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Raghunathan R, Vasquez M, Zhang K, Zhao H, Wong STC. Label-free optical imaging for brain cancer assessment. Trends Cancer 2024:S2405-8033(24)00054-2. [PMID: 38575412 DOI: 10.1016/j.trecan.2024.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Revised: 03/12/2024] [Accepted: 03/13/2024] [Indexed: 04/06/2024]
Abstract
Advances in label-free optical imaging offer a promising avenue for brain cancer assessment, providing high-resolution, real-time insights without the need for radiation or exogeneous agents. These cost-effective and intricately detailed techniques overcome the limitations inherent in magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) scans by offering superior resolution and more readily accessible imaging options. This comprehensive review explores a variety of such methods, including photoacoustic imaging (PAI), optical coherence tomography (OCT), Raman imaging, and IR microscopy. It focuses on their roles in the detection, diagnosis, and management of brain tumors. By highlighting recent advances in these imaging techniques, the review aims to underscore the importance of label-free optical imaging in enhancing early detection and refining therapeutic strategies for brain cancer.
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Affiliation(s)
- Raksha Raghunathan
- Department of Systems Medicine and Bioengineering and T.T. and W.F. Chao Center for BRAIN, Houston Methodist Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA; Advanced Cellular and Tissue Microscopy Core, Houston Methodist Neal Cancer Center and Houston Methodist Research Institute, Houston, TX 77030, USA
| | - Matthew Vasquez
- Department of Systems Medicine and Bioengineering and T.T. and W.F. Chao Center for BRAIN, Houston Methodist Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA; Advanced Cellular and Tissue Microscopy Core, Houston Methodist Neal Cancer Center and Houston Methodist Research Institute, Houston, TX 77030, USA
| | - Katherine Zhang
- Department of Systems Medicine and Bioengineering and T.T. and W.F. Chao Center for BRAIN, Houston Methodist Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA; Advanced Cellular and Tissue Microscopy Core, Houston Methodist Neal Cancer Center and Houston Methodist Research Institute, Houston, TX 77030, USA
| | - Hong Zhao
- Department of Systems Medicine and Bioengineering and T.T. and W.F. Chao Center for BRAIN, Houston Methodist Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA; Advanced Cellular and Tissue Microscopy Core, Houston Methodist Neal Cancer Center and Houston Methodist Research Institute, Houston, TX 77030, USA; Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA.
| | - Stephen T C Wong
- Department of Systems Medicine and Bioengineering and T.T. and W.F. Chao Center for BRAIN, Houston Methodist Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA; Advanced Cellular and Tissue Microscopy Core, Houston Methodist Neal Cancer Center and Houston Methodist Research Institute, Houston, TX 77030, USA; Departments of Radiology, Pathology, and Laboratory Medicine and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10065, USA
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Tugrul F, Akin Geyik G, Yalinbaş Kaya B, Peker Cengiz B, Karuk Elmas SN, Yilmaz I, Arslan FN. A biospectroscopic approach toward colorectal cancer diagnosis from bodily fluid samples via ATR-MIR spectroscopy combined with multivariate data analysis. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 304:123342. [PMID: 37688884 DOI: 10.1016/j.saa.2023.123342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 08/31/2023] [Accepted: 09/01/2023] [Indexed: 09/11/2023]
Abstract
In this study, a biospectroscopic approach was reported for the detection of spectral changes and biomarkers for the diagnosis of colorectal cancer (CC) cases from different bodily fluids (blood plasma, blood serum, saliva and colonoscopy disinfection/wash fluids) by using attenuated total reflection-mid infrared (ATR-MIR) spectroscopy. To recognize the molecular level changes in the spectral characteristics of CC and their healthy/control (CH) groups, different multivariate data analyses (HCA, LDA, PCA and SIMCA) were successfully performed over the data of ATR-MIR spectroscopy. Two hundred specimens were characterized in detail over the data of spectral regions (4000-650 cm-1 and regions V-XXII). The findings revealed that significant changes were clearly observed in the concentrations of lipid, protein, nucleic acid and carbohydrate biomolecules for cancer cases based upon their necessity to overcome energy requirements. Supervised multivariate data methodology SIMCA, presented an excellent classification for the studied groups; similarly 100% of the specimens from different bodily fluids were correctly classified by supervised methodology LDA. As a result, the developed ATR-MIR methodology for the classification of CC and their healthy groups highlighted a rapid cancer diagnosis approach from different bodily fluids; therefore, it could be guide to make well decision before histopathological assessment and to screen CC populations existing in society.
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Affiliation(s)
- Fuzuli Tugrul
- Eskişehir City Hospital, Clinic of Radiation Oncology, 26080 Eskisehir, Turkey
| | - Gonul Akin Geyik
- Karamanoglu Mehmetbey University, K.O. Science Faculty, Department of Chemistry, 70100 Karaman, Turkey
| | | | - Betul Peker Cengiz
- Eskişehir Yunus Emre State Hospital, Clinic of Medical Pathology, 26190 Eskisehir, Turkey
| | - Sukriye Nihan Karuk Elmas
- Karamanoglu Mehmetbey University, K.O. Science Faculty, Department of Chemistry, 70100 Karaman, Turkey; Istanbul University-Cerrahpaşa, Pharmacy Faculty, Department of Analytical Chemistry, 34500 Istanbul, Turkey
| | - Ibrahim Yilmaz
- Karamanoglu Mehmetbey University, K.O. Science Faculty, Department of Chemistry, 70100 Karaman, Turkey.
| | - Fatma Nur Arslan
- Karamanoglu Mehmetbey University, K.O. Science Faculty, Department of Chemistry, 70100 Karaman, Turkey.
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Bassler MC, Knoblich M, Gerhard-Hartmann E, Mukherjee A, Youssef A, Hagen R, Haug L, Goncalves M, Scherzad A, Stöth M, Ostertag E, Steinke M, Brecht M, Hackenberg S, Meyer TJ. Differentiation of Salivary Gland and Salivary Gland Tumor Tissue via Raman Imaging Combined with Multivariate Data Analysis. Diagnostics (Basel) 2023; 14:92. [PMID: 38201401 PMCID: PMC10795677 DOI: 10.3390/diagnostics14010092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 12/10/2023] [Accepted: 12/29/2023] [Indexed: 01/12/2024] Open
Abstract
Salivary gland tumors (SGTs) are a relevant, highly diverse subgroup of head and neck tumors whose entity determination can be difficult. Confocal Raman imaging in combination with multivariate data analysis may possibly support their correct classification. For the analysis of the translational potential of Raman imaging in SGT determination, a multi-stage evaluation process is necessary. By measuring a sample set of Warthin tumor, pleomorphic adenoma and non-tumor salivary gland tissue, Raman data were obtained and a thorough Raman band analysis was performed. This evaluation revealed highly overlapping Raman patterns with only minor spectral differences. Consequently, a principal component analysis (PCA) was calculated and further combined with a discriminant analysis (DA) to enable the best possible distinction. The PCA-DA model was characterized by accuracy, sensitivity, selectivity and precision values above 90% and validated by predicting model-unknown Raman spectra, of which 93% were classified correctly. Thus, we state our PCA-DA to be suitable for parotid tumor and non-salivary salivary gland tissue discrimination and prediction. For evaluation of the translational potential, further validation steps are necessary.
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Affiliation(s)
- Miriam C. Bassler
- Process Analysis and Technology (PA&T), School of Life Science, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany; (M.C.B.); (M.K.); (A.M.); (E.O.)
- Institute of Physical and Theoretical Chemistry, Faculty of Science, University of Tübingen, Auf der Morgenstelle 18, 72076 Tübingen, Germany
| | - Mona Knoblich
- Process Analysis and Technology (PA&T), School of Life Science, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany; (M.C.B.); (M.K.); (A.M.); (E.O.)
- Institute of Physical and Theoretical Chemistry, Faculty of Science, University of Tübingen, Auf der Morgenstelle 18, 72076 Tübingen, Germany
| | - Elena Gerhard-Hartmann
- Institute of Pathology, University of Würzburg, Josef-Schneider-Str. 2, 97080 Würzburg, Germany; (E.G.-H.); (A.Y.); (L.H.)
| | - Ashutosh Mukherjee
- Process Analysis and Technology (PA&T), School of Life Science, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany; (M.C.B.); (M.K.); (A.M.); (E.O.)
- Institute of Physical and Theoretical Chemistry, Faculty of Science, University of Tübingen, Auf der Morgenstelle 18, 72076 Tübingen, Germany
| | - Almoatazbellah Youssef
- Institute of Pathology, University of Würzburg, Josef-Schneider-Str. 2, 97080 Würzburg, Germany; (E.G.-H.); (A.Y.); (L.H.)
| | - Rudolf Hagen
- Department of Oto-Rhino-Laryngology, Plastic, Aesthetic & Reconstructive Head and Neck Surgery, University Hospital Würzburg, Josef-Schneider-Str. 11, 97080 Würzburg, Germany; (R.H.); (M.G.); (A.S.); (M.S.); (S.H.)
| | - Lukas Haug
- Institute of Pathology, University of Würzburg, Josef-Schneider-Str. 2, 97080 Würzburg, Germany; (E.G.-H.); (A.Y.); (L.H.)
| | - Miguel Goncalves
- Department of Oto-Rhino-Laryngology, Plastic, Aesthetic & Reconstructive Head and Neck Surgery, University Hospital Würzburg, Josef-Schneider-Str. 11, 97080 Würzburg, Germany; (R.H.); (M.G.); (A.S.); (M.S.); (S.H.)
| | - Agmal Scherzad
- Department of Oto-Rhino-Laryngology, Plastic, Aesthetic & Reconstructive Head and Neck Surgery, University Hospital Würzburg, Josef-Schneider-Str. 11, 97080 Würzburg, Germany; (R.H.); (M.G.); (A.S.); (M.S.); (S.H.)
| | - Manuel Stöth
- Department of Oto-Rhino-Laryngology, Plastic, Aesthetic & Reconstructive Head and Neck Surgery, University Hospital Würzburg, Josef-Schneider-Str. 11, 97080 Würzburg, Germany; (R.H.); (M.G.); (A.S.); (M.S.); (S.H.)
| | - Edwin Ostertag
- Process Analysis and Technology (PA&T), School of Life Science, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany; (M.C.B.); (M.K.); (A.M.); (E.O.)
| | - Maria Steinke
- Chair of Tissue Engineering and Regenerative Medicine, University Hospital Würzburg, Röntgenring 11, 97070 Würzburg, Germany;
- Fraunhofer Institute for Silicate Research ISC, Röntgenring 11, 97070 Würzburg, Germany
| | - Marc Brecht
- Process Analysis and Technology (PA&T), School of Life Science, Reutlingen University, Alteburgstr. 150, 72762 Reutlingen, Germany; (M.C.B.); (M.K.); (A.M.); (E.O.)
- Institute of Physical and Theoretical Chemistry, Faculty of Science, University of Tübingen, Auf der Morgenstelle 18, 72076 Tübingen, Germany
| | - Stephan Hackenberg
- Department of Oto-Rhino-Laryngology, Plastic, Aesthetic & Reconstructive Head and Neck Surgery, University Hospital Würzburg, Josef-Schneider-Str. 11, 97080 Würzburg, Germany; (R.H.); (M.G.); (A.S.); (M.S.); (S.H.)
| | - Till Jasper Meyer
- Department of Oto-Rhino-Laryngology, Plastic, Aesthetic & Reconstructive Head and Neck Surgery, University Hospital Würzburg, Josef-Schneider-Str. 11, 97080 Würzburg, Germany; (R.H.); (M.G.); (A.S.); (M.S.); (S.H.)
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Olbrich K, Setkowicz Z, Kawon K, Czyzycki M, Janik-Olchawa N, Carlomagno I, Aquilanti G, Chwiej J. Vibrational spectroscopy methods for investigation of the animal models of glioblastoma multiforme. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 303:123230. [PMID: 37586277 DOI: 10.1016/j.saa.2023.123230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 06/26/2023] [Accepted: 08/01/2023] [Indexed: 08/18/2023]
Abstract
Glioblastoma multiforme (GBM) is the most common and devastating primary brain tumor among adults. It is highly lethal disease, as only 25% of patients survive longer than 1 year and only 5% more than 5 years from the diagnosis. To search for the new, more effective methods of treatment, the understanding of mechanisms underlying the process of tumorigenesis is needed. The new light on this problem may be shed by the analysis of biochemical anomalies of tissues affected by tumor growth. Therefore, in the present work, we applied the Fourier transform infrared (FTIR) and Raman microspectroscopy to evaluate changes in the distribution and structure of biomolecules appearing in the rat brain as a result of glioblastoma development. In turn, synchrotron X-ray fluorescence microscopy was utilized to determine the elemental anomalies appearing in the nervous tissue. To achieve the assumed goals of the study animal models of GBM were used. The rats were subjected to the intracranial implantation of glioma cells with different degree of invasiveness. For spectroscopic investigation brain slices taken from the area of cancer cells administration were used. The obtained results revealed, among others, the decrease content of lipids and compounds containing carbonyl groups, compositional and structural changes of proteins as well as abnormalities in the distribution of low atomic number elements within the region of tumor.
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Affiliation(s)
- Karolina Olbrich
- Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
| | - Zuzanna Setkowicz
- Institute of Zoology and Biomedical Research, Jagiellonian University, Krakow, Poland
| | - Kamil Kawon
- Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
| | - Mateusz Czyzycki
- Institute for Photon Science and Synchrotron Radiation, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
| | - Natalia Janik-Olchawa
- Institute of Zoology and Biomedical Research, Jagiellonian University, Krakow, Poland
| | | | | | - Joanna Chwiej
- Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland.
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Murugappan S, Tofail SAM, Thorat ND. Raman Spectroscopy: A Tool for Molecular Fingerprinting of Brain Cancer. ACS OMEGA 2023; 8:27845-27861. [PMID: 37576695 PMCID: PMC10413827 DOI: 10.1021/acsomega.3c01848] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 07/12/2023] [Indexed: 08/15/2023]
Abstract
Brain cancer is one of those few cancers with very high mortality and low five-year survival rate. First and foremost reason for the woes is the difficulty in diagnosing and monitoring the progression of brain tumors both benign and malignant, noninvasively and in real time. This raises a need in this hour for a tool to diagnose the tumors in the earliest possible time frame. On the other hand, Raman spectroscopy which is well-known for its ability to precisely represent the molecular markers available in any sample given, including biological ones, with great sensitivity and specificity. This has led to a number of studies where Raman spectroscopy has been used in brain tumors in various ways. This review article highlights the fundamentals of Raman spectroscopy and its types including conventional Raman, SERS, SORS, SRS, CARS, etc. are used in brain tumors for diagnostics, monitoring, and even theragnostics, collating all the major works in the area. Also, the review explores how Raman spectroscopy can be even more effectively used in theragnostics and the clinical level which would make them a one-stop solution for all brain cancer needs in the future.
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Affiliation(s)
- Sivasubramanian Murugappan
- Department of Physics, Bernal
Institute and Limerick Digital Cancer Research Centre (LDCRC)
University of Limerick, Castletroy, Limerick V94T9PX, Ireland
| | - Syed A. M. Tofail
- Department of Physics, Bernal
Institute and Limerick Digital Cancer Research Centre (LDCRC)
University of Limerick, Castletroy, Limerick V94T9PX, Ireland
| | - Nanasaheb D. Thorat
- Department of Physics, Bernal
Institute and Limerick Digital Cancer Research Centre (LDCRC)
University of Limerick, Castletroy, Limerick V94T9PX, Ireland
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Guleken Z, Ceylan Z, Aday A, Bayrak AG, Hindilerden İY, Nalçacı M, Jakubczyk P, Jakubczyk D, Depciuch J. FTIR- based serum structure analysis in molecular diagnostics of essential thrombocythemia disease. JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY. B, BIOLOGY 2023; 245:112734. [PMID: 37295134 DOI: 10.1016/j.jphotobiol.2023.112734] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 04/18/2023] [Accepted: 05/30/2023] [Indexed: 06/12/2023]
Abstract
Essential thrombocythemia (ET) reflects the transformation of a multipotent hematopoietic stem cell, but its molecular pathogenesis remains obscure. Nevertheless, tyrosine kinase, especially Janus kinase 2 (JAK2), has been implicated in myeloproliferative disorders other than chronic myeloid leukaemia. FTIR analysis was performed on the blood serum of 86 patients and 45 healthy volunteers as control with FTIR spectra-based machine learning methods and chemometrics. Thus, the study aimed to determine biomolecular changes and separation of ET and healthy control groups illustration by applying chemometrics and ML techniques to spectral data. The FTIR-based results showed that in ET disease with JAK2 mutation, there are alterations in functional groups associated with lipids, proteins and nucleic acids significantly. Moreover, in ET patients the lower amount of proteins with simultaneously higher amount of lipids was noted in comparison with the control one. Furthermore, the SVM-DA model showed 100% accuracy in calibration sets in both spectral regions and 100.0% and 96.43% accuracy in prediction sets for the 800-1800 cm-1 and 2700-3000 cm-1 spectral regions, respectively. While changes in the dynamic spectra showed that CH2 bending, amide II and CO vibrations could be used as a spectroscopy marker of ET. Finally, it was found a positive correlation between FTIR peaks and first bone marrow fibrosis degree, as well as the absence of JAK2 V617F mutation. The findings of this study contribute to a better understanding of the molecular pathogenesis of ET and identifying biomolecular changes and may have implications for early diagnosis and treatment of this disease.
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Affiliation(s)
- Zozan Guleken
- Department of Physiology, Faculty of Medicine, Gaziantep, Islam, Science and Technology University, 27220, Gaziantep, Turkey.
| | - Zeynep Ceylan
- Samsun University, Faculty of Engineering, Department of Industrial Engineering, Turkey
| | - Aynur Aday
- Istanbul University, Faculty of Medicine, Department of Internal Medicine, Division of Medical Genetics, Turkey
| | - Ayşe Gül Bayrak
- Istanbul University, Faculty of Medicine, Department of Internal Medicine, Division of Medical Genetics, Turkey
| | - İpek Yönal Hindilerden
- Istanbul University Istanbul Faculty of Medicine, Department of Internal Medicine, Division of Hematology, Turkey
| | - Meliha Nalçacı
- Istanbul University Istanbul Faculty of Medicine, Department of Internal Medicine, Division of Hematology, Turkey
| | | | - Dorota Jakubczyk
- Faculty of Mathematics and Applied Physics, Rzeszow University of Technology, Powstancow Warszawy 12, PL-35959 Rzeszow, Poland
| | - Joanna Depciuch
- Institute of Nuclear Physics, PAS, 31342 Krakow, Poland; Department of Biochemistry and Molecular Biology, Medical University of Lublin, 20-093 Lublin, Poland
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Chen Q, Shi T, Du D, Wang B, Zhao S, Gao Y, Wang S, Zhang Z. Non-destructive diagnostic testing of cardiac myxoma by serum confocal Raman microspectroscopy combined with multivariate analysis. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:2578-2587. [PMID: 37114381 DOI: 10.1039/d3ay00180f] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
The symptoms of cardiac myxoma (CM) mainly occur when the tumor is growing, and the diagnosis is determined by clinical presentation. Unfortunately, there is no evidence that specific blood tests are useful in CM diagnosis. Raman spectroscopy (RS) has emerged as a promising auxiliary diagnostic tool because of its ability to simultaneously detect multiple molecular features without labelling. The objective of this study was to identify spectral markers for CM, one of the most common benign cardiac tumors with insidious onset and rapid progression. In this study, a preliminary analysis was conducted based on serum Raman spectra to obtain the spectral differences between CM patients (CM group) and healthy control subjects (normal group). Principal component analysis-linear discriminant analysis (PCA-LDA) was constructed to highlight the differences in the distribution of biochemical components among the groups according to the obtained spectral information. Principal component analysis was combined with a support vector machine model (PCA-SVM) based on three different kernel functions (linear, polynomial, and Gaussian radial basis function (RBF)) to resolve spectral variations between all study groups. The results showed that CM patients had lower serum levels of phenylalanine and carotenoid than those in the normal group, and increased levels of fatty acids. The resulting Raman data was used in a multivariate analysis to determine the Raman range that could be used for CM diagnosis. Also, the chemical interpretation of the spectral results obtained is further presented in the discussion section based on the multivariate curve resolution-alternating least squares (MCR-ALS) method. These results suggest that RS can be used as an adjunct and promising tool for CM diagnosis, and that vibrations in the fingerprint region can be used as spectral markers for the disease under study.
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Affiliation(s)
- Qiang Chen
- Department of Cardiovascular Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Tao Shi
- Department of Cardiovascular Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Dan Du
- Department of Anesthesiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
| | - Bo Wang
- Department of Anesthesiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
| | - Sha Zhao
- Department of Anesthesiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
| | - Yang Gao
- Department of Cardiovascular Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Shuang Wang
- Institute of Photonics and Photon-Technology, Northwest University, Xi'an, China
| | - Zhanqin Zhang
- Department of Anesthesiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
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Zhang S, Qi Y, Tan SPH, Bi R, Olivo M. Molecular Fingerprint Detection Using Raman and Infrared Spectroscopy Technologies for Cancer Detection: A Progress Review. BIOSENSORS 2023; 13:bios13050557. [PMID: 37232918 DOI: 10.3390/bios13050557] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 05/12/2023] [Accepted: 05/16/2023] [Indexed: 05/27/2023]
Abstract
Molecular vibrations play a crucial role in physical chemistry and biochemistry, and Raman and infrared spectroscopy are the two most used techniques for vibrational spectroscopy. These techniques provide unique fingerprints of the molecules in a sample, which can be used to identify the chemical bonds, functional groups, and structures of the molecules. In this review article, recent research and development activities for molecular fingerprint detection using Raman and infrared spectroscopy are discussed, with a focus on identifying specific biomolecules and studying the chemical composition of biological samples for cancer diagnosis applications. The working principle and instrumentation of each technique are also discussed for a better understanding of the analytical versatility of vibrational spectroscopy. Raman spectroscopy is an invaluable tool for studying molecules and their interactions, and its use is likely to continue to grow in the future. Research has demonstrated that Raman spectroscopy is capable of accurately diagnosing various types of cancer, making it a valuable alternative to traditional diagnostic methods such as endoscopy. Infrared spectroscopy can provide complementary information to Raman spectroscopy and detect a wide range of biomolecules at low concentrations, even in complex biological samples. The article concludes with a comparison of the techniques and insights into future directions.
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Affiliation(s)
- Shuyan Zhang
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 31 Biopolis Way, Nanos #07-01, Singapore 138634, Singapore
| | - Yi Qi
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 31 Biopolis Way, Nanos #07-01, Singapore 138634, Singapore
| | - Sonia Peng Hwee Tan
- Department of Biomedical Engineering, National University of Singapore (NUS), 4 Engineering Drive 3 Block 4, #04-08, Singapore 117583, Singapore
| | - Renzhe Bi
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 31 Biopolis Way, Nanos #07-01, Singapore 138634, Singapore
| | - Malini Olivo
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 31 Biopolis Way, Nanos #07-01, Singapore 138634, Singapore
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Tołpa B, Depciuch J, Jakubczyk P, Paja W, Pancerz K, Wosiak A, Kaznowska E, Gala-Błądzińska A, Cebulski J. Fourier transform infrared spectroscopic marker of glioblastoma ob-tained from machine learning and changes in the spectra. Photodiagnosis Photodyn Ther 2023; 42:103550. [PMID: 37024000 DOI: 10.1016/j.pdpdt.2023.103550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 03/27/2023] [Accepted: 03/31/2023] [Indexed: 04/08/2023]
Abstract
BACKGROUND Glioblastoma is the most malignant brain cancer with an average survival rate of 5 years. In neurosurgical practice, it is impossible to completely remove a glioblastoma because of difficulties in the intraoperative assessment of the boundaries between healthy brain tissue and glioblastoma cells. Therefore, it is important to find a new, quick, cost-effective and useful neurosurgical practice method for the intraoperative differentiation of glioblastoma from healthy brain tissue. METHODS Herein, the features of absorbance at specific wavenumbers considered characteristic of glioblastoma tissues could be markers of this cancer. We used Fourier transform infrared spectroscopy to measure the spectra of tissues collected from control and patients suffering from glioblastoma. RESULTS The spectrum obtained from glioblastoma tissues demonstrated an additional peak at 1612 cm-1 and a shift of peaks at 1675 cm-1 and 1637 cm-1. Deconvolution of amide I vibrations showed that in the glioblastoma tissue, the percentage amount of β-sheet is around 20% higher than that in the control. Moreover, the principal component analysis showed that using fingerprint and amide I regions it is possible to distinguish cancer and non-cancer samples. Machine learning methods presented that the accuracy of the results is around 100%. Finally, analysis of the differences in the rate of change of Fourier transform infrared spectroscopy spectra showed that absorbance features between 1053 cm-1 and 1056 cm-1 as well as between 1564 cm-1 and 1588 cm-1 are characteristic of glioblastoma. CONCLUSION Calculated features of absorbance at specific wavenumbers could be used as a spectroscopic marker of glioblastoma which may be useful in the future for neuronavigation.
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Affiliation(s)
- Bartłomiej Tołpa
- Department of Neurosurgery, Clinical Hospital Nr 2 in Rzeszow, Lwowska 60, 35-309, Poland
| | - Joanna Depciuch
- Institute of Nuclear Physics, Polish Academy of Sciences, 31-342 Krakow, Poland; Department of Biochemistry and Molecular Biology, Medical University of Lublin, 20-093 Lublin, Poland.
| | - Paweł Jakubczyk
- Institute of Physics, College of Natural Sciences, University of Rzeszow, PL-35959 Rzeszow Poland
| | - Wiesław Paja
- Institute of Computer Science, College of Natural Sciences, University of Rzeszow, Poland
| | - Krzysztof Pancerz
- Institute of Philosophy, John Paul II Catholic University of Lublin, Poland
| | - Agnieszka Wosiak
- Institute of Information Technology, Lodz University of Technology, Poland
| | - Ewa Kaznowska
- Institute of Medical Sciences, Medical College of Rzeszów University, Rzeszów, Poland
| | | | - Józef Cebulski
- Institute of Physics, College of Natural Sciences, University of Rzeszow, PL-35959 Rzeszow Poland
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Infrared Spectroscopy as a Potential Diagnostic Tool for Medulloblastoma. Molecules 2023; 28:molecules28052390. [PMID: 36903631 PMCID: PMC10005236 DOI: 10.3390/molecules28052390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 02/28/2023] [Accepted: 03/03/2023] [Indexed: 03/08/2023] Open
Abstract
INTRODUCTION Medulloblastoma (MB) is the most common malignant tumor of the central nervous system in childhood. FTIR spectroscopy provides a holistic view of the chemical composition of biological samples, including the detection of molecules such as nucleic acids, proteins, and lipids. This study evaluated the applicability of FTIR spectroscopy as a potential diagnostic tool for MB. MATERIALS AND METHODS FTIR spectra of MB samples from 40 children (boys/girls: 31/9; age: median 7.8 years, range 1.5-21.5 years) treated in the Oncology Department of the Children's Memorial Health Institute in Warsaw between 2010 and 2019 were analyzed. The control group consisted of normal brain tissue taken from four children diagnosed with causes other than cancer. Formalin-fixed and paraffin-embedded tissues were sectioned and used for FTIR spectroscopic analysis. The sections were examined in the mid-infrared range (800-3500 cm-1) by ATR-FTIR. Spectra were analysed using a combination of principal component analysis, hierarchical cluster analysis, and absorbance dynamics. RESULTS FTIR spectra in MB were significantly different from those of normal brain tissue. The most significant differences related to the range of nucleic acids and proteins in the region 800-1800 cm-1. Some major differences were also revealed in the quantification of protein conformations (α-helices, β-sheets, and others) in the amide I band, as well as in the absorbance dynamics in the 1714-1716 cm-1 range (nucleic acids). It was not, however, possible to clearly distinguish between the various histological subtypes of MB using FTIR spectroscopy. CONCLUSIONS MB and normal brain tissue can be distinguished from one another to some extent using FTIR spectroscopy. As a result, it may be used as a further tool to hasten and enhance histological diagnosis.
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11
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Quesnel A, Coles N, Angione C, Dey P, Polvikoski TM, Outeiro TF, Islam M, Khundakar AA, Filippou PS. Glycosylation spectral signatures for glioma grade discrimination using Raman spectroscopy. BMC Cancer 2023; 23:174. [PMID: 36809974 PMCID: PMC9942363 DOI: 10.1186/s12885-023-10588-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 01/12/2023] [Accepted: 01/27/2023] [Indexed: 02/23/2023] Open
Abstract
BACKGROUND Gliomas are the most common brain tumours with the high-grade glioblastoma representing the most aggressive and lethal form. Currently, there is a lack of specific glioma biomarkers that would aid tumour subtyping and minimally invasive early diagnosis. Aberrant glycosylation is an important post-translational modification in cancer and is implicated in glioma progression. Raman spectroscopy (RS), a vibrational spectroscopic label-free technique, has already shown promise in cancer diagnostics. METHODS RS was combined with machine learning to discriminate glioma grades. Raman spectral signatures of glycosylation patterns were used in serum samples and fixed tissue biopsy samples, as well as in single cells and spheroids. RESULTS Glioma grades in fixed tissue patient samples and serum were discriminated with high accuracy. Discrimination between higher malignant glioma grades (III and IV) was achieved with high accuracy in tissue, serum, and cellular models using single cells and spheroids. Biomolecular changes were assigned to alterations in glycosylation corroborated by analysing glycan standards and other changes such as carotenoid antioxidant content. CONCLUSION RS combined with machine learning could pave the way for more objective and less invasive grading of glioma patients, serving as a useful tool to facilitate glioma diagnosis and delineate biomolecular glioma progression changes.
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Affiliation(s)
- Agathe Quesnel
- School of Health & Life Sciences, Teesside University, TS1 3BX, Middlesbrough, UK
- National Horizons Centre, Teesside University, 38 John Dixon Ln, DL1 1HG, Darlington, UK
| | - Nathan Coles
- School of Health & Life Sciences, Teesside University, TS1 3BX, Middlesbrough, UK
- National Horizons Centre, Teesside University, 38 John Dixon Ln, DL1 1HG, Darlington, UK
| | - Claudio Angione
- National Horizons Centre, Teesside University, 38 John Dixon Ln, DL1 1HG, Darlington, UK
- School of Computing, Engineering & Digital Technologies, Teesside University, Darlington, UK
- Centre for Digital Innovation, Teesside University, Darlington, UK
| | - Priyanka Dey
- School of Health & Life Sciences, Teesside University, TS1 3BX, Middlesbrough, UK
- National Horizons Centre, Teesside University, 38 John Dixon Ln, DL1 1HG, Darlington, UK
- School of Pharmacy and Biomedical Sciences, University of Portsmouth, PO1 2UP, Portsmouth, UK
| | - Tuomo M Polvikoski
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Tiago F Outeiro
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
- Department of Experimental Neurodegeneration, Center for Biostructural Imaging of Neurodegeneration, University Medical Center, Göttingen, Germany
- Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Göttingen, Germany
| | - Meez Islam
- School of Health & Life Sciences, Teesside University, TS1 3BX, Middlesbrough, UK
- National Horizons Centre, Teesside University, 38 John Dixon Ln, DL1 1HG, Darlington, UK
| | - Ahmad A Khundakar
- School of Health & Life Sciences, Teesside University, TS1 3BX, Middlesbrough, UK
- National Horizons Centre, Teesside University, 38 John Dixon Ln, DL1 1HG, Darlington, UK
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Panagiota S Filippou
- School of Health & Life Sciences, Teesside University, TS1 3BX, Middlesbrough, UK.
- National Horizons Centre, Teesside University, 38 John Dixon Ln, DL1 1HG, Darlington, UK.
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12
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Raman Spectroscopy as a Tool to Study the Pathophysiology of Brain Diseases. Int J Mol Sci 2023; 24:ijms24032384. [PMID: 36768712 PMCID: PMC9917237 DOI: 10.3390/ijms24032384] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 01/16/2023] [Accepted: 01/18/2023] [Indexed: 01/27/2023] Open
Abstract
The Raman phenomenon is based on the spontaneous inelastic scattering of light, which depends on the molecular characteristics of the dispersant. Therefore, Raman spectroscopy and imaging allow us to obtain direct information, in a label-free manner, from the chemical composition of the sample. Since it is well established that the development of many brain diseases is associated with biochemical alterations of the affected tissue, Raman spectroscopy and imaging have emerged as promising tools for the diagnosis of ailments. A combination of Raman spectroscopy and/or imaging with tagged molecules could also help in drug delivery and tracing for treatment of brain diseases. In this review, we first describe the basics of the Raman phenomenon and spectroscopy. Then, we delve into the Raman spectroscopy and imaging modes and the Raman-compatible tags. Finally, we center on the application of Raman in the study, diagnosis, and treatment of brain diseases, by focusing on traumatic brain injury and ischemia, neurodegenerative disorders, and brain cancer.
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13
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Steiner G, Galli R, Preusse G, Michen S, Meinhardt M, Temme A, Sobottka SB, Juratli TA, Koch E, Schackert G, Kirsch M, Uckermann O. A new approach for clinical translation of infrared spectroscopy: exploitation of the signature of glioblastoma for general brain tumor recognition. J Neurooncol 2023; 161:57-66. [PMID: 36509907 PMCID: PMC9886632 DOI: 10.1007/s11060-022-04204-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 12/01/2022] [Indexed: 12/14/2022]
Abstract
PURPOSE Infrared (IR) spectroscopy has the potential for tumor delineation in neurosurgery. Previous research showed that IR spectra of brain tumors are generally characterized by reduced lipid-related and increased protein-related bands. Therefore, we propose the exploitation of these common spectral changes for brain tumor recognition. METHODS Attenuated total reflection IR spectroscopy was performed on fresh specimens of 790 patients within minutes after resection. Using principal component analysis and linear discriminant analysis, a classification model was developed on a subset of glioblastoma (n = 135) and non-neoplastic brain (n = 27) specimens, and then applied to classify the IR spectra of several types of brain tumors. RESULTS The model correctly classified 82% (517/628) of specimens as "tumor" or "non-tumor", respectively. While the sensitivity was limited for infiltrative glioma, this approach recognized GBM (86%), other types of primary brain tumors (92%) and brain metastases (92%) with high accuracy and all non-tumor samples were correctly identified. CONCLUSION The concept of differentiation of brain tumors from non-tumor brain based on a common spectroscopic tumor signature will accelerate clinical translation of infrared spectroscopy and related technologies. The surgeon could use a single instrument to detect a variety of brain tumor types intraoperatively in future clinical settings. Our data suggests that this would be associated with some risk of missing infiltrative regions or tumors, but not with the risk of removing non-tumor brain.
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Affiliation(s)
- Gerald Steiner
- Clinical Sensoring and Monitoring, Department of Anesthesiology and Intensive Care Medicine, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Roberta Galli
- Medical Physics and Biomedical Engineering, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Grit Preusse
- Clinical Sensoring and Monitoring, Department of Anesthesiology and Intensive Care Medicine, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Susanne Michen
- Department of Neurosurgery, University Hospital Carl Gustav Carus, TU, Dresden, Germany
| | - Matthias Meinhardt
- Department of Pathology (Neuropathology), University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - Achim Temme
- Department of Neurosurgery, University Hospital Carl Gustav Carus, TU, Dresden, Germany ,National Center for Tumor Diseases (NCT), Partner Site Dresden, German Cancer Research Center (DKFZ), Heidelberg, Germany ,German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stephan B. Sobottka
- Department of Neurosurgery, University Hospital Carl Gustav Carus, TU, Dresden, Germany
| | - Tareq A. Juratli
- Department of Neurosurgery, University Hospital Carl Gustav Carus, TU, Dresden, Germany
| | - Edmund Koch
- Clinical Sensoring and Monitoring, Department of Anesthesiology and Intensive Care Medicine, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Gabriele Schackert
- Department of Neurosurgery, University Hospital Carl Gustav Carus, TU, Dresden, Germany ,National Center for Tumor Diseases (NCT), Partner Site Dresden, German Cancer Research Center (DKFZ), Heidelberg, Germany ,German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Ortrud Uckermann
- Department of Neurosurgery, University Hospital Carl Gustav Carus, TU, Dresden, Germany ,Division of Medical Biology, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Carl Gustav Carus, TU Dresden, Fetscherstr. 74, 01307 Dresden, Germany
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14
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Zhang K, Liu R, Tuo Y, Ma K, Zhang D, Wang Z, Huang P. Distinguishing Asphyxia from Sudden Cardiac Death as the Cause of Death from the Lung Tissues of Rats and Humans Using Fourier Transform Infrared Spectroscopy. ACS OMEGA 2022; 7:46859-46869. [PMID: 36570197 PMCID: PMC9773813 DOI: 10.1021/acsomega.2c05968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 11/23/2022] [Indexed: 06/17/2023]
Abstract
The ability to determine asphyxia as a cause of death is important in forensic practice and helps us to judge whether a case is criminal. However, in some cases where the deceased has underlying heart disease, death by asphyxia cannot be determined by traditional autopsy and morphological observation under a microscope because there are no specific morphological features for either asphyxia or sudden cardiac death (SCD). Here, Fourier transform infrared (FTIR) spectroscopy was employed to distinguish asphyxia from SCD. A total of 40 lung tissues (collected at 0 h and 24 h postmortem) from 20 rats (10 died from asphyxia and 10 died from SCD) and 16 human lung tissues from 16 real cases were used for spectral data acquisition. After data preprocessing, 2675 spectra from rat lung tissues and 1526 spectra from human lung tissues were obtained for subsequent analysis. First, we found that there were biochemical differences in the rat lung tissues between the two causes of death by principal component analysis and partial least-squares discriminant analysis (PLS-DA), which were related to alterations in lipids, proteins, and nucleic acids. In addition, a PLS-DA classification model can be built to distinguish asphyxia from SCD. Second, based on the spectral data obtained from lung tissues allowed to decompose for 24 h, we could still distinguish asphyxia from SCD even when decomposition occurred in animal models. Nine important spectral features that contributed to the discrimination in the animal experiment were selected and further analyzed. Third, 7 of the 9 differential spectral features were also found to be significantly different in human lung tissues from 16 real cases. A support vector machine model was finally built by using the seven variables to distinguish asphyxia from SCD in the human samples. Compared with the linear PLS-DA model, its accuracy was significantly improved to 0.798, and the correct rate of determining the cause of death was 100%. This study shows the application potential of FTIR spectroscopy for exploring the subtle biochemical differences resulting from different death processes and determining the cause of death even after decomposition.
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Affiliation(s)
- Kai Zhang
- Department
of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, People’s
Republic of China
| | - Ruina Liu
- Department
of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, People’s
Republic of China
| | - Ya Tuo
- Department
of Biochemistry and Physiology, Shanghai
University of Medicine and Health Sciences, Shanghai 201318, People’s Republic of China
| | - Kaijun Ma
- Shanghai
Key Laboratory of Crime Scene Evidence, Institute of Criminal Science
and Technology, Shanghai Municipal Public
Security Bureau, Shanghai 200042, People’s Republic
of China
| | - Dongchuan Zhang
- Shanghai
Key Laboratory of Crime Scene Evidence, Institute of Criminal Science
and Technology, Shanghai Municipal Public
Security Bureau, Shanghai 200042, People’s Republic
of China
| | - Zhenyuan Wang
- Department
of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, People’s
Republic of China
| | - Ping Huang
- Shanghai
Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, People’s Republic of China
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15
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Zahn J, Germond A, Lundgren AY, Cicerone MT. Discriminating cell line specific features of antibiotic-resistant strains of Escherichia coli from Raman spectra via machine learning analysis. JOURNAL OF BIOPHOTONICS 2022; 15:e202100274. [PMID: 35238159 PMCID: PMC9262779 DOI: 10.1002/jbio.202100274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 02/02/2022] [Accepted: 02/28/2022] [Indexed: 06/14/2023]
Abstract
While Raman spectroscopy can provide label-free discrimination between highly similar biological species, the discrimination is often marginal, and optimal use of spectral information is imperative. Here, we compare two machine learning models, an artificial neural network and a support vector machine, for discriminating between Raman spectra of 11 bacterial mutants of Escherichia coli MDS42. While we find that both models discriminate the 11 bacterial strains with similarly high accuracy, sensitivity and specificity, it is clear that the models form different class boundaries. By extracting strain-specific (and function-specific) spectral features utilized by the models, we find that both models utilize a small subset of high intensity peaks while separate subsets of lower intensity peaks are utilized by only one method or the other. This analysis highlights the need for methods to use the complete spectral information more effectively, beginning with a better understanding of the distinct information gained from each model.
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Affiliation(s)
- Jessica Zahn
- Department of Chemistry and Biochemistry, Georgia Institute of Technology, 950 Atlantic Drive, Atlanta, GA 30332, USA
| | - Arno Germond
- INRAE, UR 370 Qualité des Produits Animaux (QuaPA) Équipe Imagerie & Transferts (IT), 63122 Saint-Gènes-Champanelle, France
| | - Alice Y Lundgren
- Department of Mathematics, Brigham Young University, 275 TMCB, Provo, UT 84602, USA
| | - Marcus T Cicerone
- Department of Chemistry and Biochemistry, Georgia Institute of Technology, 950 Atlantic Drive, Atlanta, GA 30332, USA
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16
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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. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 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] [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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17
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Label-Free Differentiation of Cancer and Non-Cancer Cells Based on Machine-Learning-Algorithm-Assisted Fast Raman Imaging. BIOSENSORS 2022; 12:bios12040250. [PMID: 35448310 PMCID: PMC9031282 DOI: 10.3390/bios12040250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 04/10/2022] [Accepted: 04/12/2022] [Indexed: 11/17/2022]
Abstract
This paper proposes a rapid, label-free, and non-invasive approach for identifying murine cancer cells (B16F10 melanoma cancer cells) from non-cancer cells (C2C12 muscle cells) using machine-learning-assisted Raman spectroscopic imaging. Through quick Raman spectroscopic imaging, a hyperspectral data processing approach based on machine learning methods proved capable of presenting the cell structure and distinguishing cancer cells from non-cancer muscle cells without compromising full-spectrum information. This study discovered that biomolecular information–nucleic acids, proteins, and lipids—from cells could be retrieved efficiently from low-quality hyperspectral Raman datasets and then employed for cell line differentiation.
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18
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Cameron JM, Rinaldi C, Rutherford SH, Sala A, G Theakstone A, Baker MJ. Clinical Spectroscopy: Lost in Translation? APPLIED SPECTROSCOPY 2022; 76:393-415. [PMID: 34041957 DOI: 10.1177/00037028211021846] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
This Focal Point Review paper discusses the developments of biomedical Raman and infrared spectroscopy, and the recent strive towards these technologies being regarded as reliable clinical tools. The promise of vibrational spectroscopy in the field of biomedical science, alongside the development of computational methods for spectral analysis, has driven a plethora of proof-of-concept studies which convey the potential of various spectroscopic approaches. Here we report a brief review of the literature published over the past few decades, with a focus on the current technical, clinical, and economic barriers to translation, namely the limitations of many of the early studies, and the lack of understanding of clinical pathways, health technology assessments, regulatory approval, clinical feasibility, and funding applications. The field of biomedical vibrational spectroscopy must acknowledge and overcome these hurdles in order to achieve clinical efficacy. Current prospects have been overviewed with comment on the advised future direction of spectroscopic technologies, with the aspiration that many of these innovative approaches can ultimately reach the frontier of medical diagnostics and many clinical applications.
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Affiliation(s)
| | - Christopher Rinaldi
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
| | - Samantha H Rutherford
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
| | - Alexandra Sala
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
| | - Ashton G Theakstone
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, Glasgow, UK
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19
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Akin Geyik G, Peker Cengiz B, Tugrul F, Karuk Elmas SN, Yilmaz I, Arslan FN. A rapid diagnostic approach for gastric and colon cancers via Fourier transform mid-infrared spectroscopy coupled with chemometrics from paraffin-embedded tissues. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 267:120619. [PMID: 34810101 DOI: 10.1016/j.saa.2021.120619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 10/10/2021] [Accepted: 11/09/2021] [Indexed: 06/13/2023]
Abstract
This paper describes the feasibility of Attenuated total reflection-Fourier transform mid-infrared (ATR-MIR) spectroscopy method coupled with chemometrics for the rapid diagnostic approach and screening spectral changes for gastric and colon cancers from paraffin-embedded tissues. A total number of 82 tissue samples were analyzed by a simple ATR-MIR method combined with PCA, HCA, SIMCA and LDA methodologies. Spectral analyses showed significant differences for the molecular contents particularly about the lipid, nucleic acid, protein and other biomolecules in the samples of gastric cancer (GC) and colon cancer (CC) groups from their control/healthy groups. Significant changes in the characteristic of these molecules were only observed for cancer groups based upon the increment in their biosynthesis, and they could be utilized as diagnostic spectral biomarkers. Under the optimum conditions, SIMCA provided excellent classification for diseased and control groups, with 5% significance level. As well, 97.75% of the studied tissue samples were correctly discriminated on the basis of their origin by LDA. Consequently, the findings of this study highlighted the rapid diagnosis of gastric and colon cancer cases from paraffin-embedded tissues via ATR-MIR spectroscopy complemented with chemometrics.
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Affiliation(s)
- Gonul Akin Geyik
- Department of Chemistry, Faculty of Science, University of Karamanoglu Mehmetbey, 70100 Karaman, Turkey
| | - Betul Peker Cengiz
- Clinic of Medical Pathology, Eskişehir Yunus Emre State Hospital, 26190 Eskisehir, Turkey
| | - Fuzuli Tugrul
- Clinic of Radiation Oncology, Eskişehir City Hospital, 26080 Eskisehir, Turkey
| | - Sukriye Nihan Karuk Elmas
- Department of Chemistry, Faculty of Science, University of Karamanoglu Mehmetbey, 70100 Karaman, Turkey
| | - Ibrahim Yilmaz
- Department of Chemistry, Faculty of Science, University of Karamanoglu Mehmetbey, 70100 Karaman, Turkey.
| | - Fatma Nur Arslan
- Department of Chemistry, Faculty of Science, University of Karamanoglu Mehmetbey, 70100 Karaman, Turkey.
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20
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Lilo T, Morais CL, Shenton C, Ray A, Gurusinghe N. Revising Fourier-transform infrared (FT-IR) and Raman spectroscopy towards brain cancer detection. Photodiagnosis Photodyn Ther 2022; 38:102785. [DOI: 10.1016/j.pdpdt.2022.102785] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 02/15/2022] [Accepted: 02/25/2022] [Indexed: 12/11/2022]
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21
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Kopec M, Błaszczyk M, Radek M, Abramczyk H. Raman imaging and statistical methods for analysis various type of human brain tumors and breast cancers. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 262:120091. [PMID: 34175760 DOI: 10.1016/j.saa.2021.120091] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 06/14/2021] [Accepted: 06/16/2021] [Indexed: 06/13/2023]
Abstract
Spectroscopic methods provide information on the spatial localization of biochemical components based on the analysis of vibrational spectra. Raman spectroscopy and Raman imaging can be used to analyze various types of human brain tumors and breast cancers. The objective of this study is to evaluate the Raman biomarkers to distinguish tumor types by Raman spectroscopy and Raman imaging. We have demonstrated that bands characteristic for carotenoids (1156 cm-1, 1520 cm-1), proteins (1004 cm-1), fatty acids (1444 cm-1, 1655 cm-1) and cytochrome (1585 cm-1) can be used as universal biomarkers to assess aggressiveness of human brain tumors. The sensitivity and specificity obtained from PLS-DA have been over 73%. Only for gliosarcoma WHO IV the specificity is lower and takes equal 50%. The presented results confirm clinical potential of Raman spectroscopy in oncological diagnostics.
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Affiliation(s)
- M Kopec
- Lodz University of Technology, Institute of Applied Radiation Chemistry, Laboratory of Laser Molecular Spectroscopy, Wroblewskiego 15, 93-590 Lodz, Poland.
| | - M Błaszczyk
- Medical University of Lodz, Department of Neurosurgery, Spine and Peripheral Nerve Surgery, University Hospital WAM-CSW, Zeromskiego 113, 91-647 Lodz, Poland
| | - M Radek
- Medical University of Lodz, Department of Neurosurgery, Spine and Peripheral Nerve Surgery, University Hospital WAM-CSW, Zeromskiego 113, 91-647 Lodz, Poland
| | - H Abramczyk
- Lodz University of Technology, Institute of Applied Radiation Chemistry, Laboratory of Laser Molecular Spectroscopy, Wroblewskiego 15, 93-590 Lodz, Poland
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Raman Spectroscopy and Machine Learning for IDH Genotyping of Unprocessed Glioma Biopsies. Cancers (Basel) 2021; 13:cancers13164196. [PMID: 34439355 PMCID: PMC8392399 DOI: 10.3390/cancers13164196] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 08/12/2021] [Accepted: 08/16/2021] [Indexed: 11/26/2022] Open
Abstract
Simple Summary Isocitrate dehydrogenase (IDH) mutation is one of the most important prognostic markers in glioma tumors. Raman spectroscopy (RS) is an optical technique with great potential in intraoperative molecular diagnosis and surgical guidance. We analyzed RS’s ability to detect the IDH mutation onto unprocessed glioma biopsies. A total of 2073 Raman spectra were extracted from 38 tumor specimens. From the 103 Raman shifts screened, we identified 52 shifts (related to lipids, collagen, DNA and cholesterol/phospholipids) with the highest performance in the distinction of the two groups. We described 18 shifts never used before for IDH detection with RS in fresh or frozen samples. We were able to distinguish between IDH-mutated and IDH-wild-type tumors with an accuracy and precision of 87%. RS showed optimal accuracy and precision in discriminating IDH-mutated glioma from IDH-wild-type tumors ex-vivo onto fresh surgical specimens. Abstract Isocitrate dehydrogenase (IDH) mutational status is pivotal in the management of gliomas. Patients with IDH-mutated (IDH-MUT) tumors have a better prognosis and benefit more from extended surgical resection than IDH wild-type (IDH-WT). Raman spectroscopy (RS) is a minimally invasive optical technique with great potential for intraoperative diagnosis. We evaluated the RS’s ability to characterize the IDH mutational status onto unprocessed glioma biopsies. We extracted 2073 Raman spectra from thirty-eight unprocessed samples. The classification performance was assessed using the eXtreme Gradient Boosted trees (XGB) and Support Vector Machine with Radial Basis Function kernel (RBF-SVM). Measured Raman spectra displayed differences between IDH-MUT and IDH-WT tumor tissue. From the 103 Raman shifts screened as input features, the cross-validation loop identified 52 shifts with the highest performance in the distinction of the two groups. Raman analysis showed differences in spectral features of lipids, collagen, DNA and cholesterol/phospholipids. We were able to distinguish between IDH-MUT and IDH-WT tumors with an accuracy and precision of 87%. RS is a valuable and accurate tool for characterizing the mutational status of IDH mutation in unprocessed glioma samples. This study improves RS knowledge for future personalized surgical strategy or in situ target therapies for glioma tumors.
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Luo Y, Liu H, Wu C, Paraskevaidi M, Deng Y, Shi W, Yuan Y, Feng R, Martin FL, Pang W. Diagnostic segregation of human breast tumours using Fourier-transform infrared spectroscopy coupled with multivariate analysis: Classifying cancer subtypes. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 255:119694. [PMID: 33799187 DOI: 10.1016/j.saa.2021.119694] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 03/01/2021] [Accepted: 03/07/2021] [Indexed: 06/12/2023]
Abstract
The present study aimed to investigate whether attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy coupled with multivariate analysis could be applied to discriminate and classify among breast tumour molecular subtypes based on the unique spectral "fingerprints" of their biochemical composition. The different breast cancer tissues and normal breast tissues were collected and identified by pathology and ATR-FTIR spectroscopy respectively. The study indicates that the levels of the lipid-to-protein, nucleic acid-to-lipid, phosphate-to-carbohydrate and their secondary structure ratio, including RNA-to-DNA, Amide I-to-Amide II, and RNA-to-lipid ratios were significantly altered among the molecular subtype of breast tumour compared with normal breast tissues, which helps explain the changes in the biochemical structure of different molecular phenotypes of breast cancer. Tentatively-assigned characteristic peak ratios of infrared (IR) spectra reflect the changes of the macromolecule structure in different issues to a great extent and can be used as a potential biomarker to predict the molecular subtype of breast tumour. The present study acts as the first case study to show the successful application of IR spectroscopy in classifying subtypes of breast cancer with biochemical alterations. Therefore, the present study is likely to help to provide a new diagnostic approach for the accurate diagnosis of breast tumours and differential molecular subtypes and has the potential to be used for further intraoperative management.
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Affiliation(s)
- Youhong Luo
- Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, PR China
| | - Hui Liu
- School of Public Health, Guilin Medical University, Guilin, Guangxi, PR China
| | - Chunye Wu
- Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, PR China
| | - Maria Paraskevaidi
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, UK; School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - Yujie Deng
- Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, PR China
| | - Wenjie Shi
- Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, PR China
| | - Ye Yuan
- School of Basic Medical Sciences, Guilin Medical University, Guilin, Guangxi, PR China
| | - Ruifa Feng
- The Second Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, PR China
| | | | - Weiyi Pang
- School of Public Health, Guilin Medical University, Guilin, Guangxi, PR China.
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Robert C, Tsiampali J, Fraser-Miller SJ, Neumann S, Maciaczyk D, Young SL, Maciaczyk J, Gordon KC. Molecular monitoring of glioblastoma's immunogenicity using a combination of Raman spectroscopy and chemometrics. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 252:119534. [PMID: 33588367 DOI: 10.1016/j.saa.2021.119534] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 01/18/2021] [Accepted: 01/22/2021] [Indexed: 06/12/2023]
Abstract
Raman spectroscopy (RS) has been used as a powerful diagnostic and non-invasive tool in cancer diagnosis as well as in discrimination of cancer and immune cells. In this study RS in combination with chemometrics was applied to cellular Raman spectral data to distinguish the phenotype of T-cells and monocytes after incubation with media conditioned by glioblastoma stem-cells (GSCs) showing different molecular background. For this purpose, genetic modulations of epithelial-to-mesenchymal transition (EMT) process and expression of immunomodulator CD73 were introduced. Principal component analysis of the Raman spectral data showed that T-cells and monocytes incubated with tumour-conditioned media (TCMs) of GSCs with inhibited EMT activator ZEB1 or CD73 formed distinct clusters compared to controls highlighting their differences. Further discriminatory analysis performed using linear discriminant analysis (LDA) and support vector machine classification (SVM), yielded sensitivities and specificities of over 70 and 67% respectively upon validation against an independent test set. Supporting those results, flow cytometric analysis was performed to test the influence of TCMs on cytokine profile of T-cells and monocytes. We found that ZEB1 and CD73 influence T-cell and monocyte phenotype and promote monocyte differentiation into a population of mixed pro- and anti-tumorigenic macrophages (MΦs) and dendritic cells (DCs) respectively. In conclusion, Raman spectroscopy in combination with chemometrics enabled tracking T-cells and monocytes.
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Affiliation(s)
- Chima Robert
- Dodd-Walls Centre for Photonics and Quantum Technologies, Department of Chemistry, University of Otago, Dunedin, New Zealand
| | - Julia Tsiampali
- Neurosurgery Department, University Hospital Duesseldorf, 40225 Duesseldorf, Germany
| | - Sara J Fraser-Miller
- Dodd-Walls Centre for Photonics and Quantum Technologies, Department of Chemistry, University of Otago, Dunedin, New Zealand
| | - Silke Neumann
- Department of Pathology, University of Otago, Dunedin, New Zealand
| | - Donata Maciaczyk
- Department of Pathology, University of Otago, Dunedin, New Zealand
| | - Sarah L Young
- School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Jaroslaw Maciaczyk
- Department of Neurosurgery, University Hospital Bonn, 53179 Bonn, Germany; Department of Surgical Sciences, University of Otago, Dunedin, New Zealand.
| | - Keith C Gordon
- Dodd-Walls Centre for Photonics and Quantum Technologies, Department of Chemistry, University of Otago, Dunedin, New Zealand.
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Glioma biopsies Classification Using Raman Spectroscopy and Machine Learning Models on Fresh Tissue Samples. Cancers (Basel) 2021; 13:cancers13051073. [PMID: 33802369 PMCID: PMC7959285 DOI: 10.3390/cancers13051073] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 02/17/2021] [Accepted: 02/25/2021] [Indexed: 12/14/2022] Open
Abstract
Identifying tumor cells infiltrating normal-appearing brain tissue is critical to achieve a total glioma resection. Raman spectroscopy (RS) is an optical technique with potential for real-time glioma detection. Most RS reports are based on formalin-fixed or frozen samples, with only a few studies deployed on fresh untreated tissue. We aimed to probe RS on untreated brain biopsies exploring novel Raman bands useful in distinguishing glioma and normal brain tissue. Sixty-three fresh tissue biopsies were analyzed within few minutes after resection. A total of 3450 spectra were collected, with 1377 labelled as Healthy and 2073 as Tumor. Machine learning methods were used to classify spectra compared to the histo-pathological standard. The algorithms extracted information from 60 different Raman peaks identified as the most representative among 135 peaks screened. We were able to distinguish between tumor and healthy brain tissue with accuracy and precision of 83% and 82%, respectively. We identified 19 new Raman shifts with known biological significance. Raman spectroscopy was effective and accurate in discriminating glioma tissue from healthy brain ex-vivo in fresh samples. This study added new spectroscopic data that can contribute to further develop Raman Spectroscopy as an intraoperative tool for in-vivo glioma detection.
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Cameron JM, Conn JJA, Rinaldi C, Sala A, Brennan PM, Jenkinson MD, Caldwell H, Cinque G, Syed K, Butler HJ, Hegarty MG, Palmer DS, Baker MJ. Interrogation of IDH1 Status in Gliomas by Fourier Transform Infrared Spectroscopy. Cancers (Basel) 2020; 12:E3682. [PMID: 33302429 PMCID: PMC7762605 DOI: 10.3390/cancers12123682] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 11/23/2020] [Accepted: 12/04/2020] [Indexed: 12/12/2022] Open
Abstract
Mutations in the isocitrate dehydrogenase 1 (IDH1) gene are found in a high proportion of diffuse gliomas. The presence of the IDH1 mutation is a valuable diagnostic, prognostic and predictive biomarker for the management of patients with glial tumours. Techniques involving vibrational spectroscopy, e.g., Fourier transform infrared (FTIR) spectroscopy, have previously demonstrated analytical capabilities for cancer detection, and have the potential to contribute to diagnostics. The implementation of FTIR microspectroscopy during surgical biopsy could present a fast, label-free method for molecular genetic classification. For example, the rapid determination of IDH1 status in a patient with a glioma diagnosis could inform intra-operative decision-making between alternative surgical strategies. In this study, we utilized synchrotron-based FTIR microanalysis to probe tissue microarray sections from 79 glioma patients, and distinguished the positive class (IDH1-mutated) from the IDH1-wildtype glioma, with a sensitivity and specificity of 82.4% and 83.4%, respectively. We also examined the ability of attenuated total reflection (ATR)-FTIR spectroscopy in detecting the biomolecular events and global epigenetic and metabolic changes associated with mutations in the IDH1 enzyme, in blood serum samples collected from an additional 72 brain tumour patients. Centrifugal filtration enhanced the diagnostic ability of the classification models, with balanced accuracies up to ~69%. Identification of the molecular status from blood serum prior to biopsy could further direct some patients to alternative treatment strategies.
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Affiliation(s)
- James M. Cameron
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, 99 George St., Glasgow G1 1RD, UK; (J.M.C.); (C.R.); (A.S.)
- ClinSpec Diagnostics, Technology and Innovation Centre, University of Strathclyde, 99 George St., Glasgow G1 1RD, UK; (J.J.A.C.); (H.J.B.); (M.G.H.); (D.S.P.)
| | - Justin J. A. Conn
- ClinSpec Diagnostics, Technology and Innovation Centre, University of Strathclyde, 99 George St., Glasgow G1 1RD, UK; (J.J.A.C.); (H.J.B.); (M.G.H.); (D.S.P.)
| | - Christopher Rinaldi
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, 99 George St., Glasgow G1 1RD, UK; (J.M.C.); (C.R.); (A.S.)
| | - Alexandra Sala
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, 99 George St., Glasgow G1 1RD, UK; (J.M.C.); (C.R.); (A.S.)
| | - Paul M. Brennan
- Department of Clinical Neurosciences, Translational Neurosurgery, Western General Hospital, Edinburgh EH4 2XU, UK;
| | - Michael D. Jenkinson
- Institute of Systems, Molecular and Integrated Biology, University of Liverpool & The Walton Centre NHS Foundation Trust, Lower Lane, Fazakerley, Liverpool L9 7LJ, UK;
| | - Helen Caldwell
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Division of Pathology, Western General Hospital, Crewe Road South, Edinburgh EH4 2XR, UK;
| | - Gianfelice Cinque
- Diamond Light Source, Harwell Science and Innovation Campus, Chilton, Oxfordshire OX11 0DE, UK;
| | - Khaja Syed
- Walton Research Tissue Bank, Neurosciences Laboratories, The Walton Centre NHS Foundation Trust, Lower Lane, Fazakerley, Liverpool L9 7LJ, UK;
| | - Holly J. Butler
- ClinSpec Diagnostics, Technology and Innovation Centre, University of Strathclyde, 99 George St., Glasgow G1 1RD, UK; (J.J.A.C.); (H.J.B.); (M.G.H.); (D.S.P.)
| | - Mark G. Hegarty
- ClinSpec Diagnostics, Technology and Innovation Centre, University of Strathclyde, 99 George St., Glasgow G1 1RD, UK; (J.J.A.C.); (H.J.B.); (M.G.H.); (D.S.P.)
| | - David S. Palmer
- ClinSpec Diagnostics, Technology and Innovation Centre, University of Strathclyde, 99 George St., Glasgow G1 1RD, UK; (J.J.A.C.); (H.J.B.); (M.G.H.); (D.S.P.)
- WestCHEM, Department of Pure and Applied Chemistry, Thomas Graham Building, University of Strathclyde, 295 Cathedral Str., Glasgow G1 1XL, UK
| | - Matthew J. Baker
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, 99 George St., Glasgow G1 1RD, UK; (J.M.C.); (C.R.); (A.S.)
- ClinSpec Diagnostics, Technology and Innovation Centre, University of Strathclyde, 99 George St., Glasgow G1 1RD, UK; (J.J.A.C.); (H.J.B.); (M.G.H.); (D.S.P.)
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27
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α-Helical protein absorption at post-traumatic epileptic foci monitored by Fourier transform infrared mapping. J Biosci 2020. [DOI: 10.1007/s12038-020-00028-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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28
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Use of Raman spectroscopy to evaluate the biochemical composition of normal and tumoral human brain tissues for diagnosis. Lasers Med Sci 2020; 37:121-133. [PMID: 33159308 DOI: 10.1007/s10103-020-03173-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 10/23/2020] [Indexed: 10/23/2022]
Abstract
Raman spectroscopy was used to identify biochemical differences in normal brain tissue (cerebellum and meninges) compared to tumors (glioblastoma, medulloblastoma, schwannoma, and meningioma) through biochemical information obtained from the samples. A total of 263 spectra were obtained from fragments of the normal cerebellum (65), normal meninges (69), glioblastoma (28), schwannoma (8), medulloblastoma (19), and meningioma (74), which were collected using the dispersive Raman spectrometer (830 nm, near infrared, output power of 350 mW, 20 s exposure time to obtain the spectra), coupled to a Raman probe. A spectral model based on least squares fitting was developed to estimate the biochemical concentration of 16 biochemical compounds present in brain tissue, among those that most characterized brain tissue spectra, such as linolenic acid, triolein, cholesterol, sphingomyelin, phosphatidylcholine, β-carotene, collagen, phenylalanine, DNA, glucose, and blood. From the biochemical information, the classification of the spectra in the normal and tumor groups was conducted according to the type of brain tumor and corresponding normal tissue. The classification used in discrimination models were (a) the concentrations of the biochemical constituents of the brain, through linear discriminant analysis (LDA), and (b) the tissue spectra, through the discrimination by partial least squares (PLS-DA) regression. The models obtained 93.3% discrimination accuracy through the LDA between the normal and tumor groups of the cerebellum separated according to the concentration of biochemical constituents and 94.1% in the discrimination by PLS-DA using the whole spectrum. The results obtained demonstrated that the Raman technique is a promising tool to differentiate concentrations of biochemical compounds present in brain tissues, both normal and tumor. The concentrations estimated by the biochemical model and all the information contained in the Raman spectra were both able to classify the pathological groups.
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29
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Livermore LJ, Isabelle M, Bell IM, Edgar O, Voets NL, Stacey R, Ansorge O, Vallance C, Plaha P. Raman spectroscopy to differentiate between fresh tissue samples of glioma and normal brain: a comparison with 5-ALA-induced fluorescence-guided surgery. J Neurosurg 2020; 135:469-479. [PMID: 33007757 DOI: 10.3171/2020.5.jns20376] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 05/22/2020] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Raman spectroscopy is a biophotonic tool that can be used to differentiate between different tissue types. It is nondestructive and no sample preparation is required. The aim of this study was to evaluate the ability of Raman spectroscopy to differentiate between glioma and normal brain when using fresh biopsy samples and, in the case of glioblastomas, to compare the performance of Raman spectroscopy to predict the presence or absence of tumor with that of 5-aminolevulinic acid (5-ALA)-induced fluorescence. METHODS A principal component analysis (PCA)-fed linear discriminant analysis (LDA) machine learning predictive model was built using Raman spectra, acquired ex vivo, from fresh tissue samples of 62 patients with glioma and 11 glioma-free brain samples from individuals undergoing temporal lobectomy for epilepsy. This model was then used to classify Raman spectra from fresh biopsies from resection cavities after functional guided, supramaximal glioma resection. In cases of glioblastoma, 5-ALA-induced fluorescence at the resection cavity biopsy site was recorded, and this was compared with the Raman spectral model prediction for the presence of tumor. RESULTS The PCA-LDA predictive model demonstrated 0.96 sensitivity, 0.99 specificity, and 0.99 accuracy for differentiating tumor from normal brain. Twenty-three resection cavity biopsies were taken from 8 patients after supramaximal resection (6 glioblastomas, 2 oligodendrogliomas). Raman spectroscopy showed 1.00 sensitivity, 1.00 specificity, and 1.00 accuracy for predicting tumor versus normal brain in these samples. In the glioblastoma cases, where 5-ALA-induced fluorescence was used, the performance of Raman spectroscopy was significantly better than the predictive value of 5-ALA-induced fluorescence, which showed 0.07 sensitivity, 1.00 specificity, and 0.24 accuracy (p = 0.0009). CONCLUSIONS Raman spectroscopy can accurately classify fresh tissue samples into tumor versus normal brain and is superior to 5-ALA-induced fluorescence. Raman spectroscopy could become an important intraoperative tool used in conjunction with 5-ALA-induced fluorescence to guide extent of resection in glioma surgery.
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Affiliation(s)
- Laurent J Livermore
- 1Nuffield Department of Clinical Neurosciences, and
- 3Department of Neurosurgery, Oxford University Hospitals NHS Foundation Trust, Oxford
| | - Martin Isabelle
- 4Renishaw plc, Spectroscopy Products Division, Gloucestershire
| | - Ian M Bell
- 4Renishaw plc, Spectroscopy Products Division, Gloucestershire
| | - Oliver Edgar
- 1Nuffield Department of Clinical Neurosciences, and
| | - Natalie L Voets
- 2Nuffield Department of Surgery, University of Oxford, John Radcliffe Hospital, Oxford
- 6FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Richard Stacey
- 3Department of Neurosurgery, Oxford University Hospitals NHS Foundation Trust, Oxford
| | - Olaf Ansorge
- 1Nuffield Department of Clinical Neurosciences, and
| | | | - Puneet Plaha
- 2Nuffield Department of Surgery, University of Oxford, John Radcliffe Hospital, Oxford
- 3Department of Neurosurgery, Oxford University Hospitals NHS Foundation Trust, Oxford
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30
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Sacharz J, Perez-Guaita D, Kansiz M, Nazeer SS, Wesełucha-Birczyńska A, Petratos S, Wood BR, Heraud P. Empirical study on the effects of acquisition parameters for FTIR hyperspectral imaging of brain tissue. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2020; 12:4334-4342. [PMID: 32844833 DOI: 10.1039/c9ay01200a] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Fourier transform infrared (FTIR) spectroscopic imaging is a powerful technique for molecular imaging of pathologies associated with the nervous systems including multiple sclerosis research. However, there is no standard methodology or standardized protocol for FTIR imaging of tissue sections that maximize the ability to discriminate between the molecular, white and granular layers, which is essential in the investigation of the mechanism of demyelination process. Tissue sections are heterogeneous, complex and delicate, hence the parameters to generate high quality images in minimal time becomes essential in the modern clinical laboratory. This article presents an FTIR spectroscopic imaging study of post-mortem human brain tissue testing the effects of various measurement parameters and data analysis methods on image quality and acquisition time. Hyperspectral images acquired from the same region of a tissue using a range of the most common optical and collection parameters in different combinations were compared. These included magnification (4× and 15×), number of co-added scans (1, 4, 8, 16, 32, 64 and 128 scans) and spectral resolution (4, 8 and 16 cm-1). Images were compared in terms of acquisition time, signal-to-noise (S/N) ratio, and accuracy of the discrimination between three major tissue types in a section from the cerebellum (white matter, granular and molecular layers). In the latter case, unsupervised k-means cluster (KMC) analysis was employed to generate images from the hyperspectral images, which were compared to a reference image. The classification accuracy for tissue class discrimination was highest for the 4× magnifying objective, with 4 cm-1 spectral resolution and 128 co-added scans. The 15× magnifying objective gave the best accuracy for a spectral resolution of 4 cm-1 and 64 scans (96.3%), which was just above what was achieved using the 4× magnifying objective, with 4 cm-1 spectral resolution and 32 and 64 co-added scans (95.4 and 95.6%, respectively). These findings were correlated with a decrease in S/N ratio with increasing number of scans and was generally lower for the 15× objective. However, longer scan times were required using the 15× magnifying objective, which did not justify the very small improvement in the classification of tissue types.
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Affiliation(s)
- J Sacharz
- Centre for Biospectroscopy and School of Chemistry, Monash University, 3800, Victoria, Australia. and Faculty of Chemistry, Jagiellonian University, Gronostajowa 2, 30-387, Kraków, Poland
| | - D Perez-Guaita
- Centre for Biospectroscopy and School of Chemistry, Monash University, 3800, Victoria, Australia. and FOCAS Research Institute, Technological University Dublin, City Campus, Dublin, Ireland
| | - Mustafa Kansiz
- Photothermal Spectroscopy Corp., 325 Chapala St, Santa Barbara, CA 93101, USA
| | - Shaiju S Nazeer
- Centre for Biospectroscopy and School of Chemistry, Monash University, 3800, Victoria, Australia.
| | | | - S Petratos
- Department of Neuroscience/Central Clinical School, Monash University, Alfred Centre, 99 Commercial Rd, Prahran, 3004, Victoria, Australia
| | - B R Wood
- Centre for Biospectroscopy and School of Chemistry, Monash University, 3800, Victoria, Australia.
| | - P Heraud
- Centre for Biospectroscopy and School of Chemistry, Monash University, 3800, Victoria, Australia. and Department of Microbiology and the Biomedical Discovery Institute, Faculty of Medicine, Nursing and Health Sciences, Monash University, 3800, Victoria, Australia
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Serdiuk V, Shogren KL, Kovalenko T, Rasulev B, Yaszemski M, Maran A, Voronov A. Detection of macromolecular inversion-induced structural changes in osteosarcoma cells by FTIR microspectroscopy. Anal Bioanal Chem 2020; 412:7253-7262. [PMID: 32879994 DOI: 10.1007/s00216-020-02858-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 07/01/2020] [Accepted: 08/03/2020] [Indexed: 11/29/2022]
Abstract
Fourier transform infrared (FTIR) microspectroscopy provides a biochemical fingerprint of the cells. In this study, chemical changes in 143B osteosarcoma cells were investigated using FTIR analysis of cancer cells after their treatment with polymeric invertible micellar assemblies (IMAs) and curcumin-loaded IMAs and compared with untreated osteosarcoma cells. A comprehensive principal component analysis (PCA) was applied to analyze the FTIR results and confirm noticeable changes in cell surface chemical structures in the fingerprint regions of 1480-900 cm-1. The performed clustering shows visible differences for all investigated groups of cancer cells. It is demonstrated that a combination of FTIR microspectroscopy with PCA can be an efficient approach in determining interactions of osteosarcoma cells and drug-loaded polymer micellar assemblies. Graphical abstract.
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Affiliation(s)
- Vitalii Serdiuk
- Department of Orthopedics, Mayo Clinic, Rochester, MN, 55905, USA.,Department of Coatings & Polymeric Materials, North Dakota State University, Fargo, ND, 58105, USA.,Department of Organic Chemistry, Lviv Polytechnic National University, Lviv, 79013, Ukraine
| | | | - Tetiana Kovalenko
- Department of Organic Chemistry, Lviv Polytechnic National University, Lviv, 79013, Ukraine
| | - Bakhtiyor Rasulev
- Department of Coatings & Polymeric Materials, North Dakota State University, Fargo, ND, 58105, USA
| | | | | | - Andriy Voronov
- Department of Coatings & Polymeric Materials, North Dakota State University, Fargo, ND, 58105, USA.
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Zhan Q, Li Y, Yuan Y, Liu J, Li Y. The accuracy of Raman spectroscopy in the detection and diagnosis of oral cancer: A systematic review and meta‐analysis. JOURNAL OF RAMAN SPECTROSCOPY 2020. [DOI: 10.1002/jrs.5940] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Affiliation(s)
- Qi Zhan
- State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology Sichuan University Chengdu China
| | - Yuan Li
- State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology Sichuan University Chengdu China
| | - Yihang Yuan
- State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology Sichuan University Chengdu China
| | - Jinchi Liu
- State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology Sichuan University Chengdu China
| | - Yi Li
- State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology Sichuan University Chengdu China
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Morais CLM, Santos MCD, Lima KMG, Martin FL. Improving data splitting for classification applications in spectrochemical analyses employing a random-mutation Kennard-Stone algorithm approach. Bioinformatics 2020; 35:5257-5263. [PMID: 31116391 PMCID: PMC6954661 DOI: 10.1093/bioinformatics/btz421] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Revised: 05/01/2019] [Accepted: 05/15/2019] [Indexed: 12/25/2022] Open
Abstract
Motivation Data splitting is a fundamental step for building classification models with spectral data, especially in biomedical applications. This approach is performed following pre-processing and prior to model construction, and consists of dividing the samples into at least training and test sets; herein, the training set is used for model construction and the test set for model validation. Some of the most-used methodologies for data splitting are the random selection (RS) and the Kennard-Stone (KS) algorithms; here, the former works based on a random splitting process and the latter is based on the calculation of the Euclidian distance between the samples. We propose an algorithm called the Morais-Lima-Martin (MLM) algorithm, as an alternative method to improve data splitting in classification models. MLM is a modification of KS algorithm by adding a random-mutation factor. Results RS, KS and MLM performance are compared in simulated and six real-world biospectroscopic applications using principal component analysis linear discriminant analysis (PCA-LDA). MLM generated a better predictive performance in comparison with RS and KS algorithms, in particular regarding sensitivity and specificity values. Classification is found to be more well-equilibrated using MLM. RS showed the poorest predictive response, followed by KS which showed good accuracy towards prediction, but relatively unbalanced sensitivities and specificities. These findings demonstrate the potential of this new MLM algorithm as a sample selection method for classification applications in comparison with other regular methods often applied in this type of data. Availability and implementation MLM algorithm is freely available for MATLAB at https://doi.org/10.6084/m9.figshare.7393517.v1.
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Affiliation(s)
- Camilo L M Morais
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - Marfran C D Santos
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal 59072-970, Brazil
| | - Kássio M G Lima
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal 59072-970, Brazil
| | - Francis L Martin
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
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Ghimire H, Garlapati C, Janssen EAM, Krishnamurti U, Qin G, Aneja R, Perera AGU. Protein Conformational Changes in Breast Cancer Sera Using Infrared Spectroscopic Analysis. Cancers (Basel) 2020; 12:E1708. [PMID: 32605072 PMCID: PMC7407230 DOI: 10.3390/cancers12071708] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 06/19/2020] [Accepted: 06/25/2020] [Indexed: 01/08/2023] Open
Abstract
Protein structural alterations, including misfolding and aggregation, are a hallmark of several diseases, including cancer. However, the possible clinical application of protein conformational analysis using infrared spectroscopy to detect cancer-associated structural changes in proteins has not been established yet. The present study investigates the applicability of Fourier transform infrared spectroscopy in distinguishing the sera of healthy individuals and breast cancer patients. The cancer-associated alterations in the protein structure were analyzed by fitting the amide I (1600-1700 cm-1) band of experimental curves, as well as by comparing the ratio of the absorbance values at the amide II and amide III bands, assigning those as the infrared spectral signatures. The snapshot of the breast cancer-associated alteration in circulating DNA and RNA was also evaluated by extending the spectral fitting protocol to the complex region of carbohydrates and nucleic acids, 1140-1000 cm-1. The sensitivity and specificity of these signatures, representing the ratio of the α-helix and β-pleated sheet in proteins, were both 90%. Likewise, the ratio of amides II and amide III (I1556/I1295) had a sensitivity and specificity of 100% and 80%, respectively. Thus, infrared spectroscopy can serve as a powerful tool to understand the protein structural alterations besides distinguishing breast cancer and healthy serum samples.
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Affiliation(s)
- Hemendra Ghimire
- Department of Physics and Astronomy, Georgia State University, Atlanta, GA 30303, USA;
| | | | - Emiel A. M. Janssen
- Department of Pathology, Stavanger University Hospital, Stavanger NO-4068, Norway;
| | - Uma Krishnamurti
- Department of Pathology, Emory University School of Medicine, Atlanta, GA 30322, USA;
| | - Gengsheng Qin
- Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303, USA;
| | - Ritu Aneja
- Department of Biology, Georgia State University, Atlanta, GA 30303, USA; (C.G.); (R.A.)
- Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA 30303, USA
| | - A. G. Unil Perera
- Department of Physics and Astronomy, Georgia State University, Atlanta, GA 30303, USA;
- Center for Diagnostics and Therapeutics, Georgia State University, Atlanta, GA 30303, USA
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35
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DePaoli D, Lemoine É, Ember K, Parent M, Prud’homme M, Cantin L, Petrecca K, Leblond F, Côté DC. Rise of Raman spectroscopy in neurosurgery: a review. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:1-36. [PMID: 32358930 PMCID: PMC7195442 DOI: 10.1117/1.jbo.25.5.050901] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 04/10/2020] [Indexed: 05/21/2023]
Abstract
SIGNIFICANCE Although the clinical potential for Raman spectroscopy (RS) has been anticipated for decades, it has only recently been used in neurosurgery. Still, few devices have succeeded in making their way into the operating room. With recent technological advancements, however, vibrational sensing is poised to be a revolutionary tool for neurosurgeons. AIM We give a summary of neurosurgical workflows and key translational milestones of RS in clinical use and provide the optics and data science background required to implement such devices. APPROACH We performed an extensive review of the literature, with a specific emphasis on research that aims to build Raman systems suited for a neurosurgical setting. RESULTS The main translatable interest in Raman sensing rests in its capacity to yield label-free molecular information from tissue intraoperatively. Systems that have proven usable in the clinical setting are ergonomic, have a short integration time, and can acquire high-quality signal even in suboptimal conditions. Moreover, because of the complex microenvironment of brain tissue, data analysis is now recognized as a critical step in achieving high performance Raman-based sensing. CONCLUSIONS The next generation of Raman-based devices are making their way into operating rooms and their clinical translation requires close collaboration between physicians, engineers, and data scientists.
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Affiliation(s)
- Damon DePaoli
- Université Laval, CERVO Brain Research Center, Québec, Canada
- Université Laval, Centre d’optique, Photonique et Lasers, Québec, Canada
| | - Émile Lemoine
- Polytechnique Montréal, Department of Engineering Physics, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
| | - Katherine Ember
- Polytechnique Montréal, Department of Engineering Physics, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
| | - Martin Parent
- Université Laval, CERVO Brain Research Center, Québec, Canada
| | - Michel Prud’homme
- Hôpital de l’Enfant-Jésus, Department of Neurosurgery, Québec, Canada
| | - Léo Cantin
- Hôpital de l’Enfant-Jésus, Department of Neurosurgery, Québec, Canada
| | - Kevin Petrecca
- McGill University, Montreal Neurological Institute-Hospital, Department of Neurology and Neurosurgery, Montreal, Canada
| | - Frédéric Leblond
- Polytechnique Montréal, Department of Engineering Physics, Montréal, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Canada
- Address all correspondence to Frédéric Leblond, E-mail: ; Daniel C. Côté, E-mail:
| | - Daniel C. Côté
- Université Laval, CERVO Brain Research Center, Québec, Canada
- Université Laval, Centre d’optique, Photonique et Lasers, Québec, Canada
- Address all correspondence to Frédéric Leblond, E-mail: ; Daniel C. Côté, E-mail:
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Kowalska AA, Berus S, Szleszkowski Ł, Kamińska A, Kmiecik A, Ratajczak-Wielgomas K, Jurek T, Zadka Ł. Brain tumour homogenates analysed by surface-enhanced Raman spectroscopy: Discrimination among healthy and cancer cells. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2020; 231:117769. [PMID: 31787534 DOI: 10.1016/j.saa.2019.117769] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Revised: 11/04/2019] [Accepted: 11/04/2019] [Indexed: 05/13/2023]
Abstract
One of the biggest challenge for modern medicine is to make a discrimination among healthy and cancerous tissues. Therefore, nowadays big effort of scientist are devoted to find a new way for as fast as possible diagnosis with as much as possible accuracy in distinguishing healthy from cancerous tissues. That issues are probably the most important in the case of brain tumours, when the diagnosis time plays a great role. Herein we present the surface-enhanced Raman spectroscopy (SERS) together with the principal component analysis (PCA) used to identify the spectra of different brain specimens, healthy and tumour tissues homogenates. The presented analyses include three sets of brain tissues as control samples taken from healthy objects (one set consists of samples from four brain lobes and both hemispheres; eight samples) and the brain tumours from five patients (two Anaplastic Astrocytoma and three Glioblastoma samples). Results prove that tumour brain samples can be discriminated well from the healthy tissues by using only three main principal components, with 96% of accuracy. The largest influence onto the calculated separation is attributed to the spectral regions corresponding in SERS spectra to vibrations of the L-Tryptophan (1450, 1278 cm-1), protein (1300 cm-1), phenylalanine and Amide-I (1005, 1654 cm-1). Therefore, the presented method may open the way for the probable application as a very fast diagnosis tool alternative for conventionally used histopathology or even more as an intraoperative diagnostic tool during brain tumour surgery.
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Affiliation(s)
- Aneta Aniela Kowalska
- Institute of Physical Chemistry Polish Academy of Sciences, Kasprzaka 44/52, 01-224 Warsaw, Poland.
| | - Sylwia Berus
- Institute of Physical Chemistry Polish Academy of Sciences, Kasprzaka 44/52, 01-224 Warsaw, Poland
| | - Łukasz Szleszkowski
- Department of Forensic Medicine, Forensic Medicine Unit, Wroclaw Medical University, ul. Mikulicza-Radeckiego 4, 50-386 Wroclaw, Poland
| | - Agnieszka Kamińska
- Institute of Physical Chemistry Polish Academy of Sciences, Kasprzaka 44/52, 01-224 Warsaw, Poland
| | - Alicja Kmiecik
- Department of Human Morphology and Embryology, Histology and Embryology Division, Wroclaw Medical University, ul. Chalubinskiego 6a, 50-368 Wroclaw, Poland
| | - Katarzyna Ratajczak-Wielgomas
- Department of Human Morphology and Embryology, Histology and Embryology Division, Wroclaw Medical University, ul. Chalubinskiego 6a, 50-368 Wroclaw, Poland
| | - Tomasz Jurek
- Department of Forensic Medicine, Forensic Medicine Unit, Wroclaw Medical University, ul. Mikulicza-Radeckiego 4, 50-386 Wroclaw, Poland
| | - Łukasz Zadka
- Department of Human Morphology and Embryology, Histology and Embryology Division, Wroclaw Medical University, ul. Chalubinskiego 6a, 50-368 Wroclaw, Poland
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37
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Gaifulina R, Caruana DJ, Oukrif D, Guppy NJ, Culley S, Brown R, Bell I, Rodriguez-Justo M, Lau K, Thomas GMH. Rapid and complete paraffin removal from human tissue sections delivers enhanced Raman spectroscopic and histopathological analysis. Analyst 2020; 145:1499-1510. [PMID: 31894759 PMCID: PMC7677988 DOI: 10.1039/c9an01030k] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 12/14/2019] [Indexed: 12/29/2022]
Abstract
Incomplete removal of paraffin and organic contaminants from tissues processed for diagnostic histology has been a profound barrier to the introduction of Raman spectroscopic techniques into clinical practice. We report a route to rapid and complete paraffin removal from a range of formalin-fixed paraffin embedded tissues using super mirror stainless steel slides. The method is equally effective on a range of human and animal tissues, performs equally well with archived and new samples and is compatible with standard pathology lab procedures. We describe a general enhancement of the Raman scatter and enhanced staining with antibodies used in immunohistochemistry for clinical diagnosis. We conclude that these novel slide substrates have the power to improve diagnosis through anatomical pathology by facilitating the simultaneous combination of improved, more sensitive immunohistochemical staining and simplified, more reliable Raman spectroscopic imaging, analysis and signal processing.
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Affiliation(s)
- Riana Gaifulina
- Department of Cell and Developmental Biology
, University College London
,
UK
.
; Tel: +44 (0)20 7679 6098
- Department of Chemistry
, University College London
,
UK
| | | | - Dahmane Oukrif
- Research Department of Pathology
, University College London
,
UK
| | - Naomi J. Guppy
- UCL Advanced Diagnostics
, University College Hospital
,
UK
| | - Siân Culley
- Department of Cell and Developmental Biology
, University College London
,
UK
.
; Tel: +44 (0)20 7679 6098
- MRC Laboratory for Molecular Cell Biology
, University College London
,
UK
| | - Robert Brown
- Spectroscopy Products Division
,
Renishaw plc
, UK
.
| | - Ian Bell
- Spectroscopy Products Division
,
Renishaw plc
, UK
.
| | - Manuel Rodriguez-Justo
- Department of Gastrointestinal Pathology
, University College Hospital and Department of Research Pathology/Cancer Institute
,
UCL
, UK
| | - Katherine Lau
- Spectroscopy Products Division
,
Renishaw plc
, UK
.
| | - Geraint M. H. Thomas
- Department of Cell and Developmental Biology
, University College London
,
UK
.
; Tel: +44 (0)20 7679 6098
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38
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Depciuch J, Tołpa B, Witek P, Szmuc K, Kaznowska E, Osuchowski M, Król P, Cebulski J. Raman and FTIR spectroscopy in determining the chemical changes in healthy brain tissues and glioblastoma tumor tissues. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2020; 225:117526. [PMID: 31655362 DOI: 10.1016/j.saa.2019.117526] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 09/02/2019] [Accepted: 09/09/2019] [Indexed: 06/10/2023]
Abstract
Glioblastoma, also called glioblastoma multiforme (GBM), is a particularly malignant form of primary brain tumor. This cancer accounts for 12-15% of all brain tumors. Despite the advances in neurosurgery, radio and chemotherapy the average survival rate is only 12.1-16.6 months. This is due not only to the late diagnosis of the disease, but also to ineffective treatment methods which result from the still low knowledge about the causes of glioblastoma development. Therefore, it is very important to look for new diagnostic methods of detection of the smallest features of cancer. Raman and infrared spectroscopy (FTIR) can be such methods. In this paper we discuss the chemical composition of sample glioblastoma brain tissues and marginal brain tissues using these two spectroscopy methods. Raman and FTIR spectra of cancer brain tissues showed that the highest differences in the chemical composition, compared to the control brain tissue, occur in the areas corresponding to lipids, collagen and proteins. Moreover, Raman spectroscopy also showed significant changes in the cancer tissues in the phosphatidylcholine and sphingomyelin. Interestingly, FTIR spectra after Kramers-Kronig transformations showed signals only for three peaks which corresponded to the vibrations of lipid function groups. Adjustment of the Lorenz function for these three peaks showed that only in the case of cancerous tissues the number of matching lines is different, compared to the control and marginal tissues. Therefore, we assume that lipids could be a spectroscopic marker for brain tumor. Furthermore, principal component analysis (PCA) showed that chemical changes seen between cancer and control tissues are significant and it is possible to differentiate the infected tissue from the healthy one. Interestingly, the PCA analysis also showed that adjacent brain tissues have different chemical composition than the control tissues.
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Affiliation(s)
- J Depciuch
- Institute of Nuclear Physics, Polish Academy of Sciences, 31-342 Krakow, Poland.
| | - B Tołpa
- Department of Neurosurgery, Clinical Hospital Nr 2 in Rzeszow, Lwowska 60, 35-309, Poland
| | - P Witek
- Faculty of Mathematics and Natural Sciences, Centre of Innovation and Transfer of Natural Sciences and Engineering Knowledge, University of Rzeszow, Pigonia 1, 35-959 Rzeszow, Poland
| | - K Szmuc
- Faculty of Mathematics and Natural Sciences, Centre of Innovation and Transfer of Natural Sciences and Engineering Knowledge, University of Rzeszow, Pigonia 1, 35-959 Rzeszow, Poland
| | - E Kaznowska
- Department of Patomorphology, Chair of Morphological Sciences, Medical Faculty, University of Rzeszow, Kopisto 2a, 35-959, Poland
| | - M Osuchowski
- Department of Patomorphology, Chair of Morphological Sciences, Medical Faculty, University of Rzeszow, Kopisto 2a, 35-959, Poland
| | - P Król
- Department of Physical Education, University of Rzeszow, Towarnickiego 3, 35-959 Rzeszów, Poland
| | - J Cebulski
- Faculty of Mathematics and Natural Sciences, Centre of Innovation and Transfer of Natural Sciences and Engineering Knowledge, University of Rzeszow, Pigonia 1, 35-959 Rzeszow, Poland
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39
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Xiang S, Zhao D, Hao H, Wang XU, Li L, Yang T. α-Helical protein absorption at post-traumatic epileptic foci monitored by Fourier transform infrared mapping. J Biosci 2020; 45:55. [PMID: 32345781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Tissue analysis by Fourier transform infrared (FTIR) imaging can determine the biodistribution of molecules, without pre-analytical modification. We aimed to study the infrared spectroscopic changes of α-helical proteins at post-traumatic epileptic (PTE) foci by FTIR. FITR mapping was applied to detect α-helical proteins in rat brain tissue samples with post-traumatic epilepsy. Histological examination of brain sections showed that the rat model of PTE was successfully established. At the PTE foci, high α-helical absorption regions were evident, where the color difference and absorption were significantly different from those in the low-absorption regions. This provided a distinctive and characteristic pattern at the site of lesions. The use of FTIR imaging means that it is possible to measure the molecular structural changes resulting from PTE pathologies in tissues, providing a novel adjunct to conventional pathological diagnostic techniques.
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Affiliation(s)
- Siyang Xiang
- Center of Cooperative Innovation for Judicial Civilization, Beijing 100088, China
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40
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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] [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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41
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Zheng Q, Li J, Yang L, Zheng B, Wang J, Lv N, Luo J, Martin FL, Liu D, He J. Raman spectroscopy as a potential diagnostic tool to analyse biochemical alterations in lung cancer. Analyst 2019; 145:385-392. [PMID: 31844853 DOI: 10.1039/c9an02175b] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Patient survival remains poor even after diagnosis in lung cancer cases, and the molecular events resulting from lung cancer progression remain unclear. Raman spectroscopy could be used to noninvasively and accurately reveal the biochemical properties of biological tissues on the basis of their pathological status. This study aimed at probing biomolecular changes in lung cancer, using Raman spectroscopy as a potential diagnostic tool. Herein, biochemical alterations were evident in the Raman spectra (region of 600-1800 cm-1) in normal and cancerous lung tissues. The levels of saturated and unsaturated lipids and the protein-to-lipid, nucleic acid-to-lipid, and protein-to-nucleic acid ratios were significantly altered among malignant tissues compared to normal lung tissues. These biochemical alterations in tissues during neoplastic transformation have profound implications in not only the biochemical landscape of lung cancer progression but also cytopathological classification. Based on this spectroscopic approach, classification methods including k-nearest neighbour (kNN) and support vector machine (SVM) were successfully applied to cytopathologically diagnose lung cancer with an accuracy approaching 99%. The present results indicate that Raman spectroscopy is an excellent tool to biochemically interrogate and diagnose lung cancer.
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Affiliation(s)
- Qingfeng Zheng
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| | - Junyi Li
- State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China.
| | - Lin Yang
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Bo Zheng
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jiangcai Wang
- State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China.
| | - Ning Lv
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jianbin Luo
- State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China.
| | - Francis L Martin
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - Dameng Liu
- State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China.
| | - Jie He
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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42
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Abramczyk H, Imiela A, Brożek-Płuska B, Kopeć M, Surmacki J, Śliwińska A. Aberrant Protein Phosphorylation in Cancer by Using Raman Biomarkers. Cancers (Basel) 2019; 11:E2017. [PMID: 31847192 PMCID: PMC6966530 DOI: 10.3390/cancers11122017] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 12/03/2019] [Accepted: 12/11/2019] [Indexed: 12/30/2022] Open
Abstract
(1) Background: Novel methods are required for analysing post-translational modifications of protein phosphorylation by visualizing biochemical landscapes of proteins in human normal and cancerous tissues and cells. (2) Methods: A label-free Raman method is presented for detecting spectral changes that arise in proteins due to phosphorylation in the tissue of human breasts, small intestines, and brain tumours, as well as in the normal human astrocytes and primary glioblastoma U-87 MG cell lines. Raman spectroscopy and Raman imaging are effective tools for monitoring and analysing the vibrations of functional groups involved in aberrant phosphorylation in cancer without any phosphorecognition of tag molecules. (3) Results: Our results based on 35 fresh human cancer and normal tissues prove that the aberrant tyrosine phosphorylation monitored by the unique spectral signatures of Raman vibrations is a universal characteristic in the metabolic regulation in different types of cancers. Overexpressed tyrosine phosphorylation in the human breast, small intestine and brain tissues and in the human primary glioblastoma U-87 MG cell line was monitored by using Raman biomarkers. (4) We showed that the bands at 1586 cm-1 and 829 cm-1, corresponding to phosphorylated tyrosine, play a pivotal role as a Raman biomarker of the phosphorylation status in aggressive cancers. We found that the best Raman biomarker of phosphorylation is the 1586/829 ratio showing the statistical significance at p Values of ≤ 0.05. (5) Conclusions: Raman spectroscopy and imaging have the potential to be used as screening functional assays to detect phosphorylated target proteins and will help researchers to understand the role of phosphorylation in cellular processes and cancer progression. The abnormal and excessive high level of tyrosine phosphorylation in cancer samples compared with normal samples was found in the cancerous human tissue of breasts, small intestines and brain tumours, as well as in the mitochondria and lipid droplets of the glioblastoma U-87 MG cell line. Detailed insights are presented into the intracellular oncogenic metabolic pathways mediated by phosphorylated tyrosine.
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Affiliation(s)
- Halina Abramczyk
- Laboratory of Laser Molecular Spectroscopy, Institute of Applied Radiation Chemistry, Faculty of Chemistry, Lodz University of Technology, Wroblewskiego 15, 93-590 Lodz, Poland; (A.I.); (B.B.-P.); (M.K.); (J.S.)
| | - Anna Imiela
- Laboratory of Laser Molecular Spectroscopy, Institute of Applied Radiation Chemistry, Faculty of Chemistry, Lodz University of Technology, Wroblewskiego 15, 93-590 Lodz, Poland; (A.I.); (B.B.-P.); (M.K.); (J.S.)
| | - Beata Brożek-Płuska
- Laboratory of Laser Molecular Spectroscopy, Institute of Applied Radiation Chemistry, Faculty of Chemistry, Lodz University of Technology, Wroblewskiego 15, 93-590 Lodz, Poland; (A.I.); (B.B.-P.); (M.K.); (J.S.)
| | - Monika Kopeć
- Laboratory of Laser Molecular Spectroscopy, Institute of Applied Radiation Chemistry, Faculty of Chemistry, Lodz University of Technology, Wroblewskiego 15, 93-590 Lodz, Poland; (A.I.); (B.B.-P.); (M.K.); (J.S.)
| | - Jakub Surmacki
- Laboratory of Laser Molecular Spectroscopy, Institute of Applied Radiation Chemistry, Faculty of Chemistry, Lodz University of Technology, Wroblewskiego 15, 93-590 Lodz, Poland; (A.I.); (B.B.-P.); (M.K.); (J.S.)
| | - Agnieszka Śliwińska
- Faculty of Medicine, Medical University of Lodz, Chair of Department of Nucleic Acids Biochemistry, Pomorska 251, 92-213 Lodz, Poland;
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Huefner A, Kuan WL, Mason SL, Mahajan S, Barker RA. Serum Raman spectroscopy as a diagnostic tool in patients with Huntington's disease. Chem Sci 2019; 11:525-533. [PMID: 32190272 PMCID: PMC7067270 DOI: 10.1039/c9sc03711j] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Accepted: 11/14/2019] [Indexed: 12/18/2022] Open
Abstract
Huntington's disease is an inherited fatal progressive neurodegenerative disorder. A possible new Raman ‘spectral’ biomarker was identified that uses a tiny drop of patients' blood serum; thus can have immense diagnostic and therapeutic implications.
Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by an abnormal CAG expansion in exon 1 of the huntingtin (HTT) gene. Given its genetic basis it is possible to study patients both in the pre-manifest and manifest stages of the condition. While disease onset can be modelled using CAG repeat size, there are no easily accessible biomarkers that can objectively track disease progression. Here, we employed a holistic approach using spectral profiles generated using both surface-enhanced Raman spectroscopy (SERS) and Raman Spectroscopy (RS), on the serum of healthy participants and HD patients covering a wide spectrum of disease stages. We found that there was both genotype- and gender-specific segregation on using the full range in the fingerprint region with both SERS and RS. On a more detailed interrogation using specific spectral intervals, SERS revealed significant correlations with disease progression, in particular progression from pre-manifest through to advanced HD was associated with serum molecules related to protein misfolding and nucleotide catabolism. Thus, this study shows the potential of Raman spectroscopy-based techniques for stratification of patients and, of SERS, in particular, to track disease status through provision of ‘spectral’ biomarkers in HD, with clinical applications for other diseases and trials looking at disease modifying therapies.
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Affiliation(s)
- Anna Huefner
- Department of Chemistry , University of Cambridge , Lensfield Road , Cambridge , CB2 1WE , UK.,John van Geest Centre for Brain Repair , the WT-MRC Cambridge Stem Cell Institute , University of Cambridge , Forvie Site, Robinson Way , Cambridge , CB2 0PY , UK .
| | - Wei-Li Kuan
- John van Geest Centre for Brain Repair , the WT-MRC Cambridge Stem Cell Institute , University of Cambridge , Forvie Site, Robinson Way , Cambridge , CB2 0PY , UK .
| | - Sarah L Mason
- John van Geest Centre for Brain Repair , the WT-MRC Cambridge Stem Cell Institute , University of Cambridge , Forvie Site, Robinson Way , Cambridge , CB2 0PY , UK .
| | - Sumeet Mahajan
- The Institute for Life Sciences , the School of Chemistry , University of Southampton , Highfield Campus , Southampton , SO17 1BJ , UK .
| | - Roger A Barker
- John van Geest Centre for Brain Repair , the WT-MRC Cambridge Stem Cell Institute , University of Cambridge , Forvie Site, Robinson Way , Cambridge , CB2 0PY , UK .
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Galli R, Meinhardt M, Koch E, Schackert G, Steiner G, Kirsch M, Uckermann O. Rapid Label-Free Analysis of Brain Tumor Biopsies by Near Infrared Raman and Fluorescence Spectroscopy-A Study of 209 Patients. Front Oncol 2019; 9:1165. [PMID: 31750251 PMCID: PMC6848276 DOI: 10.3389/fonc.2019.01165] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Accepted: 10/17/2019] [Indexed: 01/09/2023] Open
Abstract
In brain surgery, novel technologies are continuously developed to achieve better tumor delineation and maximize the extent of resection. Raman spectroscopy is an optical method that enables to retrieve a molecular signature of tissue biochemical composition in order to identify tumor and normal tissue. Here, the translation of Raman spectroscopy to the surgical practice for discerning a variety of different tumor entities from non-neoplastic brain parenchyma was investigated. Fresh unprocessed biopsies obtained from brain tumor surgery were analyzed over 1.5 years including all patients that gave consent. Measurements were performed with a Raman microscope by medical personnel as routine activity. The Raman and fluorescence signals of the acquired spectra were analyzed by principal component analysis, followed by supervised classification to discriminate non-tumor tissue vs. tumor and distinguish tumor entities. Histopathology of the measured biopsies was performed as reference. Classification led to the correct recognition of all non-neoplastic biopsies (7/7) and of 97% of the investigated tumor biopsies (195/202). For instance, GBM was recognized as tumor with a correct rate of 94% if primary, and of 100% if recurrent. Astrocytoma and oligodendroglioma were recognized as tumor with correct rates of 86 and 90%, respectively. All brain metastases, meningioma and schwannoma were correctly recognized as tumor and distinguished from non-neoplastic brain tissue. Furthermore, metastases were discerned from glioma with correct rate of 90%. Oligodendroglioma and astrocytoma IDH1-mutant, which differ in the presence of 1p/19q codeletion, were discerned with a correct rate of 81%. These results demonstrate the feasibility of rapid brain tumors recognition and extraction of diagnostic information by Raman spectroscopy, using a protocol that can be easily included in the routine surgical workflow.
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Affiliation(s)
- Roberta Galli
- Clinical Sensoring and Monitoring, Anesthesiology and Intensive Care Medicine, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Matthias Meinhardt
- Neuropathology, Institute of Pathology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Edmund Koch
- Clinical Sensoring and Monitoring, Anesthesiology and Intensive Care Medicine, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Gabriele Schackert
- Neurosurgery, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Gerald Steiner
- Clinical Sensoring and Monitoring, Anesthesiology and Intensive Care Medicine, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Matthias Kirsch
- Neurosurgery, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Ortrud Uckermann
- Neurosurgery, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
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Abstract
Abstract
A potential role of optical technologies in medicine including micro-Raman spectroscopy is diagnosis of bacteria, cells and tissues which is covered in this chapter. The main advantage of Raman-based methods to complement and augment diagnostic tools is that unsurpassed molecular specificity is achieved without labels and in a nondestructive way. Principles and applications of micro-Raman spectroscopy in the context of medicine will be described. First, Raman spectra of biomolecules representing proteins, nucleic acids, lipids and carbohydrates are introduced. Second, microbial applications are summarized with the focus on typing on species and strain level, detection of infections, antibiotic resistance and biofilms. Third, cytological applications are presented to classify single cells and study cell metabolism and drug–cell interaction. Fourth, applications to tissue characterization start with discussion of lateral resolution for Raman imaging followed by Raman-based detection of pathologies and combination with other modalities. Finally, an outlook is given to translate micro-Raman spectroscopy as a clinical tool to solve unmet needs in point-of-care applications and personalized treatment of diseases.
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46
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Duan P, Li J, Yang W, Li X, Long M, Feng X, Zhang Y, Chen C, Morais CLM, Martin FL, Luo J, Liu D, Xiong C. Fourier transform infrared and Raman-based biochemical profiling of different grades of pure foetal-type hepatoblastoma. JOURNAL OF BIOPHOTONICS 2019; 12:e201800304. [PMID: 30993892 DOI: 10.1002/jbio.201800304] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Revised: 04/05/2019] [Accepted: 04/07/2019] [Indexed: 06/09/2023]
Abstract
The biomolecular events resulting from the progression of hepatoblastoma remain to be elucidated. Fourier-transform infrared (FTIR) and Raman spectroscopies are capable of noninvasively and accurately capturing the biochemical properties of biological tissue from its pathological status. Our aim was to probe critial biomolecular changes of liver accompanying the progression of pure foetal hepatoblastoma (PFH) by FTIR and Raman spectroscopies. Herein, biochemical alterations were both evident in the FTIR spectra (regions of 3100-2800 cm-1 and 1800-900 cm-1 ) and the Raman spectra (region of 1800-400 cm-1 ) among normal, borderline and malignant liver tissues. Compared with normal tissues, the ratios of protein-to-lipid, α-helix-to-β-sheet, RNA-to-DNA, CH3 methyl-to-CH2 methylene, glucose-to-phospholipids, and unsaturated-to-saturated lipids intensities were significantly higher in malignant tissues, while the ratios of RNA-to-Amide II, DNA-to-Amide II, glycogen-to-cholesterol and Amide I-to-Amide II intensities were remarkably lower. These biochemical alterations in the transition from normal to malignant have profound implications not only for cyto-pathological classification but also for molecular understanding of PFH progression. The successive changes of the spectral characteristics have been shown to be consistent with the development of PFH, indicating that FTIR and Raman spectroscopies are excellent tools to interrogate the biochemical features of different grades of PFH.
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Affiliation(s)
- Peng Duan
- Institute of Reproductive Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Center for Reproductive Medicine, Xiangyang No. 1 People's Hospital, Hubei University of Medicine, Xiangyang, China
| | - Junyi Li
- State Key Laboratory of Tribology, Tsinghua University, Beijing, China
| | - Weiyingxue Yang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiandong Li
- Department of Clinical Laboratory, Taihe Hospital, Hubei University of Medicine, Shiyan, China
| | - Manman Long
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaobing Feng
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuge Zhang
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chunling Chen
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Camilo L M Morais
- Lancashire Teaching Hospitals NHS Trust, Preston, UK
- Biocel Ltd, Hull, UK
| | | | - Jianbin Luo
- State Key Laboratory of Tribology, Tsinghua University, Beijing, China
| | - Dameng Liu
- State Key Laboratory of Tribology, Tsinghua University, Beijing, China
| | - Chengliang Xiong
- Institute of Reproductive Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Center for Reproductive Medicine, Wuhan Tongji Reproductive Medicine Hospital, Wuhan, China
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Morais CLM, Paraskevaidi M, Cui L, Fullwood NJ, Isabelle M, Lima KMG, Martin-Hirsch PL, Sreedhar H, Trevisan J, Walsh MJ, Zhang D, Zhu YG, Martin FL. Standardization of complex biologically derived spectrochemical datasets. Nat Protoc 2019; 14:1546-1577. [PMID: 30953040 DOI: 10.1038/s41596-019-0150-x] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2018] [Accepted: 02/12/2019] [Indexed: 12/17/2022]
Abstract
Spectroscopic techniques such as Fourier-transform infrared (FTIR) spectroscopy are used to study interactions of light with biological materials. This interaction forms the basis of many analytical assays used in disease screening/diagnosis, microbiological studies, and forensic/environmental investigations. Advantages of spectrochemical analysis are its low cost, minimal sample preparation, non-destructive nature and substantially accurate results. However, an urgent need exists for repetition and validation of these methods in large-scale studies and across different research groups, which would bring the method closer to clinical and/or industrial implementation. For this to succeed, it is important to understand and reduce the effect of random spectral alterations caused by inter-individual, inter-instrument and/or inter-laboratory variations, such as variations in air humidity and CO2 levels, and aging of instrument parts. Thus, it is evident that spectral standardization is critical to the widespread adoption of these spectrochemical technologies. By using calibration transfer procedures, in which the spectral response of a secondary instrument is standardized to resemble the spectral response of a primary instrument, different sources of variation can be normalized into a single model using computational-based methods, such as direct standardization (DS) and piecewise direct standardization (PDS); therefore, measurements performed under different conditions can generate the same result, eliminating the need for a full recalibration. Here, we have constructed a protocol for model standardization using different transfer technologies described for FTIR spectrochemical applications. This is a critical step toward the construction of a practical spectrochemical analysis model for daily routine analysis, where uncertain and random variations are present.
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Affiliation(s)
- Camilo L M Morais
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK.
| | - Maria Paraskevaidi
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK.
| | - Li Cui
- Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, China
| | - Nigel J Fullwood
- Division of Biomedical and Life Sciences, Faculty of Health and Medicine, Lancaster University, Lancaster, UK
| | - Martin Isabelle
- Spectroscopy Products Division, Renishaw plc., New Mills, Wotton-under-Edge, UK
| | - Kássio M G Lima
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Pierre L Martin-Hirsch
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation, Preston, UK
| | - Hari Sreedhar
- Department of Pathology, University of Illinois at Chicago, Chicago, IL, USA
| | - Júlio Trevisan
- Institute of Astronomy, Geophysics and Atmospheric Sciences, University of São Paulo, São Paulo, Brazil
| | - Michael J Walsh
- Department of Pathology, University of Illinois at Chicago, Chicago, IL, USA
| | - Dayi Zhang
- School of Environment, Tsinghua University, Beijing, China
| | - Yong-Guan Zhu
- Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, China
| | - Francis L Martin
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK.
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48
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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 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] [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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49
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Duan P, Liu B, Morais CLM, Zhao J, Li X, Tu J, Yang W, Chen C, Long M, Feng X, Martin FL, Xiong C. 4-Nonylphenol effects on rat testis and sertoli cells determined by spectrochemical techniques coupled with chemometric analysis. CHEMOSPHERE 2019; 218:64-75. [PMID: 30469005 DOI: 10.1016/j.chemosphere.2018.11.086] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Revised: 11/11/2018] [Accepted: 11/12/2018] [Indexed: 06/09/2023]
Abstract
Herein, vibrational spectroscopy has been applied for qualitative identification of biomolecular alterations that occur in cells and tissues following chemical treatment. Towards this end, we combined attenuated total reflection Fourier-transform infrared (ATR-FTIR) and Raman spectroscopy to assess testicular toxicology after 4-nonylphenol (NP) exposure, an estrogenic endocrine disruptor affecting testicular function in rats and other species. Rats aged 21, 35 or 50 days received NP at intra-peritoneal doses of 0, 25, 50 or 100 mg/kg for 20 consecutive days. Primary Sertoli cells (SCs) were treated with NP at various concentrations (0, 2.5, 5, 10 or 20 μM) for 12 h. Post-exposure, testicular cells, interstitial tissue and SCs were interrogated respectively using spectrochemical techniques coupled with multivariate analysis. Distinct biomolecular segregation between the NP-exposed samples vs. control were observed based on infrared (IR) spectral regions of 3200-2800 cm-1 and 1800-900 cm-1, and the Raman spectral region of 1800-900 cm-1. For in vivo experiments, the main wavenumbers responsible for segregation varied significantly among the three age classes. The main IR and Raman band differences between NP-exposed and control groups were observed for Amide (proteins), lipids and DNA/RNA. An interesting finding was that the peptide aggregation level, Amide Ӏ-to-Amide II ratio, and phosphate-to-carbohydrate ratio were considerably reduced in ex vivo NP-exposed testicular cells or SCs in vitro. This study demonstrates that ATR-FTIR and Raman spectroscopy techniques can be applied towards analysing NP-induced testicular biomolecular alterations.
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Affiliation(s)
- Peng Duan
- Family Planning Research Institute, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China; Center for Reproductive Medicine, Xiangyang No. 1 People's Hospital, Hubei University of Medicine, Xiangyang, 441000, China
| | - Bisen Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Camilo L M Morais
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - Jing Zhao
- Department of Epidemiology and Health Statistics, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan, 430030, China
| | - Xiandong Li
- Department of Clinical Laboratory, Taihe Hospital, Hubei University of Medicine, Shiyan, 442000, China
| | - Jian Tu
- Reproductive Medicine Center, Maternal and Child Health Care Hospital of Yueyang City, Yueyang, 414000, China
| | - Weiyingxue Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Chunling Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Manman Long
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaobing Feng
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Francis L Martin
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK.
| | - Chengliang Xiong
- Family Planning Research Institute, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China; Center for Reproductive Medicine, Wuhan Tongji Reproductive Medicine Hospital, 128 Sanyang Road, Wuhan, 430013, China.
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50
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Skolik P, McAinsh MR, Martin FL. ATR-FTIR spectroscopy non-destructively detects damage-induced sour rot infection in whole tomato fruit. PLANTA 2019; 249:925-939. [PMID: 30488286 DOI: 10.1007/s00425-018-3060-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2018] [Accepted: 11/23/2018] [Indexed: 05/20/2023]
Abstract
ATR-FTIR spectroscopy with subsequent multivariate analysis non-destructively identifies plant-pathogen interactions during disease progression, both directly and indirectly, through alterations in the spectral fingerprint. Plant-environment interactions are essential to understanding crop biology, optimizing crop use, and minimizing loss to ensure food security. Damage-induced pathogen infection of delicate fruit crops such as tomato (Solanum lycopersicum) are therefore important processes related to crop biology and modern horticulture. Fruit epidermis as a first barrier at the plant-environment interface, is specifically involved in environmental interactions and often shows substantial structural and functional changes in response to unfavourable conditions. Methods available to investigate such systems in their native form, however, are limited by often required and destructive sample preparation, or scarce amounts of molecular level information. To explore biochemical changes and evaluate diagnostic potential for damage-induced pathogen infection of cherry tomato (cv. Piccolo) both directly and indirectly, mid-infrared (MIR) spectroscopy was applied in combination with exploratory multivariate analysis. ATR-FTIR fingerprint spectra (1800-900 cm-1) of healthy, damaged or sour rot-infected tomato fruit were acquired and distinguished using principal component analysis and linear discriminant analysis (PCA-LDA). Main biochemical constituents of healthy tomato fruit epidermis are characterized while multivariate analysis discriminated subtle biochemical changes distinguishing healthy tomato from damaged, early or late sour rot-infected tomato indirectly based solely on changes in the fruit epidermis. Sour rot causing agent Geotrichum candidum was detected directly in vivo and characterized based on spectral features distinct from tomato fruit. Diagnostic potential for indirect pathogen detection based on tomato fruit skin was evaluated using the linear discriminant classifier (PCA-LDC). Exploratory and diagnostic analysis of ATR-FTIR spectra offers biological insights and detection potential for intact plant-pathogen systems as they are found in horticultural industries.
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Affiliation(s)
- Paul Skolik
- Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | - Martin R McAinsh
- Lancaster Environment Centre, Lancaster University, Lancaster, UK.
| | - Francis L Martin
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK.
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