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Sezer G, Sahin F, Onses MS, Cumaoglu A. Activation of epidermal growth factor receptors in triple-negative breast cancer cells by morphine; analysis through Raman spectroscopy and machine learning. Talanta 2024; 272:125827. [PMID: 38432124 DOI: 10.1016/j.talanta.2024.125827] [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] [Received: 12/16/2023] [Revised: 02/20/2024] [Accepted: 02/21/2024] [Indexed: 03/05/2024]
Abstract
Triple negative breast cancer (TNBC) is a very aggressive form of breast cancer, and the analgesic drug morphine has been shown to promote the proliferation of TNBC cells. This article investigates whether morphine causes activation of epidermal growth factor receptors (EGFR), the roles of μ-opioid and EGFR receptors on TNBC cell proliferation and migration. While examining the changes with molecular techniques, we also aimed to investigate the analysis ability of Raman spectroscopy and machine learning-based approach. Effects of morphine on the proliferation and migration of MDA.MB.231 cells were evaluated by MTT and scratch wound-healing tests, respectively. Morphine-induced phosphorylation of the EGFR was analyzed by western blotting in the presence and absence of μ-receptor antagonist naltrexone and the EGFR-tyrosine kinase inhibitor gefitinib. Morphine-induced EGFR phosphorylation and cell migration were significantly inhibited by pretreatments with both naltrexone and gefitinib; however, morphine-increased cell proliferation was inhibited only by naltrexone. While morphine-induced changes were observed in the Raman scatterings of the cells, the inhibitory effect of naltrexone was analyzed with similarity to the control group. Principal component analysis (PCA) of the Raman confirmed the epidermal growth factor (EGF)-like effect of morphine and was inhibited by naltrexone and partly by gefitinib pretreatments. Our in vitro results suggest that combining morphine with an EGFR inhibitor or a peripherally acting opioidergic receptor antagonist may be a good strategy for pain relief without triggering cancer proliferation and migration in TNBC patients. In addition, our results demonstrated the feasibility of the Raman spectroscopy and machine learning-based approach as an effective method to investigate the effects of agents in cancer cells without the need for complex and time-consuming sample preparation. The support vector machine (SVM) with linear kernel automatically classified the effects of drugs on cancer cells with ∼95% accuracy.
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Affiliation(s)
- Gulay Sezer
- Department of Pharmacology, Faculty of Medicine, Erciyes University, 38039, Kayseri, Turkey; Genkok Genome and Stem Cell Center, Erciyes University, 38039, Kayseri, Turkey.
| | - Furkan Sahin
- Department of Biomedical Engineering, Faculty of Engineering and Architecture, Beykent University, 34398, Istanbul, Turkey; ERNAM - Erciyes University Nanotechnology Application and Research Center, 38039, Kayseri, Turkey
| | - M Serdar Onses
- ERNAM - Erciyes University Nanotechnology Application and Research Center, 38039, Kayseri, Turkey; Department of Materials Science and Engineering, Erciyes University, 38039, Kayseri, Turkey; UNAM-National Nanotechnology Research Center, Institute of Materials Science and Nanotechnology, Bilkent University, 06800, Ankara, Turkey
| | - Ahmet Cumaoglu
- Department of Biochemistry, School of Pharmacy, Erciyes University, Kayseri, Turkey
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2
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Lopes DF, Silverio A, Schmidt AKA, Picca GB, Silveira L. Characterization of biomarkers in blood serum for cancer diagnosis in dogs using Raman spectroscopy. JOURNAL OF BIOPHOTONICS 2024; 17:e202300338. [PMID: 38100121 DOI: 10.1002/jbio.202300338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 10/25/2023] [Accepted: 12/03/2023] [Indexed: 03/26/2024]
Abstract
Biomarkers of cancer in sera of domestic dogs were detected through Raman spectroscopy with 830 nm excitation. Raman spectra of sera from 61 dogs (31 healthy and 30 with cancer, resulting in 154 and 200 spectra, respectively) were submitted to principal component analysis (PCA) for feature extraction and partial least squares (PLS) regression for discrimination between Healthy and Cancer groups. In the PCA, the peaks at 1132, 1342, 1368, and 1453 cm-1 (albumin and phenylalanine) were higher for the Cancer group. The "redshift" of the peaks at 621, 1003, and 1032 cm-1 (conformational change in proteins and/or bonds at sites close to the aromatic ring of amino acids) occurred in the Cancer group, and the peaks at 451 cm-1 (tryptophan) and 1441 cm-1 (lipids) were higher for the Healthy group. The PLS-DA classified the serum spectra in Healthy and Cancer groups with high accuracy (78%).
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Affiliation(s)
| | | | | | | | - Landulfo Silveira
- Universidade Anhembi Morumbi-UAM, São Paulo, Brazil
- Center for Innovation, Technology and Education-CITÉ, Parque Tecnológico de São José dos Campos, São José dos Campos, São Paulo, Brazil
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Kralova K, Kral M, Vrtelka O, Setnicka V. Comparative study of Raman spectroscopy techniques in blood plasma-based clinical diagnostics: A demonstration on Alzheimer's disease. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 304:123392. [PMID: 37716043 DOI: 10.1016/j.saa.2023.123392] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 08/26/2023] [Accepted: 09/08/2023] [Indexed: 09/18/2023]
Abstract
Nowadays, there are still many diseases with limited or no reliable methods of early diagnosis. A popular approach in clinical diagnostic research is Raman spectroscopy, as a relatively simple, cost-effective, and high-throughput method for searching for disease-specific alterations in the composition of blood plasma. However, the high variability of the experimental designs, targeted diseases, or statistical processing in the individual studies makes it challenging to compare and compile the results to critically assess the applicability of Raman spectroscopy in real clinical practice. This study aimed to compare data from a single series of blood plasma samples of patients with Alzheimer's disease and non-demented elderly controls obtained by four different techniques/experimental setups - Raman spectroscopy with excitation at 532 and 785 nm, Raman optical activity, and surface-enhanced Raman scattering spectroscopy. The obtained results showed that the spectra from each Raman spectroscopy technique contain different information about biomolecules of blood plasma or their conformation and may, therefore, offer diverse points of view on underlying biochemical processes of the disease. The classification models based on the datasets generated by the three non-chiroptical variants of Raman spectroscopy exhibited comparable diagnostic performance, all reaching an accuracy close to or equal to 80%. Raman optical activity achieved only 60% classification accuracy, suggesting its limited applicability in the specific case of Alzheimer's disease diagnostics. The described differences in the outputs of the four utilized techniques/setups of Raman spectroscopy imply that their choice may crucially affect the acquired results and thus should be approached carefully concerning the specific purpose.
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Affiliation(s)
- Katerina Kralova
- Department of Analytical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technická 5, 166 28 Prague 6, Czech Republic
| | - Martin Kral
- Department of Physical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technická 5, 166 28 Prague 6, Czech Republic
| | - Ondrej Vrtelka
- Department of Analytical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technická 5, 166 28 Prague 6, Czech Republic
| | - Vladimir Setnicka
- Department of Analytical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technická 5, 166 28 Prague 6, Czech Republic.
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Khristoforova Y, Bratchenko L, Bratchenko I. Raman-Based Techniques in Medical Applications for Diagnostic Tasks: A Review. Int J Mol Sci 2023; 24:15605. [PMID: 37958586 PMCID: PMC10647591 DOI: 10.3390/ijms242115605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 10/23/2023] [Accepted: 10/24/2023] [Indexed: 11/15/2023] Open
Abstract
Raman spectroscopy is a widely developing approach for noninvasive analysis that can provide information on chemical composition and molecular structure. High chemical specificity calls for developing different medical diagnostic applications based on Raman spectroscopy. This review focuses on the Raman-based techniques used in medical diagnostics and provides an overview of such techniques, possible areas of their application, and current limitations. We have reviewed recent studies proposing conventional Raman spectroscopy and surface-enhanced Raman spectroscopy for rapid measuring of specific biomarkers of such diseases as cardiovascular disease, cancer, neurogenerative disease, and coronavirus disease (COVID-19). As a result, we have discovered several most promising Raman-based applications to identify affected persons by detecting some significant spectral features. We have analyzed these approaches in terms of their potentially diagnostic power and highlighted the remaining challenges and limitations preventing their translation into clinical settings.
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Affiliation(s)
| | | | - Ivan Bratchenko
- Department of Laser and Biotechnical Systems, Samara National Research University, 34 Moskovskoye Shosse, Samara 443086, Russia; (Y.K.)
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Saha P, Sawant S, Deshmukh A, Hole A, Murali Krishna C. Serum Raman spectroscopy: Prognostic applications in oral cancers. Head Neck 2023; 45:1244-1254. [PMID: 36919570 DOI: 10.1002/hed.27338] [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: 09/09/2022] [Revised: 01/30/2023] [Accepted: 02/22/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND Loco-regional recurrences attributable to field cancerization and minimal residual cancer, remain prime causes of mortality in oral cancer (OC) subjects. The current study evaluates potential of serum Raman spectroscopy (SRS) to identify recurrence-prone OC subjects. METHODS Raman spectra of serum from eight healthy subjects (H) and 57 OC subjects (with-recurrence [R], without-recurrence [NR], and with suspicious-lesions [S]), before (BS) and after (AS) surgical excision of tumor were recorded. OC subjects were followed-up for 7-years. RESULTS DNA and protein alterations were observed in AS sera of all groups. 4-, 3-, and 2-model multivariate analyses were used to stratify BS and AS groups. H spectra were 100% distinguishable from all other groups. AS, R and NR were distinguished with high accuracy (84%) in all models. No stratification (~50%) was observed BS. CONCLUSION SRS shows potential to identify recurrence prone subjects, post-surgery, using serum collected as early as 1 week after surgery.
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Affiliation(s)
- Panchali Saha
- Tata Memorial Centre, Advanced Centre for Treatment, Education and Research in Cancer, Navi Mumbai, Maharashtra, India.,Training School Complex, Homi Bhabha National Institute, Anushakti Nagar, Maharashtra, India
| | - Sharada Sawant
- Tata Memorial Centre, Advanced Centre for Treatment, Education and Research in Cancer, Navi Mumbai, Maharashtra, India
| | - Atul Deshmukh
- Centre for Interdisciplinary Research, D.Y. Patil University, Navi Mumbai, Maharashtra, India
| | - Arti Hole
- Tata Memorial Centre, Advanced Centre for Treatment, Education and Research in Cancer, Navi Mumbai, Maharashtra, India
| | - C Murali Krishna
- Tata Memorial Centre, Advanced Centre for Treatment, Education and Research in Cancer, Navi Mumbai, Maharashtra, India.,Training School Complex, Homi Bhabha National Institute, Anushakti Nagar, Maharashtra, India
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Han S, Chen C, Chen C, Wu L, Wu X, Lu C, Zhang X, Chao P, Lv X, Jia Z, Hou J. Coupling annealed silver nanoparticles with a porous silicon Bragg mirror SERS substrate and machine learning for rapid non-invasive disease diagnosis. Anal Chim Acta 2023; 1254:341116. [PMID: 37005026 DOI: 10.1016/j.aca.2023.341116] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Revised: 01/13/2023] [Accepted: 03/16/2023] [Indexed: 03/19/2023]
Abstract
Ag2O-Ag-porous silicon Bragg mirror (PSB) composite SERS substrates were successfully synthesized by using a combination of electrochemical and thermochemical methods. Test results showed that the SERS signal increased and decreased as the annealing temperature used for the substrate increased, where the most intense SERS signal was obtained using a substrate annealed at 300 °C. Stability test results showed substantial enhancement of the SERS signal intensity of the Ag2O-Ag-PSB composite one month after preparation compared with that of conventional Ag-PSB. We conclude that Ag2O nanoshells play an essential role in SERS signal enhancement. Ag2O prevents natural oxidation of Ag nanoparticles (AgNPs) and has a solid localized surface plasmon resonance (LSPR). SERS signal enhancement was tested using this substrate for serum from patients with Sjögren's syndrome (SS) and Diabetic nephropathy (DN), as well as from healthy controls (HC). SERS feature extraction was performed using principal component analysis (PCA). The extracted features were analyzed by a support vector machine (SVM) algorithm. Finally, a rapid screening model for SS and HC, as well as DN and HC, was developed and used to perform controlled experiments. The results showed that the diagnostic accuracy, sensitivity and selectivity for SERS technology combined with machine learning algorithms reached 90.7%, 93.4% and 86.7% for SS/HC and 89.3%, 95.6% and 80% for DN/HC, respectively. The results of this study show that the composite substrate has excellent potential to be developed into a commercially available SERS chip for medical testing.
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Discovering Glioma Tissue through Its Biomarkers' Detection in Blood by Raman Spectroscopy and Machine Learning. Pharmaceutics 2023; 15:pharmaceutics15010203. [PMID: 36678833 PMCID: PMC9862809 DOI: 10.3390/pharmaceutics15010203] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 12/27/2022] [Accepted: 12/29/2022] [Indexed: 01/11/2023] Open
Abstract
The most commonly occurring malignant brain tumors are gliomas, and among them is glioblastoma multiforme. The main idea of the paper is to estimate dependency between glioma tissue and blood serum biomarkers using Raman spectroscopy. We used the most common model of human glioma when continuous cell lines, such as U87, derived from primary human tumor cells, are transplanted intracranially into the mouse brain. We studied the separability of the experimental and control groups by machine learning methods and discovered the most informative Raman spectral bands. During the glioblastoma development, an increase in the contribution of lactate, tryptophan, fatty acids, and lipids in dried blood serum Raman spectra were observed. This overlaps with analogous results of glioma tissues from direct Raman spectroscopy studies. A non-linear relationship between specific Raman spectral lines and tumor size was discovered. Therefore, the analysis of blood serum can track the change in the state of brain tissues during the glioma development.
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Wang X, Xie F, Yang Y, Zhao J, Wu G, Wang S. Rapid Diagnosis of Ductal Carcinoma In Situ and Breast Cancer Based on Raman Spectroscopy of Serum Combined with Convolutional Neural Network. BIOENGINEERING (BASEL, SWITZERLAND) 2023; 10:bioengineering10010065. [PMID: 36671637 PMCID: PMC9854817 DOI: 10.3390/bioengineering10010065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 12/22/2022] [Accepted: 12/27/2022] [Indexed: 01/06/2023]
Abstract
Ductal carcinoma in situ (DCIS) and breast cancer are common female breast diseases and pose a serious health threat to women. Early diagnosis of breast cancer and DCIS can help to develop targeted treatment plans in time. In this paper, we investigated the feasibility of using Raman spectroscopy combined with convolutional neural network (CNN) to discriminate between healthy volunteers, breast cancer and DCIS patients. Raman spectra were collected from the sera of 241 healthy volunteers, 463 breast cancer and 100 DCIS patients, and a total of 804 spectra were recorded. The pre-processed Raman spectra were used as the input of CNN to establish a model to classify the three different spectra. After using cross-validation to optimize its hyperparameters, the model's final classification performance was assessed using an unknown test set. For comparison with other machine learning algorithms, we additionally built models using support vector machine (SVM), random forest (RF) and k-nearest neighbor (KNN) methods. The final accuracies for CNN, SVM, RF and KNN were 98.76%, 94.63%, 80.99% and 78.93%, respectively. The values for area under curve (AUC) were 0.999, 0.994, 0.931 and 0.900, respectively. Therefore, our study results demonstrate that CNN outperforms three traditional algorithms in terms of classification performance for Raman spectral data and can be a useful auxiliary diagnostic tool of breast cancer and DCIS.
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Affiliation(s)
- Xianglei Wang
- School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Fei Xie
- Department of Breast Center, Peking University People’s Hospital, Beijing 100044, China
| | - Yang Yang
- Department of Breast Center, Peking University People’s Hospital, Beijing 100044, China
| | - Jin Zhao
- Department of Breast Center, Peking University People’s Hospital, Beijing 100044, China
| | - Guohua Wu
- School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
- Correspondence: (G.W.); (S.W.)
| | - Shu Wang
- Department of Breast Center, Peking University People’s Hospital, Beijing 100044, China
- Correspondence: (G.W.); (S.W.)
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Zniber M, Vahdatiyekta P, Huynh TP. Analysis of urine using electronic tongue towards non-invasive cancer diagnosis. Biosens Bioelectron 2023; 219:114810. [PMID: 36272349 DOI: 10.1016/j.bios.2022.114810] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 04/27/2022] [Accepted: 10/11/2022] [Indexed: 11/06/2022]
Abstract
Electronic tongues (e-tongues) have been broadly employed in monitoring the quality of food, beverage, cosmetics, and pharmaceutical products, and in diagnosis of diseases, as the e-tongues can discriminate samples of high complexity, reduce interference of the matrix, offer rapid response. Compared to other analytical approaches using expensive and complex instrumentation as well as required sample preparation, the e-tongue is non-destructive, miniaturizable and on-site method with little or no preparation of samples. Even though e-tongues are successfully commercialized, their application in cancer diagnosis from urine samples is underestimated. In this review, we would like to highlight the various analytical techniques such as Raman spectroscopy, infrared spectroscopy, fluorescence spectroscopy, and electrochemical methods (potentiometry and voltammetry) used as e-tongues for urine analysis towards non-invasive cancer diagnosis. Besides, different machine learning approaches, for instance, supervised and unsupervised learning algorithms are introduced to analyze extracted chemical data. Finally, capabilities of e-tongues in distinguishing between patients diagnosed with cancer and healthy controls are highlighted.
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Affiliation(s)
- Mohammed Zniber
- Laboratory of Molecular Science and Engineering, Åbo Akademi University, 20500, Turku, Finland
| | - Parastoo Vahdatiyekta
- Laboratory of Molecular Science and Engineering, Åbo Akademi University, 20500, Turku, Finland
| | - Tan-Phat Huynh
- Laboratory of Molecular Science and Engineering, Åbo Akademi University, 20500, Turku, Finland.
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10
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Zheng X, Wu G, Lv G, Yin L, Lv X. Rapid discrimination of hepatic echinococcosis patients' serum using vibrational spectroscopy combined with support vector machines. Photodiagnosis Photodyn Ther 2022; 40:103027. [PMID: 35882291 DOI: 10.1016/j.pdpdt.2022.103027] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 07/16/2022] [Accepted: 07/20/2022] [Indexed: 12/14/2022]
Abstract
Echinococcosis is a severe zoonotic parasitic disease, and it is continuing to be a significant public health issue. The course of the disease is usually slow, and patients often remain asymptomatic for years. There is no standardized and widely accepted treatment, so early and accurate diagnosis is essential. Herein, this study utilized vibrational spectroscopic techniques, namely Raman and Fourier Transform Infrared (FTIR) spectroscopy, to quickly and accurately distinguish hepatic echinococcosis (HE) patients' serum from the healthy group. Serum samples were collected from HE patients as well as healthy control subjects, and then the Raman and FTIR spectra of the two groups were recorded. After a series of pre-processing, support vector machines (SVMs) were then used to establish the classification models for the two spectral data sets. The performance of each diagnostic model was evaluated using leave-one-out cross-validation (LOOCV) and hold-out validation methods, respectively. For the distinction between HE and healthy groups, these two spectroscopic techniques had achieved satisfactory classification results, and the diagnostic capabilities of the Raman technique were comparable to that of the FTIR method. The results demonstrate that vibrational spectroscopy has great potential in the rapid and accurate detection of HE and is expected to make up for the shortcomings of the existing clinical diagnosis methods.
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Affiliation(s)
- Xiangxiang Zheng
- School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Guohua Wu
- School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.
| | - Guodong Lv
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, China
| | - Longfei Yin
- School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Xiaoyi Lv
- School of Software, Xinjiang University, Urumqi 830091, China
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11
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Goff NK, Dou T, Higgins S, Horn EJ, Morey R, McClellan K, Kurouski D, Rogovskyy AS. Testing Raman spectroscopy as a diagnostic approach for Lyme disease patients. Front Cell Infect Microbiol 2022; 12:1006134. [PMID: 36389168 PMCID: PMC9647194 DOI: 10.3389/fcimb.2022.1006134] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 09/05/2022] [Indexed: 11/29/2022] Open
Abstract
Lyme disease (LD), the leading tick-borne disease in the Northern hemisphere, is caused by spirochetes of several genospecies of the Borreliella burgdorferi sensu lato complex. LD is a multi-systemic and highly debilitating illness that is notoriously challenging to diagnose. The main drawbacks of the two-tiered serology, the only approved diagnostic test in the United States, include poor sensitivity, background seropositivity, and cross-reactivity. Recently, Raman spectroscopy (RS) was examined for its LD diagnostic utility by our earlier proof-of-concept study. The previous investigation analyzed the blood from mice that were infected with 297 and B31 strains of Borreliella burgdorferi sensu stricto (s.s.). The selected strains represented two out of the three major clades of B. burgdorferi s.s. isolates found in the United States. The obtained results were encouraging and prompted us to further investigate the RS diagnostic capacity for LD in this study. The present investigation has analyzed blood of mice infected with European genospecies, Borreliella afzelii or Borreliella garinii, or B. burgdorferi N40, a strain of the third major class of B. burgdorferi s.s. in the United States. Moreover, 90 human serum samples that originated from LD-confirmed, LD-negative, and LD-probable human patients were also analyzed by RS. The overall results demonstrated that blood samples from Borreliella-infected mice were identified with 96% accuracy, 94% sensitivity, and 100% specificity. Furthermore, human blood samples were analyzed with 88% accuracy, 85% sensitivity, and 90% specificity. Together, the current data indicate that RS should be further explored as a potential diagnostic test for LD patients.
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Affiliation(s)
- Nicolas K. Goff
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, United States
| | - Tianyi Dou
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, United States
| | - Samantha Higgins
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, United States
| | | | - Rohini Morey
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, United States
| | - Kyle McClellan
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, United States
| | - Dmitry Kurouski
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, United States
- *Correspondence: Dmitry Kurouski, ; Artem S. Rogovskyy,
| | - Artem S. Rogovskyy
- Department of Veterinary Pathobiology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, United States
- *Correspondence: Dmitry Kurouski, ; Artem S. Rogovskyy,
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12
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Rapid label-free detection of cholangiocarcinoma from human serum using Raman spectroscopy. PLoS One 2022; 17:e0275362. [PMID: 36227878 PMCID: PMC9562168 DOI: 10.1371/journal.pone.0275362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Accepted: 09/15/2022] [Indexed: 11/25/2022] Open
Abstract
Cholangiocarcinoma (CCA) is highly prevalent in the northeastern region of Thailand. Current diagnostic methods for CCA are often expensive, time-consuming, and require medical professionals. Thus, there is a need for a simple and low-cost CCA screening method. This work developed a rapid label-free technique by Raman spectroscopy combined with the multivariate statistical methods of principal component analysis and linear discriminant analysis (PCA-LDA), aiming to analyze and classify between CCA (n = 30) and healthy (n = 30) serum specimens. The model's classification performance was validated using k-fold cross validation (k = 5). Serum levels of cholesterol (548, 700 cm-1), tryptophan (878 cm-1), and amide III (1248,1265 cm-1) were found to be statistically significantly higher in the CCA patients, whereas serum beta-carotene (1158, 1524 cm-1) levels were significantly lower. The peak heights of these identified Raman marker bands were input into an LDA model, achieving a cross-validated diagnostic sensitivity and specificity of 71.33% and 90.00% in distinguishing the CCA from healthy specimens. The PCA-LDA technique provided a higher cross-validated sensitivity and specificity of 86.67% and 96.67%. To conclude, this work demonstrated the feasibility of using Raman spectroscopy combined with PCA-LDA as a helpful tool for cholangiocarcinoma serum-based screening.
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13
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Bratchenko LA, Al-Sammarraie SZ, Tupikova EN, Konovalova DY, Lebedev PA, Zakharov VP, Bratchenko IA. Analyzing the serum of hemodialysis patients with end-stage chronic kidney disease by means of the combination of SERS and machine learning. BIOMEDICAL OPTICS EXPRESS 2022; 13:4926-4938. [PMID: 36187246 PMCID: PMC9484439 DOI: 10.1364/boe.455549] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 03/11/2022] [Accepted: 03/18/2022] [Indexed: 05/29/2023]
Abstract
The aim of this paper is a multivariate analysis of SERS characteristics of serum in hemodialysis patients, which includes constructing classification models (PLS-DA, CNN) by the presence/absence of end-stage chronic kidney disease (CKD) with dialysis and determining the most informative spectral bands for identifying dialysis patients by variable importance distribution. We found the spectral bands that are informative for detecting the hemodialysis patients: the 641 cm-1, 724 cm-1, 1094 cm-1 and 1393 cm-1 bands are associated with the degree of kidney function inhibition; and the 1001 cm-1 band is able to demonstrate the distinctive features of hemodialysis patients with end-stage CKD.
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Affiliation(s)
- Lyudmila A Bratchenko
- Department of Laser and Biotechnical Systems, Samara University, 34 Moskovskoe Shosse, Samara, 443086, Russia
| | - Sahar Z Al-Sammarraie
- Department of Laser and Biotechnical Systems, Samara University, 34 Moskovskoe Shosse, Samara, 443086, Russia
| | - Elena N Tupikova
- Department of Chemistry, Samara University, 34 Moskovskoe Shosse, Samara, 443086, Russia
| | - Daria Y Konovalova
- Department of Internal Medicine, Samara State Medical University, 159 Tashkentskaya Street, Samara, 443095, Russia
| | - Peter A Lebedev
- Department of Internal Medicine, Samara State Medical University, 159 Tashkentskaya Street, Samara, 443095, Russia
| | - Valery P Zakharov
- Department of Laser and Biotechnical Systems, Samara University, 34 Moskovskoe Shosse, Samara, 443086, Russia
| | - Ivan A Bratchenko
- Department of Laser and Biotechnical Systems, Samara University, 34 Moskovskoe Shosse, Samara, 443086, Russia
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Marzi J, Fuhrmann E, Brauchle E, Singer V, Pfannstiel J, Schmidt I, Hartmann H. Non-Invasive Three-Dimensional Cell Analysis in Bioinks by Raman Imaging. ACS APPLIED MATERIALS & INTERFACES 2022; 14:30455-30465. [PMID: 35777738 PMCID: PMC9284518 DOI: 10.1021/acsami.1c24463] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
3D bioprinting is an emerging biofabrication strategy using bioinks, comprising cells and biocompatible materials, to produce functional tissue models. Despite progress in building increasingly complex objects, biological analyses in printed constructs remain challenging. Especially, methods that allow non-invasive and non-destructive evaluation of embedded cells are largely missing. Here, we implemented Raman imaging for molecular-sensitive investigations on bioprinted objects. Different aspects such as culture formats (2D, 3D-cast, and 3D-printed), cell types (endothelial cells and fibroblasts), and the selection of the biopolymer (alginate, alginate/nanofibrillated cellulose, alginate/gelatin) were considered and evaluated. Raman imaging allowed for marker-independent identification and localization of subcellular components against the surrounding biomaterial background. Furthermore, single-cell analysis of spectral signatures, performed by multivariate analysis, demonstrated discrimination between endothelial cells and fibroblasts and identified cellular features influenced by the bioprinting process. In summary, Raman imaging was successfully established to analyze cells in 3D culture in situ and evaluate them with regard to the localization of different cell types and their molecular phenotype as a valuable tool for quality control of bioprinted objects.
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Affiliation(s)
- Julia Marzi
- NMI
Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen 72770, Germany
- Institute
of Biomedical Engineering, Department for Medical Technologies &
Regenerative Medicine, Eberhard Karls University, Tübingen 72074, Germany
- Cluster
of Excellence iFIT (EXC 2180) Image-Guided and Functionally Instructed
Tumor Therapies, University of Tübingen, Tübingen 72074, Germany
| | - Ellena Fuhrmann
- NMI
Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen 72770, Germany
| | - Eva Brauchle
- NMI
Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen 72770, Germany
- Institute
of Biomedical Engineering, Department for Medical Technologies &
Regenerative Medicine, Eberhard Karls University, Tübingen 72074, Germany
- Cluster
of Excellence iFIT (EXC 2180) Image-Guided and Functionally Instructed
Tumor Therapies, University of Tübingen, Tübingen 72074, Germany
| | - Verena Singer
- NMI
Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen 72770, Germany
| | - Jessica Pfannstiel
- NMI
Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen 72770, Germany
| | - Isabelle Schmidt
- NMI
Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen 72770, Germany
| | - Hanna Hartmann
- NMI
Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen 72770, Germany
- . Phone: +49712151530872
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15
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Application of Surface-Enhanced Raman Spectroscopy in the Screening of Pulmonary Adenocarcinoma Nodules. BIOMED RESEARCH INTERNATIONAL 2022; 2022:4368928. [PMID: 35782079 PMCID: PMC9246604 DOI: 10.1155/2022/4368928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/03/2022] [Accepted: 06/09/2022] [Indexed: 11/24/2022]
Abstract
This study is aimed at evaluating the feasibility of a screening method for the pulmonary adenocarcinoma nodules through surface-enhanced Raman spectroscopy (SERS). Objective. Using SERS to measure serum from pulmonary nodules and healthy subjects, intraoperative biopsy pathological diagnosis was regarded as the gold standard for labeling serum samples. To explore the application value of SERS in the differential diagnosis of pulmonary adenocarcinoma nodules, benign nodules, and healthy, we build a machine learning model. Method. We collected 116 serum samples from patients. Radiographically confirmed nodules less than 3 cm in maximum diameter in all patients, including 58 cancer (pathologic diagnosis: adenocarcinoma nodules, labeled as cancer) patients, 58 pathologic diagnoses as benign nodule (labeled as benign) patients, and 63 healthy (labeled as normal) people from the clinical laboratory of Sichuan Cancer Hospital. Gold nanorods were employed as SERS substrates. Support vector machine (SVM) was used to classify the normal, benign, and cancer sample groups, and SVM model evaluated using cross-validation. Results. The average SERS spectra of serum were significantly different between the normal group and the cancer/benign group. While the average SERS spectra of the cancer group and the benign group differed slightly, for the cancer, benign, and normal groups, SVM models can predict with 93.33% accuracy. Conclusion. This exploratory study demonstrates that the SERS technique based on nanoparticles in conjunction with SVM has great potential as a clinical auxiliary diagnosis and screening for pulmonary adenocarcinoma nodules.
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16
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Barik AK, M SP, N M, Pai MV, Upadhya R, Pai AK, Lukose J, Chidangil S. A micro-Raman spectroscopy study of inflammatory condition of human cervix: Probing of Tissues and blood plasma samples. Photodiagnosis Photodyn Ther 2022; 39:102948. [PMID: 35661825 DOI: 10.1016/j.pdpdt.2022.102948] [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: 03/08/2022] [Revised: 05/20/2022] [Accepted: 06/01/2022] [Indexed: 10/18/2022]
Abstract
The present study explores the application of the micro-Raman spectroscopy technique to discriminate normal and cervicitis condition from cervical malignancy by analyzing the Raman signatures of tissues and plasma samples of the same subjects. The Raman peaks from tissue samples at 1026 cm-1,1298 cm-1 and 1243 cm-1 are attributed to glycogen, fatty acids and collagen and are found to be reliable signatures capable of identifying cervicitis and normal condition from cervical cancer. The Raman signatures from plasma samples belonging to carbohydrates (578 cm-1), lipids (1059 cm-1) and nucleic acids (1077 cm-1,1341 cm-1 and 1357 cm-1) are quite useful to classify various stages of cervix at par with tissue based diagnosis. The PCA-SVM based classification of the spectral data indicates the potential of Raman spectroscopy based liquid biopsy to rule out false diagnosis of cervicitis as cervical malignancy.
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Affiliation(s)
- Ajaya Kumar Barik
- Centre of Excellence for Biophotonics, Department of Atomic and Molecular Physics, Manipal Academy of Higher Education, Manipal, India
| | - Sanoop Pavithran M
- Centre of Excellence for Biophotonics, Department of Atomic and Molecular Physics, Manipal Academy of Higher Education, Manipal, India
| | - Mithun N
- Centre of Excellence for Biophotonics, Department of Atomic and Molecular Physics, Manipal Academy of Higher Education, Manipal, India
| | - Muralidhar V Pai
- Department of Obstetrics and Gynecology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Rekha Upadhya
- Department of Obstetrics and Gynecology, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Abhilash K Pai
- Department of Data Science & Computer Applications, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India
| | - Jijo Lukose
- Centre of Excellence for Biophotonics, Department of Atomic and Molecular Physics, Manipal Academy of Higher Education, Manipal, India
| | - Santhosh Chidangil
- Centre of Excellence for Biophotonics, Department of Atomic and Molecular Physics, Manipal Academy of Higher Education, Manipal, India.
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17
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Raman spectroscopy: current applications in breast cancer diagnosis, challenges and future prospects. Br J Cancer 2022; 126:1125-1139. [PMID: 34893761 PMCID: PMC8661339 DOI: 10.1038/s41416-021-01659-5] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 11/11/2021] [Accepted: 11/25/2021] [Indexed: 12/26/2022] Open
Abstract
Despite significant improvements in the way breast cancer is managed and treated, it continues to persist as a leading cause of death worldwide. If detected and diagnosed early, when tumours are small and localised, there is a considerably higher chance of survival. However, current methods for detection and diagnosis lack the required sensitivity and specificity for identifying breast cancer at the asymptomatic or very early stages. Thus, there is a need to develop more rapid and reliable methods, capable of detecting disease earlier, for improved disease management and patient outcome. Raman spectroscopy is a non-destructive analytical technique that can rapidly provide highly specific information on the biochemical composition and molecular structure of samples. In cancer, it has the capacity to probe very early biochemical changes that accompany malignant transformation, even prior to the onset of morphological changes, to produce a fingerprint of disease. This review explores the application of Raman spectroscopy in breast cancer, including discussion on its capabilities in analysing both ex-vivo tissue and liquid biopsy samples, and its potential in vivo applications. The review also addresses current challenges and potential future uses of this technology in cancer research and translational clinical application.
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18
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Haldavnekar R, Venkatakrishnan A, Kiani A. Tracking the Evolution of Metastasis with Self-Functionalized 3D Nanoprobes. ACS APPLIED BIO MATERIALS 2022; 5:1633-1647. [PMID: 35316034 DOI: 10.1021/acsabm.2c00043] [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: 11/30/2022]
Abstract
Despite recent advances in cancer treatment, metastasis is the cause of mortality in 90% of cancer cases. It has now been well-established that dissemination of cancer cells to distant sites occurs very early during tumorigenesis, resulting in the minimal effect of surgical or chemotherapeutic treatments after the detection of metastasis. The underlying reason for this challenge is mostly due to the limited understanding of molecular mechanisms of the metastasis cascade, particularly related to metastatic traits. Therefore, there is an urgent need to investigate this currently invisible evolution of metastasis. The tracking of metastasis evolution has not been addressed yet. Here, we introduce, for the first time, a synchronous approach to unveil the molecular mechanisms of the metastasis cascade. As cancer stem cells (CSCs) demonstrate cancer initiation, drug resistance, metastasis, and tumor relapse and can exist in a quasi-intermediate epithelial-mesenchymal transition state, the tumor-initiating events during a CSCs metamorphosis were monitored with single-cell sensitivity. Because of the invasive and resistive properties of the metastable intermediate CSCs, investigation of the molecular profiles of the quasi-intermediate CSCs was necessary for the detection of metastasis dissemination. For this purpose, the ultrasensitive technique of surface-enhanced Raman scattering (SERS) was adopted. Titanium-based, biocompatible three-dimensional (3D) nanoprobes that were synthesized for multiphoton ionization achieved a substantial SERS enhancement of ∼80-fold due to the oxygen vacancy-enriched composition of the nanoprobes. The 3D interconnected complex nanoarchitecture of the nanoprobes enabled us to entrap the nonadherent CSCs of three metastatic cancer cell lines (triple negative breast adenocarcinoma (MDAMB231), human Caucasian colon adenocarcinoma (COLO 205), and cervical adenocarcinoma (HeLa)─all very aggressive forms of cancer). The nanoprobes not only promoted the CSC proliferation to successfully attain the quasi-intermediate states but also monitored its reprogramming into a cancer cell state. The nanoprobes substantially amplified weak intracellular Raman signals to capture the molecular events during a CSC transformation. The detection of cancer was achieved with 100% accuracy. We experimentally demonstrated that the molecular signatures of CSC reprogramming are cancer-type specific. This observation enabled us to identify the origin of metastasis with 100% accuracy, providing more clarity on the relatively unknown quasi-intermediate states. This first demonstration of CSC-based tracking of metastasis evolution has the potential to provide an insightful perspective of tumorigenesis that could be useful in cancer diagnosis and prognosis as well as in the monitoring of therapeutic interventions.
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Affiliation(s)
- Rupa Haldavnekar
- Institute for Biomedical Engineering, Science and Technology, 209 Victoria Street, Toronto, Ontario M5B 1T8, Canada.,Ultrashort Laser Nanomanufacturing research facility, Department of Mechanical and Industrial Engineering, Ryerson University, 350 Victoria Street, Toronto, Ontario M5B2K3, Canada.,BioNanoInterface Facility, Department of Mechanical and Industrial Engineering, Ryerson University, 350 Victoria Street, Toronto, Ontario M5B2K3, Canada.,Nanocharacterization Laboratory, Department of Aerospace Engineering, Ryerson University, 350 Victoria Street, Toronto, Ontario M5B2K3, Canada.,Department of Biomedical Engineering, Ryerson University, 350 Victoria Street, Toronto, Ontario M5B2K3, Canada
| | - Akshay Venkatakrishnan
- Department of Basic Medical Sciences, The University of Western Ontario, 1151 Richmond Street, London, Ontario N6A3K7, Canada
| | - Amirkianoosh Kiani
- Silicon Hall: Micro/Nano Manufacturing Facility, Faculty of Engineering and Applied Science, Ontario Tech University, 2000 Simcoe Street N, Oshawa, Ontario L1G0C5, Canada.,Department of Mechanical and Manufacturing Engineering, Ontario Tech University, 2000 Simcoe Street N, Oshawa, Ontario L1G0C5, Canada
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19
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Wiemann J, Briggs DEG. Raman spectroscopy is a powerful tool in molecular paleobiology: An analytical response to Alleon et al. (https://doi.org/10.1002/bies.202000295). Bioessays 2022; 44:e2100070. [PMID: 34993976 DOI: 10.1002/bies.202100070] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 12/03/2021] [Accepted: 12/07/2021] [Indexed: 01/08/2023]
Abstract
A recent article argued that signals from conventional Raman spectroscopy of organic materials are overwhelmed by edge filter and fluorescence artefacts. The article targeted a subset of Raman spectroscopic investigations of fossil and modern organisms and has implications for the utility of conventional Raman spectroscopy in comparative tissue analytics. The inferences were based on circular reasoning centered around the unconventional analysis of spectra from just two samples, one modern, and one fossil. We validated the disputed signals with in situ Fourier-Transform Infrared (FT-IR) Spectroscopy and through replication with different lasers, filters, and operators in independent laboratories. Our Raman system employs a holographic notch filter which is not affected by edge filter or other artefacts. Multiple lines of evidence confirm that conventional Raman spectra of fossils contain biologically and geologically meaningful information. Statistical analyses of large Raman and FT-IR spectral data sets reveal patterns in fossil composition and yield valuable insights into the history of life.
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Affiliation(s)
- Jasmina Wiemann
- Department of Earth and Planetary Sciences, Yale University, New Haven, Connecticut, USA.,Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA.,Dinosaur Institute, Natural History Museum of LA County, Los Angeles, California, USA
| | - Derek E G Briggs
- Department of Earth and Planetary Sciences, Yale University, New Haven, Connecticut, USA.,Yale Peabody Museum of Natural History, New Haven, Connecticut, USA
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20
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Akbar S, Majeed MI, Nawaz H, Rashid N, Tariq A, Hameed W, Shakeel S, Dastgir G, Bari RZA, Iqbal M, Nawaz A, Akram M. Surface-Enhanced Raman Spectroscopic (SERS) Characterization of Low Molecular Weight Fraction of the Serum of Breast Cancer Patients with Principal Component Analysis (PCA) and Partial Least Square-Discriminant Analysis (PLS-DA). ANAL LETT 2021. [DOI: 10.1080/00032719.2021.2017948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Saba Akbar
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | | | - Haq Nawaz
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Nosheen Rashid
- Department of Chemistry, University of Education, Faisalabad, Pakistan
| | - Ayesha Tariq
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Wajeeha Hameed
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Samra Shakeel
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Ghulam Dastgir
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Rana Zaki Abdul Bari
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Maham Iqbal
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Amna Nawaz
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Maria Akram
- Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, Pakistan
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21
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Das D, Bhattacharjee K, Barman MJ, Bhattacharjee H, Maity S, Bandyopadhyay D, Thakur S, Deshmukh S, Garg M, Deka A. Pathologic evidence of retinoblastoma seeds supported by field emission scanning electron microscopy and Raman spectroscopy. Indian J Ophthalmol 2021; 69:3612-3617. [PMID: 34827005 PMCID: PMC8837303 DOI: 10.4103/ijo.ijo_436_21] [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] [Indexed: 11/13/2022] Open
Abstract
Purpose: The aim of this study was to examine the pathology of retinoblastoma (RB) seeds with supportive evidence by field emission scanning electron microscopy and Raman spectroscopy. Methods: This study was a laboratory-based observational study. Enucleated eyeballs received in the ocular pathology department of a tertiary eye care center in northeast India were included in the cohort after obtaining written informed consent during the surgery. The study was carried out for 6 years (2015–2020). Most of the eyeballs were Group-E RBs. Standard eyeballs sectioning were done by bread loaf techniques. Gross documentations included RB seeds seen in the smallest calotte done with utmost care. Seeds were documented also in permanent sections. Scanning electron microscopy and Raman spectroscopy were carried out in an index case. Results: Out of the total 59 cases, 35 RB cases had different seedings. The mean age at enucleation was 2.9 years. RB seeds were seen in vitreous (n = 19), subretinal plus vitreous (n = 7), anterior chamber (n = 1), over crystalline lens (n = 3), retinal surface (n = 1), retinal pigment epithelium (RPE; n = 2), subretinal (n = 1), calcified seeds (n = 2). Other characteristics were dusts (n = 7), clouds (n = 11), spheres (n = 4), and unspecified type (n = 13). Histopathological high-risk factors showed significant choroidal (n = 22) and optic nerve (n = 15) involvement. Few cases had extraocular spread. Undifferentiated tumor (n = 24) was seen with higher evidence of necrosis (n = 23). Raman spectra differentiated the seeds from the normal tissue on the basis of lipid and protein content. Conclusion: This study highlights the different types of RB seeds with high-risk factors. The morphology of those seeds showed the difference between vitreous and subretinal seeds under advanced microscopic observations.
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Affiliation(s)
- Dipankar Das
- Departments of Ocular Pathology, Uveitis and Neuro-Ophthalmology, Sri Sankaradeva Nethralaya, Guwahati, Assam, India
| | - Kasturi Bhattacharjee
- Department of Oculoplasty, Cataract and Refractive Surgery, Sri Sankaradeva Nethralaya, Guwahati, Assam, India
| | - Manab J Barman
- Department of Vitreo-Retina, Sri Sankaradeva Nethralaya, Guwahati, Assam, India
| | | | - Surjendu Maity
- Centre for Nanotechnology and Department of Chemical Engineering, Indian Institute of Technology, Guwahati, Assam, India
| | - Dipankar Bandyopadhyay
- Centre for Nanotechnology and Department of Chemical Engineering, Indian Institute of Technology, Guwahati, Assam, India
| | - Siddharth Thakur
- Centre for Nanotechnology and Department of Chemical Engineering, Indian Institute of Technology, Guwahati, Assam, India
| | - Saurabh Deshmukh
- Department of Vitreo-Retina, Sri Sankaradeva Nethralaya, Guwahati, Assam, India
| | - Mohit Garg
- Department of Ophthalmology, Sri Sankaradeva Nethralaya, Guwahati, Assam, India
| | - Apurba Deka
- Department of Ocular Pathology, Sri Sankaradeva Nethralaya, Guwahati, Assam, India
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22
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Lei J, Yang D, Li R, Dai Z, Zhang C, Yu Z, Wu S, Pang L, Liang S, Zhang Y. Label-free surface-enhanced Raman spectroscopy for diagnosis and analysis of serum samples with different types lung cancer. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 261:120021. [PMID: 34116414 DOI: 10.1016/j.saa.2021.120021] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 05/07/2021] [Accepted: 05/23/2021] [Indexed: 05/20/2023]
Abstract
Screening and detection of early lung cancer is important for diagnosis and prognosis. Intervention in early stage of lung cancer can significantly improve the cure and survival of patients. Surface-enhanced Raman spectroscopy (SERS) is an increasingly popular method of diagnosing cancer. We used silver nanoparticles (AgNPs) as the Raman-enhanced substrate to increase Raman signals, which contributes to the subsequent classification of lung cancer and normal serum. SERS acquired from the serum indicated the difference in biochemical components between cancerous (n = 51) lung serum and normal (n = 18) serum. Principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) were utilized to establish the identification model, and the various indicators of PLS-DA were all superior to those of the PLS model. Our study offers a new proposal for the universal applicability of analysis and identification with SERS of serum samples in clinical diagnosis.
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Affiliation(s)
- Jia Lei
- School of Physics, Dalian University of Technology, Dalian, 116023, People's Republic of China
| | - Dafu Yang
- The Second Department of Thoracic Medical Oncology, The Second Hospital of Dalian Medical University, Dalian, People's Republic of China
| | - Rui Li
- School of Physics, Dalian University of Technology, Dalian, 116023, People's Republic of China.
| | - ZhaoXia Dai
- The Second Department of Thoracic Medical Oncology, The Second Hospital of Dalian Medical University, Dalian, People's Republic of China.
| | - Chenlei Zhang
- Department of Thoracic Surgery, Liaoning Cancer Hospital & Institute, Cancer Hospital of Dalian University of Technology, Shenyang 110042, People's Republic of China
| | - Zhanwu Yu
- Department of Thoracic Surgery, Liaoning Cancer Hospital & Institute, Cancer Hospital of Dalian University of Technology, Shenyang 110042, People's Republic of China
| | - Shifa Wu
- School of Physics, Dalian University of Technology, Dalian, 116023, People's Republic of China
| | - Lu Pang
- School of Materials Science and Engineering, Dalian University of Technology, Dalian 116024, People's Republic of China
| | - Shanshan Liang
- The Key Laboratory of Biomarker High Throughput Screening and Target Translation of Breast and Gastrointestinal Tumor, Oncology Department, Affiliated Zhongshan Hospital of Dalian University, Dalian 116023, People's Republic of China
| | - Yi Zhang
- School of Physics, Dalian University of Technology, Dalian, 116023, People's Republic of China
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23
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Giamougiannis P, Silva RVO, Freitas DLD, Lima KMG, Anagnostopoulos A, Angelopoulos G, Naik R, Wood NJ, Martin-Hirsch PL, Martin FL. Raman spectroscopy of blood and urine liquid biopsies for ovarian cancer diagnosis: identification of chemotherapy effects. JOURNAL OF BIOPHOTONICS 2021; 14:e202100195. [PMID: 34296515 DOI: 10.1002/jbio.202100195] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2021] [Revised: 07/19/2021] [Accepted: 07/20/2021] [Indexed: 06/13/2023]
Abstract
Blood plasma and serum Raman spectroscopy for ovarian cancer diagnosis has been applied in pilot studies, with promising results. Herein, a comparative analysis of these biofluids, with a novel assessment of urine, was conducted by Raman spectroscopy application in a large patient cohort. Spectra were obtained through samples measurements from 116 ovarian cancer patients and 307 controls. Principal component analysis identified significant spectral differences between cancers without previous treatment (n = 71) and following neo-adjuvant chemotherapy (NACT), (n = 45). Application of five classification algorithms achieved up to 73% sensitivity for plasma, high specificities and accuracies for both blood biofluids, and lower performance for urine. A drop in sensitivities for the NACT group in plasma and serum, with an opposite trend in urine, suggest that Raman spectroscopy could identify chemotherapy-related changes. This study confirms that biofluids' Raman spectroscopy can contribute in ovarian cancer's diagnostic work-up and demonstrates its potential in monitoring treatment response.
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Affiliation(s)
- Panagiotis Giamougiannis
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Raissa V O Silva
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Daniel L D Freitas
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Kássio M G Lima
- Institute of Chemistry, Biological Chemistry and Chemometrics, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Antonios Anagnostopoulos
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK
| | - Georgios Angelopoulos
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK
| | - Raj Naik
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK
| | - Nicholas J Wood
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK
| | - Pierre L Martin-Hirsch
- Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK
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24
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Githaiga JI, Angeyo HK, Kaduki KA, Bulimo WD, Ojuka DK. Quantitative Raman spectroscopy of breast cancer malignancy utilizing higher-order principal components: A preliminary study. SCIENTIFIC AFRICAN 2021. [DOI: 10.1016/j.sciaf.2021.e01035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
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25
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Detection of inaccessible head and neck lesions using human saliva and fluorescence spectroscopy. Lasers Med Sci 2021; 37:1821-1827. [PMID: 34637056 PMCID: PMC8506087 DOI: 10.1007/s10103-021-03437-4] [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: 05/14/2021] [Accepted: 10/01/2021] [Indexed: 12/04/2022]
Abstract
Head and neck cancer detection using fluorescence spectroscopy from human saliva is reported here. This study has been conducted on squamous cell carcinoma (SCC), and dysplastic (precancer) and control (normal) groups using an in-house developed compact set-up. Fluorescence set-up consists of a 375-nm laser diode and optical components. Spectral bands of flavin adenine dinucleotide (FAD), porphyrins, and Raman are observed in the spectral range of 400 to 800 nm. Presence of FAD and porphyrin bands in human saliva is confirmed by the liquid phantoms of FAD and porphyrin. Significant differences in fluorescence intensities among all the three groups are observed. Three spectral ranges from 455 to 600, 605 to 770, and 400 to 800 nm are selected for each group and area values under each spectral range are computed. To differentiate among the groups, receiver operating characteristic (ROC) analysis is employed on the area values. ROC differentiates among the groups with accuracies of 98%, 92.85%, and 81.13% respectively in the spectral ranges of 400 to 800 nm. However, in other two spectral ranges (455 to 600 and 605 to 770 nm), low accuracy values are found. Obtained accuracy values indicate that selection of human saliva for head and neck cancer detection may be a good alternative.
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26
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Grieve S, Puvvada N, Phinyomark A, Russell K, Murugesan A, Zed E, Hassan A, Legare JF, Kienesberger PC, Pulinilkunnil T, Reiman T, Scheme E, Brunt KR. Nanoparticle surface-enhanced Raman spectroscopy as a noninvasive, label-free tool to monitor hematological malignancy. Nanomedicine (Lond) 2021; 16:2175-2188. [PMID: 34547916 DOI: 10.2217/nnm-2021-0076] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Aim: Monitoring minimal residual disease remains a challenge to the effective medical management of hematological malignancies; yet surface-enhanced Raman spectroscopy (SERS) has emerged as a potential clinical tool to do so. Materials & methods: We developed a cell-free, label-free SERS approach using gold nanoparticles (nanoSERS) to classify hematological malignancies referenced against two control cohorts: healthy and noncancer cardiovascular disease. A predictive model was built using machine-learning algorithms to incorporate disease burden scores for patients under standard treatment upon. Results: Linear- and quadratic-discriminant analysis distinguished three cohorts with 69.8 and 71.4% accuracies, respectively. A predictive nanoSERS model correlated (MSE = 1.6) with established clinical parameters. Conclusion: This study offers a proof-of-concept for the noninvasive monitoring of disease progression, highlighting the potential to incorporate nanoSERS into translational medicine.
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Affiliation(s)
- Stacy Grieve
- Department of Biology, University of New Brunswick, Saint John, New Brunswick, Canada.,IMPART investigator team, Canada
| | - Nagaprasad Puvvada
- Department of Pharmacology, Dalhousie University, Saint John, New Brunswick, Canada.,Department of Chemistry, Indrashil University, Gujarat, India
| | - Angkoon Phinyomark
- IMPART investigator team, Canada.,Institute of Biomedical Engineering, University of New Brunswick, Fredericton, New Brunswick, Canada
| | - Kevin Russell
- Faculty of Medicine, Dalhousie University, Saint John, New Brunswick, Canada
| | - Alli Murugesan
- Department of Biology, University of New Brunswick, Saint John, New Brunswick, Canada.,Faculty of Medicine, Dalhousie University, Saint John, New Brunswick, Canada
| | - Elizabeth Zed
- Department of Oncology, Saint John Regional Hospital, Saint John, New Brunswick, Canada
| | - Ansar Hassan
- IMPART investigator team, Canada.,Department of Cardiac Surgery, Saint John Regional Hospital, Saint John, New Brunswick, Canada
| | - Jean-Francois Legare
- IMPART investigator team, Canada.,Department of Cardiac Surgery, Saint John Regional Hospital, Saint John, New Brunswick, Canada
| | - Petra C Kienesberger
- IMPART investigator team, Canada.,Faculty of Medicine, Dalhousie University, Saint John, New Brunswick, Canada.,Department of Biochemistry & Molecular Biology, Dalhousie University, Saint John, New Brunswick, Canada
| | - Thomas Pulinilkunnil
- IMPART investigator team, Canada.,Faculty of Medicine, Dalhousie University, Saint John, New Brunswick, Canada.,Department of Biochemistry & Molecular Biology, Dalhousie University, Saint John, New Brunswick, Canada
| | - Tony Reiman
- Department of Biology, University of New Brunswick, Saint John, New Brunswick, Canada.,IMPART investigator team, Canada.,Faculty of Medicine, Dalhousie University, Saint John, New Brunswick, Canada.,Department of Oncology, Saint John Regional Hospital, Saint John, New Brunswick, Canada
| | - Erik Scheme
- IMPART investigator team, Canada.,Institute of Biomedical Engineering, University of New Brunswick, Fredericton, New Brunswick, Canada.,Faculty of Medicine, Dalhousie University, Saint John, New Brunswick, Canada
| | - Keith R Brunt
- IMPART investigator team, Canada.,Department of Pharmacology, Dalhousie University, Saint John, New Brunswick, Canada.,Faculty of Medicine, Dalhousie University, Saint John, New Brunswick, Canada
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27
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Li X, Chen H, Zhang S, Yang H, Gao S, Xu H, Wang L, Xu R, Zhou F, Hu J, Zhao J, Zeng H. Blood plasma resonance Raman spectroscopy combined with multivariate analysis for esophageal cancer detection. JOURNAL OF BIOPHOTONICS 2021; 14:e202100010. [PMID: 34092038 DOI: 10.1002/jbio.202100010] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 04/28/2021] [Accepted: 06/02/2021] [Indexed: 06/12/2023]
Abstract
We herein report a novel, reliable and inexpensive method for detecting esophageal cancer using blood plasma resonance Raman spectroscopy combined with multivariate analysis methods. The blood plasma samples were divided into late stage cancer group (n = 164), early stage cancer group (n = 35) and normal group (n = 135) based on clinical pathological diagnosis. Using a specially designed quartz capillary tube as sample holder, we obtained higher quality resonance Raman spectra of blood plasma than existing method. The study demonstrated that the carotenoids levels in blood plasma were reduced in esophageal cancer patients. The area under the receiver operating characteristic curve (and 95% confidence interval) calculated by wavenumber selection and principal component analysis combined with linear discriminant analysis (PC-LDA) algorithm were 0.894 (0.858-0.929), 0.901 (0.841-0.960) and 0.871 (0.799-0.942) for differentiating late cancer from normal, late cancer from early cancer, and early cancer from normal respectively. The contribution from the two carotenoids wavenumber regions of 1155 and 1515 cm-1 were more than 84.2%. The results show that the plasma carotenoids could be a potential biomarker for screening esophageal cancer using resonance Raman spectroscopy combined with wavenumber selection and PC-LDA algorithms.
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Affiliation(s)
- Xianchang Li
- Anyang Tumor Hospital, The 4th Affiliated Hospital of Henan University of Science and Technology, Anyang, China
- State Key Laboratory of Esophageal Cancer Prevention and Treatment and Henan Key Laboratory for Esophageal Cancer Research of The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Henan Joint International Research Laboratory of Nanocomposite Sensing Materials, School of Chemical and Environmental Engineering, Anyang Institute of Technology, Anyang, China
| | - Hongjun Chen
- Anyang Tumor Hospital, The 4th Affiliated Hospital of Henan University of Science and Technology, Anyang, China
| | - Shiding Zhang
- Henan Joint International Research Laboratory of Nanocomposite Sensing Materials, School of Chemical and Environmental Engineering, Anyang Institute of Technology, Anyang, China
| | - Haijun Yang
- Anyang Tumor Hospital, The 4th Affiliated Hospital of Henan University of Science and Technology, Anyang, China
| | - Shanshan Gao
- Henan Joint International Research Laboratory of Nanocomposite Sensing Materials, School of Chemical and Environmental Engineering, Anyang Institute of Technology, Anyang, China
| | - Haisheng Xu
- Anyang Tumor Hospital, The 4th Affiliated Hospital of Henan University of Science and Technology, Anyang, China
| | - Lidong Wang
- State Key Laboratory of Esophageal Cancer Prevention and Treatment and Henan Key Laboratory for Esophageal Cancer Research of The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ruiping Xu
- Anyang Tumor Hospital, The 4th Affiliated Hospital of Henan University of Science and Technology, Anyang, China
| | - Fuyou Zhou
- Anyang Tumor Hospital, The 4th Affiliated Hospital of Henan University of Science and Technology, Anyang, China
| | - Jiming Hu
- Key Laboratory of Analytical Chemistry for Biology and Medicine (Ministry of Education), College of Chemistry and Molecular Sciences, Wuhan University, Wuhan, China
| | - Jianhua Zhao
- Department of Dermatology and Skin Science, University of British Columbia, Vancouver, British Columbia, Canada
- Imaging Unit - Department of Integrative Oncology, BC Cancer Research Centre, Vancouver, British Columbia, Canada
| | - Haishan Zeng
- Department of Dermatology and Skin Science, University of British Columbia, Vancouver, British Columbia, Canada
- Imaging Unit - Department of Integrative Oncology, BC Cancer Research Centre, Vancouver, British Columbia, Canada
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28
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Roadmap on Universal Photonic Biosensors for Real-Time Detection of Emerging Pathogens. PHOTONICS 2021. [DOI: 10.3390/photonics8080342] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The COVID-19 pandemic has made it abundantly clear that the state-of-the-art biosensors may not be adequate for providing a tool for rapid mass testing and population screening in response to newly emerging pathogens. The main limitations of the conventional techniques are their dependency on virus-specific receptors and reagents that need to be custom-developed for each recently-emerged pathogen, the time required for this development as well as for sample preparation and detection, the need for biological amplification, which can increase false positive outcomes, and the cost and size of the necessary equipment. Thus, new platform technologies that can be readily modified as soon as new pathogens are detected, sequenced, and characterized are needed to enable rapid deployment and mass distribution of biosensors. This need can be addressed by the development of adaptive, multiplexed, and affordable sensing technologies that can avoid the conventional biological amplification step, make use of the optical and/or electrical signal amplification, and shorten both the preliminary development and the point-of-care testing time frames. We provide a comparative review of the existing and emergent photonic biosensing techniques by matching them to the above criteria and capabilities of preventing the spread of the next global pandemic.
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29
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Giardina G, Micko A, Bovenkamp D, Krause A, Placzek F, Papp L, Krajnc D, Spielvogel CP, Winklehner M, Höftberger R, Vila G, Andreana M, Leitgeb R, Drexler W, Wolfsberger S, Unterhuber A. Morpho-Molecular Metabolic Analysis and Classification of Human Pituitary Gland and Adenoma Biopsies Based on Multimodal Optical Imaging. Cancers (Basel) 2021; 13:3234. [PMID: 34209497 PMCID: PMC8267638 DOI: 10.3390/cancers13133234] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 06/23/2021] [Accepted: 06/24/2021] [Indexed: 12/12/2022] Open
Abstract
Pituitary adenomas count among the most common intracranial tumors. During pituitary oncogenesis structural, textural, metabolic and molecular changes occur which can be revealed with our integrated ultrahigh-resolution multimodal imaging approach including optical coherence tomography (OCT), multiphoton microscopy (MPM) and line scan Raman microspectroscopy (LSRM) on an unprecedented cellular level in a label-free manner. We investigated 5 pituitary gland and 25 adenoma biopsies, including lactotroph, null cell, gonadotroph, somatotroph and mammosomatotroph as well as corticotroph. First-level binary classification for discrimination of pituitary gland and adenomas was performed by feature extraction via radiomic analysis on OCT and MPM images and achieved an accuracy of 88%. Second-level multi-class classification was performed based on molecular analysis of the specimen via LSRM to discriminate pituitary adenomas subtypes with accuracies of up to 99%. Chemical compounds such as lipids, proteins, collagen, DNA and carotenoids and their relation could be identified as relevant biomarkers, and their spatial distribution visualized to provide deeper insight into the chemical properties of pituitary adenomas. Thereby, the aim of the current work was to assess a unique label-free and non-invasive multimodal optical imaging platform for pituitary tissue imaging and to perform a multiparametric morpho-molecular metabolic analysis and classification.
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Affiliation(s)
- Gabriel Giardina
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; (G.G.); (D.B.); (A.K.); (F.P.); (R.L.); (W.D.); (A.U.)
| | - Alexander Micko
- Department of Neurosurgery, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; (A.M.); (S.W.)
| | - Daniela Bovenkamp
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; (G.G.); (D.B.); (A.K.); (F.P.); (R.L.); (W.D.); (A.U.)
| | - Arno Krause
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; (G.G.); (D.B.); (A.K.); (F.P.); (R.L.); (W.D.); (A.U.)
| | - Fabian Placzek
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; (G.G.); (D.B.); (A.K.); (F.P.); (R.L.); (W.D.); (A.U.)
| | - Laszlo Papp
- QIMP Team, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; (L.P.); (D.K.)
| | - Denis Krajnc
- QIMP Team, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; (L.P.); (D.K.)
| | - Clemens P. Spielvogel
- Christian Doppler Laboratory for Applied Metabolomics, Division of Nuclear Medicine, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria;
| | - Michael Winklehner
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; (M.W.); (R.H.)
| | - Romana Höftberger
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; (M.W.); (R.H.)
| | - Greisa Vila
- Department of Internal Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria;
| | - Marco Andreana
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; (G.G.); (D.B.); (A.K.); (F.P.); (R.L.); (W.D.); (A.U.)
| | - Rainer Leitgeb
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; (G.G.); (D.B.); (A.K.); (F.P.); (R.L.); (W.D.); (A.U.)
| | - Wolfgang Drexler
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; (G.G.); (D.B.); (A.K.); (F.P.); (R.L.); (W.D.); (A.U.)
| | - Stefan Wolfsberger
- Department of Neurosurgery, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; (A.M.); (S.W.)
| | - Angelika Unterhuber
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria; (G.G.); (D.B.); (A.K.); (F.P.); (R.L.); (W.D.); (A.U.)
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30
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Farber C, Morey R, Krimmer M, Kurouski D, Rogovskyy AS. Exploring a possibility of using Raman spectroscopy for detection of Lyme disease. JOURNAL OF BIOPHOTONICS 2021; 14:e202000477. [PMID: 33486893 DOI: 10.1002/jbio.202000477] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 01/18/2021] [Accepted: 01/19/2021] [Indexed: 06/12/2023]
Abstract
Lyme disease (LD), one of the most prevalent tick-borne diseases in the United States (US), is caused by Borreliella burgdorferi sensu stricto (Bb). To date, in the US, LD diagnostics is primarily based on validated two-tiered serological testing, which overall exhibits low sensitivity among other drawbacks. In the present study, a potential of Raman spectroscopy (RS) to detect Bb infection in mice has been explored. For that, C3H mice were infected with wild-type Bb strains, 297, B31, or B31-derived mutant, ∆vlsE. Blood samples taken prior to and post Bb infection were subjected to RS. The data demonstrated that RS did not directly detect Bb spirochetes in blood, but rather sensed biochemical changes associated with Bb infection. Despite Bb infection-associated blood changes detectable by RS were very limited, the partial least square discriminant analysis showed that the average true positive rates were 86% for 297 and 89% for B31 and ∆vlsE.
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Affiliation(s)
- Charles Farber
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas, USA
| | - Rohini Morey
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas, USA
| | - Mark Krimmer
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas, USA
| | - Dmitry Kurouski
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas, USA
| | - Artem S Rogovskyy
- Department of Veterinary Pathobiology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, USA
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31
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Raman Spectral Signatures of Serum-Derived Extracellular Vesicle-Enriched Isolates May Support the Diagnosis of CNS Tumors. Cancers (Basel) 2021; 13:cancers13061407. [PMID: 33808766 PMCID: PMC8003579 DOI: 10.3390/cancers13061407] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 03/12/2021] [Accepted: 03/16/2021] [Indexed: 02/08/2023] Open
Abstract
Investigating the molecular composition of small extracellular vesicles (sEVs) for tumor diagnostic purposes is becoming increasingly popular, especially for diseases for which diagnosis is challenging, such as central nervous system (CNS) malignancies. Thorough examination of the molecular content of sEVs by Raman spectroscopy is a promising but hitherto barely explored approach for these tumor types. We attempt to reveal the potential role of serum-derived sEVs in diagnosing CNS tumors through Raman spectroscopic analyses using a relevant number of clinical samples. A total of 138 serum samples were obtained from four patient groups (glioblastoma multiforme, non-small-cell lung cancer brain metastasis, meningioma and lumbar disc herniation as control). After isolation, characterization and Raman spectroscopic assessment of sEVs, the Principal Component Analysis-Support Vector Machine (PCA-SVM) algorithm was performed on the Raman spectra for pairwise classifications. Classification accuracy (CA), sensitivity, specificity and the Area Under the Curve (AUC) value derived from Receiver Operating Characteristic (ROC) analyses were used to evaluate the performance of classification. The groups compared were distinguishable with 82.9-92.5% CA, 80-95% sensitivity and 80-90% specificity. AUC scores in the range of 0.82-0.9 suggest excellent and outstanding classification performance. Our results support that Raman spectroscopic analysis of sEV-enriched isolates from serum is a promising method that could be further developed in order to be applicable in the diagnosis of CNS tumors.
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32
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Zheng X, Wu G, Lv G, Yin L, Luo B, Lv X, Chen C. Combining derivative Raman with autofluorescence to improve the diagnosis performance of echinococcosis. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 247:119083. [PMID: 33137629 DOI: 10.1016/j.saa.2020.119083] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Revised: 09/25/2020] [Accepted: 10/12/2020] [Indexed: 05/22/2023]
Abstract
Echinococcosis is a zoonotic parasitic disease transmitted by animals and distributed all over the world. There is no standardized and widely accepted treatment method, and early and accurate diagnosis is crucial for the prevention and cure of echinococcosis. Here, we explored the feasibility of using derivative Raman in combination with autofluorescence (AF) to improve the diagnosis performance of echinococcosis. The spectra of serum samples from patients with echinococcosis, as well as healthy volunteers, were recorded at 633 nm excitation. The normalized mean Raman spectra showed that there is a decrease in the relative amounts of β carotene and phenylalanine and an increase in the percentage of tryptophan, tyrosine, and glutamic acid contents in the serum of echinococcosis patients as compared to that of healthy subjects. Then, principal components analysis (PCA), combined with linear discriminant analysis (LDA), were adopted to distinguish echinococcosis patients from healthy volunteers. Based on the area under the ROC curve (AUC) value, the derivative Raman + AF spectral data set achieved the optimal results. The AUC value was improved by 0.08 for derivative Raman + AF (AUC = 0.98), compared to Raman alone. The results demonstrated that the fusion of derivative Raman and AF could effectively improve the performance of the diagnostic model, and this technique has great application potential in the clinical screening of echinococcosis.
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Affiliation(s)
- Xiangxiang Zheng
- School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Guohua Wu
- School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.
| | - Guodong Lv
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830000, China
| | - Longfei Yin
- School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Bin Luo
- State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Xiaoyi Lv
- School of Software, Xinjiang University, Urumqi 830046, China; College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China
| | - Chen Chen
- College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China
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33
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Sabtu SN, Sani SFA, Looi LM, Chiew SF, Pathmanathan D, Bradley DA, Osman Z. Indication of high lipid content in epithelial-mesenchymal transitions of breast tissues. Sci Rep 2021; 11:3250. [PMID: 33547362 PMCID: PMC7864999 DOI: 10.1038/s41598-021-81426-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 12/21/2020] [Indexed: 02/06/2023] Open
Abstract
The epithelial-mesenchymal transition (EMT) is a crucial process in cancer progression and metastasis. Study of metabolic changes during the EMT process is important in seeking to understand the biochemical changes associated with cancer progression, not least in scoping for therapeutic strategies aimed at targeting EMT. Due to the potential for high sensitivity and specificity, Raman spectroscopy was used here to study the metabolic changes associated with EMT in human breast cancer tissue. For Raman spectroscopy measurements, tissue from 23 patients were collected, comprising non-lesional, EMT and non-EMT formalin-fixed and paraffin embedded breast cancer samples. Analysis was made in the fingerprint Raman spectra region (600-1800 cm-1) best associated with cancer progression biochemical changes in lipid, protein and nucleic acids. The ANOVA test followed by the Tukey's multiple comparisons test were conducted to see if there existed differences between non-lesional, EMT and non-EMT breast tissue for Raman spectroscopy measurements. Results revealed that significant differences were evident in terms of intensity between the non-lesional and EMT samples, as well as the EMT and non-EMT samples. Multivariate analysis involving independent component analysis, Principal component analysis and non-negative least square were used to analyse the Raman spectra data. The results show significant differences between EMT and non-EMT cancers in lipid, protein, and nucleic acids. This study demonstrated the capability of Raman spectroscopy supported by multivariate analysis in analysing metabolic changes in EMT breast cancer tissue.
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Affiliation(s)
- Siti Norbaini Sabtu
- Department of Physics, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, Malaysia
| | - S F Abdul Sani
- Department of Physics, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, Malaysia.
| | - L M Looi
- Department of Pathology, Faculty of Medicine, University of Malaya, 50603, Kuala Lumpur, Malaysia
| | - S F Chiew
- Department of Pathology, Faculty of Medicine, University of Malaya, 50603, Kuala Lumpur, Malaysia
| | - Dharini Pathmanathan
- Institute of Mathematical Sciences, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, Malaysia
| | - D A Bradley
- Centre for Biomedical Physics, Sunway University, Jalan Universiti, 46150, Petaling Jaya, Malaysia
- Department of Physics, University of Surrey, Guildford, GU2 7XH, UK
| | - Z Osman
- Department of Physics, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, Malaysia
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34
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Microbial phenomics linking the phenotype to function: The potential of Raman spectroscopy. J Microbiol 2021; 59:249-258. [DOI: 10.1007/s12275-021-0590-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 12/03/2020] [Accepted: 12/07/2020] [Indexed: 12/14/2022]
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35
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Identification of Molecular Basis for Objective Discrimination of Breast Cancer Cells (MCF-7) from Normal Human Mammary Epithelial Cells by Raman Microspectroscopy and Multivariate Curve Resolution Analysis. Int J Mol Sci 2021; 22:ijms22020800. [PMID: 33466869 PMCID: PMC7830327 DOI: 10.3390/ijms22020800] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 01/08/2021] [Accepted: 01/10/2021] [Indexed: 12/24/2022] Open
Abstract
Raman spectroscopy (RS), a non-invasive and label-free method, has been suggested to improve accuracy of cytological and even histopathological diagnosis. To our knowledge, this novel technique tends to be employed without concrete knowledge of molecular changes in cells. Therefore, identification of Raman spectral markers for objective diagnosis is necessary for universal adoption of RS. As a model study, we investigated human mammary epithelial cells (HMEpC) and breast cancer cells (MCF-7) by RS and employed various multivariate analyses (MA) including principal components analysis (PCA), linear discriminant analysis (LDA), and support vector machine (SVM) to estimate diagnostic accuracy. Furthermore, to elucidate the underlying molecular changes in cancer cells, we utilized multivariate curve resolution analysis–alternating least squares (MCR-ALS) with non-negative constraints to extract physically meaningful spectra from complex cellular data. Unsupervised PCA and supervised MA, such as LDA and SVM, classified HMEpC and MCF-7 fairly well with high accuracy but without revealing molecular basis. Employing MCR-ALS analysis we identified five pure biomolecular spectra comprising DNA, proteins and three independent unsaturated lipid components. Relative abundance of lipid 1 seems to be strictly regulated between the two groups of cells and could be the basis for excellent discrimination by chemometrics-assisted RS. It was unambiguously assigned to linoleate rich glyceride and therefore serves as a Raman spectral marker for reliable diagnosis. This study successfully identified Raman spectral markers and demonstrated the potential of RS to become an excellent cytodiagnostic tool that can both accurately and objectively discriminates breast cancer from normal cells.
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36
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Li J, Qin J, Zeng H, Li J, Wang K, Wang S. Unveiling dose- and time-dependent osteosarcoma cell responses to the γ-secretase inhibitor, DAPT, by confocal Raman microscopy. JOURNAL OF BIOPHOTONICS 2020; 13:e202000238. [PMID: 32697432 DOI: 10.1002/jbio.202000238] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 07/06/2020] [Accepted: 07/19/2020] [Indexed: 05/08/2023]
Abstract
Using confocal Raman micro-spectroscopy, this study aims to elucidate the cellular responses of the γ-secretase inhibitor, N-[N-(3,5-difluorophenacetyl)-L-alanyl]-S-phenylglycine t-butyl ester (DAPT), in osteosarcoma (OS) cells in a dose- and time-dependent manner. The K7M2 murine OS cell line was treated with different DAPT doses (0, 10, 20, and 40 μM) for 24 and 48 hours before investigations. Significant compositional changes (nucleic acids, protein and lipid) after DAPT treatment were addressed, which testified inhibitory effect of DAPT on the growth of OS cells. Moreover, both partial least squares-discriminant analysis (PLS-DA) and principal component analysis-linear discriminant analysis (PCA-LDA) analyses revealed governing composition variations among groups by distinguishing their spectral characteristics. Furthermore, by adopting leave-one-out cross validation method, it is shown that PLS-DA exhibited more classification capacity than PCA-LDA algorithm. Hence, by understanding the DAPT-based cellular variations, the achieved results provided an experimental foundation to establish new DAPT-based anticancer therapeutic strategies, and preclinical Raman analytical methodologies on drug-cell interactions.
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Affiliation(s)
- Jie Li
- Institute of Photonics and Photon-Technology, Northwest University, Xi'an, Shaanxi, China
| | - Jie Qin
- Department of Orthopedics, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Haishan Zeng
- Imaging Unit-Integrative Oncology Department, BC Cancer Research Center, Vancouver, BC, Canada
| | - Jing Li
- Department of Orthopedics, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Kaige Wang
- Institute of Photonics and Photon-Technology, Northwest University, Xi'an, Shaanxi, China
| | - Shuang Wang
- Institute of Photonics and Photon-Technology, Northwest University, Xi'an, Shaanxi, China
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Zhou H, Simmons CS, Sarntinoranont M, Subhash G. Raman Spectroscopy Methods to Characterize the Mechanical Response of Soft Biomaterials. Biomacromolecules 2020; 21:3485-3497. [PMID: 32833438 DOI: 10.1021/acs.biomac.0c00818] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Raman spectroscopy has been used extensively to characterize the influence of mechanical deformation on microstructure changes in biomaterials. While traditional piezo-spectroscopy has been successful in assessing internal stresses of hard biomaterials by tracking prominent peak shifts, peak shifts due to applied loads are near or below the resolution limit of the spectrometer for soft biomaterials with moduli in the kilo- to mega-Pascal range. In this Review, in addition to peak shifts, other spectral features (e.g., polarized intensity and intensity ratio) that provide quantitative assessments of microstructural orientation and secondary structure in soft biomaterials and their strain dependence are discussed. We provide specific examples for each method and classify sensitive Raman characteristic bands common across natural (e.g., soft tissue) and synthetic (e.g., polymeric scaffolds) soft biomaterials upon mechanical deformation. This Review can provide guidance for researchers aiming to analyze micromechanics of soft tissues and engineered tissue constructs by Raman spectroscopy.
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Affiliation(s)
- Hui Zhou
- Mechanical and Aerospace Engineering, University of Florida, Gainesville, Florida 32611, United States
| | - Chelsey S Simmons
- Mechanical and Aerospace Engineering, University of Florida, Gainesville, Florida 32611, United States
| | - Malisa Sarntinoranont
- Mechanical and Aerospace Engineering, University of Florida, Gainesville, Florida 32611, United States
| | - Ghatu Subhash
- Mechanical and Aerospace Engineering, University of Florida, Gainesville, Florida 32611, United States
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Medipally DKR, Cullen D, Untereiner V, Sockalingum GD, Maguire A, Nguyen TNQ, Bryant J, Noone E, Bradshaw S, Finn M, Dunne M, Shannon AM, Armstrong J, Meade AD, Lyng FM. Vibrational spectroscopy of liquid biopsies for prostate cancer diagnosis. Ther Adv Med Oncol 2020; 12:1758835920918499. [PMID: 32821294 PMCID: PMC7412923 DOI: 10.1177/1758835920918499] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Accepted: 03/18/2020] [Indexed: 12/24/2022] Open
Abstract
Background: Screening for prostate cancer with prostate specific antigen and digital rectal examination allows early diagnosis of prostate malignancy but has been associated with poor sensitivity and specificity. There is also a considerable risk of over-diagnosis and over-treatment, which highlights the need for better tools for diagnosis of prostate cancer. This study investigates the potential of high throughput Raman and Fourier Transform Infrared (FTIR) spectroscopy of liquid biopsies for rapid and accurate diagnosis of prostate cancer. Methods: Blood samples (plasma and lymphocytes) were obtained from healthy control subjects and prostate cancer patients. FTIR and Raman spectra were recorded from plasma samples, while Raman spectra were recorded from the lymphocytes. The acquired spectral data was analysed with various multivariate statistical methods, principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and classical least squares (CLS) fitting analysis. Results: Discrimination was observed between the infrared and Raman spectra of plasma and lymphocytes from healthy donors and prostate cancer patients using PCA. In addition, plasma and lymphocytes displayed differentiating signatures in patients exhibiting different Gleason scores. A PLS-DA model was able to discriminate these groups with sensitivity and specificity rates ranging from 90% to 99%. CLS fitting analysis identified key analytes that are involved in the development and progression of prostate cancer. Conclusions: This technology may have potential as an alternative first stage diagnostic triage for prostate cancer. This technology can be easily adaptable to many other bodily fluids and could be useful for translation of liquid biopsy-based diagnostics into the clinic.
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Affiliation(s)
- Dinesh K R Medipally
- Radiation and Environmental Science Centre, Focas Research Institute, Technological University Dublin, Dublin, Ireland
| | - Daniel Cullen
- Radiation and Environmental Science Centre, Focas Research Institute, Technological University Dublin, Dublin, Ireland
| | - Valérie Untereiner
- Université de Reims Champagne-Ardenne, BioSpecT EA 7506, UFR Pharmacie, Reims, France
| | - Ganesh D Sockalingum
- Université de Reims Champagne-Ardenne, BioSpecT EA 7506, UFR Pharmacie, Reims, France
| | - Adrian Maguire
- Radiation and Environmental Science Centre, Focas Research Institute, Technological University Dublin, Dublin, Ireland
| | - Thi Nguyet Que Nguyen
- Radiation and Environmental Science Centre, Focas Research Institute, Technological University Dublin, Dublin, Ireland
| | - Jane Bryant
- Radiation and Environmental Science Centre, Focas Research Institute, Technological University Dublin, Dublin, Ireland
| | - Emma Noone
- Clinical Trials Unit, St Luke's Radiation Oncology Network, St Luke's Hospital, Dublin, Ireland
| | - Shirley Bradshaw
- Clinical Trials Unit, St Luke's Radiation Oncology Network, St Luke's Hospital, Dublin, Ireland
| | - Marie Finn
- Clinical Trials Unit, St Luke's Radiation Oncology Network, St Luke's Hospital, Dublin, Ireland
| | - Mary Dunne
- Clinical Trials Unit, St Luke's Radiation Oncology Network, St Luke's Hospital, Dublin, Ireland
| | | | | | - Aidan D Meade
- School of Physics & Clinical & Optometric Sciences, Technological University Dublin, Kevin Street, Dublin, Dublin D08 NF82, Ireland
| | - Fiona M Lyng
- Radiation and Environmental Science Centre, Focas Research Institute, Technological University Dublin, Dublin, Dublin D08 NF82, Ireland
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Maitra I, Morais CLM, Lima KMG, Ashton KM, Date RS, Martin FL. Raman spectral discrimination in human liquid biopsies of oesophageal transformation to adenocarcinoma. JOURNAL OF BIOPHOTONICS 2020; 13:e201960132. [PMID: 31794123 DOI: 10.1002/jbio.201960132] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 11/27/2019] [Accepted: 11/30/2019] [Indexed: 06/10/2023]
Abstract
The aim of this study was to determine whether Raman spectroscopy combined with chemometric analysis can be applied to interrogate biofluids (plasma, serum, saliva and urine) towards detecting oesophageal stages through to oesophageal adenocarcinoma [normal/squamous epithelium, inflammatory, Barrett's, low-grade dysplasia, high-grade dysplasia and oesophageal adenocarcinoma (OAC)]. The chemometric analysis of the spectral data was performed using principal component analysis, successive projections algorithm or genetic algorithm (GA) followed by quadratic discriminant analysis (QDA). The genetic algorithm quadratic discriminant analysis (GA-QDA) model using a few selected wavenumbers for saliva and urine samples achieved 100% classification for all classes. For plasma and serum, the GA-QDA model achieved excellent accuracy in all oesophageal stages (>90%). The main GA-QDA features responsible for sample discrimination were: 1012 cm-1 (C─O stretching of ribose), 1336 cm-1 (Amide III and CH2 wagging vibrations from glycine backbone), 1450 cm-1 (methylene deformation) and 1660 cm-1 (Amide I). The results of this study are promising and support the concept that Raman on biofluids may become a useful and objective diagnostic tool to identify oesophageal disease stages from squamous epithelium to OAC.
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Affiliation(s)
- Ishaan Maitra
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Camilo L M Morais
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
| | - Kássio M G Lima
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
- Biological Chemistry and Chemometrics, Institute of Chemistry, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Katherine M Ashton
- Lancashire Teaching Hospitals NHS Foundation Trust, Royal Preston Hospital, Preston, UK
| | - Ravindra S Date
- Lancashire Teaching Hospitals NHS Foundation Trust, Royal Preston Hospital, Preston, UK
| | - Francis L Martin
- School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, UK
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Li J, Ding J, Liu X, Tang B, Bai X, Wang Y, Li S, Wang X. Label-free serum detection of Trichinella spiralis using surface-enhanced Raman spectroscopy combined with multivariate analysis. Acta Trop 2020; 203:105314. [PMID: 31866336 DOI: 10.1016/j.actatropica.2019.105314] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 12/18/2019] [Accepted: 12/18/2019] [Indexed: 11/17/2022]
Abstract
Based on blood serum surface-enhanced Raman spectroscopy (SERS) analysis, this paper proposed a simple and unlabeled non-invasive serum detection for T. spiralis infection. Serum samples were collected and analyzed from 40 rats at 0 days post infection (dpi) (normal rats), 19 uninfected rats, and 16 rats infected with T. spiralis at 28 dpi, using SERS measurements. Multivariate statistical techniques, such as linear discriminant analysis (LDA) and principal components analysis (PCA), were used to analyze and identify the obtained blood serum SERS spectra. The diagnosis algorithms, based on PCA-LDA, achieved a diagnostic sensitivity of 87.5%, a specificity of 94.7%, and an accuracy of 91.4% for separating the samples infected with T. spiralis from the control samples. This exploratory study demonstrated that colloidal Ag NPs-based SERS serum analysis technique combined with PCA-LDA has a great potential in improving the detection of T. spiralis infection and onsite screening.
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Affiliation(s)
- Jian Li
- Key Laboratory of Zoonosis Research, Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun 130062, China
| | - Jing Ding
- Key Laboratory of Zoonosis Research, Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun 130062, China
| | - Xiaolei Liu
- Key Laboratory of Zoonosis Research, Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun 130062, China
| | - Bin Tang
- Key Laboratory of Zoonosis Research, Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun 130062, China
| | - Xue Bai
- Key Laboratory of Zoonosis Research, Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun 130062, China
| | - Yang Wang
- Key Laboratory of Zoonosis Research, Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun 130062, China
| | - Shicun Li
- Key Laboratory of Zoonosis Research, Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun 130062, China
| | - Xuelin Wang
- Key Laboratory of Zoonosis Research, Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun 130062, China.
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Breast cancer detection by ATR-FTIR spectroscopy of blood serum and multivariate data-analysis. Talanta 2020; 214:120857. [PMID: 32278436 DOI: 10.1016/j.talanta.2020.120857] [Citation(s) in RCA: 63] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 02/16/2020] [Accepted: 02/19/2020] [Indexed: 12/31/2022]
Abstract
Detection of breast cancer has particular importance for the diagnosis of cancer diseases. This is the most common type of cancer among women. Breast cancer is a malignant tumor of the glandular tissue of the breast. It is proposed to use infrared spectroscopy of blood serum as a simple and quick way to detect breast cancer. The paper presents the results of research using the methods of multivariate processing of IR spectra of human blood serum obtained by ATR-FTIR spectroscopy. The paper presents the results of research using the methods of multivariate processing of IR spectra of human blood serum obtained by ATR-FTIR spectroscopy. A sufficiently large sample of patients and healthy donors was diagnosed. Blood samples are examined from 66 patients who are clinically diagnosed with breast cancer and 80 healthy volunteers. A feature of the applied approach was a combination of the method of principal component analysis (PCA) and principal component regression (PCR) for processing the IR spectra of blood serum. The PCA method allows us to determine the spectral bands referring for the intensity differences between the control group and the patient group. Shown, that the range of 1306-1250cm-1 in the IR spectrum of blood serum is diagnostically significant for breast cancer. This range corresponds to the vibrations of several functional groups of DNA and RNA, which play a key role in discrimination in breast cancer screening using ATR-FTIR spectroscopy. It is shown that the proposed method has advantages in ease of use for clinical diagnosis and gives good results for the identification of breast cancer. The values of sensitivity (92.3%) and specificity (87.1%) obtained using the PCR method are close to those of mammography and ultrasound. This indicates the possibility of using this method in real clinical laboratory diagnostics.
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Song D, Yu F, Chen S, Chen Y, He Q, Zhang Z, Zhang J, Wang S. Raman spectroscopy combined with multivariate analysis to study the biochemical mechanism of lung cancer microwave ablation. BIOMEDICAL OPTICS EXPRESS 2020; 11:1061-1072. [PMID: 32133237 PMCID: PMC7041477 DOI: 10.1364/boe.383869] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Revised: 01/14/2020] [Accepted: 01/15/2020] [Indexed: 05/24/2023]
Abstract
Lung cancer is the leading cause of death in cancer patients, and microwave ablation (MWA) has been extensively used in clinical treatment. In this study, we characterized the spectra of MWA-treated and untreated lung squamous cell carcinoma (LSCC) tissues, as well as healthy lung tissue, and conducted a preliminary analysis of spectral variations associated with MWA treatment. The results of characteristic spectral analysis of different types of tissues indicated that MWA treatment induces an increase in the content of nucleic acids, proteins, and lipid components in lung cancer tissues. The discriminant model based on the principal component analysis - linear discriminant analysis (PCA-LDA) algorithm together with leave-one-out cross validation (LOOCV) method yield the sensitivities of 90%, 80%, and 96%, and specificities of 86.2%, 93.8%, and 100% among untreated and MWA-treated cancerous tissue, and healthy lung tissue, respectively. These results indicate that Raman spectroscopy combined with multivariate analysis techniques can be used to explore the biochemical response mechanism of cancerous tissue to MWA therapy.
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Affiliation(s)
- Dongliang Song
- Institute of Photonics and Photon-Technology, Northwest University, Xi'an, Shaanxi, 710069, China
- Department of physics, Northwest University, Xi'an, Shaanxi, 710069, China
| | - Fan Yu
- Institute of Photonics and Photon-Technology, Northwest University, Xi'an, Shaanxi, 710069, China
| | - Shilin Chen
- Thoracic Surgery, Nanjing Medical University Affiliated Cancer Hospital, Jiangsu Cancer Hospital, Nanjing, Jiangsu, 210009, China
| | - Yishen Chen
- Institute of Photonics and Photon-Technology, Northwest University, Xi'an, Shaanxi, 710069, China
| | - Qingli He
- Department of physics, Northwest University, Xi'an, Shaanxi, 710069, China
| | - Zhe Zhang
- Department of Pathology, Nanjing Medical University Affiliated Cancer Hospital, Jiangsu Cancer Hospital, Nanjing, Jiangsu, 210009, China
| | - Jingyuan Zhang
- Department of Pathology, Nanjing Medical University Affiliated Cancer Hospital, Jiangsu Cancer Hospital, Nanjing, Jiangsu, 210009, China
| | - Shuang Wang
- Institute of Photonics and Photon-Technology, Northwest University, Xi'an, Shaanxi, 710069, China
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Raman spectroscopy as a non-invasive diagnostic technique for endometriosis. Sci Rep 2019; 9:19795. [PMID: 31875014 PMCID: PMC6930314 DOI: 10.1038/s41598-019-56308-y] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Accepted: 12/10/2019] [Indexed: 11/08/2022] Open
Abstract
Endometriosis is a condition in which the endometrium, the layer of tissue that usually covers the inside of the uterus, grows outside the uterus. One of its severe effects is sub-fertility. The exact reason for endometriosis is still unknown and under investigation. Tracking the symptoms is not sufficient for diagnosing the disease. A successful diagnosis can only be made using laparoscopy. During the disease, the amount of some molecules (i.e., proteins, antigens) changes in the blood. Raman spectroscopy provides information about biochemicals without using dyes or external labels. In this study, Raman spectroscopy is used as a non-invasive diagnostic method for endometriosis. The Raman spectra of 94 serum samples acquired from 49 patients and 45 healthy individuals were compared for this study. Principal Component Analysis (PCA), k- Nearest Neighbors (kNN), and Support Vector Machines (SVM) were used in the analysis. According to the results (using 80 measurements for training and 14 measurements for the test set), it was found that kNN-weighted gave the best classification model with sensitivity and specificity values of 80.5% and 89.7%, respectively. Testing the model with unseen data yielded a sensitivity value of 100% and a specificity value of 100%. To the best of our knowledge, this is the first study in which Raman spectroscopy was used in combination with PCA and classification algorithms as a non-invasive method applied on blood sera for the diagnosis of endometriosis.
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44
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Huefner A, Kuan WL, Mason SL, Mahajan S, Barker RA. Serum Raman spectroscopy as a diagnostic tool in patients with Huntington's disease. Chem Sci 2019; 11:525-533. [PMID: 32190272 PMCID: PMC7067270 DOI: 10.1039/c9sc03711j] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Accepted: 11/14/2019] [Indexed: 12/18/2022] Open
Abstract
Huntington's disease is an inherited fatal progressive neurodegenerative disorder. A possible new Raman ‘spectral’ biomarker was identified that uses a tiny drop of patients' blood serum; thus can have immense diagnostic and therapeutic implications.
Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by an abnormal CAG expansion in exon 1 of the huntingtin (HTT) gene. Given its genetic basis it is possible to study patients both in the pre-manifest and manifest stages of the condition. While disease onset can be modelled using CAG repeat size, there are no easily accessible biomarkers that can objectively track disease progression. Here, we employed a holistic approach using spectral profiles generated using both surface-enhanced Raman spectroscopy (SERS) and Raman Spectroscopy (RS), on the serum of healthy participants and HD patients covering a wide spectrum of disease stages. We found that there was both genotype- and gender-specific segregation on using the full range in the fingerprint region with both SERS and RS. On a more detailed interrogation using specific spectral intervals, SERS revealed significant correlations with disease progression, in particular progression from pre-manifest through to advanced HD was associated with serum molecules related to protein misfolding and nucleotide catabolism. Thus, this study shows the potential of Raman spectroscopy-based techniques for stratification of patients and, of SERS, in particular, to track disease status through provision of ‘spectral’ biomarkers in HD, with clinical applications for other diseases and trials looking at disease modifying therapies.
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Affiliation(s)
- Anna Huefner
- Department of Chemistry , University of Cambridge , Lensfield Road , Cambridge , CB2 1WE , UK.,John van Geest Centre for Brain Repair , the WT-MRC Cambridge Stem Cell Institute , University of Cambridge , Forvie Site, Robinson Way , Cambridge , CB2 0PY , UK .
| | - Wei-Li Kuan
- John van Geest Centre for Brain Repair , the WT-MRC Cambridge Stem Cell Institute , University of Cambridge , Forvie Site, Robinson Way , Cambridge , CB2 0PY , UK .
| | - Sarah L Mason
- John van Geest Centre for Brain Repair , the WT-MRC Cambridge Stem Cell Institute , University of Cambridge , Forvie Site, Robinson Way , Cambridge , CB2 0PY , UK .
| | - Sumeet Mahajan
- The Institute for Life Sciences , the School of Chemistry , University of Southampton , Highfield Campus , Southampton , SO17 1BJ , UK .
| | - Roger A Barker
- John van Geest Centre for Brain Repair , the WT-MRC Cambridge Stem Cell Institute , University of Cambridge , Forvie Site, Robinson Way , Cambridge , CB2 0PY , UK .
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Naseer K, Saleem M, Ali S, Mirza B, Qazi J. Identification of new spectral signatures from hepatitis C virus infected human sera. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2019; 222:117181. [PMID: 31202032 DOI: 10.1016/j.saa.2019.117181] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Revised: 05/01/2019] [Accepted: 05/26/2019] [Indexed: 05/27/2023]
Abstract
Hepatitis C virus (HCV) infection is one of the leading causes of morbidity and mortality worldwide. Mortality linked with HCV infection can be lowered with effective and prompt diagnosis in early stages of infection. In this study potential of Raman spectroscopy to differentiate between healthy and HCV infected serum samples was investigated. Clear differences were observed in the Raman spectra of HCV infected and healthy sera samples. Using the analysis of variance (ANOVA) and t-test (p < 0.001) on Raman spectra of diseased and healthy samples, we observed eleven unique Raman bands at 676, 825, 853, 936, 1029, 1105, 1155, 1305, 1620, 1654 and 1757 cm-1 associated with only HCV infected sera and have not been reported in earlier studies. In addition, six Raman bands at 556, 585, 716, 815, 1273 and 1142 cm-1were observed in healthy sera only. Three Raman bands at 1330, 1526 and 1572 cm-1 were observed in both type of samples but their intensity was drastically reduced in diseased samples. Various multivariate analysis techniques were employed to demonstrate the robustness of the results. We employed multivariate and unsupervised principal component analysis (PCA) in conjunction with supervised classification linear discriminant analysis (LDA), using ten-fold jackknife cross-validation, in order to develop effective diagnostic algorithm technique (PCA-LDA). Our PCA-LDA model yielded sufficient sensitivity and specificity i.e. correctly identified all infected samples included in this study. Ours results indicate that these unique Raman bands have the potential to be used as biomarkers for optical diagnosis of HCV infection.
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Affiliation(s)
- Khulla Naseer
- Faculty of Biological Sciences, Qauid-i-Azam University, Islamabad, Pakistan
| | - Muhammad Saleem
- Agri. & Biophotonics Division, National Institute of Laser and Optronics (NILOP), Lehtrar Road, Islamabad, Pakistan
| | - Safdar Ali
- Directorate General National Repository, P.O. Box 1175, Islamabad, Pakistan
| | - Bushra Mirza
- Faculty of Biological Sciences, Qauid-i-Azam University, Islamabad, Pakistan
| | - Javaria Qazi
- Faculty of Biological Sciences, Qauid-i-Azam University, Islamabad, Pakistan.
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Nargis HF, Nawaz H, Ditta A, Mahmood T, Majeed MI, Rashid N, Muddassar M, Bhatti HN, Saleem M, Jilani K, Bonnier F, Byrne HJ. Raman spectroscopy of blood plasma samples from breast cancer patients at different stages. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2019; 222:117210. [PMID: 31176149 DOI: 10.1016/j.saa.2019.117210] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Revised: 05/02/2019] [Accepted: 05/26/2019] [Indexed: 06/09/2023]
Abstract
Raman spectroscopy was employed for the characterization of blood plasma samples from patients at different stages of breast cancer. Blood plasma samples taken from clinically diagnosed breast cancer patients were compared with healthy controls using multivariate data analysis techniques (principal components analysis - PCA) to establish Raman spectral features which can be considered spectral markers of breast cancer development. All the stages of the disease can be differentiated from normal samples. It is also found that stage 2 and 3 are biochemically similar, but can be differentiated from each other by PCA. The Raman spectral data of the stage 4 is found to be biochemically distinct, but very variable between patients. Raman spectral features associated with DNA and proteins were identified, which are exclusive to patient plasma samples. Moreover, there are several other spectral features which are strikingly different in the blood plasma samples of different stages of breast cancer. In order to further explore the potential of Raman spectroscopy as the basis of a minimally invasive screening technique for breast cancer diagnosis and staging, PCA-Factorial Discriminant Analysis (FDA) was employed to classify the Raman spectral datasets of the blood plasma samples of the breast cancer patients, according to different stages of the disease, yielding promisingly high values of sensitivity and specificity for all stages.
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Affiliation(s)
- H F Nargis
- Department of Chemistry, University of Agriculture, Faisalabad, Pakistan
| | - H Nawaz
- Department of Chemistry, University of Agriculture, Faisalabad, Pakistan.
| | - A Ditta
- Department of Chemistry, University of Agriculture, Faisalabad, Pakistan
| | - T Mahmood
- Department of Chemistry, University of Agriculture, Faisalabad, Pakistan
| | - M I Majeed
- Department of Chemistry, University of Agriculture, Faisalabad, Pakistan
| | - N Rashid
- University of Central Punjab, Faisalabad campus, Faisalabad, Pakistan
| | - M Muddassar
- Department of Biosciences, COMSATS University Islamabad, Park Road, Islamabad, Pakistan
| | - H N Bhatti
- Department of Chemistry, University of Agriculture, Faisalabad, Pakistan
| | - M Saleem
- National Institute of Lasers and Optronics (NILOP), Islamabad, Pakistan
| | - K Jilani
- Department of Biochemistry, University of Agriculture, Faisalabad, Pakistan
| | - F Bonnier
- EA 6295 Nano-médicaments and nano-sondes, Université de Tours, Tours, France
| | - H J Byrne
- FOCAS Research Institute, Technological University Dublin, Kevin Street, Dublin 8, Ireland
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Multivariate Statistical Analysis of Surface Enhanced Raman Spectra of Human Serum for Alzheimer’s Disease Diagnosis. APPLIED SCIENCES-BASEL 2019. [DOI: 10.3390/app9163256] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Alzheimer’s disease (AD) is the most common form of dementia worldwide and is characterized by progressive cognitive decline. Along with being incurable and lethal, AD is difficult to diagnose with high levels of accuracy. Blood serum from Alzheimer’s disease (AD) patients was analyzed by surface-enhanced Raman spectroscopy (SERS) coupled with multivariate statistical analysis. The obtained spectra were compared with spectra from healthy controls (HC) to develop a simple test for AD detection. Serum spectra from AD patients were further compared to spectra from patients with other neurodegenerative dementias (OD). Colloidal silver nanoparticles (AgNPs) were used as the SERS-active substrates. Classification experiments involving serum SERS spectra using artificial neural networks (ANNs) achieved a diagnostic sensitivity around 96% for differentiating AD samples from HC samples in a binary model and 98% for differentiating AD, HC, and OD samples in a tertiary model. The results from this proof-of-concept study demonstrate the great potential of SERS blood serum analysis to be developed further into a novel clinical assay for the effective and accurate diagnosis of AD.
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In vivo detection of oral precancer using a fluorescence-based, in-house-fabricated device: a Mahalanobis distance-based classification. Lasers Med Sci 2019; 34:1243-1251. [PMID: 30659473 DOI: 10.1007/s10103-019-02720-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Accepted: 01/10/2019] [Indexed: 02/04/2023]
Abstract
In vivo detection of oral precancer has been carried out by a fluorescence-based, in-house-developed handheld probe on three groups: oral squamous cell carcinoma (OSCC), dysplastic (precancer), and control (normal). Measurements have been performed on a total of 141 patients and volunteers of different age groups. Excitation wavelength of 405 nm was used and fluorescence emission spectra were recorded in the scan range of 450.14 to 763.41 nm at very low incident power (122 μW) from different oral sites buccal mucosa (BM), lateral boarder of tongue (LBT), and dorsal surface of tongue (DST). Spectral profiles are found to vary among the three groups as well as among the different oral sites. Major and minor bands of flavin adenine dinucleotide (FAD) and porphyrins near 500, 634, 676, 689, and 703 nm have been obtained. Porphyrin contribution is found to be more dominant than the FAD in OSCC and dysplastic groups as compared to the control group. A better classification has been observed using the entire spectral range rather than restricting to individual bands, by application of principal component analysis (PCA), Mahalanobis distance model, and receiver operating characteristic analysis (ROC). ROC on Mahalanobis distance differentiates OSCC to normal, dysplastic to normal, and OSCC to dysplastic with sensitivities from 71% to 98%, 92% to 94% and 81% to 93% and specificities 91% to 100%, 86% to 100% and 79% to 97% for oral sites BM, LBT and DST. LBT and DST appear to be more sensitive to dysplasia detection as compared to BM.
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Mehta K, Atak A, Sahu A, Srivastava S, C MK. An early investigative serum Raman spectroscopy study of meningioma. Analyst 2019; 143:1916-1923. [PMID: 29620771 DOI: 10.1039/c8an00224j] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Meningiomas represent one of the most frequently reported non-glial, primary brain and central nervous system (CNS) tumors. Meningiomas often display a spectrum of anomalous locations and morphological attributes, deterring their timely diagnosis. Majority of them are sporadic in nature and thus the present-day screening strategies, including radiological investigations, often result in misdiagnosis due to their aberrant and equivocal radiological facets. Therefore, it is pertinent to explore less invasive and patient-friendly biofluids such as serum for their screening and diagnostics. The utility of serum Raman spectroscopy in diagnosis and therapeutic monitoring of cancers has been reported in the literature. In the present study, for the first time, to the best of our knowledge, we have explored Raman spectroscopy to classify the sera of meningioma and control subjects. For this exploration, 35 samples each of meningioma and control subjects were accrued and the spectra revealed variance in the levels of DNA, proteins, lipids, amino acids and β-carotene, i.e., a relatively higher protein, DNA and lipid content in meningioma. Subsequent Principal Component Analysis (PCA) and Principal Component-Linear Discriminant Analysis (PC-LDA) followed by Leave-One-Out Cross-Validation (LOOCV) and limited independent test data, in a patient-wise approach, yielded a classification efficiency of 92% and 80% for healthy and meningioma, respectively. Additionally, in the analogous analysis between healthy and different grades of meningioma, similar results were obtained. These results indicate the potential of Raman spectroscopy in differentiating meningioma. As present methods suffer from known limitations, with the prospective validation on a larger cohort, serum Raman spectroscopy could be an adjuvant/alternative approach in the clinical management of meningioma.
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Affiliation(s)
- Kanika Mehta
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai-400076, India.
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Auner GW, Koya SK, Huang C, Broadbent B, Trexler M, Auner Z, Elias A, Mehne KC, Brusatori MA. Applications of Raman spectroscopy in cancer diagnosis. Cancer Metastasis Rev 2018; 37:691-717. [PMID: 30569241 PMCID: PMC6514064 DOI: 10.1007/s10555-018-9770-9] [Citation(s) in RCA: 166] [Impact Index Per Article: 27.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Novel approaches toward understanding the evolution of disease can lead to the discovery of biomarkers that will enable better management of disease progression and improve prognostic evaluation. Raman spectroscopy is a promising investigative and diagnostic tool that can assist in uncovering the molecular basis of disease and provide objective, quantifiable molecular information for diagnosis and treatment evaluation. This technique probes molecular vibrations/rotations associated with chemical bonds in a sample to obtain information on molecular structure, composition, and intermolecular interactions. Raman scattering occurs when light interacts with a molecular vibration/rotation and a change in polarizability takes place during molecular motion. This results in light being scattered at an optical frequency shifted (up or down) from the incident light. By monitoring the intensity profile of the inelastically scattered light as a function of frequency, the unique spectroscopic fingerprint of a tissue sample is obtained. Since each sample has a unique composition, the spectroscopic profile arising from Raman-active functional groups of nucleic acids, proteins, lipids, and carbohydrates allows for the evaluation, characterization, and discrimination of tissue type. This review provides an overview of the theory of Raman spectroscopy, instrumentation used for measurement, and variation of Raman spectroscopic techniques for clinical applications in cancer, including detection of brain, ovarian, breast, prostate, and pancreatic cancers and circulating tumor cells.
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Affiliation(s)
- Gregory W Auner
- Michael and Marian Ilitch Department of Surgery, School of Medicine, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA.
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA.
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA.
- Henry Ford Health Systems, Detroit Institute of Ophthalmology, Grosse Pointe Park, MI, 48230, USA.
| | - S Kiran Koya
- Michael and Marian Ilitch Department of Surgery, School of Medicine, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
| | - Changhe Huang
- Michael and Marian Ilitch Department of Surgery, School of Medicine, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
| | - Brandy Broadbent
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
| | - Micaela Trexler
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
| | - Zachary Auner
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
- Department of Physics & Astronomy, Wayne State University, Detroit, MI, 48202, USA
| | - Angela Elias
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
| | - Katlyn Curtin Mehne
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
| | - Michelle A Brusatori
- Michael and Marian Ilitch Department of Surgery, School of Medicine, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Department of Biomedical Engineering, College of Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, 48202, USA
- Smart Sensors and Integrated Microsystems Program, Wayne State University, Detroit, MI, 48202, USA
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