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Eissa T, Leonardo C, Kepesidis KV, Fleischmann F, Linkohr B, Meyer D, Zoka V, Huber M, Voronina L, Richter L, Peters A, Žigman M. Plasma infrared fingerprinting with machine learning enables single-measurement multi-phenotype health screening. Cell Rep Med 2024:101625. [PMID: 38944038 DOI: 10.1016/j.xcrm.2024.101625] [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: 10/11/2023] [Revised: 04/19/2024] [Accepted: 06/07/2024] [Indexed: 07/01/2024]
Abstract
Infrared spectroscopy is a powerful technique for probing the molecular profiles of complex biofluids, offering a promising avenue for high-throughput in vitro diagnostics. While several studies showcased its potential in detecting health conditions, a large-scale analysis of a naturally heterogeneous potential patient population has not been attempted. Using a population-based cohort, here we analyze 5,184 blood plasma samples from 3,169 individuals using Fourier transform infrared (FTIR) spectroscopy. Applying a multi-task classification to distinguish between dyslipidemia, hypertension, prediabetes, type 2 diabetes, and healthy states, we find that the approach can accurately single out healthy individuals and characterize chronic multimorbid states. We further identify the capacity to forecast the development of metabolic syndrome years in advance of onset. Dataset-independent testing confirms the robustness of infrared signatures against variations in sample handling, storage time, and measurement regimes. This study provides the framework that establishes infrared molecular fingerprinting as an efficient modality for populational health diagnostics.
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Affiliation(s)
- Tarek Eissa
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany; Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany; School of Computation, Information and Technology, Technical University of Munich (TUM), Garching, Germany.
| | - Cristina Leonardo
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany
| | - Kosmas V Kepesidis
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany; Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany; Center for Molecular Fingerprinting (CMF), Budapest, Hungary
| | - Frank Fleischmann
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany; Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany
| | - Birgit Linkohr
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Daniel Meyer
- Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany; Center for Molecular Fingerprinting (CMF), Budapest, Hungary
| | - Viola Zoka
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany; Center for Molecular Fingerprinting (CMF), Budapest, Hungary
| | - Marinus Huber
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany; Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany
| | - Liudmila Voronina
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany
| | - Lothar Richter
- School of Computation, Information and Technology, Technical University of Munich (TUM), Garching, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany; School of Public Health, Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer, Ludwig Maximilian University of Munich (LMU), Munich, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Munich, Munich, Germany
| | - Mihaela Žigman
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany; Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany.
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2
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Yim A, Alberto M, Sharma V, Green A, Mclean A, du Plessis J, Wong LM, Wood B, Ischia J, Raman J, Bolton D. Near-infrared spectroscopy as a novel method of ex vivo bladder cancer tissue characterisation. BJU Int 2024; 133 Suppl 4:44-52. [PMID: 38238965 DOI: 10.1111/bju.16226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
Abstract
OBJECTIVE To evaluate near-infrared (NIR) spectroscopy in differentiating between benign and malignant bladder pathologies ex vivo immediately after resection, including the grade and stage of malignancy. PATIENTS AND METHODS A total of 355 spectra were measured on 71 bladder specimens from patients undergoing transurethral resection of bladder tumour (TURBT) between April and August 2022. Scan time was 5 s, undertaken using a portable NIR spectrometer within 10 min from excision. Specimens were then sent for routine histopathological correlation. Machine learning models were applied to the spectral dataset to construct diagnostic algorithms; these were then tested for their ability to predict the histological diagnosis of each sample using its NIR spectrum. RESULTS A two-group algorithm comparing low- vs high-grade urothelial cancer demonstrated 97% sensitivity, 99% specificity, and the area under the receiver operating characteristic curve (AUC) was 0.997. A three-group algorithm predicting stages Ta vs T1 vs T2 achieved 97% sensitivity, 92% specificity, and the AUC was 0.996. CONCLUSIONS This first study evaluating the diagnostic potential of NIR spectroscopy in urothelial cancer shows that it can be accurately used to assess tissue in an ex vivo setting immediately after TURBT. This offers point-of-care assessment of bladder pathology, with potential to influence the extent of resection, reducing both the need for re-resection where invasive disease may be suspected, and also the potential for complications where extent of diagnostic resection can be limited. Further studies utilising fibre-optic probes offer the potential for in vivo assessment.
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Affiliation(s)
- Arthur Yim
- Department of Urology, Austin Health, Heidelberg, Victoria, Australia
- Young Urology Researchers Organisation (YURO), Melbourne, Victoria, Australia
| | - Matthew Alberto
- Department of Urology, Austin Health, Heidelberg, Victoria, Australia
| | - Varun Sharma
- Department of Cardiac Surgery, Austin Health, Heidelberg, Victoria, Australia
- Department of Surgery, University of Melbourne, Melbourne, Victoria, Australia
- Spectromix Lab, Melbourne, Victoria, Australia
| | - Alexander Green
- Centre for Biospectroscopy, Monash University, Clayton, Victoria, Australia
| | - Aaron Mclean
- Centre for Biospectroscopy, Monash University, Clayton, Victoria, Australia
| | - Justin du Plessis
- Department of Anatomical Pathology, Austin Health, Heidelberg, Victoria, Australia
| | - Lih-Ming Wong
- Department of Urology, Austin Health, Heidelberg, Victoria, Australia
| | - Bayden Wood
- Spectromix Lab, Melbourne, Victoria, Australia
- Centre for Biospectroscopy, Monash University, Clayton, Victoria, Australia
| | - Joseph Ischia
- Department of Urology, Austin Health, Heidelberg, Victoria, Australia
| | - Jaishankar Raman
- Department of Cardiac Surgery, Austin Health, Heidelberg, Victoria, Australia
- Department of Surgery, University of Melbourne, Melbourne, Victoria, Australia
- Spectromix Lab, Melbourne, Victoria, Australia
| | - Damien Bolton
- Department of Urology, Austin Health, Heidelberg, Victoria, Australia
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3
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Félix MM, Tavares MV, Santos IP, Batista de Carvalho ALM, Batista de Carvalho LAE, Marques MPM. Cervical Squamous Cell Carcinoma Diagnosis by FTIR Microspectroscopy. Molecules 2024; 29:922. [PMID: 38474435 DOI: 10.3390/molecules29050922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 02/09/2024] [Accepted: 02/17/2024] [Indexed: 03/14/2024] Open
Abstract
Cervical cancer was considered the fourth most common cancer worldwide in 2020. In order to reduce mortality, an early diagnosis of the tumor is required. Currently, this type of cancer occurs mostly in developing countries due to the lack of vaccination and screening against the Human Papillomavirus. Thus, there is an urgent clinical need for new methods aiming at a reliable screening and an early diagnosis of precancerous and cancerous cervical lesions. Vibrational spectroscopy has provided very good results regarding the diagnosis of various tumors, particularly using Fourier transform infrared microspectroscopy, which has proved to be a promising complement to the currently used histopathological methods of cancer diagnosis. This spectroscopic technique was applied to the analysis of cryopreserved human cervical tissue samples, both squamous cell carcinoma (SCC) and non-cancer samples. A dedicated Support Vector Machine classification model was constructed in order to categorize the samples into either normal or malignant and was subsequently validated by cross-validation, with an accuracy higher than 90%.
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Affiliation(s)
- Maria M Félix
- Molecular Physical-Chemistry R&D Unit, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal
| | - Mariana V Tavares
- Molecular Physical-Chemistry R&D Unit, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal
- Gynaecology Department, Portuguese Oncology Institute of Porto, 4200-072 Porto, Portugal
| | - Inês P Santos
- Molecular Physical-Chemistry R&D Unit, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal
| | - Ana L M Batista de Carvalho
- Molecular Physical-Chemistry R&D Unit, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal
| | - Luís A E Batista de Carvalho
- Molecular Physical-Chemistry R&D Unit, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal
| | - Maria Paula M Marques
- Molecular Physical-Chemistry R&D Unit, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal
- Department of Life Sciences, Faculty of Science and Technology, University of Coimbra, 3000-456 Coimbra, Portugal
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Villamanca JJ, Hermogino LJ, Ong KD, Paguia B, Abanilla L, Lim A, Angeles LM, Espiritu B, Isais M, Tomas RC, Albano PM. Predicting the Likelihood of Colorectal Cancer with Artificial Intelligence Tools Using Fourier Transform Infrared Signals Obtained from Tumor Samples. APPLIED SPECTROSCOPY 2022; 76:1412-1428. [PMID: 35821580 DOI: 10.1177/00037028221116083] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The early and accurate detection of colorectal cancer (CRC) significantly affects its prognosis and clinical management. However, current standard diagnostic procedures for CRC often lack sensitivity and specificity since most rely on visual examination. Hence, there is a need to develop more accurate methods for its diagnosis. Support vector machine (SVM) and feedforward neural network (FNN) models were designed using the Fourier transform infrared (FT-IR) spectral data of several colorectal tissues that were unanimously identified as either benign or malignant by different unrelated pathologists. The set of samples in which the pathologists had discordant readings were then analyzed using the AI models described above. Between the SVM and NN models, the NN model was able to outperform the SVM model based on their prediction confidence scores. Using the spectral data of the concordant samples as training set, the FNN was able to predict the histologically diagnosed malignant tissues (n = 118) at 59.9-99.9% confidence (average = 93.5%). Of the 118 samples, 84 (71.18%) were classified with an above average confidence score, 34 (28.81%) classified below the average confidence score, and none was misclassified. Moreover, it was able to correctly identify the histologically confirmed benign samples (n = 83) at 51.5-99.7% confidence (average = 91.64%). Of the 83 samples, 60 (72.29%) were classified with an above average confidence score, 22 (26.51%) classified below the average confidence score, and only 1 sample (1.20%) was misclassified. The study provides additional proof of the ability of attenuated total reflection (ATR) FT-IR enhanced by AI tools to predict the likelihood of CRC without dependence on morphological changes in tissues.
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Affiliation(s)
- John Jerald Villamanca
- Department of Biological Sciences, College of Science, 564927University of Santo Tomas, Manila, Philippines
| | - Lemuel John Hermogino
- Department of Biological Sciences, College of Science, 564927University of Santo Tomas, Manila, Philippines
| | - Katherine Denise Ong
- Department of Biological Sciences, College of Science, 564927University of Santo Tomas, Manila, Philippines
| | - Brian Paguia
- Department of Biological Sciences, College of Science, 564927University of Santo Tomas, Manila, Philippines
| | - Lorenzo Abanilla
- Department of Pathology, Divine Word Hospital, Tacloban City, Philippines
| | - Antonio Lim
- Department of Pathology, Divine Word Hospital, Tacloban City, Philippines
| | - Lara Mae Angeles
- Department of Pathology, 596481University of Santo Tomas Hospital, Manila, Philippines
| | - Bernadette Espiritu
- Department of Pathology, 603332Bulacan Medical Center, Malolos City, Philippines
| | - Maura Isais
- Department of Pathology, 603332Bulacan Medical Center, Malolos City, Philippines
- The Graduate School, 595547University of Santo Tomas, Manila, Philippines
| | - Rock Christian Tomas
- Department of Electrical Engineering, 54729University of the Philippines Los Baños, Los Baños, Philippines
| | - Pia Marie Albano
- Department of Biological Sciences, College of Science, 564927University of Santo Tomas, Manila, Philippines
- Department of Pathology, Divine Word Hospital, Tacloban City, Philippines
- Research Center for the Natural and Applied Sciences, 564927University of Santo Tomas, Manila, Philippines
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5
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George RS, Sivaperumal P, Roy A. Extracellular polymeric substances from marine actinobacterium of Micromonospora sp. and their antioxidant activity. J Adv Pharm Technol Res 2022; 13:S80-S83. [PMID: 36643140 PMCID: PMC9836164 DOI: 10.4103/japtr.japtr_335_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 06/30/2022] [Accepted: 07/02/2022] [Indexed: 01/17/2023] Open
Abstract
Actinobacteria, Gram-positive bacteria are the largest phyla among the major species in the bacteria domain. Micromonospora sp. is one of the secondary metabolite-producing Actinobacteria, and it has a comprehensive spectrum of antibacterial, antifungal, antitumor, antiviral, antiparasitic, diabetogenic anti-inflammatory, insecticidal, inhibitory of enzyme, antioxidant, and other biological activities. The objective of the study is to assess the antioxidant activity of the Actinobacterium Micromonospora sp. producing extracellular polymeric substances (EPSs). Enumeration and isolation of Actinobacteria from sediment samples are done. The marine Actinobacteria, Micromonospora sp. are identified by melanoid pigments and other chemotaxonomical characteristics. EPS is produced from the potential marine Actinobacteria and their components are estimated. The total antioxidant value is found for the EPS. The antioxidant activity of the ascorbic acid equivalent which was 142.65 μg/ml was equivalent to 150 μg/ml of the total antioxidant activity of the EPS produced. The role of different antioxidants and the action in different diseases were challenged since they could act as many mechanisms such as reducing power, providing hydrogen to radicals, and scavenging activity (free radical). To conclude, the potent antioxidant activity was obtained from Actinobacteria Micromonospora sp. producing extracellular substances. These extracts might bear anticancer metabolites and are considered a potent anticancer drug.
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Affiliation(s)
- Rinki Susan George
- Department of Pharmacology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India
| | - Pitchiah Sivaperumal
- Marine Biomedical Research Lab and Environmental Toxicology Unit, Cellular and Molecular Research Centre, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India,Address for correspondence: Dr. Pitchiah Sivaperumal, Marine Biomedical Research Lab and Environmental Toxicology Unit, Cellular and Molecular Research Centre, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai - 600 077, Tamil Nadu, India. E-mail:
| | - Anitha Roy
- Department of Pharmacology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India
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Kepesidis KV, Bozic-Iven M, Huber M, Abdel-Aziz N, Kullab S, Abdelwarith A, Al Diab A, Al Ghamdi M, Hilal MA, Bahadoor MRK, Sharma A, Dabouz F, Arafah M, Azzeer AM, Krausz F, Alsaleh K, Zigman M, Nabholtz JM. Breast-cancer detection using blood-based infrared molecular fingerprints. BMC Cancer 2021; 21:1287. [PMID: 34856945 PMCID: PMC8638519 DOI: 10.1186/s12885-021-09017-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 11/16/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Breast cancer screening is currently predominantly based on mammography, tainted with the occurrence of both false positivity and false negativity, urging for innovative strategies, as effective detection of early-stage breast cancer bears the potential to reduce mortality. Here we report the results of a prospective pilot study on breast cancer detection using blood plasma analyzed by Fourier-transform infrared (FTIR) spectroscopy - a rapid, cost-effective technique with minimal sample volume requirements and potential to aid biomedical diagnostics. FTIR has the capacity to probe health phenotypes via the investigation of the full repertoire of molecular species within a sample at once, within a single measurement in a high-throughput manner. In this study, we take advantage of cross-molecular fingerprinting to probe for breast cancer detection. METHODS We compare two groups: 26 patients diagnosed with breast cancer to a same-sized group of age-matched healthy, asymptomatic female participants. Training with support-vector machines (SVM), we derive classification models that we test in a repeated 10-fold cross-validation over 10 times. In addition, we investigate spectral information responsible for BC identification using statistical significance testing. RESULTS Our models to detect breast cancer achieve an average overall performance of 0.79 in terms of area under the curve (AUC) of the receiver operating characteristic (ROC). In addition, we uncover a relationship between the effect size of the measured infrared fingerprints and the tumor progression. CONCLUSION This pilot study provides the foundation for further extending and evaluating blood-based infrared probing approach as a possible cross-molecular fingerprinting modality to tackle breast cancer detection and thus possibly contribute to the future of cancer screening.
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Affiliation(s)
- Kosmas V Kepesidis
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany.
- Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany.
| | - Masa Bozic-Iven
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany
| | - Marinus Huber
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany
- Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany
| | - Nashwa Abdel-Aziz
- Oncology Centre, King Saud University (Medical City), Riyadh, Saudi Arabia
| | - Sharif Kullab
- Oncology Centre, King Saud University (Medical City), Riyadh, Saudi Arabia
| | - Ahmed Abdelwarith
- Oncology Centre, King Saud University (Medical City), Riyadh, Saudi Arabia
| | | | - Mohammed Al Ghamdi
- Oncology Centre, King Saud University (Medical City), Riyadh, Saudi Arabia
| | - Muath Abu Hilal
- Oncology Centre, King Saud University (Medical City), Riyadh, Saudi Arabia
| | - Mohun R K Bahadoor
- Clinical Operations, International Cancer Research Group (ICRG), Sharjah, United Arab Emirates
| | - Abhishake Sharma
- Clinical Operations, International Cancer Research Group (ICRG), Sharjah, United Arab Emirates
| | - Farida Dabouz
- Clinical Operations, International Cancer Research Group (ICRG), Sharjah, United Arab Emirates
| | - Maria Arafah
- Pathology Department, King Saud University, Riyadh, Saudi Arabia
| | - Abdallah M Azzeer
- Physics and Astronomy Department, Attosecond Science Laboratory, King Saud University, Riyadh, Saudi Arabia
| | - Ferenc Krausz
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany
- Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany
| | - Khalid Alsaleh
- Oncology Centre, King Saud University (Medical City), Riyadh, Saudi Arabia
| | - Mihaela Zigman
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany
- Laboratory for Attosecond Physics, Max Planck Institute of Quantum Optics (MPQ), Garching, Germany
| | - Jean-Marc Nabholtz
- Department of Laser Physics, Ludwig Maximilian University of Munich (LMU), Garching, Germany
- Oncology Centre, King Saud University (Medical City), Riyadh, Saudi Arabia
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7
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Richards O, Jenkins C, Griffiths H, Paczkowska E, Dunstan PR, Jones S, Morgan M, Thomas T, Bowden J, Nakimuli A, Nair M, Thornton CA. Vibrational Spectroscopy: A Valuable Screening and Diagnostic Tool for Obstetric Disorders? Front Glob Womens Health 2021; 1:610582. [PMID: 34816172 PMCID: PMC8593960 DOI: 10.3389/fgwh.2020.610582] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 12/11/2020] [Indexed: 12/24/2022] Open
Abstract
Preeclampsia (PE) is a common obstetric disorder typically affecting 2–8% of all pregnancies and can lead to several adverse obstetric outcomes for both mother and fetus with the greatest burden of severe outcomes in low middle-income countries (LMICs), therefore, screening for PE is vital. Globally, screening is based on maternal characteristics and medical history which are nonspecific for the disorder. In 2004, the World Health Organization acknowledged that no clinically useful test was able to predict the onset of PE, which prompted a universal search for alternative means of screening. Over the past decade or so, emphasis has been placed on the use of maternal characteristics in conjunction with biomarkers of disease combined into predictive algorithms, however these are yet to transition into the clinic and are cost prohibitive in LMICs. As a result, the screening paradigm for PE remains unchanged. It is evident that novel approaches are needed. Vibrational spectroscopy, specifically Raman spectroscopy and Fourier-transform infrared spectroscopy (FTIR), could provide better alternatives suited for implementation in low resource settings as no specialized reagents are required for conventional approaches and there is a drive to portable platforms usable in both urban and rual community settings. These techniques are based on light scattering and absorption, respectively, allowing detailed molecular analysis of samples to produce a unique molecular fingerprint of diseased states. The specificity of vibrational spectroscopy might well make it suited for application in other obstetric disorders such as gestational diabetes mellitus and obstetric cholestasis. In this review, we summarize current approaches sought as alternatives to current screening methodologies and introduce how vibrational spectroscopy could offer superior screening and diagnostic paradigms in obstetric care. Additionally, we propose a real benefit of such tools in LMICs where limited resources battle the higher prevalence of obstetric disorders.
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Affiliation(s)
- Oliver Richards
- Institute of Life Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Cerys Jenkins
- Department of Physics, College of Science, Swansea University, Swansea, United Kingdom
| | - Helena Griffiths
- Institute of Life Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Edyta Paczkowska
- Institute of Life Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
| | - Peter R Dunstan
- Department of Physics, College of Science, Swansea University, Swansea, United Kingdom
| | - Sharon Jones
- Maternity and Child Health, Singleton Hospital, Swansea Bay University Health Board, Swansea, United Kingdom
| | - Margery Morgan
- Maternity and Child Health, Singleton Hospital, Swansea Bay University Health Board, Swansea, United Kingdom
| | - Tanya Thomas
- Maternity and Child Health, Singleton Hospital, Swansea Bay University Health Board, Swansea, United Kingdom
| | - Jayne Bowden
- Maternity and Child Health, Singleton Hospital, Swansea Bay University Health Board, Swansea, United Kingdom
| | - Annettee Nakimuli
- Department of Obstetrics and Gynaecology, School of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
| | - Manju Nair
- Maternity and Child Health, Singleton Hospital, Swansea Bay University Health Board, Swansea, United Kingdom
| | - Catherine A Thornton
- Institute of Life Science, Swansea University Medical School, Swansea University, Swansea, United Kingdom
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8
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Huber M, Kepesidis KV, Voronina L, Fleischmann F, Fill E, Hermann J, Koch I, Milger-Kneidinger K, Kolben T, Schulz GB, Jokisch F, Behr J, Harbeck N, Reiser M, Stief C, Krausz F, Zigman M. Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer. eLife 2021; 10:68758. [PMID: 34696827 PMCID: PMC8547961 DOI: 10.7554/elife.68758] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 09/13/2021] [Indexed: 01/11/2023] Open
Abstract
Recent omics analyses of human biofluids provide opportunities to probe selected species of biomolecules for disease diagnostics. Fourier-transform infrared (FTIR) spectroscopy investigates the full repertoire of molecular species within a sample at once. Here, we present a multi-institutional study in which we analysed infrared fingerprints of plasma and serum samples from 1639 individuals with different solid tumours and carefully matched symptomatic and non-symptomatic reference individuals. Focusing on breast, bladder, prostate, and lung cancer, we find that infrared molecular fingerprinting is capable of detecting cancer: training a support vector machine algorithm allowed us to obtain binary classification performance in the range of 0.78-0.89 (area under the receiver operating characteristic curve [AUC]), with a clear correlation between AUC and tumour load. Intriguingly, we find that the spectral signatures differ between different cancer types. This study lays the foundation for high-throughput onco-IR-phenotyping of four common cancers, providing a cost-effective, complementary analytical tool for disease recognition.
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Affiliation(s)
- Marinus Huber
- Ludwig Maximilians University Munich (LMU), Department of Laser Physics, Garching, Germany.,Max Planck Institute of Quantum Optics (MPQ), Laboratory for Attosecond Physics, Garching, Germany
| | - Kosmas V Kepesidis
- Ludwig Maximilians University Munich (LMU), Department of Laser Physics, Garching, Germany.,Max Planck Institute of Quantum Optics (MPQ), Laboratory for Attosecond Physics, Garching, Germany
| | - Liudmila Voronina
- Ludwig Maximilians University Munich (LMU), Department of Laser Physics, Garching, Germany
| | - Frank Fleischmann
- Ludwig Maximilians University Munich (LMU), Department of Laser Physics, Garching, Germany
| | - Ernst Fill
- Max Planck Institute of Quantum Optics (MPQ), Laboratory for Attosecond Physics, Garching, Germany
| | - Jacqueline Hermann
- Ludwig Maximilians University Munich (LMU), Department of Laser Physics, Garching, Germany
| | - Ina Koch
- Asklepios Biobank for Lung Diseases, Department of Thoracic Surgery, Member of the German Center for Lung Research, DZL, Asklepios Fachkliniken München-Gauting, Munich, Germany
| | - Katrin Milger-Kneidinger
- University Hospital of the Ludwig Maximilians University Munich (LMU), Department of Internal Medicine V, Munich, Germany
| | - Thomas Kolben
- University Hospital of the Ludwig Maximilians University Munich (LMU), Department of Obstetrics and Gynecology, Breast Center and Comprehensive Cancer Center (CCLMU), Munich, Germany
| | - Gerald B Schulz
- University Hospital of the Ludwig Maximilians University Munich (LMU), Department of Urology, Munich, Germany
| | - Friedrich Jokisch
- University Hospital of the Ludwig Maximilians University Munich (LMU), Department of Urology, Munich, Germany
| | - Jürgen Behr
- University Hospital of the Ludwig Maximilians University Munich (LMU), Department of Internal Medicine V, Munich, Germany
| | - Nadia Harbeck
- University Hospital of the Ludwig Maximilians University Munich (LMU), Department of Obstetrics and Gynecology, Breast Center and Comprehensive Cancer Center (CCLMU), Munich, Germany
| | - Maximilian Reiser
- University Hospital of the Ludwig Maximilians University Munich (LMU), Department of Clinical Radiology, Munich, Germany
| | - Christian Stief
- University Hospital of the Ludwig Maximilians University Munich (LMU), Department of Urology, Munich, Germany
| | - Ferenc Krausz
- Ludwig Maximilians University Munich (LMU), Department of Laser Physics, Garching, Germany.,Max Planck Institute of Quantum Optics (MPQ), Laboratory for Attosecond Physics, Garching, Germany
| | - Mihaela Zigman
- Ludwig Maximilians University Munich (LMU), Department of Laser Physics, Garching, Germany.,Max Planck Institute of Quantum Optics (MPQ), Laboratory for Attosecond Physics, Garching, Germany
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