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Wang Y, Fang L, Wang Y, Xiong Z. Current Trends of Raman Spectroscopy in Clinic Settings: Opportunities and Challenges. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2300668. [PMID: 38072672 PMCID: PMC10870035 DOI: 10.1002/advs.202300668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 09/08/2023] [Indexed: 02/17/2024]
Abstract
Early clinical diagnosis, effective intraoperative guidance, and an accurate prognosis can lead to timely and effective medical treatment. The current conventional clinical methods have several limitations. Therefore, there is a need to develop faster and more reliable clinical detection, treatment, and monitoring methods to enhance their clinical applications. Raman spectroscopy is noninvasive and provides highly specific information about the molecular structure and biochemical composition of analytes in a rapid and accurate manner. It has a wide range of applications in biomedicine, materials, and clinical settings. This review primarily focuses on the application of Raman spectroscopy in clinical medicine. The advantages and limitations of Raman spectroscopy over traditional clinical methods are discussed. In addition, the advantages of combining Raman spectroscopy with machine learning, nanoparticles, and probes are demonstrated, thereby extending its applicability to different clinical phases. Examples of the clinical applications of Raman spectroscopy over the last 3 years are also integrated. Finally, various prospective approaches based on Raman spectroscopy in clinical studies are surveyed, and current challenges are discussed.
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Affiliation(s)
- Yumei Wang
- Department of NephrologyUnion HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan430022China
| | - Liuru Fang
- Hubei Province Key Laboratory of Systems Science in Metallurgical ProcessWuhan University of Science and TechnologyWuhan430081China
| | - Yuhua Wang
- Hubei Province Key Laboratory of Systems Science in Metallurgical ProcessWuhan University of Science and TechnologyWuhan430081China
| | - Zuzhao Xiong
- Hubei Province Key Laboratory of Systems Science in Metallurgical ProcessWuhan University of Science and TechnologyWuhan430081China
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Monaghan JF, Cullen D, Wynne C, Lyng FM, Meade AD. Effect of pre-analytical variables on Raman and FTIR spectral content of lymphocytes. Analyst 2023; 148:5422-5434. [PMID: 37750362 DOI: 10.1039/d3an00686g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/27/2023]
Abstract
The use of Fourier transform infrared (FTIR) and Raman spectroscopy (RS) for the analysis of lymphocytes in clinical applications is increasing in the field of biomedicine. The pre-analytical phase, which is the most vulnerable stage of the testing process, is where most errors and sample variance occur; however, it is unclear how pre-analytical variables affect the FTIR and Raman spectra of lymphocytes. In this study, we evaluated how pre-analytical procedures undertaken before spectroscopic analysis influence the spectral integrity of lymphocytes purified from the peripheral blood of male volunteers (n = 3). Pre-analytical variables investigated were associated with (i) sample preparation, (blood collection systems, anticoagulant, needle gauges), (ii) sample storage (fresh or frozen), and (iii) sample processing (inter-operator variability, time to lymphocyte isolation). Although many of these procedural pre-analytical variables did not alter the spectral signature of the lymphocytes, evidence of spectral effects due to the freeze-thaw cycle, in vitro culture inter-operator variability and the time to lymphocyte isolation was observed. Although FTIR and RS possess clinical potential, their translation into a clinical environment is impeded by a lack of standardisation and harmonisation of protocols related to the preparation, storage, and processing of samples, which hinders uniform, accurate, and reproducible analysis. Therefore, further development of protocols is required to successfully integrate these techniques into current clinical workflows.
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Affiliation(s)
- Jade F Monaghan
- School of Physics, Clinical and Optometric Sciences, Technological University Dublin, Central Quad, City Campus, Grangegorman, D07 XT95, Ireland.
- Radiation and Environmental Science Centre, Focas Research Institute, Technological University Dublin, Aungier Street, D02 HW71, Ireland
| | - Daniel Cullen
- School of Physics, Clinical and Optometric Sciences, Technological University Dublin, Central Quad, City Campus, Grangegorman, D07 XT95, Ireland.
- Radiation and Environmental Science Centre, Focas Research Institute, Technological University Dublin, Aungier Street, D02 HW71, Ireland
| | - Claire Wynne
- School of Biological, Health and Sports Sciences, Technological University Dublin, Central Quad, City Campus, Grangegorman, D07 XT95, Ireland
| | - Fiona M Lyng
- School of Physics, Clinical and Optometric Sciences, Technological University Dublin, Central Quad, City Campus, Grangegorman, D07 XT95, Ireland.
- Radiation and Environmental Science Centre, Focas Research Institute, Technological University Dublin, Aungier Street, D02 HW71, Ireland
| | - Aidan D Meade
- School of Physics, Clinical and Optometric Sciences, Technological University Dublin, Central Quad, City Campus, Grangegorman, D07 XT95, Ireland.
- Radiation and Environmental Science Centre, Focas Research Institute, Technological University Dublin, Aungier Street, D02 HW71, Ireland
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Davoudi F, Moradi A, Becker TM, Lock JG, Abbey B, Fontanarosa D, Haworth A, Clements J, Ecker RC, Batra J. Genomic and Phenotypic Biomarkers for Precision Medicine Guidance in Advanced Prostate Cancer. Curr Treat Options Oncol 2023; 24:1451-1471. [PMID: 37561382 PMCID: PMC10547634 DOI: 10.1007/s11864-023-01121-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/21/2023] [Indexed: 08/11/2023]
Abstract
OPINION STATEMENT Prostate cancer (PCa) is the second most diagnosed malignant neoplasm and is one of the leading causes of cancer-related death in men worldwide. Despite significant advances in screening and treatment of PCa, given the heterogeneity of this disease, optimal personalized therapeutic strategies remain limited. However, emerging predictive and prognostic biomarkers based on individual patient profiles in combination with computer-assisted diagnostics have the potential to guide precision medicine, where patients may benefit from therapeutic approaches optimally suited to their disease. Also, the integration of genotypic and phenotypic diagnostic methods is supporting better informed treatment decisions. Focusing on advanced PCa, this review discusses polygenic risk scores for screening of PCa and common genomic aberrations in androgen receptor (AR), PTEN-PI3K-AKT, and DNA damage response (DDR) pathways, considering clinical implications for diagnosis, prognosis, and treatment prediction. Furthermore, we evaluate liquid biopsy, protein biomarkers such as serum testosterone levels, SLFN11 expression, total alkaline phosphatase (tALP), neutrophil-to-lymphocyte ratio (NLR), tissue biopsy, and advanced imaging tools, summarizing current phenotypic biomarkers and envisaging more effective utilization of diagnostic and prognostic biomarkers in advanced PCa. We conclude that prognostic and treatment predictive biomarker discovery can improve the management of patients, especially in metastatic stages of advanced PCa. This will result in decreased mortality and enhanced quality of life and help design a personalized treatment regimen.
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Affiliation(s)
- Fatemeh Davoudi
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, 4059 Australia
- Department of Medical Genetics, School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Afshin Moradi
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, 4059 Australia
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, 4059 Australia
- Translational Research Institute, Queensland University of Technology, Brisbane, 4102 Australia
| | - Therese M. Becker
- Ingham Institute for Applied Medical Research, University of Western Sydney and University of New South Wales, Liverpool, 2170 Australia
| | - John G. Lock
- Ingham Institute for Applied Medical Research, University of Western Sydney and University of New South Wales, Liverpool, 2170 Australia
- School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, 2052 Australia
| | - Brian Abbey
- Department of Mathematical and Physical Sciences, School of Computing Engineering and Mathematical Sciences, La Trobe Institute for Molecular Sciences, La Trobe University, Bundoora, VIC Australia
| | - Davide Fontanarosa
- School of Clinical Sciences, Queensland University of Technology, Gardens Point Campus, 2 George St, Brisbane, QLD 4000 Australia
- Centre for Biomedical Technologies (CBT), Queensland University of Technology, Brisbane, QLD 4000 Australia
| | - Annette Haworth
- Institute of Medical Physics, School of Physics, University of Sydney, Camperdown, NSW 2006 Australia
| | - Judith Clements
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, 4059 Australia
- Translational Research Institute, Queensland University of Technology, Brisbane, 4102 Australia
| | - Rupert C. Ecker
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, 4059 Australia
- Translational Research Institute, Queensland University of Technology, Brisbane, 4102 Australia
- TissueGnostics GmbH, EU 1020 Vienna, Austria
| | - Jyotsna Batra
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, 4059 Australia
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, 4059 Australia
- Translational Research Institute, Queensland University of Technology, Brisbane, 4102 Australia
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Application of Advanced Non-Linear Spectral Decomposition and Regression Methods for Spectroscopic Analysis of Targeted and Non-Targeted Irradiation Effects in an In-Vitro Model. Int J Mol Sci 2022; 23:ijms232112986. [DOI: 10.3390/ijms232112986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 09/30/2022] [Accepted: 10/11/2022] [Indexed: 12/24/2022] Open
Abstract
Irradiation of the tumour site during treatment for cancer with external-beam ionising radiation results in a complex and dynamic series of effects in both the tumour itself and the normal tissue which surrounds it. The development of a spectral model of the effect of each exposure and interaction mode between these tissues would enable label free assessment of the effect of radiotherapeutic treatment in practice. In this study Fourier transform Infrared microspectroscopic imaging was employed to analyse an in-vitro model of radiotherapeutic treatment for prostate cancer, in which a normal cell line (PNT1A) was exposed to low-dose X-ray radiation from the scattered treatment beam, and also to irradiated cell culture medium (ICCM) from a cancer cell line exposed to a treatment relevant dose (2 Gy). Various exposure modes were studied and reference was made to previously acquired data on cellular survival and DNA double strand break damage. Spectral analysis with manifold methods, linear spectral fitting, non-linear classification and non-linear regression approaches were found to accurately segregate spectra on irradiation type and provide a comprehensive set of spectral markers which differentiate on irradiation mode and cell fate. The study demonstrates that high dose irradiation, low-dose scatter irradiation and radiation-induced bystander exposure (RIBE) signalling each produce differential effects on the cell which are observable through spectroscopic analysis.
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A Comparison of PCA-LDA and PLS-DA Techniques for Classification of Vibrational Spectra. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12115345] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Vibrational spectroscopies provide information about the biochemical and structural environment of molecular functional groups inside samples. Over the past few decades, Raman and infrared-absorption-based techniques have been extensively used to investigate biological materials under different pathological conditions. Interesting results have been obtained, so these techniques have been proposed for use in a clinical setting for diagnostic purposes, as complementary tools to conventional cytological and histological techniques. In most cases, the differences between vibrational spectra measured for healthy and diseased samples are small, even if these small differences could contain useful information to be used in the diagnostic field. Therefore, the interpretation of the results requires the use of analysis techniques able to highlight the minimal spectral variations that characterize a dataset of measurements acquired on healthy samples from a dataset of measurements relating to samples in which a pathology occurs. Multivariate analysis techniques, which can handle large datasets and explore spectral information simultaneously, are suitable for this purpose. In the present study, two multivariate statistical techniques, principal component analysis-linear discriminate analysis (PCA-LDA) and partial least square-discriminant analysis (PLS-DA) were used to analyse three different datasets of vibrational spectra, each one including spectra of two different classes: (i) a simulated dataset comprising control-like and exposed-like spectra, (ii) a dataset of Raman spectra measured for control and proton beam-exposed MCF10A breast cells and (iii) a dataset of FTIR spectra measured for malignant non-metastatic MCF7 and metastatic MDA-MB-231 breast cancer cells. Both PCA-LDA and PLS-DA techniques were first used to build a discrimination model by using calibration sets of spectra extracted from the three datasets. Then, the classification performance was established by using test sets of unknown spectra. The achieved results point out that the built classification models were able to distinguish the different spectra types with accuracy between 93% and 100%, sensitivity between 86% and 100% and specificity between 90% and 100%. The present study confirms that vibrational spectroscopy combined with multivariate analysis techniques has considerable potential for establishing reliable diagnostic models.
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Howe O, Lyng FM, Mothersill C. Women's contributions to radiobiology in Ireland; from small beginnings…. Int J Radiat Biol 2021; 98:331-340. [PMID: 34010091 DOI: 10.1080/09553002.2021.1931529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
OBJECTIVES To describe the contribution of women radiobiologists in Ireland to the development of the discipline internationally and at home and to discuss the history of radiobiology in Ireland to date. This parallels the history of the evolution of a small radiobiology group in Kevin Street, Dublin Institute of Technology (DIT) which was formerly part of the City of Dublin Vocational Education Committee. There followed years of development first as a radiobiological research center which evolved in the FOCAS Research Institute now embedded within Technological University Dublin (TU Dublin). CONCLUSIONS Over the last 45 years, the women of the Radiation and Environmental Science Centre (RESC) contributed to the major paradigm shift in low dose radiobiology contributing exciting new research concerning non-targeted effects, including discovery of lethal mutations, medium transfer bystander mechanisms, and signaling pathways. They also developed translational research using human explant culture systems with unique immunocytochemical methods and more recently evolved to molecular and spectroscopic analysis of clinical samples. The RESC also developed unique in vitro research methods into effects of radiation on non-human species of concern in ecosystems.
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Affiliation(s)
- Orla Howe
- School of Biological and Health Sciences, Technological University Dublin, Dublin, Ireland.,Radiation and Environmental Science Centre, FOCAS Research Institute, Dublin, Ireland
| | - Fiona M Lyng
- Radiation and Environmental Science Centre, FOCAS Research Institute, Dublin, Ireland.,School of Physics & Clinical & Optometric Sciences, Technological University Dublin, Dublin, Ireland
| | - Carmel Mothersill
- Radiation and Environmental Science Centre, FOCAS Research Institute, Dublin, Ireland.,Department of Biology, Life Sciences building, McMaster University, Hamilton, Canada
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