Trust
- Royal Preston Hospital
- Preston PR2 9HT
- UK
| | - Francis L. Martin
- School of Pharmacy and Biomedical Sciences
- University of Central Lancashire
- Preston PR1 2HE
- UK
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13
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Morais CLM, Lilo T, Ashton KM, Davis C, Dawson TP, Gurusinghe N, Martin FL. Determination of meningioma brain tumour grades using Raman microspectroscopy imaging. Analyst 2019; 144:7024-7031. [DOI: 10.1039/c9an01551e] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Raman microspectroscopy imaging was used to distinguish 90 brain tissue samples into meningiomas Grade I and Grade II.
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Affiliation(s)
- Camilo L. M. Morais
- School of Pharmacy and Biomedical Sciences
- University of Central Lancashire
- Preston PR1 2HE
- UK
| | - Taha Lilo
- School of Pharmacy and Biomedical Sciences
- University of Central Lancashire
- Preston PR1 2HE
- UK
- Neurosurgery
| | - Katherine M. Ashton
- Neuropathology
- Royal Preston Hospital
- Lancashire Teaching Hospitals NHS Trust
- Preston PR2 9HT
- UK
| | - Charles Davis
- School of Pharmacy and Biomedical Sciences
- University of Central Lancashire
- Preston PR1 2HE
- UK
| | - Timothy P. Dawson
- Neuropathology
- Royal Preston Hospital
- Lancashire Teaching Hospitals NHS Trust
- Preston PR2 9HT
- UK
| | - Nihal Gurusinghe
- Neurosurgery
- Royal Preston Hospital
- Lancashire Teaching Hospitals NHS Trust
- Preston PR2 9HT
- UK
| | - Francis L. Martin
- School of Pharmacy and Biomedical Sciences
- University of Central Lancashire
- Preston PR1 2HE
- UK
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14
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Smith BR, Ashton KM, Brodbelt A, Dawson T, Jenkinson MD, Hunt NT, Palmer DS, Baker MJ. Combining random forest and 2D correlation analysis to identify serum spectral signatures for neuro-oncology. Analyst 2018; 141:3668-78. [PMID: 26818218 DOI: 10.1039/c5an02452h] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Fourier transform infrared (FTIR) spectroscopy has long been established as an analytical technique for the measurement of vibrational modes of molecular systems. More recently, FTIR has been used for the analysis of biofluids with the aim of becoming a tool to aid diagnosis. For the clinician, this represents a convenient, fast, non-subjective option for the study of biofluids and the diagnosis of disease states. The patient also benefits from this method, as the procedure for the collection of serum is much less invasive and stressful than traditional biopsy. This is especially true of patients in whom brain cancer is suspected. A brain biopsy is very unpleasant for the patient, potentially dangerous and can occasionally be inconclusive. We therefore present a method for the diagnosis of brain cancer from serum samples using FTIR and machine learning techniques. The scope of the study involved 433 patients from whom were collected 9 spectra each in the range 600-4000 cm(-1). To begin the development of the novel method, various pre-processing steps were investigated and ranked in terms of final accuracy of the diagnosis. Random forest machine learning was utilised as a classifier to separate patients into cancer or non-cancer categories based upon the intensities of wavenumbers present in their spectra. Generalised 2D correlational analysis was then employed to further augment the machine learning, and also to establish spectral features important for the distinction between cancer and non-cancer serum samples. Using these methods, sensitivities of up to 92.8% and specificities of up to 91.5% were possible. Furthermore, ratiometrics were also investigated in order to establish any correlations present in the dataset. We show a rapid, computationally light, accurate, statistically robust methodology for the identification of spectral features present in differing disease states. With current advances in IR technology, such as the development of rapid discrete frequency collection, this approach is of importance to enable future clinical translation and enables IR to achieve its potential.
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Affiliation(s)
- Benjamin R Smith
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, 295 Cathedral Street, Glasgow, Scotland G1 1XL, UK. and WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow G1 1RD, UK.
| | - Katherine M Ashton
- Neuropathology, Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane, Fulwood, Preston, PR2 9HT, UK
| | - Andrew Brodbelt
- Neurosurgery, The Walton Centre NHS Foundation Trust, Lower Lane, Fazakerley, Liverpool, L9 7LJ, UK
| | - Timothy Dawson
- Neuropathology, Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane, Fulwood, Preston, PR2 9HT, UK
| | - Michael D Jenkinson
- Neurosurgery, The Walton Centre NHS Foundation Trust, Lower Lane, Fazakerley, Liverpool, L9 7LJ, UK
| | - Neil T Hunt
- SUPA, Department of Physics, University of Strathclyde, 107 Rottenrow East, Glasgow, G4 0NG, UK
| | - David S Palmer
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, 295 Cathedral Street, Glasgow, Scotland G1 1XL, UK.
| | - Matthew J Baker
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow G1 1RD, UK.
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Bury D, Faust G, Paraskevaidi M, Ashton KM, Dawson TP, Martin FL. Phenotyping Metastatic Brain Tumors Applying Spectrochemical Analyses: Segregation of Different Cancer Types. ANAL LETT 2018. [DOI: 10.1080/00032719.2018.1479412] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Danielle Bury
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Guy Faust
- Department of Oncology, University Hospitals of Leicester NHS Trust, Leicester, Leicestershire, UK
| | - Maria Paraskevaidi
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Katherine M. Ashton
- Department of Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston, UK
| | - Timothy P. Dawson
- Department of Neuropathology, Royal Preston Hospital, Lancashire Teaching Hospitals NHS Trust, Preston, UK
| | - Francis L. Martin
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
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Stables R, Clemens G, Butler HJ, Ashton KM, Brodbelt A, Dawson TP, Fullwood LM, Jenkinson MD, Baker MJ. Feature driven classification of Raman spectra for real-time spectral brain tumour diagnosis using sound. Analyst 2018; 142:98-109. [PMID: 27757448 DOI: 10.1039/c6an01583b] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Spectroscopic diagnostics have been shown to be an effective tool for the analysis and discrimination of disease states from human tissue. Furthermore, Raman spectroscopic probes are of particular interest as they allow for in vivo spectroscopic diagnostics, for tasks such as the identification of tumour margins during surgery. In this study, we investigate a feature-driven approach to the classification of metastatic brain cancer, glioblastoma (GB) and non-cancer from tissue samples, and we provide a real-time feedback method for endoscopic diagnostics using sound. To do this, we first evaluate the sensitivity and specificity of three classifiers (SVM, KNN and LDA), when trained with both sub-band spectral features and principal components taken directly from Raman spectra. We demonstrate that the feature extraction approach provides an increase in classification accuracy of 26.25% for SVM and 25% for KNN. We then discuss the molecular assignment of the most salient sub-bands in the dataset. The most salient sub-band features are mapped to parameters of a frequency modulation (FM) synthesizer in order to generate audio clips from each tissue sample. Based on the properties of the sub-band features, the synthesizer was able to maintain similar sound timbres within the disease classes and provide different timbres between disease classes. This was reinforced via listening tests, in which participants were able to discriminate between classes with mean classification accuracy of 71.1%. Providing intuitive feedback via sound frees the surgeons' visual attention to remain on the patient, allowing for greater control over diagnostic and surgical tools during surgery, and thus promoting clinical translation of spectroscopic diagnostics.
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Affiliation(s)
- Ryan Stables
- Digital Media Technology Laboratory, Millennium Point, City Centre Campus Birmingham City University, West Midlands, B47XG, UK
| | - Graeme Clemens
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G11RD, UK. Twitter:@ChemistryBaker and Centre for Materials Science, Division of Chemistry, University of Central Lancashire, Preston, PR12HE, UK
| | - Holly J Butler
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G11RD, UK. Twitter:@ChemistryBaker
| | - Katherine M Ashton
- Neuropathology, Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane North, Preston, PR29HT, UK
| | - Andrew Brodbelt
- Neuropathology, Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane North, Preston, PR29HT, UK
| | - Timothy P Dawson
- Neuropathology, Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane North, Preston, PR29HT, UK
| | - Leanne M Fullwood
- Centre for Materials Science, Division of Chemistry, University of Central Lancashire, Preston, PR12HE, UK
| | - Michael D Jenkinson
- The Walton Centre for Neurology and Neurosurgery, The Walton Centre NHS Trust, Lower Lane, Liverpool, L97LJ, UK
| | - Matthew J Baker
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G11RD, UK. Twitter:@ChemistryBaker
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Hands JR, Clemens G, Lea RW, Ashton KM, Dawson TP, Jenkinson MD, Brodbelt A, Davis C, Stables R, Baker MJ. OP19DEVELOPING STRATIFIED SERUM SPECTROSCOPIC DIAGNOSTICS FOR BRAIN TUMOURS: FINDING THE FEATURES. Neuro Oncol 2015. [DOI: 10.1093/neuonc/nov283.19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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18
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Pangeni RP, Channathodiyil P, Huen DS, Eagles LW, Johal BK, Pasha D, Hadjistephanou N, Nevell O, Davies CL, Adewumi AI, Khanom H, Samra IS, Buzatto VC, Chandrasekaran P, Shinawi T, Dawson TP, Ashton KM, Davis C, Brodbelt AR, Jenkinson MD, Bièche I, Latif F, Darling JL, Warr TJ, Morris MR. The GALNT9, BNC1 and CCDC8 genes are frequently epigenetically dysregulated in breast tumours that metastasise to the brain. Clin Epigenetics 2015; 7:57. [PMID: 26052355 PMCID: PMC4457099 DOI: 10.1186/s13148-015-0089-x] [Citation(s) in RCA: 68] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2014] [Accepted: 05/11/2015] [Indexed: 01/12/2023] Open
Abstract
Background Tumour metastasis to the brain is a common and deadly development in certain cancers; 18–30 % of breast tumours metastasise to the brain. The contribution that gene silencing through epigenetic mechanisms plays in these metastatic tumours is not well understood. Results We have carried out a bioinformatic screen of genome-wide breast tumour methylation data available at The Cancer Genome Atlas (TCGA) and a broad literature review to identify candidate genes that may contribute to breast to brain metastasis (BBM). This analysis identified 82 candidates. We investigated the methylation status of these genes using Combined Bisulfite and Restriction Analysis (CoBRA) and identified 21 genes frequently methylated in BBM. We have identified three genes, GALNT9, CCDC8 and BNC1, that were frequently methylated (55, 73 and 71 %, respectively) and silenced in BBM and infrequently methylated in primary breast tumours. CCDC8 was commonly methylated in brain metastases and their associated primary tumours whereas GALNT9 and BNC1 were methylated and silenced only in brain metastases, but not in the associated primary breast tumours from individual patients. This suggests differing roles for these genes in the evolution of metastatic tumours; CCDC8 methylation occurs at an early stage of metastatic evolution whereas methylation of GANLT9 and BNC1 occurs at a later stage of tumour evolution. Knockdown of these genes by RNAi resulted in a significant increase in the migratory and invasive potential of breast cancer cell lines. Conclusions These findings indicate that GALNT9 (an initiator of O-glycosylation), CCDC8 (a regulator of microtubule dynamics) and BNC1 (a transcription factor with a broad range of targets) may play a role in the progression of primary breast tumours to brain metastases. These genes may be useful as prognostic markers and their products may provide novel therapeutic targets. Electronic supplementary material The online version of this article (doi:10.1186/s13148-015-0089-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Rajendra P Pangeni
- Brain Tumour Research Centre, University of Wolverhampton, Wolverhampton, UK
| | | | - David S Huen
- School of Biology, Chemistry and Forensic Sciences, University of Wolverhampton, Wolverhampton, UK
| | - Lawrence W Eagles
- Brain Tumour Research Centre, University of Wolverhampton, Wolverhampton, UK
| | - Balraj K Johal
- School of Biology, Chemistry and Forensic Sciences, University of Wolverhampton, Wolverhampton, UK
| | - Dawar Pasha
- School of Biology, Chemistry and Forensic Sciences, University of Wolverhampton, Wolverhampton, UK
| | - Natasa Hadjistephanou
- School of Biology, Chemistry and Forensic Sciences, University of Wolverhampton, Wolverhampton, UK
| | - Oliver Nevell
- School of Biology, Chemistry and Forensic Sciences, University of Wolverhampton, Wolverhampton, UK
| | - Claire L Davies
- School of Biology, Chemistry and Forensic Sciences, University of Wolverhampton, Wolverhampton, UK
| | - Ayobami I Adewumi
- School of Biology, Chemistry and Forensic Sciences, University of Wolverhampton, Wolverhampton, UK
| | - Hamida Khanom
- School of Biology, Chemistry and Forensic Sciences, University of Wolverhampton, Wolverhampton, UK
| | - Ikroop S Samra
- School of Biology, Chemistry and Forensic Sciences, University of Wolverhampton, Wolverhampton, UK
| | - Vanessa C Buzatto
- School of Biology, Chemistry and Forensic Sciences, University of Wolverhampton, Wolverhampton, UK
| | - Preethi Chandrasekaran
- School of Biology, Chemistry and Forensic Sciences, University of Wolverhampton, Wolverhampton, UK
| | - Thoraia Shinawi
- Centre for Rare Diseases and Personalised Medicine, School of Clinical and Experimental Medicine, University of Birmingham, Birmingham, UK
| | - Timothy P Dawson
- Department of Neurosciences, Lancashire Teaching Hospitals NHS Foundation Trust, Royal Preston Hospital, Fulwood, Preston, UK
| | - Katherine M Ashton
- Department of Neurosciences, Lancashire Teaching Hospitals NHS Foundation Trust, Royal Preston Hospital, Fulwood, Preston, UK
| | - Charles Davis
- Department of Neurosciences, Lancashire Teaching Hospitals NHS Foundation Trust, Royal Preston Hospital, Fulwood, Preston, UK
| | | | | | - Ivan Bièche
- Department of Genetics, Institute Curie, Paris, France
| | - Farida Latif
- Centre for Rare Diseases and Personalised Medicine, School of Clinical and Experimental Medicine, University of Birmingham, Birmingham, UK
| | - John L Darling
- Brain Tumour Research Centre, University of Wolverhampton, Wolverhampton, UK
| | - Tracy J Warr
- Brain Tumour Research Centre, University of Wolverhampton, Wolverhampton, UK
| | - Mark R Morris
- Brain Tumour Research Centre, University of Wolverhampton, Wolverhampton, UK ; School of Biology, Chemistry and Forensic Sciences, University of Wolverhampton, Wolverhampton, UK ; Centre for Rare Diseases and Personalised Medicine, School of Clinical and Experimental Medicine, University of Birmingham, Birmingham, UK
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Hands JR, Dorling KM, Abel P, Ashton KM, Brodbelt A, Davis C, Dawson T, Jenkinson MD, Lea RW, Walker C, Baker MJ. Attenuated total reflection fourier transform infrared (ATR-FTIR) spectral discrimination of brain tumour severity from serum samples. J Biophotonics 2014; 7:189-199. [PMID: 24395599 DOI: 10.1002/jbio.201300149] [Citation(s) in RCA: 83] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2013] [Revised: 11/06/2013] [Accepted: 11/28/2013] [Indexed: 06/03/2023]
Abstract
Gliomas are the most frequent primary brain tumours in adults with over 9,000 people diagnosed each year in the UK. A rapid, reagent-free and cost-effective diagnostic regime using serum spectroscopy would allow for rapid diagnostic results and for swift treatment planning and monitoring within the clinical environment. We report the use of ATR-FTIR spectral data combined with a RBF-SVM for the diagnosis of gliomas (high-grade and low-grade) from non-cancer with sensitivities and specificities on average of 93.75 and 96.53% respectively. The proposed diagnostic regime has the ability to reduce mortality and morbidity rates.
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Affiliation(s)
- James R Hands
- Centre for Materials Science, Division of Chemistry, JB Firth Building, University of Central Lancashire, Preston, PR1 2HE, UK
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Gajjar K, Heppenstall LD, Pang W, Ashton KM, Trevisan J, Patel II, Llabjani V, Stringfellow HF, Martin-Hirsch PL, Dawson T, Martin FL. Diagnostic segregation of human brain tumours using Fourier-transform infrared and/or Raman spectroscopy coupled with discriminant analysis. Anal Methods 2012; 5:89-102. [PMID: 24098310 PMCID: PMC3789135 DOI: 10.1039/c2ay25544h] [Citation(s) in RCA: 105] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
The most common initial treatment received by patients with a brain tumour is surgical removal of the growth. Precise histopathological diagnosis of brain tumours is to some extent subjective. Furthermore, currently available diagnostic imaging techniques to delineate the excision border during cytoreductive surgery lack the required spatial precision to aid surgeons. We set out to determine whether infrared (IR) and/or Raman spectroscopy combined with multivariate analysis could be applied to discriminate between normal brain tissue and different tumour types (meningioma, glioma and brain metastasis) based on the unique spectral "fingerprints" of their biochemical composition. Formalin-fixed paraffin-embedded tissue blocks of normal brain and different brain tumours were de-waxed, mounted on low-E slides and desiccated before being analyzed using attenuated total reflection Fourier-transform IR (ATR-FTIR) and Raman spectroscopy. ATR-FTIR spectroscopy showed a clear segregation between normal and different tumour subtypes. Discrimination of tumour classes was also apparent with Raman spectroscopy. Further analysis of spectral data revealed changes in brain biochemical structure associated with different tumours. Decreased tentatively-assigned lipid-to-protein ratio was associated with increased tumour progression. Alteration in cholesterol esters-to-phenylalanine ratio was evident in grade IV glioma and metastatic tumours. The current study indicates that IR and/or Raman spectroscopy have the potential to provide a novel diagnostic approach in the accurate diagnosis of brain tumours and have potential for application in intra-operative diagnosis.
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Affiliation(s)
- Ketan Gajjar
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
- Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane North, Preston, Lancashire, UK
| | - Lara D. Heppenstall
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
| | - Weiyi Pang
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
| | - Katherine M. Ashton
- Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane North, Preston, Lancashire, UK
| | - Júlio Trevisan
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
| | - Imran I. Patel
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
| | - Valon Llabjani
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
| | - Helen F. Stringfellow
- Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane North, Preston, Lancashire, UK
| | - Pierre L. Martin-Hirsch
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
- Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane North, Preston, Lancashire, UK
| | - Timothy Dawson
- Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane North, Preston, Lancashire, UK
| | - Francis L. Martin
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
- ; Tel: +44 (0)1524 510206
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21
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Taylor SE, Cheung KT, Patel II, Trevisan J, Stringfellow HF, Ashton KM, Wood NJ, Keating PJ, Martin-Hirsch PL, Martin FL. Infrared spectroscopy with multivariate analysis to interrogate endometrial tissue: a novel and objective diagnostic approach. Br J Cancer 2011; 104:790-7. [PMID: 21326237 PMCID: PMC3048205 DOI: 10.1038/sj.bjc.6606094] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Endometrial cancer is the most common gynaecological malignancy in the United Kingdom. Diagnosis currently involves subjective expert interpretation of highly processed tissue, primarily using microscopy. Previous work has shown that infrared (IR) spectroscopy can be used to distinguish between benign and malignant cells in a variety of tissue types. METHODS Tissue was obtained from 76 patients undergoing hysterectomy, 36 had endometrial cancer. Slivers of endometrial tissue (tumour and tumour-adjacent tissue if present) were dissected and placed in fixative solution. Before analysis, tissues were thinly sliced, washed, mounted on low-E slides and desiccated; 10 IR spectra were obtained per slice by attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy. Derived data was subjected to principal component analysis followed by linear discriminant analysis. Post-spectroscopy analyses, tissue sections were haematoxylin and eosin-stained to provide histological verification. RESULTS Using this approach, it is possible to distinguish benign from malignant endometrial tissue, and various subtypes of both. Cluster vector plots of benign (verified post-spectroscopy to be free of identifiable pathology) vs malignant tissue indicate the importance of the lipid and secondary protein structure (Amide I and Amide II) regions of the spectrum. CONCLUSION These findings point towards the possibility of a simple objective test for endometrial cancer using ATR-FTIR spectroscopy. This would facilitate earlier diagnosis and so reduce the morbidity and mortality associated with this disease.
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Affiliation(s)
- S E Taylor
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Bailrigg, Lancaster LA1 4YQ, UK.
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Cheung KT, Trevisan J, Kelly JG, Ashton KM, Stringfellow HF, Taylor SE, Singh MN, Martin-Hirsch PL, Martin FL. Fourier-transform infrared spectroscopy discriminates a spectral signature of endometriosis independent of inter-individual variation. Analyst 2011; 136:2047-55. [DOI: 10.1039/c0an00972e] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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Kelly JG, Singh MN, Stringfellow HF, Walsh MJ, Nicholson JM, Bahrami F, Ashton KM, Pitt MA, Martin-Hirsch PL, Martin FL. Derivation of a subtype-specific biochemical signature of endometrial carcinoma using synchrotron-based Fourier-transform infrared microspectroscopy. Cancer Lett 2009; 274:208-17. [DOI: 10.1016/j.canlet.2008.09.018] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2008] [Revised: 07/19/2008] [Accepted: 09/10/2008] [Indexed: 11/16/2022]
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Ragavan N, Hewitt R, Cooper LJ, Ashton KM, Hindley AC, Nicholson CM, Fullwood NJ, Matanhelia SS, Martin FL. CYP1B1 expression in prostate is higher in the peripheral than in the transition zone. Cancer Lett 2004; 215:69-78. [PMID: 15374634 DOI: 10.1016/j.canlet.2004.06.051] [Citation(s) in RCA: 49] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2004] [Revised: 06/27/2004] [Accepted: 06/29/2004] [Indexed: 11/19/2022]
Abstract
Prostate cancer (CaP) mostly occurs in the peripheral zone whereas benign prostatic hypertrophy (BPH) occurs in the transition zone. Human prostates (n = 12) were obtained, with ethical approval, from radical retropubic prostatectomies. Following resection, tissue sets consisting of peripheral zone and transition zone were isolated from a lobe pre-operatively identified as negative for CaP. Real-time RT-PCR was employed to quantitatively examine CYP1A1, CYP1A2 and CYP1B1. Quantifiable CYP1A1 expression was observed (in nine out of twelve tissue sets) whilst CYP1A2 mRNA transcripts, although detectable (in six out of twelve tissue sets), were unquantifiable. In ten tissue sets, 2- to 6-fold higher CYP1B1 expression in peripheral zone as compared to transition zone was observed. In the other two, equal CYP1B1 expression levels were observed; retrospective examination identified malignancy in one of the zones. Inter-individual variations (up to 10-fold) in CYP1B1 were also noted. Immunohistochemistry for CYP1B1 showed epithelial and stromal nuclear staining. Since CYP1B1 metabolises hormones and carcinogens our results, if confirmed, suggest that this enzyme may influence susceptibility to CaP.
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Affiliation(s)
- Narasimhan Ragavan
- Department of Biological Sciences, IENS, Lancaster University, Lancaster LA1 4YQ, UK
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