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Shree P, Aggarwal Y, Kumar M, Majhee L, Singh NN, Prakash O, Chandra A, Mahuli SA, Shamsi S, Rai A. Saliva Based Diagnostic Prediction of Oral Squamous Cell Carcinoma using FTIR Spectroscopy. Indian J Otolaryngol Head Neck Surg 2024; 76:2282-2289. [PMID: 38883442 PMCID: PMC11169329 DOI: 10.1007/s12070-023-04294-z] [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: 10/07/2023] [Accepted: 10/14/2023] [Indexed: 06/18/2024] Open
Abstract
Oral cancer ranks as the sixth most prevalent form of cancer worldwide, presenting a significant public health concern. According to the World Health Organization (WHO), within a 5-year period following diagnosis, the mortality rate among oral cancer patients of all stages stands at 45%. In this study, a total of 60 patients divided into 2 groups were recruited. Group A included 30 histo-pathologically confirmed OSCC patients and Group B included 30 healthy controls. A standardized procedure was followed to collect saliva samples. FTIR spectroscopy was done for all the saliva samples collected from both Group A and B. An IR Prestige-21 (Shimadzu Corp, Japan) spectrometer was used to record IR spectra in the 40-4000 cm-1 range SVM classifier was applied in the classification of disease state from normal subjects using FTIR data. The peaks were identified at wave no 1180 cm-1, 1230 cm-1, 1340 cm-1, 1360 cm-1, 1420 cm-1, 1460 cm-1, 1500 cm-1, 1540 cm-1, 1560 cm-1, and 1637 cm-1. The observed results of SVM demonstrated the accuracy of 91.66% in the classification of Cancer tissues from the normal subjects with sensitivity of 83.33% while specificity and precision of 100.0%. The development of oral cancer leads to noticeable alterations in the secondary structure of proteins. These findings emphasize the promising use of ATR-FTIR platforms in conjunction with machine learning as a reliable, non-invasive, reagent-free, and highly sensitive method for screening and monitoring individuals with oral cancer.
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Affiliation(s)
- Priya Shree
- Dental College, Rajendra Institute of Medical Sciences (RIMS), Bariatu, Ranchi, Jharkhand 834009 India
| | - Yogendra Aggarwal
- Department of Bioengineering and Biotechnology, Birla Institute of Technology Mesra, Ranchi, India
| | - Manish Kumar
- Department of Bioengineering, Birla Institute of Technology, Mesra, Ranchi, 835215 India
| | - Lakhan Majhee
- Department of Pharmacology, Rajendra Institute of Medical Sciences, Ranchi, India
| | - Narendra Nath Singh
- Oral Pathology, Microbiology and Forensic Odontology, Dental College, Rajendra Institute of Medical Sciences (RIMS), Bariatu, Ranchi, 834009 India
| | - Om Prakash
- Oral and Maxillofacial Pathology, Dental College, Rajendra Institute of Medical Sciences (RIMS), Bariatu, Ranchi, 834009 India
| | - Akhilesh Chandra
- Department of Oral Pathology and Microbiology, Faculty of Dental Sciences, Banaras Hindu University, Varanasi, India
| | - Simpy Amit Mahuli
- Dental College, Rajendra Institute of Medical Sciences (RIMS), Bariatu, Ranchi, 834009 India
| | - Shoa Shamsi
- Dental College, Rajendra Institute of Medical Sciences (RIMS), Bariatu, Ranchi, 834009 India
| | - Arpita Rai
- Dental College, Rajendra Institute of Medical Sciences (RIMS), Bariatu, Ranchi, Jharkhand 834009 India
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Zupančič B, Ugwoke CK, Abdelmonaem MEA, Alibegović A, Cvetko E, Grdadolnik J, Šerbec A, Umek N. Exploration of macromolecular phenotype of human skeletal muscle in diabetes using infrared spectroscopy. Front Endocrinol (Lausanne) 2023; 14:1308373. [PMID: 38189046 PMCID: PMC10769457 DOI: 10.3389/fendo.2023.1308373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 11/29/2023] [Indexed: 01/09/2024] Open
Abstract
Introduction The global burden of diabetes mellitus is escalating, and more efficient investigative strategies are needed for a deeper understanding of underlying pathophysiological mechanisms. The crucial role of skeletal muscle in carbohydrate and lipid metabolism makes it one of the most susceptible tissues to diabetes-related metabolic disorders. In tissue studies, conventional histochemical methods have several technical limitations and have been shown to inadequately characterise the biomolecular phenotype of skeletal muscle to provide a holistic view of the pathologically altered proportions of macromolecular constituents. Materials and methods In this pilot study, we examined the composition of five different human skeletal muscles from male donors diagnosed with type 2 diabetes and non-diabetic controls. We analysed the lipid, glycogen, and collagen content in the muscles in a traditional manner with histochemical assays using different staining techniques. This served as a reference for comparison with the unconventional analysis of tissue composition using Fourier-transform infrared spectroscopy as an alternative methodological approach. Results A thorough chemometric post-processing of the infrared spectra using a multi-stage spectral decomposition allowed the simultaneous identification of various compositional details from a vibrational spectrum measured in a single experiment. We obtained multifaceted information about the proportions of the different macromolecular constituents of skeletal muscle, which even allowed us to distinguish protein constituents with different structural properties. The most important methodological steps for a comprehensive insight into muscle composition have thus been set and parameters identified that can be used for the comparison between healthy and diabetic muscles. Conclusion We have established a methodological framework based on vibrational spectroscopy for the detailed macromolecular analysis of human skeletal muscle that can effectively complement or may even serve as an alternative to histochemical assays. As this is a pilot study with relatively small sample sets, we remain cautious at this stage in drawing definitive conclusions about diabetes-related changes in skeletal muscle composition. However, the main focus and contribution of our work has been to provide an alternative, simple and efficient approach for this purpose. We are confident that we have achieved this goal and have brought our methodology to a level from which it can be successfully transferred to a large-scale study that allows the effects of diabetes on skeletal muscle composition and the interrelationships between the macromolecular tissue alterations due to diabetes to be investigated.
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Affiliation(s)
- Barbara Zupančič
- Laboratory for Molecular Structural Dynamics, Theory Department, National Institute of Chemistry, Ljubljana, Slovenia
| | | | - Mohamed Elwy Abdelhamed Abdelmonaem
- Laboratory for Molecular Structural Dynamics, Theory Department, National Institute of Chemistry, Ljubljana, Slovenia
- Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | - Armin Alibegović
- Department of Forensic Medicine and Deontology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Erika Cvetko
- Institute of Anatomy, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Jože Grdadolnik
- Laboratory for Molecular Structural Dynamics, Theory Department, National Institute of Chemistry, Ljubljana, Slovenia
| | - Anja Šerbec
- Institute of Anatomy, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Nejc Umek
- Institute of Anatomy, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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Bhargava R. Digital Histopathology by Infrared Spectroscopic Imaging. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2023; 16:205-230. [PMID: 37068745 PMCID: PMC10408309 DOI: 10.1146/annurev-anchem-101422-090956] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Infrared (IR) spectroscopic imaging records spatially resolved molecular vibrational spectra, enabling a comprehensive measurement of the chemical makeup and heterogeneity of biological tissues. Combining this novel contrast mechanism in microscopy with the use of artificial intelligence can transform the practice of histopathology, which currently relies largely on human examination of morphologic patterns within stained tissue. First, this review summarizes IR imaging instrumentation especially suited to histopathology, analyses of its performance, and major trends. Second, an overview of data processing methods and application of machine learning is given, with an emphasis on the emerging use of deep learning. Third, a discussion on workflows in pathology is provided, with four categories proposed based on the complexity of methods and the analytical performance needed. Last, a set of guidelines, termed experimental and analytical specifications for spectroscopic imaging in histopathology, are proposed to help standardize the diversity of approaches in this emerging area.
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Affiliation(s)
- Rohit Bhargava
- Department of Bioengineering; Department of Electrical and Computer Engineering; Department of Mechanical Science and Engineering; Department of Chemical and Biomolecular Engineering; Department of Chemistry; Cancer Center at Illinois; and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA;
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Großerueschkamp F, Jütte H, Gerwert K, Tannapfel A. Advances in Digital Pathology: From Artificial Intelligence to Label-Free Imaging. Visc Med 2021; 37:482-490. [PMID: 35087898 DOI: 10.1159/000518494] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 07/14/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Digital pathology, in its primary meaning, describes the utilization of computer screens to view scanned histology slides. Digitized tissue sections can be easily shared for a second opinion. In addition, it allows tissue image analysis using specialized software to identify and measure events previously observed by a human observer. These tissue-based readouts were highly reproducible and precise. Digital pathology has developed over the years through new technologies. Currently, the most discussed development is the application of artificial intelligence to automatically analyze tissue images. However, even new label-free imaging technologies are being developed to allow imaging of tissues by means of their molecular composition. SUMMARY This review provides a summary of the current state-of-the-art and future digital pathologies. Developments in the last few years have been presented and discussed. In particular, the review provides an outlook on interesting new technologies (e.g., infrared imaging), which would allow for deeper understanding and analysis of tissue thin sections beyond conventional histopathology. KEY MESSAGES In digital pathology, mathematical methods are used to analyze images and draw conclusions about diseases and their progression. New innovative methods and techniques (e.g., label-free infrared imaging) will bring significant changes in the field in the coming years.
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Affiliation(s)
- Frederik Großerueschkamp
- Center for Protein Diagnostics (PRODI), Biospectroscopy, Ruhr University Bochum, Bochum, Germany.,Department of Biophysics, Faculty of Biology and Biotechnology, Ruhr University Bochum, Bochum, Germany
| | - Hendrik Jütte
- Center for Protein Diagnostics (PRODI), Biospectroscopy, Ruhr University Bochum, Bochum, Germany.,Institute of Pathology, Ruhr University Bochum, Bochum, Germany
| | - Klaus Gerwert
- Center for Protein Diagnostics (PRODI), Biospectroscopy, Ruhr University Bochum, Bochum, Germany.,Department of Biophysics, Faculty of Biology and Biotechnology, Ruhr University Bochum, Bochum, Germany
| | - Andrea Tannapfel
- Center for Protein Diagnostics (PRODI), Biospectroscopy, Ruhr University Bochum, Bochum, Germany.,Institute of Pathology, Ruhr University Bochum, Bochum, Germany
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Vermassen T, Himpe J, Coopman R, Van Praet C, Lumen N, Rottey S, Delanghe J. Prognostic Features of Near-Infrared Spectroscopy Following Primary Radical Prostatectomy. Cancers (Basel) 2021; 13:cancers13236034. [PMID: 34885144 PMCID: PMC8656494 DOI: 10.3390/cancers13236034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 11/25/2021] [Accepted: 11/25/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Only a few biomarkers have been evaluated for their prognostic value with regard to biochemical recurrence (BCR) following primary radical prostatectomy. We explored the possibilities of using near-infrared (NIR) spectroscopy as a prognostic biomarker for BCR-free survival (BCR-FS). METHODS Tissue specimens from 82 prostate cancer patients were obtained. Formalin-fixed paraffin-embedded slides (hematoxylin-eosin-stained) were analyzed using NIR spectroscopy. Prognostic features for BCR-FS were determined following normalization of the spectra. RESULTS Several differences were found throughout the NIR spectrum for the patients with or without BCR, for both the first derivative and second derivative of the NIR spectrum. Following categorization and Cox regression analysis, spectral regions at 5236 cm-1 (first derivative; median BCR-FS not reached versus 3.2 years; HRhigh = 0.18 [0.08-0.39]; and p < 0.0001) and at 5956 cm-1 (second derivative; median BCR-FS not reached versus 3.8 years; HRlow = 0.22 [0.10-0.48]; and p = 0.0002) showed prognostic properties for BCR-FS. The combination of both parameters further increased the prognostic value of NIR (p < 0.0001). CONCLUSIONS We demonstrated NIR spectral variations between patients with or without BCR, which have been shown to have prognostic value. This easy-to-use technique could possibly further improve post-primary radical prostatectomy monitoring and swift referral to adjuvant local therapies. Further elaboration is highly recommended to fully elucidate these variations and to gain a deeper insight into the changing chemical and physical compositions of the prostate tumor architecture.
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Affiliation(s)
- Tijl Vermassen
- Department of Medical Oncology, University Hospital Ghent, 9000 Ghent, Belgium;
- Correspondence: ; Tel.: +32-9-332-5449
| | - Jonas Himpe
- Department of Clinical Chemistry, Microbiology and Immunology, Ghent University, 9000 Ghent, Belgium; (J.H.); (J.D.)
| | - Renaat Coopman
- Department of Plastic, Reconstructive and Aesthetic Surgery, University Hospital Ghent, 9000 Ghent, Belgium;
| | - Charles Van Praet
- Department of Urology, University Hospital Ghent, 9000 Ghent, Belgium; (C.V.P.); (N.L.)
| | - Nicolaas Lumen
- Department of Urology, University Hospital Ghent, 9000 Ghent, Belgium; (C.V.P.); (N.L.)
| | - Sylvie Rottey
- Department of Medical Oncology, University Hospital Ghent, 9000 Ghent, Belgium;
| | - Joris Delanghe
- Department of Clinical Chemistry, Microbiology and Immunology, Ghent University, 9000 Ghent, Belgium; (J.H.); (J.D.)
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Tang J, Henderson A, Gardner P. Exploring AdaBoost and Random Forests machine learning approaches for infrared pathology on unbalanced data sets. Analyst 2021; 146:5880-5891. [PMID: 34570844 DOI: 10.1039/d0an02155e] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
The use of infrared spectroscopy to augment decision-making in histopathology is a promising direction for the diagnosis of many disease types. Hyperspectral images of healthy and diseased tissue, generated by infrared spectroscopy, are used to build chemometric models that can provide objective metrics of disease state. It is important to build robust and stable models to provide confidence to the end user. The data used to develop such models can have a variety of characteristics which can pose problems to many model-building approaches. Here we have compared the performance of two machine learning algorithms - AdaBoost and Random Forests - on a variety of non-uniform data sets. Using samples of breast cancer tissue, we devised a range of training data capable of describing the problem space. Models were constructed from these training sets and their characteristics compared. In terms of separating infrared spectra of cancerous epithelium tissue from normal-associated tissue on the tissue microarray, both AdaBoost and Random Forests algorithms were shown to give excellent classification performance (over 95% accuracy) in this study. AdaBoost models were more robust when datasets with large imbalance were provided. The outcomes of this work are a measure of classification accuracy as a function of training data available, and a clear recommendation for choice of machine learning approach.
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Affiliation(s)
- Jiayi Tang
- Department of Chemical Engineering and Analytical Science, Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
| | - Alex Henderson
- Department of Chemical Engineering and Analytical Science, Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
| | - Peter Gardner
- Department of Chemical Engineering and Analytical Science, Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
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Araújo R, Ramalhete L, Paz H, Ladeira C, Calado CRC. A new method to predict genotoxic effects based on serum molecular profile. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 255:119680. [PMID: 33744838 DOI: 10.1016/j.saa.2021.119680] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 02/19/2021] [Accepted: 03/01/2021] [Indexed: 05/11/2023]
Abstract
It is critical to develop new methods to assess genotoxic effects in human biomonitoring since the conventional methods are usually laborious, time-consuming, and expensive. It is aimed to evaluate if the analysis of a drop of serum by Fourier Transform Infrared spectroscopy, allow to assess genotoxic effects in occupational exposure to cytostatic drugs in hospital professionals, as obtained by the lymphocyte cytokinesis-block micronucleus assay. It was considered peripheral blood from hospital professionals exposed to cytostatic drugs (n = 22) and from a non-exposed group (n = 36). It was observed that workers occupationally exposed presented a higher number of micronuclei (p < 0.05) in lymphocytes, in relation to the non-exposed group. The serum Fourier Transform Infrared spectra from exposed workers presented diverse different peaks (p < 0.01) in relation to the non-exposed group. The hierarchical cluster analysis of serum spectra separated serum samples of the exposed group from the non-exposed group with 61% sensitivity and 88% specificity. A support vector machine model of serum spectra enables to predict exposure with high accuracy (0.91), precision (0.89), sensitivity (0.86), F1 score (0.87) and AUC (0.96). Therefore, Fourier Transform Infrared spectroscopic analysis of a drop of serum enabled to predict in a rapid and simple mode the genotoxic effects of cytostatic drugs. The method presents therefore potential for high-dimension screening of exposure of genotoxic substances, due to its simplicity and rapid setup mode.
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Affiliation(s)
- Rúben Araújo
- ISEL - Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal.
| | - Luís Ramalhete
- ISEL - Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal; CSTL-T - Centro de Sangue e da Transplantação de Lisboa - Instituto Português do Sangue e Transplantação, IP, Alameda das Linhas de Torres, n°117, 1769-001 Lisboa, Portugal
| | - Hélder Paz
- ISEL - Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
| | - Carina Ladeira
- H&TRC - Health & Technology Research Center, Escola Superior de Tecnologia da Saúde (ESTeSL), Instituto Politécnico de Lisboa, Avenida D. João II, lote 4.69.01, Parque das Nações, 1990-096 Lisboa, Portugal; NOVA National School of Public Health, Public Health Research Centre, Universidade NOVA de Lisboa, Lisbon, Portugal; Comprehensive Health Research Center (CHRC), Universidade NOVA de Lisboa, Portugal
| | - Cecília R C Calado
- ISEL - Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal; CIMOSM, ISEL - Centro de Investigação em Modelação e Optimização de Sistemas Multifuncionais, ISEL, Portugal
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Discrimination of malignant from benign thyroid lesions through neural networks using FTIR signals obtained from tissues. Anal Bioanal Chem 2021; 413:2163-2180. [PMID: 33569645 DOI: 10.1007/s00216-021-03183-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 01/11/2021] [Accepted: 01/18/2021] [Indexed: 10/22/2022]
Abstract
The current gold standard in cancer diagnosis-the microscopic examination of hematoxylin and eosin (H&E)-stained biopsies-is prone to bias since it greatly relies on visual examination. Hence, there is a need to develop a more sensitive and specific method for diagnosing cancer. Here, Fourier transform infrared (FTIR) spectroscopy of thyroid tumors (n = 164; 76 malignant, 88 benign) was performed and five (5) neural network (NN) models were designed to discriminate the obtained spectral data. PCA-LDA was used as classical benchmark for comparison. Each NN model was evaluated using a stratified 10-fold cross-validation method to avoid overfitting, and the performance metrics-accuracy, area under the curve (AUC), positive predictive value (PPV), negative predictive value (NPV), specificity rate (SR), and recall rate (RR)-were averaged for comparison. All NN models were able to perform excellently as classifiers, and all were able to surpass the LDA model in terms of accuracy. Among the NN models, the RNN model performed best, having an AUC of 95.29% ± 6.08%, an accuracy of 98.06% ± 2.87%, a PPV of 98.57% ± 4.52%, a NPV of 93.18% ± 7.93%, a SR value of 98.89% ± 3.51%, and a RR value of 91.25% ± 10.29%. The RNN model outperformed the LDA model for all metrics except for the AUC, NPV, and RR. In conclusion, NN-based tools were able to predict thyroid cancer based on infrared spectroscopy of tissues with a high level of diagnostic performance in comparison to the gold standard.
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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: 10] [Impact Index Per Article: 2.5] [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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Vibrational Spectroscopy for In Vitro Monitoring Stem Cell Differentiation. Molecules 2020; 25:molecules25235554. [PMID: 33256146 PMCID: PMC7729886 DOI: 10.3390/molecules25235554] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Revised: 11/21/2020] [Accepted: 11/23/2020] [Indexed: 12/12/2022] Open
Abstract
Stem cell technology has attracted considerable attention over recent decades due to its enormous potential in regenerative medicine and disease therapeutics. Studying the underlying mechanisms of stem cell differentiation and tissue generation is critical, and robust methodologies and different technologies are required. Towards establishing improved understanding and optimised triggering and control of differentiation processes, analytical techniques such as flow cytometry, immunohistochemistry, reverse transcription polymerase chain reaction, RNA in situ hybridisation analysis, and fluorescence-activated cell sorting have contributed much. However, progress in the field remains limited because such techniques provide only limited information, as they are only able to address specific, selected aspects of the process, and/or cannot visualise the process at the subcellular level. Additionally, many current analytical techniques involve the disruption of the investigation process (tissue sectioning, immunostaining) and cannot monitor the cellular differentiation process in situ, in real-time. Vibrational spectroscopy, as a label-free, non-invasive and non-destructive analytical technique, appears to be a promising candidate to potentially overcome many of these limitations as it can provide detailed biochemical fingerprint information for analysis of cells, tissues, and body fluids. The technique has been widely used in disease diagnosis and increasingly in stem cell technology. In this work, the efforts regarding the use of vibrational spectroscopy to identify mechanisms of stem cell differentiation at a single cell and tissue level are summarised. Both infrared absorption and Raman spectroscopic investigations are explored, and the relative merits, and future perspectives of the techniques are discussed.
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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: 22] [Impact Index Per Article: 5.5] [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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12
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Bangaoil R, Santillan A, Angeles LM, Abanilla L, Lim A, Ramos MC, Fellizar A, Guevarra L, Albano PM. ATR-FTIR spectroscopy as adjunct method to the microscopic examination of hematoxylin and eosin-stained tissues in diagnosing lung cancer. PLoS One 2020; 15:e0233626. [PMID: 32469931 PMCID: PMC7259682 DOI: 10.1371/journal.pone.0233626] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 05/10/2020] [Indexed: 12/24/2022] Open
Abstract
Lung cancer remains the leading cause of cancer-related death worldwide. Since prognosis and treatment outcomes rely on fast and accurate diagnosis, there is a need for more cost-effective, sensitive, and specific method for lung cancer detection. Thus, this study aimed to determine the ability of ATR-FTIR in discriminating malignant from benign lung tissues and evaluate its concordance with H&E staining. Three (3) 5μm-thick sections were cut from formalin fixed paraffin embedded (FFPE) cell or tissue blocks from patients with lung lesions. The outer sections were H&E-stained and sent to two (2) pathologists to confirm the histopathologic diagnosis. The inner section was deparaffinized by standard xylene method and then subjected to ATR-FTIR analysis. Distinct spectral profiles that distinguished (p<0.05) one sample from another, called the "fingerprint region", were observed in five (5) peak patterns representing the amides, lipids, and nucleic acids. Principal component analysis and hierarchical cluster analysis evidently clustered the benign from malignant tissues. ATR-FTIR showed 97.73% sensitivity, 92.45% specificity, 94.85% accuracy, 91.49% positive predictive value and 98.00% negative predictive value in discriminating benign from malignant lung tissue. Further, strong agreement was observed between histopathologic readings and ATR-FTIR analysis. This study shows the potential of ATR-FTIR spectroscopy as a potential adjunct method to the gold standard, the microscopic examination of hematoxylin and eosin (H&E)-stained tissues, in diagnosing lung cancer.
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Affiliation(s)
- Ruth Bangaoil
- The Graduate School, University of Santo Tomas, Manila, Philippines
- Research Center for the Natural and Applied Sciences, University of Santo Tomas, Manila, Philippines
- University of Santo Tomas Hospital, Manila, Philippines
| | - Abegail Santillan
- The Graduate School, University of Santo Tomas, Manila, Philippines
- Research Center for the Natural and Applied Sciences, University of Santo Tomas, Manila, Philippines
| | - Lara Mae Angeles
- University of Santo Tomas Hospital, Manila, Philippines
- Faculty of Medicine and Surgery, University of Santo Tomas, Manila, Philippines
| | - Lorenzo Abanilla
- Divine Word Hospital, Tacloban City, Northern Leyte, Philippines
| | - Antonio Lim
- Divine Word Hospital, Tacloban City, Northern Leyte, Philippines
| | - Ma. Cristina Ramos
- The Graduate School, University of Santo Tomas, Manila, Philippines
- Research Center for the Natural and Applied Sciences, University of Santo Tomas, Manila, Philippines
- Mariano Marcos Memorial Hospital and Medical Center, Ilocos Norte, Philippines
| | - Allan Fellizar
- The Graduate School, University of Santo Tomas, Manila, Philippines
- Research Center for the Natural and Applied Sciences, University of Santo Tomas, Manila, Philippines
- College of Science, University of Santo Tomas, Manila, Philippines
| | - Leonardo Guevarra
- Research Center for the Natural and Applied Sciences, University of Santo Tomas, Manila, Philippines
- Faculty of Pharmacy, University of Santo Tomas, Manila, Philippines
| | - Pia Marie Albano
- The Graduate School, University of Santo Tomas, Manila, Philippines
- Research Center for the Natural and Applied Sciences, University of Santo Tomas, Manila, Philippines
- Mariano Marcos Memorial Hospital and Medical Center, Ilocos Norte, Philippines
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13
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Biofluid diagnostics by FTIR spectroscopy: A platform technology for cancer detection. Cancer Lett 2020; 477:122-130. [DOI: 10.1016/j.canlet.2020.02.020] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 01/31/2020] [Accepted: 02/14/2020] [Indexed: 12/19/2022]
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14
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Cameron JM, Butler HJ, Smith BR, Hegarty MG, Jenkinson MD, Syed K, Brennan PM, Ashton K, Dawson T, Palmer DS, Baker MJ. Developing infrared spectroscopic detection for stratifying brain tumour patients: glioblastoma multiforme vs. lymphoma. Analyst 2020; 144:6736-6750. [PMID: 31612875 DOI: 10.1039/c9an01731c] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Over a third of brain tumour patients visit their general practitioner more than five times prior to diagnosis in the UK, leading to 62% of patients being diagnosed as emergency presentations. Unfortunately, symptoms are non-specific to brain tumours, and the majority of these patients complain of headaches on multiple occasions before being referred to a neurologist. As there are currently no methods in place for the early detection of brain cancer, the affected patients' average life expectancy is reduced by 20 years. These statistics indicate that the current pathway is ineffective, and there is a vast need for a rapid diagnostic test. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy is sensitive to the hallmarks of cancer, as it analyses the full range of macromolecular classes. The combination of serum spectroscopy and advanced data analysis has previously been shown to rapidly and objectively distinguish brain tumour severity. Recently, a novel high-throughput ATR accessory has been developed, which could be cost-effective to the National Health Service in the UK, and valuable for clinical translation. In this study, 765 blood serum samples have been collected from healthy controls and patients diagnosed with various types of brain cancer, contributing to one of the largest spectroscopic studies to date. Three robust machine learning techniques - random forest, partial least squares-discriminant analysis and support vector machine - have all provided promising results. The novel high-throughput technology has been validated by separating brain cancer and non-cancer with balanced accuracies of 90% which is comparable to the traditional fixed diamond crystal methodology. Furthermore, the differentiation of brain tumour type could be useful for neurologists, as some are difficult to distinguish through medical imaging alone. For example, the highly aggressive glioblastoma multiforme and primary cerebral lymphoma can appear similar on magnetic resonance imaging (MRI) scans, thus are often misdiagnosed. Here, we report the ability of infrared spectroscopy to distinguish between glioblastoma and lymphoma patients, at a sensitivity and specificity of 90.1% and 86.3%, respectively. A reliable serum diagnostic test could avoid the need for surgery and speed up time to definitive chemotherapy and radiotherapy.
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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.
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15
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A Simple, Label-Free, and High-Throughput Method to Evaluate the Epigallocatechin-3-Gallate Impact in Plasma Molecular Profile. High Throughput 2020; 9:ht9020009. [PMID: 32283584 PMCID: PMC7349803 DOI: 10.3390/ht9020009] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 04/02/2020] [Accepted: 04/03/2020] [Indexed: 12/27/2022] Open
Abstract
Epigallocatechin-3-gallate (EGCG), the major catechin present in green tea, presents diverse appealing biological activities, such as antioxidative, anti-inflammatory, antimicrobial, and antiviral activities, among others. The present work evaluated the impact in the molecular profile of human plasma from daily consumption of 225 mg of EGCG for 90 days. Plasma from peripheral blood was collected from 30 healthy human volunteers and analyzed by high-throughput Fourier transform infrared spectroscopy. To capture the biochemical information while minimizing the interference of physical phenomena, several combinations of spectra pre-processing methods were evaluated by principal component analysis. The pre-processing method that led to the best class separation, that is, between the plasma spectral data collected at the beginning and after the 90 days, was a combination of atmospheric correction with a second derivative spectra. A hierarchical cluster analysis of second derivative spectra also highlighted the fact that plasma acquired before EGCG consumption presented a distinct molecular profile after the 90 days of EGCG consumption. It was also possible by partial least squares regression discriminant analysis to correctly predict all unlabeled plasma samples (not used for model construction) at both timeframes. We observed that the similarity in composition among the plasma samples was higher in samples collected after EGCG consumption when compared with the samples taken prior to EGCG consumption. Diverse negative peaks of the normalized second derivative spectra, associated with lipid and protein regions, were significantly affected (p < 0.001) by EGCG consumption, according to the impact of EGCG consumption on the patients’ blood, low density and high density lipoproteins ratio. In conclusion, a single bolus dose of 225 mg of EGCG, ingested throughout a period of 90 days, drastically affected plasma molecular composition in all participants, which raises awareness regarding prolonged human exposure to EGCG. Because the analysis was conducted in a high-throughput, label-free, and economic analysis, it could be applied to high-dimension molecular epidemiological studies to further promote the understanding of the effect of bio-compound consumption mode and frequency.
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16
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Deep Learning for Hyperspectral Image Analysis, Part II: Applications to Remote Sensing and Biomedicine. HYPERSPECTRAL IMAGE ANALYSIS 2020. [DOI: 10.1007/978-3-030-38617-7_4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
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17
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Rakib F, Ali CM, Yousuf M, Afifi M, Bhatt PR, Ullah E, Al-Saad K, Ali MHM. Investigation of Biochemical Alterations in Ischemic Stroke Using Fourier Transform Infrared Imaging Spectroscopy-A Preliminary Study. Brain Sci 2019; 9:brainsci9110293. [PMID: 31717715 PMCID: PMC6895834 DOI: 10.3390/brainsci9110293] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 10/20/2019] [Accepted: 10/22/2019] [Indexed: 12/26/2022] Open
Abstract
Objective: Brain damage, long-term disability and death are the dreadful consequences of ischemic stroke. It causes imbalance in the biochemical constituents that distorts the brain dynamics. Understanding the sub-cellular alterations associated with the stroke will contribute to deeper molecular understanding of brain plasticity and recovery. Current routine approaches examining lipid and protein biochemical changes post stoke can be difficult. Fourier Transform Infrared (FTIR) imaging spectroscopy can play a vital role in detecting these molecular alterations on a sub-cellular level due to its high spatial resolution, accuracy and sensitivity. This study investigates the biochemical and molecular changes in peri-infract zone (PIZ) (contiguous area not completely damaged by stroke) and ipsi-lesional white matter (WM) (right below the stroke and PIZ regions) nine weeks post photothrombotic ischemic stroke in rats. Materials and Methods: FTIR imaging spectroscopy and transmission electron microscopy (TEM) techniques were applied to investigate brain tissue samples while hematoxylin and eosin (H&E) stained images of adjacent sections were prepared for comparison and examination the morphological changes post stroke. Results: TEM results revealed shearing of myelin sheaths and loss of cell membrane, structure and integrity after ischemic stroke. FTIR results showed that ipsi-lesional PIZ and WM experienced reduction in total protein and total lipid content compared to contra-lesional hemisphere. The lipid/protein ratio reduced in PIZ and adjacent WM indicated lipid peroxidation, which results in lipid chain fragmentation and an increase in olefinic content. Protein structural change is observed in PIZ due to the shift from random coli and α-helical structures to β-sheet conformation. Conclusion: FTIR imaging bio-spectroscopy provide novel biochemical information at sub-cellular levels that be difficult to be obtained by routine approaches. The results suggest that successful therapeutic strategy that is based on administration of anti-oxidant therapy, which could reduce and prevent neurotoxicity by scavenging the lipid peroxidation products. This approach will mitigate tissue damage in chronic ischemic period. FTIR imaging bio-spectroscopy can be used as a powerful tool and offer new approach in stroke and neurodegenerative diseases research.
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Affiliation(s)
- Fazle Rakib
- Department of Chemistry and Earth Sciences, Qatar University, Doha 2713, Qatar; (F.R.); (C.M.A.); (M.A.); (P.R.B.)
| | - Carmen M. Ali
- Department of Chemistry and Earth Sciences, Qatar University, Doha 2713, Qatar; (F.R.); (C.M.A.); (M.A.); (P.R.B.)
| | - Mohammed Yousuf
- Central Laboratory Unit (CLU), Qatar University, Doha 2713, Qatar;
| | - Mohammed Afifi
- Department of Chemistry and Earth Sciences, Qatar University, Doha 2713, Qatar; (F.R.); (C.M.A.); (M.A.); (P.R.B.)
| | - Pooja R. Bhatt
- Department of Chemistry and Earth Sciences, Qatar University, Doha 2713, Qatar; (F.R.); (C.M.A.); (M.A.); (P.R.B.)
| | - Ehsan Ullah
- Qatar Computing Research Institute (QCRI), Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF), Education City, Doha 34110, Qatar;
| | - Khalid Al-Saad
- Department of Chemistry and Earth Sciences, Qatar University, Doha 2713, Qatar; (F.R.); (C.M.A.); (M.A.); (P.R.B.)
- Correspondence: (K.A.-S.); (M.H.M.A.)
| | - Mohamed H. M. Ali
- Diabetes Research Center, Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF), Doha 34110, Qatar
- Qatar National Library, Doha 5825, Qatar
- Correspondence: (K.A.-S.); (M.H.M.A.)
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18
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Mittal S, Bhargava R. A comparison of mid-infrared spectral regions on accuracy of tissue classification. Analyst 2019; 144:2635-2642. [PMID: 30839958 DOI: 10.1039/c8an01782d] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Infrared (IR) spectroscopic imaging, utilizing both the molecular and structural disease signatures, enables extensive profiling of tumors and their microenvironments. Here, we examine the relative merits of using either the fingerprint or the high frequency regions of the IR spectrum for tissue histopathology. We selected a complex model as a test case, evaluating both stromal and epithelial segmentation for various breast pathologies. IR spectral classification in each of these spectral windows is quantitatively assessed by estimating area under the curve (AUC) of the receiver operating characteristic curve (ROC) for pixel level accuracy and images for diagnostic ability. We found only small differences, though some that may be sufficiently important in diagnostic tasks to be clinically significant, between the two regions with the fingerprint region-based classifiers consistently emerging as more accurate. The work provides added evidence and comparison with fingerprint region, complex models, and previously untested tissue type (breast) - that the use of restricted spectral regions can provide high accuracy. Our study indicates that the fingerprint region is ideal for epithelial and stromal models to obtain high pixel level accuracies. Glass slides provide a limited spectral feature set but provides accurate information at the patient level.
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Affiliation(s)
- Shachi Mittal
- Department of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
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19
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An Innovative Platform Merging Elemental Analysis and Ftir Imaging for Breast Tissue Analysis. Sci Rep 2019; 9:9854. [PMID: 31285452 PMCID: PMC6614471 DOI: 10.1038/s41598-019-46056-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Accepted: 06/17/2019] [Indexed: 12/16/2022] Open
Abstract
Histopathology and immunohistology remain the gold standard for breast cancer diagnostic. Yet, these approaches do not usually provide a sufficiently detailed characterization of the pathology. The purpose of this work is to demonstrate for the first time that elemental analysis and Fourier transform infrared spectroscopy microscopic examination of breast tissue sections can be merged into one dataset to provide a single set of markers based on both organic molecules and inorganic trace elements. For illustrating the method, 6 mammary tissue sections were used. Fourier transform infrared (FTIR) spectroscopy images reported a fingerprint of the organic molecules present in the tissue section and laser ablation elemental analysis (LA-ICP-MS) images brought inorganic element profiles. The 6 tissue sections provided 31 106 and 150,000 spectra for FTIR and LA-ICP-MS spectra respectively. The results bring the proof of concept that breast tissue can be analyzed simultaneously by FTIR spectroscopy and laser ablation elemental analysis (LA-ICP-MS) to provide in both case reasonably high resolution images. We show how to bring the images obtained by the two methods to a same spatial resolution and how to use image registration to analyze the data originating from both techniques as one block of data. We finally demonstrates the elemental analysis is orthogonal to all FTIR markers as no significant correlation is found between FTIR and LA-ICP-MS data. Combining FTIR and LA-ICP-MS imaging becomes possible, providing two orthogonal methods which can bring an unprecedented diversity of information on the tissue. This opens a new avenue of tissue section analyses providing unprecedented diagnostic potential.
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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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Vermassen T, De Bruyne S, Himpe J, Lumen N, Callewaert N, Rottey S, Delanghe J. N-Linked Glycosylation and Near-Infrared Spectroscopy in the Diagnosis of Prostate Cancer. Int J Mol Sci 2019; 20:ijms20071592. [PMID: 30934974 PMCID: PMC6479798 DOI: 10.3390/ijms20071592] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 03/21/2019] [Accepted: 03/23/2019] [Indexed: 01/07/2023] Open
Abstract
Background: Performing a prostate biopsy is the most robust and reliable way to diagnose prostate cancer (PCa), and to determine the disease grading. As little to no biochemical markers for prostate tissue exist, we explored the possibilities of tissue N-glycosylation and near-infrared spectroscopy (NIR) in PCa diagnosis. Methods: Tissue specimens from 100 patients (benign prostate hyperplasia (BPH), n = 50; and PCa, n = 50) were obtained. The fresh-frozen tissue was dispersed and a tissue N-glycosylation profile was determined. Consequently, the formalin-fixed paraffin-embedded slides were analyzed using NIR spectroscopy. A comparison was made between the benign and malignant tissue, and between the various Gleason scores. Results: A difference was observed for the tissue of N-glycosylation between the benign and malignant tissue. These differences were located in the fycosylation ratios and the total amount of bi- and tetra-antennary structures (all p < 0.0001). These differences were also present between various Gleason scores. In addition, the NIR spectra revealed changes between the benign and malignant tissue in several regions. Moreover, spectral ranges of 1055–1065 nm and 1450–1460 nm were significantly different between the Gleason scores (p = 0.0042 and p = 0.0195). Conclusions: We have demonstrated biochemical changes in the N-glycan profile of prostate tissue, which allows for the distinction between malignant and benign tissue, as well as between various Gleason scores. These changes can be correlated to the changes observed in the NIR spectra. This could possibly further improve the histological assessment of PCa diagnosis, although further method validation is needed.
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Affiliation(s)
- Tijl Vermassen
- Department of Medical Oncology, Ghent University Hospital, 9000 Ghent, Belgium.
| | - Sander De Bruyne
- Department of Clinical Chemistry, Microbiology and Immunology, Ghent University, 9000 Ghent, Belgium.
| | - Jonas Himpe
- Department of Clinical Chemistry, Microbiology and Immunology, Ghent University, 9000 Ghent, Belgium.
| | - Nicolaas Lumen
- Department of Urology, Ghent University Hospital, 9000 Ghent, Belgium.
| | - Nico Callewaert
- Unit for Medical Biotechnology, Inflammation Research Center, VIB⁻Ghent University, 9052 Zwijnaarde, Belgium.
| | - Sylvie Rottey
- Department of Medical Oncology, Ghent University Hospital, 9000 Ghent, Belgium.
| | - Joris Delanghe
- Department of Clinical Chemistry, Microbiology and Immunology, Ghent University, 9000 Ghent, Belgium.
- Department of Clinical Chemistry, Ghent University Hospital, 9000 Ghent, Belgium.
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22
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Marques V, Cunha B, Couto A, Sampaio P, Fonseca LP, Aleixo S, Calado CRC. Characterization of gastric cells infection by diverse Helicobacter pylori strains through Fourier-transform infrared spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2019; 210:193-202. [PMID: 30453195 DOI: 10.1016/j.saa.2018.11.001] [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: 06/12/2018] [Revised: 10/29/2018] [Accepted: 11/02/2018] [Indexed: 06/09/2023]
Abstract
The infection of Helicobacter pylori, covering 50% of the world-population, leads to diverse gastric diseases as ulcers and cancer along the life-time of the human host. To promote the discovery of biomarkers of bacterial infection, in the present work, Fourier-transform infrared spectra were acquired from adenocarcinoma gastric cells, incubated with H. pylori strains presenting different genotypes concerning the virulent factors cytotoxin associated gene A and vacuolating cytotoxin A. Defined absorbance ratios were evaluated by diverse methods of statistical inference, according to the fulfillment of the tests assumptions. It was possible to define from the gastric cells, diverse absorbance ratios enabling to discriminate: i) The infection; ii) the bacteria genotype; and iii) the gastric disease of the patients from which the bacteria were isolated. These biomarkers could fasten the knowledge of the complex infection process while promoting a platform for a new diagnostic method, rapid but also specific and sensitive towards the diagnosis of both infection and bacterial virulence.
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Affiliation(s)
- Vanda Marques
- ISEL-Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
| | - Bernardo Cunha
- ISEL-Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal; IBB-Institute for Biotechnology and Bioengineering, Centre for Biological and Chemical Engineering, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisboa, Portugal
| | - Andreia Couto
- ISEL-Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
| | - Pedro Sampaio
- Faculty of Engineering, Lusophone University of Humanities and Technology, Campo Grande, 376, 1749-019 Lisbon, Portugal
| | - Luís P Fonseca
- IBB-Institute for Biotechnology and Bioengineering, Centre for Biological and Chemical Engineering, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisboa, Portugal
| | - Sandra Aleixo
- ISEL-Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal; Centro de Estatística e Aplicações, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal
| | - Cecília R C Calado
- ISEL-Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal.
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23
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Berisha S, Lotfollahi M, Jahanipour J, Gurcan I, Walsh M, Bhargava R, Van Nguyen H, Mayerich D. Deep learning for FTIR histology: leveraging spatial and spectral features with convolutional neural networks. Analyst 2019; 144:1642-1653. [PMID: 30644947 DOI: 10.1039/c8an01495g] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Current methods for cancer detection rely on tissue biopsy, chemical labeling/staining, and examination of the tissue by a pathologist. Though these methods continue to remain the gold standard, they are non-quantitative and susceptible to human error. Fourier transform infrared (FTIR) spectroscopic imaging has shown potential as a quantitative alternative to traditional histology. However, identification of histological components requires reliable classification based on molecular spectra, which are susceptible to artifacts introduced by noise and scattering. Several tissue types, particularly in heterogeneous tissue regions, tend to confound traditional classification methods. Convolutional neural networks (CNNs) are the current state-of-the-art in image classification, providing the ability to learn spatial characteristics of images. In this paper, we demonstrate that CNNs with architectures designed to process both spectral and spatial information can significantly improve classifier performance over per-pixel spectral classification. We report classification results after applying CNNs to data from tissue microarrays (TMAs) to identify six major cellular and acellular constituents of tissue, namely adipocytes, blood, collagen, epithelium, necrosis, and myofibroblasts. Experimental results show that the use of spatial information in addition to the spectral information brings significant improvements in the classifier performance and allows classification of cellular subtypes, such as adipocytes, that exhibit minimal chemical information but have distinct spatial characteristics. This work demonstrates the application and efficiency of deep learning algorithms in improving the diagnostic techniques in clinical and research activities related to cancer.
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Affiliation(s)
- Sebastian Berisha
- Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA.
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24
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Kar S, Katti DR, Katti KS. Fourier transform infrared spectroscopy based spectral biomarkers of metastasized breast cancer progression. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2019; 208:85-96. [PMID: 30292907 DOI: 10.1016/j.saa.2018.09.052] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Revised: 09/28/2018] [Accepted: 09/29/2018] [Indexed: 06/08/2023]
Abstract
Breast cancer is a global health issue and the second leading cause of cancer death in women. Breast cancer tends to migrate to bone and causes bone metastases which is ultimately the cause of death. Here, we report the use of FTIR to identify spectral biomarkers of cancer progression on 3D in vitro model of breast cancer bone metastasis. Our results indicate that the following spectral biomarkers can monitor cancer progression, for example, lipids (CH2 asymmetric/CH2 symmetric stretch), Amide I/Amide II, and RNA/DNA. Principal component analysis also confirmed the involvement of protein, lipids and nucleic acids in cancer progression on sequential culture. The collective observations from this study suggest successful application of FTIR as a non-invasive and accurate method to identify biochemical changes in cancer cells during the progression of breast cancer bone metastasis.
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Affiliation(s)
- Sumanta Kar
- Department of Civil and Environmental Engineering, CIE 201, NDSU, Fargo, ND 58104, United States of America
| | - Dinesh R Katti
- Department of Civil and Environmental Engineering, CIE 201, NDSU, Fargo, ND 58104, United States of America
| | - Kalpana S Katti
- Department of Civil and Environmental Engineering, CIE 201, NDSU, Fargo, ND 58104, United States of America.
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25
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Pilling MJ, Henderson A, Shanks JH, Brown MD, Clarke NW, Gardner P. Infrared spectral histopathology using haematoxylin and eosin (H&E) stained glass slides: a major step forward towards clinical translation. Analyst 2018; 142:1258-1268. [PMID: 27921102 DOI: 10.1039/c6an02224c] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Infrared spectral histopathology has shown great promise as an important diagnostic tool, with the potential to complement current pathological methods. While promising, clinical translation has been hindered by the impracticalities of using infrared transmissive substrates which are both fragile and prohibitively very expensive. Recently, glass has been proposed as a potential replacement which, although largely opaque in the infrared, allows unrestricted access to the high wavenumber region (2500-3800 cm-1). Recent studies using unstained tissue on glass have shown that despite utilising only the amide A band, good discrimination between histological classes could be achieved, and suggest the potential of discriminating between normal and malignant tissue. However unstained tissue on glass has the potential to disrupt the pathologist workflow, since it needs to be stained following infrared chemical imaging. In light of this, we report on the very first infrared Spectral Histopathology SHP study utilising coverslipped H&E stained tissue on glass using samples as received from the pathologist. In this paper we present a rigorous study using results obtained from an extended patient sample set consisting of 182 prostate tissue cores obtained from 100 different patients, on 18 separate H&E slides. Utilising a Random Forest classification model we demonstrate that we can rapidly classify four classes of histology of an independent test set with a high degree of accuracy (>90%). We investigate different degrees of staining using nine separate prostate serial sections, and demonstrate that we discriminate on biomarkers rather than the presence of the stain. Finally, using a four-class model we show that we can discriminate normal epithelium, malignant epithelium, normal stroma and cancer associated stroma with classification accuracies over 95%.
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Affiliation(s)
- Michael J Pilling
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
| | - Alex Henderson
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
| | | | - Michael D Brown
- Genito Urinary Cancer Research Group, Division of Molecular & Clinical Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Paterson Building, The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, UK
| | - Noel W Clarke
- Genito Urinary Cancer Research Group, Division of Molecular & Clinical Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Paterson Building, The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, UK
| | - Peter Gardner
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
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26
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Siqueira LFS, Lima KMG. MIR-biospectroscopy coupled with chemometrics in cancer studies. Analyst 2018; 141:4833-47. [PMID: 27433557 DOI: 10.1039/c6an01247g] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
This review focuses on chemometric techniques applied in MIR-biospectroscopy for cancer diagnosis and analysis over the last ten years of research. Experimental applications of chemometrics coupled with biospectroscopy are discussed throughout this work. The advantages and drawbacks of this association are also highlighted. Chemometric algorithms are evidenced as a powerful tool for cancer diagnosis, classification, and in different matrices. In fact, it is shown how chemometrics can be implemented along all different types of cancer analyses.
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Affiliation(s)
- Laurinda F S Siqueira
- Biological Chemistry and Chemometrics, Institute of Chemistry, Federal University of Rio Grande of Norte, Natal 59072-970, RN-Brazil.
| | - Kássio M G Lima
- Biological Chemistry and Chemometrics, Institute of Chemistry, Federal University of Rio Grande of Norte, Natal 59072-970, RN-Brazil.
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27
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Smith BR, Ashton KM, Brodbelt A, Dawson T, Jenkinson MD, Hunt NT, Palmer DS, Baker MJ. Combining random forest and 2D correlation analysis to identify serum spectral signatures for neuro-oncology. Analyst 2018; 141:3668-78. [PMID: 26818218 DOI: 10.1039/c5an02452h] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Fourier transform infrared (FTIR) spectroscopy has long been established as an analytical technique for the measurement of vibrational modes of molecular systems. More recently, FTIR has been used for the analysis of biofluids with the aim of becoming a tool to aid diagnosis. For the clinician, this represents a convenient, fast, non-subjective option for the study of biofluids and the diagnosis of disease states. The patient also benefits from this method, as the procedure for the collection of serum is much less invasive and stressful than traditional biopsy. This is especially true of patients in whom brain cancer is suspected. A brain biopsy is very unpleasant for the patient, potentially dangerous and can occasionally be inconclusive. We therefore present a method for the diagnosis of brain cancer from serum samples using FTIR and machine learning techniques. The scope of the study involved 433 patients from whom were collected 9 spectra each in the range 600-4000 cm(-1). To begin the development of the novel method, various pre-processing steps were investigated and ranked in terms of final accuracy of the diagnosis. Random forest machine learning was utilised as a classifier to separate patients into cancer or non-cancer categories based upon the intensities of wavenumbers present in their spectra. Generalised 2D correlational analysis was then employed to further augment the machine learning, and also to establish spectral features important for the distinction between cancer and non-cancer serum samples. Using these methods, sensitivities of up to 92.8% and specificities of up to 91.5% were possible. Furthermore, ratiometrics were also investigated in order to establish any correlations present in the dataset. We show a rapid, computationally light, accurate, statistically robust methodology for the identification of spectral features present in differing disease states. With current advances in IR technology, such as the development of rapid discrete frequency collection, this approach is of importance to enable future clinical translation and enables IR to achieve its potential.
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Affiliation(s)
- Benjamin R Smith
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, 295 Cathedral Street, Glasgow, Scotland G1 1XL, UK. and WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow G1 1RD, UK.
| | - Katherine M Ashton
- Neuropathology, Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane, Fulwood, Preston, PR2 9HT, UK
| | - Andrew Brodbelt
- Neurosurgery, The Walton Centre NHS Foundation Trust, Lower Lane, Fazakerley, Liverpool, L9 7LJ, UK
| | - Timothy Dawson
- Neuropathology, Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane, Fulwood, Preston, PR2 9HT, UK
| | - Michael D Jenkinson
- Neurosurgery, The Walton Centre NHS Foundation Trust, Lower Lane, Fazakerley, Liverpool, L9 7LJ, UK
| | - Neil T Hunt
- SUPA, Department of Physics, University of Strathclyde, 107 Rottenrow East, Glasgow, G4 0NG, UK
| | - David S Palmer
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, 295 Cathedral Street, Glasgow, Scotland G1 1XL, UK.
| | - Matthew J Baker
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow G1 1RD, UK.
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28
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Doherty J, Zhang Z, Wehbe K, Cinque G, Gardner P, Denbigh J. Increased optical pathlength through aqueous media for the infrared microanalysis of live cells. Anal Bioanal Chem 2018; 410:5779-5789. [PMID: 29968104 PMCID: PMC6096700 DOI: 10.1007/s00216-018-1188-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Revised: 05/25/2018] [Accepted: 06/06/2018] [Indexed: 12/13/2022]
Abstract
The study of live cells using Fourier transform infrared spectroscopy (FTIR) and FTIR microspectroscopy (FT-IRMS) intrinsically yields more information about cell metabolism than comparable experiments using dried or chemically fixed samples. There are, however, a number of barriers to obtaining high-quality vibrational spectra of live cells, including correction for the significant contributions of water bands to the spectra, and the physical stresses placed upon cells by compression in short pathlength sample holders. In this study, we present a water correction method that is able to result in good-quality cell spectra from water layers of 10 and 12 μm and demonstrate that sufficient biological detail is retained to separate spectra of live cells based upon their exposure to different novel anti-cancer agents. The IR brilliance of a synchrotron radiation (SR) source overcomes the problem of the strong water absorption and provides cell spectra with good signal-to-noise ratio for further analysis. Supervised multivariate analysis (MVA) and investigation of average spectra have shown significant separation between control cells and cells treated with the DNA cross-linker PL63 on the basis of phosphate and DNA-related signatures. Meanwhile, the same control cells can be significantly distinguished from cells treated with the protein kinase inhibitor YA1 based on changes in the amide II region. Each of these separations can be linked directly to the known biochemical mode of action of each agent. Graphical abstract ![]()
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Affiliation(s)
- James Doherty
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.,School of Chemical Engineering and Analytical Science, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.,Diamond Light Source, Diamond House, Harwell Science and Innovation Campus, Didcot, Oxfordshire, OX11 0DE, UK
| | - Zhe Zhang
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.,School of Chemical Engineering and Analytical Science, University of Manchester, Oxford Road, Manchester, M13 9PL, UK
| | - Katia Wehbe
- Diamond Light Source, Diamond House, Harwell Science and Innovation Campus, Didcot, Oxfordshire, OX11 0DE, UK
| | - Gianfelice Cinque
- Diamond Light Source, Diamond House, Harwell Science and Innovation Campus, Didcot, Oxfordshire, OX11 0DE, UK
| | - Peter Gardner
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK. .,School of Chemical Engineering and Analytical Science, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
| | - Joanna Denbigh
- Biomedical Research Centre, School of Environment and Life Sciences, University of Salford, Salford, M5 4WT, UK.
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29
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Mankar R, Walsh MJ, Bhargava R, Prasad S, Mayerich D. Selecting optimal features from Fourier transform infrared spectroscopy for discrete-frequency imaging. Analyst 2018; 143:1147-1156. [PMID: 29404544 PMCID: PMC5860915 DOI: 10.1039/c7an01888f] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Tissue histology utilizing chemical and immunohistochemical labels plays an important role in biomedicine and disease diagnosis. Recent research suggests that mid-infrared (IR) spectroscopic imaging may augment histology by providing quantitative molecular information. One of the major barriers to this approach is long acquisition time using Fourier-transform infrared (FTIR) spectroscopy. Recent advances in discrete frequency sources, particularly quantum cascade lasers (QCLs), may mitigate this problem by allowing selective sampling of the absorption spectrum. However, DFIR imaging only provides a significant advantage when the number of spectral samples is minimized, requiring a priori knowledge of important spectral features. In this paper, we demonstrate the use of a GPU-based genetic algorithm (GA) using linear discriminant analysis (LDA) for DFIR feature selection. Our proposed method relies on pre-acquired broadband FTIR images for feature selection. Based on user-selected criteria for classification accuracy, our algorithm provides a minimal set of features that can be used with DFIR in a time-frame more practical for clinical diagnosis.
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Affiliation(s)
- Rupali Mankar
- Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA.
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30
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Ghimire H, Venkataramani M, Bian Z, Liu Y, Perera AGU. ATR-FTIR spectral discrimination between normal and tumorous mouse models of lymphoma and melanoma from serum samples. Sci Rep 2017; 7:16993. [PMID: 29209060 PMCID: PMC5717051 DOI: 10.1038/s41598-017-17027-4] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2017] [Accepted: 11/21/2017] [Indexed: 11/23/2022] Open
Abstract
This study presents, attenuated total reflection Fourier transforms infrared spectroscopy of dried serum samples in an effort to assess biochemical changes induced by non-Hodgkin's lymphoma and subcutaneous melanoma. An EL4 mouse model of non-Hodgkin lymphoma and a B16 mouse model of subcutaneous melanoma are used to extract a snapshot of tumor-associated alteration in the serum. The study of both cancer-bearing mouse models in wild types and their corresponding control types, emphasizes the diagnostic potential of this approach as a screening technique for non-Hodgkin lymphoma and melanoma skin cancer. Infrared absorbance values of the different spectral bands, hierarchical clustering and integral values of the component bands by curve fitting, show statistically significant differences (student's t-test, two-tailed unequal variance p-value < 0.05) between spectra representing healthy and tumorous mouse. This technique may thus be useful for having individualized route maps for rapid evaluation of lymphoma and melanoma status and associated therapeutic modalities.
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Affiliation(s)
- Hemendra Ghimire
- Department of Physics and Astronomy, GSU, Atlanta, GA, 30303, USA
| | - Mahathi Venkataramani
- Center of Diagnostics and Therapeutics, Georgia State University, Atlanta, GA, 30302, USA
- Center for Inflammation, Immunity and Infection, Georgia State University, Atlanta, GA, 30303, USA
| | - Zhen Bian
- Center for Inflammation, Immunity and Infection, Georgia State University, Atlanta, GA, 30303, USA
| | - Yuan Liu
- Center of Diagnostics and Therapeutics, Georgia State University, Atlanta, GA, 30302, USA
- Center for Inflammation, Immunity and Infection, Georgia State University, Atlanta, GA, 30303, USA
| | - A G Unil Perera
- Department of Physics and Astronomy, GSU, Atlanta, GA, 30303, USA.
- Center of Diagnostics and Therapeutics, Georgia State University, Atlanta, GA, 30302, USA.
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31
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Verdonck M, Denayer A, Delvaux B, Garaud S, De Wind R, Desmedt C, Sotiriou C, Willard-Gallo K, Goormaghtigh E. Characterization of human breast cancer tissues by infrared imaging. Analyst 2017; 141:606-19. [PMID: 26535413 DOI: 10.1039/c5an01512j] [Citation(s) in RCA: 51] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Fourier Transform InfraRed (FTIR) spectroscopy coupled to microscopy (IR imaging) has shown unique advantages in detecting morphological and molecular pathologic alterations in biological tissues. The aim of this study was to evaluate the potential of IR imaging as a diagnostic tool to identify characteristics of breast epithelial cells and the stroma. In this study a total of 19 breast tissue samples were obtained from 13 patients. For 6 of the patients, we also obtained Non-Adjacent Non-Tumor tissue samples. Infrared images were recorded on the main cell/tissue types identified in all breast tissue samples. Unsupervised Principal Component Analyses and supervised Partial Least Square Discriminant Analyses (PLS-DA) were used to discriminate spectra. Leave-one-out cross-validation was used to evaluate the performance of PLS-DA models. Our results show that IR imaging coupled with PLS-DA can efficiently identify the main cell types present in FFPE breast tissue sections, i.e. epithelial cells, lymphocytes, connective tissue, vascular tissue and erythrocytes. A second PLS-DA model could distinguish normal and tumor breast epithelial cells in the breast tissue sections. A patient-specific model reached particularly high sensitivity, specificity and MCC rates. Finally, we showed that the stroma located close or at distance from the tumor exhibits distinct spectral characteristics. In conclusion FTIR imaging combined with computational algorithms could be an accurate, rapid and objective tool to identify/quantify breast epithelial cells and differentiate tumor from normal breast tissue as well as normal from tumor-associated stroma, paving the way to the establishment of a potential complementary tool to ensure safe tumor margins.
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Affiliation(s)
- M Verdonck
- Laboratory of Structure and Function of Biological Membranes, Center of Structural Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium.
| | - A Denayer
- Laboratory of Structure and Function of Biological Membranes, Center of Structural Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium.
| | - B Delvaux
- Laboratory of Structure and Function of Biological Membranes, Center of Structural Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium.
| | - S Garaud
- Molecular Immunology Unit, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - R De Wind
- Pathological Anatomy Department, Institut Jules Bordet, Brussels, Belgium
| | - C Desmedt
- Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Brussels, Belgium
| | - C Sotiriou
- Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Brussels, Belgium
| | - K Willard-Gallo
- Molecular Immunology Unit, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium
| | - E Goormaghtigh
- Laboratory of Structure and Function of Biological Membranes, Center of Structural Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium.
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32
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Schwaighofer A, Brandstetter M, Lendl B. Quantum cascade lasers (QCLs) in biomedical spectroscopy. Chem Soc Rev 2017; 46:5903-5924. [DOI: 10.1039/c7cs00403f] [Citation(s) in RCA: 102] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
This review focuses on the recent applications of QCLs in mid-IR spectroscopy of clinically relevant samples.
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Affiliation(s)
- Andreas Schwaighofer
- Institute of Chemical Technologies and Analytics
- Vienna University of Technology
- 1060 Vienna
- Austria
| | | | - Bernhard Lendl
- Institute of Chemical Technologies and Analytics
- Vienna University of Technology
- 1060 Vienna
- Austria
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33
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A decade (2004 – 2014) of FTIR prostate cancer spectroscopy studies: An overview of recent advancements. Trends Analyt Chem 2016. [DOI: 10.1016/j.trac.2016.05.028] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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34
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Hands JR, Clemens G, Stables R, Ashton K, Brodbelt A, Davis C, Dawson TP, Jenkinson MD, Lea RW, Walker C, Baker MJ. Brain tumour differentiation: rapid stratified serum diagnostics via attenuated total reflection Fourier-transform infrared spectroscopy. J Neurooncol 2016; 127:463-72. [PMID: 26874961 PMCID: PMC4835510 DOI: 10.1007/s11060-016-2060-x] [Citation(s) in RCA: 93] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2015] [Accepted: 01/22/2016] [Indexed: 01/07/2023]
Abstract
The ability to diagnose cancer rapidly with high sensitivity and specificity is essential to exploit advances in new treatments to lead significant reductions in mortality and morbidity. Current cancer diagnostic tests observing tissue architecture and specific protein expression for specific cancers suffer from inter-observer variability, poor detection rates and occur when the patient is symptomatic. A new method for the detection of cancer using 1 μl of human serum, attenuated total reflection-Fourier transform infrared spectroscopy and pattern recognition algorithms is reported using a 433 patient dataset (3897 spectra). To the best of our knowledge, we present the largest study on serum mid-infrared spectroscopy for cancer research. We achieve optimum sensitivities and specificities using a Radial Basis Function Support Vector Machine of between 80.0 and 100 % for all strata and identify the major spectral features, hence biochemical components, responsible for the discrimination within each stratum. We assess feature fed-SVM analysis for our cancer versus non-cancer model and achieve 91.5 and 83.0 % sensitivity and specificity respectively. We demonstrate the use of infrared light to provide a spectral signature from human serum to detect, for the first time, cancer versus non-cancer, metastatic cancer versus organ confined, brain cancer severity and the organ of origin of metastatic disease from the same sample enabling stratified diagnostics depending upon the clinical question asked.
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Affiliation(s)
- James R Hands
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, 99 George Street, Glasgow, G11RD, UK
| | - Graeme Clemens
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, 99 George Street, Glasgow, G11RD, UK
- Centre for Materials Science, Division of Chemistry, University of Central Lancashire, Preston, PR12HE, UK
| | - Ryan Stables
- Digital Media Technology Laboratory, Millennium Point, City Centre Campus Birmingham City University, West Midlands, B47XG, UK
| | - Katherine Ashton
- Neuropathology, Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane North, Preston, PR29HT, UK
| | - Andrew Brodbelt
- The Walton Centre for Neurology and Neurosurgery, The Walton Centre NHS Trust, Lower Lane, Liverpool, L97LJ, UK
| | - Charles Davis
- Neuropathology, Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane North, Preston, PR29HT, UK
| | - Timothy P Dawson
- Neuropathology, Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital, Sharoe Green Lane North, Preston, PR29HT, UK
| | - Michael D Jenkinson
- The Walton Centre for Neurology and Neurosurgery, The Walton Centre NHS Trust, Lower Lane, Liverpool, L97LJ, UK
| | - Robert W Lea
- School of Pharmacy and Biomedical Sciences, Maudland Building, University of Central Lancashire, Preston, PR12HE, UK
| | - Carol Walker
- The Walton Centre for Neurology and Neurosurgery, The Walton Centre NHS Trust, Lower Lane, Liverpool, L97LJ, UK
| | - Matthew J Baker
- WestCHEM, Department of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, 99 George Street, Glasgow, G11RD, UK.
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35
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Pilling M, Gardner P. Fundamental developments in infrared spectroscopic imaging for biomedical applications. Chem Soc Rev 2016; 45:1935-57. [PMID: 26996636 DOI: 10.1039/c5cs00846h] [Citation(s) in RCA: 77] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Infrared chemical imaging is a rapidly emerging field with new advances in instrumentation, data acquisition and data analysis. These developments have had significant impact in biomedical applications and numerous studies have now shown that this technology offers great promise for the improved diagnosis of the diseased state. Relying on purely biochemical signatures rather than contrast from exogenous dyes and stains, infrared chemical imaging has the potential to revolutionise histopathology for improved disease diagnosis. In this review we discuss the recent advances in infrared spectroscopic imaging specifically related to spectral histopathology (SHP) and consider the current state of the field. Finally we consider the practical application of SHP for disease diagnosis and consider potential barriers to clinical translation highlighting current directions and the future outlook.
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Affiliation(s)
- Michael Pilling
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
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36
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Nallala J, Lloyd GR, Shepherd N, Stone N. High-resolution FTIR imaging of colon tissues for elucidation of individual cellular and histopathological features. Analyst 2016; 141:630-9. [DOI: 10.1039/c5an01871d] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Comparison of spectral-histopathological features of a colon tissue measured using a conventional (5.5 μm × 5.5 μm, left) and a high-magnification (1.1 μm × 1.1 μm, right) FTIR imaging system with respect to HE stained tissue (middle).
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Affiliation(s)
| | - Gavin Rhys Lloyd
- Biophotonics Research Unit
- Gloucestershire Royal Hospital
- Gloucester
- UK
| | - Neil Shepherd
- Department of Pathology
- Gloucestershire Hospitals NHS Foundation Trust
- Gloucester
- UK
| | - Nick Stone
- Biomedical Physics
- School of Physics
- University of Exeter
- UK
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37
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Pilling MJ, Henderson A, Bird B, Brown MD, Clarke NW, Gardner P. High-throughput quantum cascade laser (QCL) spectral histopathology: a practical approach towards clinical translation. Faraday Discuss 2016; 187:135-54. [DOI: 10.1039/c5fd00176e] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Infrared microscopy has become one of the key techniques in the biomedical research field for interrogating tissue. In partnership with multivariate analysis and machine learning techniques, it has become widely accepted as a method that can distinguish between normal and cancerous tissue with both high sensitivity and high specificity. While spectral histopathology (SHP) is highly promising for improved clinical diagnosis, several practical barriers currently exist, which need to be addressed before successful implementation in the clinic. Sample throughput and speed of acquisition are key barriers and have been driven by the high volume of samples awaiting histopathological examination. FTIR chemical imaging utilising FPA technology is currently state-of-the-art for infrared chemical imaging, and recent advances in its technology have dramatically reduced acquisition times. Despite this, infrared microscopy measurements on a tissue microarray (TMA), often encompassing several million spectra, takes several hours to acquire. The problem lies with the vast quantities of data that FTIR collects; each pixel in a chemical image is derived from a full infrared spectrum, itself composed of thousands of individual data points. Furthermore, data management is quickly becoming a barrier to clinical translation and poses the question of how to store these incessantly growing data sets. Recently, doubts have been raised as to whether the full spectral range is actually required for accurate disease diagnosis using SHP. These studies suggest that once spectral biomarkers have been predetermined it may be possible to diagnose disease based on a limited number of discrete spectral features. In this current study, we explore the possibility of utilising discrete frequency chemical imaging for acquiring high-throughput, high-resolution chemical images. Utilising a quantum cascade laser imaging microscope with discrete frequency collection at key diagnostic wavelengths, we demonstrate that we can diagnose prostate cancer with high sensitivity and specificity. Finally we extend the study to a large patient dataset utilising tissue microarrays, and show that high sensitivity and specificity can be achieved using high-throughput, rapid data collection, thereby paving the way for practical implementation in the clinic.
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Affiliation(s)
- Michael J. Pilling
- Manchester Institute of Biotechnology
- University of Manchester
- Manchester
- UK
| | - Alex Henderson
- Manchester Institute of Biotechnology
- University of Manchester
- Manchester
- UK
| | | | - Mick D. Brown
- Genito Urinary Cancer Research Group
- Institute of Cancer Sciences
- Paterson Building
- The University of Manchester
- Manchester
| | - Noel W. Clarke
- Genito Urinary Cancer Research Group
- Institute of Cancer Sciences
- Paterson Building
- The University of Manchester
- Manchester
| | - Peter Gardner
- Manchester Institute of Biotechnology
- University of Manchester
- Manchester
- UK
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Großerueschkamp F, Kallenbach-Thieltges A, Behrens T, Brüning T, Altmayer M, Stamatis G, Theegarten D, Gerwert K. Marker-free automated histopathological annotation of lung tumour subtypes by FTIR imaging. Analyst 2015; 140:2114-20. [PMID: 25529256 DOI: 10.1039/c4an01978d] [Citation(s) in RCA: 71] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
By integration of FTIR imaging and a novel trained random forest classifier, lung tumour classes and subtypes of adenocarcinoma are identified in fresh-frozen tissue slides automated and marker-free. The tissue slices are collected under standard operation procedures within our consortium and characterized by current gold standards in histopathology. In addition, meta data of the patients are taken. The improved standards on sample collection and characterization results in higher accuracy and reproducibility as compared to former studies and allows here for the first time the identification of adenocarcinoma subtypes by this approach. The differentiation of subtypes is especially important for prognosis and therapeutic decision.
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Affiliation(s)
- Frederik Großerueschkamp
- Protein Research Unit Ruhr within Europe (PURE), Department of Biophysics, Ruhr University Bochum, Germany.
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Pilling MJ, Bassan P, Gardner P. Comparison of transmission and transflectance mode FTIR imaging of biological tissue. Analyst 2015; 140:2383-92. [PMID: 25672838 DOI: 10.1039/c4an01975j] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
FTIR microscopy is a powerful technique which has become popular due to its ability to provide complementary information during histopathological assessment of biomedical tissue samples. Recently however, questions have been raised on the suitability of the transflection mode of operation for clinical diagnosis due to the so called Electric Field Standing Wave (EFSW) effect. In this paper we compare chemical images measured in transmission and transflection from prostate tissue obtained from five different patients, and discuss the variability of the spectra acquired with each sampling modality. We find that spectra obtained in transflection undergo a non-linear distortion, i.e. non-linear variations in absorption band strength across the spectra, and that there are significant differences in spectra measured from the same area of tissue depending on the mode of operation. Principal Component Analysis (PCA) is used to highlight that poorer discrimination between benign and cancerous tissue is obtained in transflection mode. In addition we show that use of second derivatives, while qualitatively improves spectral discrimination, does not completely alleviate the underlying problem.
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Affiliation(s)
- Michael J Pilling
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.
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40
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Verdonck M, Garaud S, Duvillier H, Willard-Gallo K, Goormaghtigh E. Label-free phenotyping of peripheral blood lymphocytes by infrared imaging. Analyst 2015; 140:2247-56. [PMID: 25516910 DOI: 10.1039/c4an01855a] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
It is now widely accepted that the immune microenvironment of tumors and more precisely Tumor Infiltrating Lymphocytes (TIL) play an important role in cancer development and outcome. TILs are considered to be important prognostic and predictive factors based on a growing body of clinical evidence; however, their presence at the tumor site is not currently assessed routinely. FTIR (Fourier transform infrared) imaging has proven it has value in studying a range of tumors, particularly for characterizing tumor cells. Currently, very little is known about the potential for FTIR imaging to characterize TIL. The present proof of concept study investigates the ability of FTIR imaging to identify the principal lymphocyte subpopulations present in human peripheral blood (PB). A negative cell isolation method was employed to select pure, label-free, helper T cells (CD4(+)), cytotoxic T cells (CD8(+)) and B cells (CD19(+)) from six healthy donors PB by Fluorescence Activated Cell Sorting (FACS). Cells were centrifuged onto Barium Fluoride windows and ten infrared images were recorded for each lymphocyte subpopulation from all six donors. After spectral pre-treatment, statistical analyses were performed. Unsupervised Principal Component Analyses (PCA) revealed that in the absence of donor variability, CD4(+) T cells, CD8(+) T cells and B cells each display distinct IR spectral features. Supervised Partial Least Square Discriminant Analyses (PLS-DA) demonstrated that the differences between the three lymphocyte subpopulations are reflected in their IR spectra, permitting their individual identification even when significant donor variability is present. Our results also show that a distinct spectral signature is associated with antibody binding. To our knowledge this is the first study reporting that FTIR imaging can effectively identify T and B lymphocytes and differentiate helper T cells from cytotoxic T cells. This proof of concept study demonstrates that FTIR imaging is a reliable tool for the identification of lymphocyte subpopulations and has the potential for use in characterizing TIL.
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Affiliation(s)
- M Verdonck
- Laboratory for the Structure and Function of Biological Membranes, Center for Structural Biology and Bioinformatics, Université Libre de Bruxelles, Campus Plaine, Bd du Triomphe 2, CP206/02, B1050 Brussels, Belgium.
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41
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Rosa F, Sales KC, Cunha BR, Couto A, Lopes MB, Calado CRC. A comprehensive high-throughput FTIR spectroscopy-based method for evaluating the transfection event: estimating the transfection efficiency and extracting associated metabolic responses. Anal Bioanal Chem 2015; 407:8097-108. [PMID: 26329279 DOI: 10.1007/s00216-015-8983-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2015] [Revised: 07/29/2015] [Accepted: 08/14/2015] [Indexed: 12/11/2022]
Abstract
Reporter genes are routinely used in every laboratory for molecular and cellular biology for studying heterologous gene expression and general cellular biological mechanisms, such as transfection processes. Although well characterized and broadly implemented, reporter genes present serious limitations, either by involving time-consuming procedures or by presenting possible side effects on the expression of the heterologous gene or even in the general cellular metabolism. Fourier transform mid-infrared (FT-MIR) spectroscopy was evaluated to simultaneously analyze in a rapid (minutes) and high-throughput mode (using 96-wells microplates), the transfection efficiency, and the effect of the transfection process on the host cell biochemical composition and metabolism. Semi-adherent HEK and adherent AGS cell lines, transfected with the plasmid pVAX-GFP using Lipofectamine, were used as model systems. Good partial least squares (PLS) models were built to estimate the transfection efficiency, either considering each cell line independently (R (2) ≥ 0.92; RMSECV ≤ 2 %) or simultaneously considering both cell lines (R (2) = 0.90; RMSECV = 2 %). Additionally, the effect of the transfection process on the HEK cell biochemical and metabolic features could be evaluated directly from the FT-IR spectra. Due to the high sensitivity of the technique, it was also possible to discriminate the effect of the transfection process from the transfection reagent on KEK cells, e.g., by the analysis of spectral biomarkers and biochemical and metabolic features. The present results are far beyond what any reporter gene assay or other specific probe can offer for these purposes.
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Affiliation(s)
- Filipa Rosa
- Faculdade de Engenharia, Universidade Católica Portuguesa, Estrada Otávio Pato, 2635-631, Rio de Mouro, Portugal
| | - Kevin C Sales
- Faculdade de Engenharia, Universidade Católica Portuguesa, Estrada Otávio Pato, 2635-631, Rio de Mouro, Portugal
| | - Bernardo R Cunha
- Faculdade de Engenharia, Universidade Católica Portuguesa, Estrada Otávio Pato, 2635-631, Rio de Mouro, Portugal
| | - Andreia Couto
- Faculdade de Engenharia, Universidade Católica Portuguesa, Estrada Otávio Pato, 2635-631, Rio de Mouro, Portugal
| | - Marta B Lopes
- Faculdade de Engenharia, Universidade Católica Portuguesa, Estrada Otávio Pato, 2635-631, Rio de Mouro, Portugal.,Instituto de Telecomunicações, Instituto Superior Técnico, 1049-001, Lisbon, Portugal
| | - Cecília R C Calado
- Instituto Superior de Engenharia de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007, Lisbon, Portugal.
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42
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Bassan P, Weida MJ, Rowlette J, Gardner P. Large scale infrared imaging of tissue micro arrays (TMAs) using a tunable Quantum Cascade Laser (QCL) based microscope. Analyst 2015; 139:3856-9. [PMID: 24965124 DOI: 10.1039/c4an00638k] [Citation(s) in RCA: 102] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Chemical imaging in the field of vibrational spectroscopy is developing into a promising tool to complement digital histopathology. Applications include screening of biopsy tissue via automated recognition of tissue/cell type and disease state based on the chemical information from the spectrum. For integration into clinical practice, data acquisition needs to be speeded up to implement a rack based system where specimens are rapidly imaged to compete with current visible scanners where 100's of slides can be scanned overnight. Current Fourier transform infrared (FTIR) imaging with focal plane array (FPA) detectors are currently the state-of-the-art instrumentation for infrared absorption chemical imaging, however recent development in broadly tunable lasers in the mid-IR range is considered the most promising potential candidate for next generation microscopes. In this paper we test a prototype quantum cascade laser (QCL) based spectral imaging microscope with a focus on discrete frequency chemical imaging. We demonstrate how a protein chemical image of the amide I band (1655 cm(-1)) of a 2 × 2.4 cm(2) breast tissue microarray (TMA) containing over 200 cores can be measured in 9 min. This result indicates that applications requiring chemical images from a few key wavelengths would be ideally served by laser-based microscopes.
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Affiliation(s)
- Paul Bassan
- Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester M1 7DN, UK.
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43
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Leslie LS, Wrobel TP, Mayerich D, Bindra S, Emmadi R, Bhargava R. High definition infrared spectroscopic imaging for lymph node histopathology. PLoS One 2015; 10:e0127238. [PMID: 26039216 PMCID: PMC4454651 DOI: 10.1371/journal.pone.0127238] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2015] [Accepted: 04/14/2015] [Indexed: 11/19/2022] Open
Abstract
Chemical imaging is a rapidly emerging field in which molecular information within samples can be used to predict biological function and recognize disease without the use of stains or manual identification. In Fourier transform infrared (FT-IR) spectroscopic imaging, molecular absorption contrast provides a large signal relative to noise. Due to the long mid-IR wavelengths and sub-optimal instrument design, however, pixel sizes have historically been much larger than cells. This limits both the accuracy of the technique in identifying small regions, as well as the ability to visualize single cells. Here we obtain data with micron-sized sampling using a tabletop FT-IR instrument, and demonstrate that the high-definition (HD) data lead to accurate identification of multiple cells in lymph nodes that was not previously possible. Highly accurate recognition of eight distinct classes - naïve and memory B cells, T cells, erythrocytes, connective tissue, fibrovascular network, smooth muscle, and light and dark zone activated B cells was achieved in healthy, reactive, and malignant lymph node biopsies using a random forest classifier. The results demonstrate that cells currently identifiable only through immunohistochemical stains and cumbersome manual recognition of optical microscopy images can now be distinguished to a similar level through a single IR spectroscopic image from a lymph node biopsy.
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Affiliation(s)
- L. Suzanne Leslie
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Tomasz P. Wrobel
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - David Mayerich
- Department of Electrical and Computer Engineering, University of Houston, Houston, Texas, United States America
| | - Snehal Bindra
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Rajyasree Emmadi
- Department of Pathology, University of Illinois at Chicago, Chicago, Illinois, United States of America
| | - Rohit Bhargava
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Illinois, United States of America
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Illinois, United States of America
- Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Illinois, United States of America
- Department of Chemistry, University of Illinois at Urbana-Champaign, Illinois, United States of America
- * E-mail:
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44
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Nallala J, Lloyd GR, Stone N. Evaluation of different tissue de-paraffinization procedures for infrared spectral imaging. Analyst 2015; 140:2369-75. [DOI: 10.1039/c4an02122c] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Differential distribution of paraffin in a normal colon tissue section after various de-Waxing procedures in comparison to a paraffinized tissue.
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Affiliation(s)
| | - Gavin Rhys Lloyd
- Biophotonics Research Unit
- Gloucestershire Royal Hospital
- Gloucester
- UK
| | - Nicholas Stone
- Biomedical Physics
- School of Physics
- University of Exeter
- Exeter, EX4 4QL
- UK
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45
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Surowka AD, Adamek D, Szczerbowska-Boruchowska M. The combination of artificial neural networks and synchrotron radiation-based infrared micro-spectroscopy for a study on the protein composition of human glial tumors. Analyst 2015; 140:2428-38. [DOI: 10.1039/c4an01867b] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Protein-related changes associated with the development of human brain gliomas are of increasing interest in modern neuro-oncology.
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Affiliation(s)
- A. D. Surowka
- AGH University of Science and Technology
- Faculty of Physics and Applied Computer Science
- 30-059 Krakow
- Poland
| | - D. Adamek
- Jagiellonian University
- Faculty of Medicine
- Department of Neuropathology
- Chair of Pathomorphology
- Krakow
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46
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Maguire A, Vega-Carrascal I, Bryant J, White L, Howe O, Lyng FM, Meade AD. Competitive evaluation of data mining algorithms for use in classification of leukocyte subtypes with Raman microspectroscopy. Analyst 2015; 140:2473-81. [DOI: 10.1039/c4an01887g] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
In this study Raman spectral data from peripheral blood mononuclear cells (PBMCs) is used for the competitive evaluation of three data-mining models in discriminating a highly pure population of T-cell lymphocytes from other myeloid cells within the PBMCs fraction.
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Affiliation(s)
- A. Maguire
- School of Physics
- Dublin Institute of Technology
- Dublin
- Ireland
- Radiation and Environmental Science Centre (RESC)
| | - I. Vega-Carrascal
- Radiation and Environmental Science Centre (RESC)
- Dublin Institute of Technology
- Dublin
- Ireland
| | - J. Bryant
- Radiation and Environmental Science Centre (RESC)
- Dublin Institute of Technology
- Dublin
- Ireland
| | - L. White
- Radiation and Environmental Science Centre (RESC)
- Dublin Institute of Technology
- Dublin
- Ireland
- School of Biological Sciences
| | - O. Howe
- Radiation and Environmental Science Centre (RESC)
- Dublin Institute of Technology
- Dublin
- Ireland
- School of Biological Sciences
| | - F. M. Lyng
- School of Physics
- Dublin Institute of Technology
- Dublin
- Ireland
- Radiation and Environmental Science Centre (RESC)
| | - A. D. Meade
- School of Physics
- Dublin Institute of Technology
- Dublin
- Ireland
- Radiation and Environmental Science Centre (RESC)
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47
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Baker MJ, Trevisan J, Bassan P, Bhargava R, Butler HJ, Dorling KM, Fielden PR, Fogarty SW, Fullwood NJ, Heys KA, Hughes C, Lasch P, Martin-Hirsch PL, Obinaju B, Sockalingum GD, Sulé-Suso J, Strong RJ, Walsh MJ, Wood BR, Gardner P, Martin FL. Using Fourier transform IR spectroscopy to analyze biological materials. Nat Protoc 2014; 9:1771-91. [PMID: 24992094 PMCID: PMC4480339 DOI: 10.1038/nprot.2014.110] [Citation(s) in RCA: 1000] [Impact Index Per Article: 100.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing.
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Affiliation(s)
- Matthew J Baker
- 1] Centre for Materials Science, Division of Chemistry, University of Central Lancashire, Preston, UK. [2] Present address: WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow, UK
| | - Júlio Trevisan
- 1] Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK. [2] School of Computing and Communications, Lancaster University, Lancaster, UK
| | - Paul Bassan
- Manchester Institute of Biotechnology (MIB), University of Manchester, Manchester, UK
| | - Rohit Bhargava
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Holly J Butler
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | - Konrad M Dorling
- Centre for Materials Science, Division of Chemistry, University of Central Lancashire, Preston, UK
| | - Peter R Fielden
- Department of Chemistry, Lancaster University, Lancaster, UK
| | - Simon W Fogarty
- 1] Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK. [2] Division of Biomedical and Life Sciences, School of Health and Medicine, Lancaster University, Lancaster, UK
| | - Nigel J Fullwood
- Division of Biomedical and Life Sciences, School of Health and Medicine, Lancaster University, Lancaster, UK
| | - Kelly A Heys
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | - Caryn Hughes
- Manchester Institute of Biotechnology (MIB), University of Manchester, Manchester, UK
| | - Peter Lasch
- Proteomics and Spectroscopy (ZBS 6), Robert-Koch-Institut, Berlin, Germany
| | - Pierre L Martin-Hirsch
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | - Blessing Obinaju
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | - Ganesh D Sockalingum
- Equipe MéDIAN-Biophotonique et Technologies pour la Santé, Université de Reims Champagne-Ardenne, UnitéMEDyC, CNRS UMR7369, UFR Pharmacie, SFR CAP-Santé FED4231, Reims, France
| | - Josep Sulé-Suso
- Institute for Science and Technology in Medicine, School of Medicine, Keele University, Stoke-on-Trent, UK
| | - Rebecca J Strong
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | - Michael J Walsh
- Department of Pathology, College of Medicine Research Building (COMRB), University of Illinois at Chicago, Chicago, Illinois, USA
| | - Bayden R Wood
- Centre for Biospectroscopy and School of Chemistry, Monash University, Clayton, Victoria, Australia
| | - Peter Gardner
- Manchester Institute of Biotechnology (MIB), University of Manchester, Manchester, UK
| | - Francis L Martin
- Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK
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Cheng HY, Ko FH, Lai LJ. Using Novel Method to Detect Different Cancer-Cell Stages of Model Human Lung Carcinoma. J Clin Lab Anal 2014; 29:285-8. [PMID: 25043757 DOI: 10.1002/jcla.21766] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2014] [Accepted: 03/17/2014] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Synchrotron radiation infrared (SR-IR) microspectroscopy and SR-IR spectroscopic imaging are extremely valuable techniques for determining the molecular composition of biological and biomedical samples. In this work, SR-IR is applied in the study of the lung cancer cells in different cell cycles. METHODS We use a novel synchrotron based radiation infrared system combined synchronized model human lung carcinoma to reveal its unique character pattern. RESULTS After using SR-IR microspectroscopy, we discovered that the ratio of protein to lipid in G1 and G2 states is around 4.0 and 6.1, respectively. Moreover, for the DNA at the wavenumber position of 1225 cm(-1) , the intensity ratio of G2 state to G1 state is approximately 1.6. These data indicate that the cell in G1 state has more lipid composition to prepare for the DNA synthesis, but the cell in G2 state has more protein composition to prepare for the mitosis. The cell has larger DNA concentration in G2 state, which can be explained for the DNA synthesis. CONCLUSION Through our research, we demonstrate that different growth state of cancer cell presenting unique functional groups concentration profiles and distribution via using SR-IR microspectrometry. These applications will provide another ways to improve modern cancer screening in the future.
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Affiliation(s)
- Hao-Yuan Cheng
- Department of Materials Science and Engineering, National Chiao Tung University, Taiwan, ROC
| | - Fu-Hsiang Ko
- Department of Materials Science and Engineering, National Chiao Tung University, Taiwan, ROC
| | - Lee-Jene Lai
- National Synchrotron Radiation Research Center, Taiwan, ROC
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49
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Simonova D, Karamancheva I. Application of Fourier Transform Infrared Spectroscopy for Tumor Diagnosis. BIOTECHNOL BIOTEC EQ 2014. [DOI: 10.5504/bbeq.2013.0106] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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50
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Bassan P, Mellor J, Shapiro J, Williams KJ, Lisanti MP, Gardner P. Transmission FT-IR chemical imaging on glass substrates: applications in infrared spectral histopathology. Anal Chem 2014; 86:1648-53. [PMID: 24410403 DOI: 10.1021/ac403412n] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Fourier transform-infrared (FT-IR) chemical imaging in transmission mode has traditionally been performed on expensive mid-IR transparent windows such as barium/calcium fluoride, which are more fragile than glass, making preparation in the histopathology laboratories more cumbersome. A solution is presented here by using cheap glass substrates for the FT-IR chemical imaging, which has a high-wavenumber transmission window allowing measurement of the C-H, N-H, and O-H stretches occurring at ca. 2500-3800 cm(-1). The "fingerprint" region of the IR spectrum occurring below 1800 cm(-1) is not obtainable; however, we demonstrate that a wealth of information is contained in the high wavenumber range using 71 patients on a breast tissue microarray (TMA) as a model for investigation. Importantly, we demonstrate that the tissue can be classified into four basic tissue cell types and that using just the epithelial cells, reasonable discrimination of normal and malignant tissue can be found.
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Affiliation(s)
- Paul Bassan
- Manchester Institute of Biotechnology, University of Manchester , 131 Princess Street, Manchester M1 7DN, U.K
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