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Lasalvia M, Capozzi V, Perna G. Classification of healthy and cancerous colon cells by Fourier transform infrared spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 321:124683. [PMID: 38908360 DOI: 10.1016/j.saa.2024.124683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 06/04/2024] [Accepted: 06/18/2024] [Indexed: 06/24/2024]
Abstract
Colorectal cancer is one of the most diagnosed types of cancer in developed countries. Current diagnostic methods are partly dependent on pathologist experience and laboratories instrumentation. In this study, we used Fourier Transform Infrared (FTIR) spectroscopy in transflection mode, combined with Principal Components Analysis followed by Linear Discriminant Analysis (PCA-LDA) and Partial Least Squares - Discriminant Analysis (PLS-DA), to build a classification algorithm to diagnose colon cancer in cell samples, based on absorption spectra measured in two spectral ranges of the mid-infrared spectrum. In particular, PCA technique highlights small biochemical differences between healthy and cancerous cells: these are related to the larger lipid content in the former compared with the latter and to the larger relative amount of protein and nucleic acid components in the cancerous cells compared with the healthy ones. Comparison of the classification accuracy of PCA-LDA and PLS-DA methods applied to FTIR spectra measured in the 1000-1800 cm-1 (low wavenumber range, LWR) and 2700-3700 cm-1 (high wavenumber range, HWR) remarks that both algorithms are able to classify hidden class FTIR spectra with excellent accuracy (100 %) in both spectral regions. This is a hopeful result for clinical translation of infrared spectroscopy: in fact, it makes reliable the predictions obtained using FTIR measurements carried out only in the HWR, in which the glass slides used in clinical laboratories are transparent to IR radiation.
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Affiliation(s)
- Maria Lasalvia
- Dipartimento di Medicina Clinica e Sperimentale, Università di Foggia, 71122 Foggia, Italy
| | - Vito Capozzi
- Dipartimento di Medicina Clinica e Sperimentale, Università di Foggia, 71122 Foggia, Italy
| | - Giuseppe Perna
- Dipartimento di Medicina Clinica e Sperimentale, Università di Foggia, 71122 Foggia, Italy.
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2
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Kralova K, Vrtelka O, Fouskova M, Smirnova TA, Michalkova L, Hribek P, Urbanek P, Kuckova S, Setnicka V. Comprehensive spectroscopic, metabolomic, and proteomic liquid biopsy in the diagnostics of hepatocellular carcinoma. Talanta 2024; 270:125527. [PMID: 38134814 DOI: 10.1016/j.talanta.2023.125527] [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: 07/15/2023] [Revised: 11/30/2023] [Accepted: 12/04/2023] [Indexed: 12/24/2023]
Abstract
Liquid biopsy is a very topical issue in clinical diagnostics research nowadays. In this study, we explored and compared various analytical approaches to blood plasma analysis. Finally, we proposed a comprehensive procedure, which, thanks to the utilization of multiple analytical techniques, allowed the targeting of various biomolecules in blood plasma reflecting diverse biological processes underlying disease development. The potential of such an approach, combining proteomics, metabolomics, and vibrational spectroscopy along with preceding blood plasma fractionation, was demonstrated on blood plasma samples of patients suffering from hepatocellular carcinoma in cirrhotic terrain (n = 20) and control subjects with liver cirrhosis (n = 20) as well as healthy subjects (n = 20). Most of the applied methods allowed the classification of the samples with an accuracy exceeding 80.0 % and therefore have the potential to be used as a stand-alone method in clinical diagnostics. Moreover, a final panel of 48 variables obtained by a combination of the utilized analytical methods enabled the discrimination of the hepatocellular carcinoma samples from cirrhosis with 94.3 % cross-validated accuracy. Thus, this study, although limited by the cohort size, clearly demonstrated the benefit of the multimethod approach in clinical diagnosis.
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Affiliation(s)
- Katerina Kralova
- Department of Analytical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technicka 5, 166 28, Prague 6, Czech Republic
| | - Ondrej Vrtelka
- Department of Analytical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technicka 5, 166 28, Prague 6, Czech Republic
| | - Marketa Fouskova
- Department of Analytical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technicka 5, 166 28, Prague 6, Czech Republic
| | - Tatiana Anatolievna Smirnova
- Department of Biochemistry and Microbiology, Faculty of Food and Biochemical Technology, University of Chemistry and Technology, Prague, Technicka 5, 166 28, Prague 6, Czech Republic
| | - Lenka Michalkova
- Department of Analytical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technicka 5, 166 28, Prague 6, Czech Republic; Department of Analytical Chemistry, Institute of Chemical Process Fundamentals of the CAS, Rozvojova 135, 165 02, Prague 6, Czech Republic
| | - Petr Hribek
- Military University Hospital Prague, Department of Medicine 1st Faculty of Medicine Charles University and Military University Hospital Prague, U Vojenske Nemocnice 1200, 169 02, Prague 6, Czech Republic; Department of Internal Medicine, Faculty of Military Health Sciences in Hradec Kralove, University of Defense, Trebesska 1575, 500 01, Hradec Kralove, Czech Republic
| | - Petr Urbanek
- Military University Hospital Prague, Department of Medicine 1st Faculty of Medicine Charles University and Military University Hospital Prague, U Vojenske Nemocnice 1200, 169 02, Prague 6, Czech Republic
| | - Stepanka Kuckova
- Department of Biochemistry and Microbiology, Faculty of Food and Biochemical Technology, University of Chemistry and Technology, Prague, Technicka 5, 166 28, Prague 6, Czech Republic
| | - Vladimir Setnicka
- Department of Analytical Chemistry, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Technicka 5, 166 28, Prague 6, Czech Republic.
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3
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Hunt NT. Using 2D-IR Spectroscopy to Measure the Structure, Dynamics, and Intermolecular Interactions of Proteins in H 2O. Acc Chem Res 2024; 57:685-692. [PMID: 38364823 PMCID: PMC10918835 DOI: 10.1021/acs.accounts.3c00682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/30/2024] [Accepted: 01/30/2024] [Indexed: 02/18/2024]
Abstract
Infrared (IR) spectroscopy probes molecular structure at the level of the chemical bond or functional group. In the case of proteins, the most informative band in the IR spectrum is the amide I band, which arises predominantly from the C═O stretching vibration of the peptide link. The folding of proteins into secondary and tertiary structures leads to vibrational coupling between peptide units, generating specific amide I spectral signatures that provide a fingerprint of the macromolecular conformation. Ultrafast two-dimensional IR (2D-IR) spectroscopy allows the amide I band of a protein to be spread over a second frequency dimension in a way that mirrors 2D-NMR methods. This means that amide I 2D-IR spectroscopy produces a spectral map that is exquisitely sensitive to protein structure and dynamics and so provides detailed insights that cannot be matched by IR absorption spectroscopy. As a result, 2D-IR spectroscopy has emerged as a powerful tool for probing protein structure and dynamics over a broad range of time and length scales in the solution phase at room temperature. However, the protein amide I band coincides with an IR absorption from the bending vibration of water (δHOH), the natural biological solvent. To circumvent this problem, protein IR studies are routinely performed in D2O solutions because H/D substitution shifts the solvent bending mode (δDOD) to a lower frequency, revealing the amide I band. While effective, this method raises fundamental questions regarding the impact of the change in solvent mass on the structural or solvation dynamics of the protein and the removal of the energetic resonance between solvent and solute.In this Account, a series of studies applying 2D-IR to study the spectroscopy and dynamics of proteins in H2O-rich solvents is reviewed. A comparison of IR absorption spectroscopy and 2D-IR spectroscopy of protein-containing fluids is used to demonstrate the basis of the approach before a series of applications is presented. These range from measurements of fundamental protein biophysics to recent applications of machine learning to gain insight into protein-drug binding in complex mixtures. An outlook is presented, considering the potential for 2D-IR measurements to contribute to our understanding of protein behavior under near-physiological conditions, along with an evaluation of the obstacles that still need to be overcome.
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Affiliation(s)
- Neil T. Hunt
- Department of Chemistry and York Biomedical
Research Institute, University of York, Heslington, York, YO10
5DD, U.K.
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4
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Yu Y, Liang C, Wan QQ, Jin D, Liu X, Zhang Z, Sun ZY, Zhang GJ. Integrated FET sensing microsystem for specific detection of pancreatic cancer exosomal miRNA10b. Anal Chim Acta 2023; 1284:341995. [PMID: 37996166 DOI: 10.1016/j.aca.2023.341995] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 10/29/2023] [Accepted: 11/01/2023] [Indexed: 11/25/2023]
Abstract
Tumor-derived exosome (TD-Ex) serves as a crucial early diagnostic biomarker of pancreatic cancer (PC). However, accurate identification of TD-Ex from PC is still a challenging work. In this paper, a detection microsystem that integrates magnetic separation and FET biosensor is developed, which is capable of selectively separating TD-Ex of PC from the plasma and detecting exosomal miRNA10b in a sensitive and specific manner. The magnetic beads were functionalized with dual antibody (GPC-1 antibody and EpCAM antibody), enabling selective recognition and capture of PC-derived exosomes. On the other hand, a peptide nucleic acid (PNA)- functionalized reduced graphene oxide field-effect transistor (RGO FET) biosensor was subsequently utilized to detect the exosomal miRNA10b, which is highly expressed in PC- derived exosomes. This system could achieve a low detection limit down to 78 fM, and selectively identify miRNA10b from single-base mismatched miRNA. In addition, 40 clinical plasma samples were tested with this microsystem, and the results indicate that it could effectively distinguish PC patients from healthy individuals. The assay combines specific capture and enrichment of PC-derived exosomes with sensitive and selective detection of exosomal miRNA, showing its potential to be used as an effective scheme for PC early diagnosis.
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Affiliation(s)
- Yi Yu
- School of Laboratory Medicine, Hubei University of Chinese Medicine, 16 Huangjia Lake West Road, Wuhan, 430065, China
| | - Chunzi Liang
- School of Laboratory Medicine, Hubei University of Chinese Medicine, 16 Huangjia Lake West Road, Wuhan, 430065, China
| | | | - Dan Jin
- School of Laboratory Medicine, Hubei University of Chinese Medicine, 16 Huangjia Lake West Road, Wuhan, 430065, China
| | - Xi Liu
- School of Laboratory Medicine, Hubei University of Chinese Medicine, 16 Huangjia Lake West Road, Wuhan, 430065, China
| | - Zhiyong Zhang
- Key Laboratory for the Physics and Chemistry of Nanodevices and Center for Carbon-based Electronics, Department of Electronics, Peking University, Beijing, 100871, China.
| | - Zhong-Yue Sun
- School of Laboratory Medicine, Hubei University of Chinese Medicine, 16 Huangjia Lake West Road, Wuhan, 430065, China.
| | - Guo-Jun Zhang
- School of Laboratory Medicine, Hubei University of Chinese Medicine, 16 Huangjia Lake West Road, Wuhan, 430065, China.
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5
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Szymoński K, Skirlińska-Nosek K, Lipiec E, Sofińska K, Czaja M, Wilkosz N, Krupa M, Wanat F, Ulatowska-Białas M, Adamek D. Combined analytical approach empowers precise spectroscopic interpretation of subcellular components of pancreatic cancer cells. Anal Bioanal Chem 2023; 415:7281-7295. [PMID: 37906289 PMCID: PMC10684650 DOI: 10.1007/s00216-023-04997-w] [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: 09/04/2023] [Revised: 09/27/2023] [Accepted: 10/09/2023] [Indexed: 11/02/2023]
Abstract
The lack of specific and sensitive early diagnostic options for pancreatic cancer (PC) results in patients being largely diagnosed with late-stage disease, thus inoperable and burdened with high mortality. Molecular spectroscopic methodologies, such as Raman or infrared spectroscopies, show promise in becoming a leader in screening for early-stage cancer diseases, including PC. However, should such technology be introduced, the identification of differentiating spectral features between various cancer types is required. This would not be possible without the precise extraction of spectra without the contamination by necrosis, inflammation, desmoplasia, or extracellular fluids such as mucous that surround tumor cells. Moreover, an efficient methodology for their interpretation has not been well defined. In this study, we compared different methods of spectral analysis to find the best for investigating the biomolecular composition of PC cells cytoplasm and nuclei separately. Sixteen PC tissue samples of main PC subtypes (ductal adenocarcinoma, intraductal papillary mucinous carcinoma, and ampulla of Vater carcinoma) were collected with Raman hyperspectral mapping, resulting in 191,355 Raman spectra and analyzed with comparative methodologies, specifically, hierarchical cluster analysis, non-negative matrix factorization, T-distributed stochastic neighbor embedding, principal components analysis (PCA), and convolutional neural networks (CNN). As a result, we propose an innovative approach to spectra classification by CNN, combined with PCA for molecular characterization. The CNN-based spectra classification achieved over 98% successful validation rate. Subsequent analyses of spectral features revealed differences among PC subtypes and between the cytoplasm and nuclei of their cells. Our study establishes an optimal methodology for cancer tissue spectral data classification and interpretation that allows precise and cognitive studies of cancer cells and their subcellular components, without mixing the results with cancer-surrounding tissue. As a proof of concept, we describe findings that add to the spectroscopic understanding of PC.
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Affiliation(s)
- Krzysztof Szymoński
- Department of Pathomorphology, Medical College, Jagiellonian University, Kraków, Poland.
- Department of Pathomorphology, University Hospital, Kraków, Poland.
| | - Katarzyna Skirlińska-Nosek
- Faculty of Physics, Astronomy and Applied Computer Science, M. Smoluchowski Institute of Physics, Jagiellonian University, Kraków, Poland
- Doctoral School of Exact and Natural Sciences, Jagiellonian University, Kraków, Poland
| | - Ewelina Lipiec
- Faculty of Physics, Astronomy and Applied Computer Science, M. Smoluchowski Institute of Physics, Jagiellonian University, Kraków, Poland
| | - Kamila Sofińska
- Faculty of Physics, Astronomy and Applied Computer Science, M. Smoluchowski Institute of Physics, Jagiellonian University, Kraków, Poland
| | - Michał Czaja
- Faculty of Physics, Astronomy and Applied Computer Science, M. Smoluchowski Institute of Physics, Jagiellonian University, Kraków, Poland
- Doctoral School of Exact and Natural Sciences, Jagiellonian University, Kraków, Poland
| | - Natalia Wilkosz
- Faculty of Physics, Astronomy and Applied Computer Science, M. Smoluchowski Institute of Physics, Jagiellonian University, Kraków, Poland
- AGH University of Krakow, Faculty of Physics and Applied Computer Science, Kraków, Poland
| | - Matylda Krupa
- Department of Pathomorphology, Medical College, Jagiellonian University, Kraków, Poland
| | - Filip Wanat
- Department of Pathomorphology, Medical College, Jagiellonian University, Kraków, Poland
| | - Magdalena Ulatowska-Białas
- Department of Pathomorphology, Medical College, Jagiellonian University, Kraków, Poland
- Department of Pathomorphology, University Hospital, Kraków, Poland
| | - Dariusz Adamek
- Department of Pathomorphology, Medical College, Jagiellonian University, Kraków, Poland
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6
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Xue Y, Zheng X, Wu G, Wang J. Rapid diagnosis of cervical cancer based on serum FTIR spectroscopy and support vector machines. Lasers Med Sci 2023; 38:276. [PMID: 38001244 DOI: 10.1007/s10103-023-03930-y] [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: 09/15/2023] [Accepted: 11/06/2023] [Indexed: 11/26/2023]
Abstract
Cervical cancer is one of the most common malignant tumors among female gynecological diseases. This paper aims to explore the feasibility of utilizing serum Fourier Transform Infrared (FTIR) spectroscopy, combined with machine learning and deep learning algorithms, to efficiently differentiate between healthy individuals, hysteromyoma patients, and cervical cancer patients. In this study, serum samples from 30 groups of hysteromyoma, 36 groups of cervical cancer, and 30 healthy groups were collected and FTIR spectra of each group were recorded. In addition, the raw datasets were averaged according to the number of scans to obtain an average dataset, and the raw datasets were spectrally enhanced to obtain an augmentation dataset, resulting in a total of three sets of data with sizes of 258, 96, and 1806, respectively. Then, the hyperparameters in the four kernel functions of the Support Vector Machine (SVM) model were optimized by grid search and leave-one-out (LOO) cross-validation. The resulting SVM models achieved recognition accuracies ranging from 85.0% to 100.0% on the test set. Furthermore, a one-dimensional convolutional neural network (1D-CNN) demonstrated a recognition accuracy of 75.0% to 90.0% on the test set. It can be concluded that the use of serum FTIR spectroscopy combined with the SVM algorithm for the diagnosis of cervical cancer has important medical significance.
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Affiliation(s)
- Yunfei Xue
- College of Software, Xinjiang University, 830046, Urumqi, China
| | - Xiangxiang Zheng
- Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems, School of Electrical Engineering and Automation, Tianjin University of Technology, 300384, Tianjin, China
| | - Guohua Wu
- School of Electronic Engineering, Beijing University of Posts and Telecommunicationsn, 100876, Beijing, China.
| | - Jing Wang
- State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Department of Gynecology, The First Affiliated Hospital of Xinjiang Medical University, 830054, Urumqi, China
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7
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Sala A, Cameron JM, Brennan PM, Crosbie EJ, Curran T, Gray E, Martin-Hirsch P, Palmer DS, Rehman IU, Rattray NJW, Baker MJ. Global serum profiling: an opportunity for earlier cancer detection. J Exp Clin Cancer Res 2023; 42:207. [PMID: 37580713 PMCID: PMC10426107 DOI: 10.1186/s13046-023-02786-y] [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: 06/03/2023] [Accepted: 07/30/2023] [Indexed: 08/16/2023] Open
Abstract
The advances in cancer research achieved in the last 50 years have been remarkable and have provided a deeper knowledge of this disease in many of its conceptual and biochemical aspects. From viewing a tumor as a 'simple' aggregate of mutant cells and focusing on detecting key cell changes leading to the tumorigenesis, the understanding of cancer has broadened to consider it as a complex organ interacting with its close and far surroundings through tumor and non-tumor cells, metabolic mechanisms, and immune processes. Metabolism and the immune system have been linked to tumorigenesis and malignancy progression along with cancer-specific genetic mutations. However, most technologies developed to overcome the barriers to earlier detection are focused solely on genetic information. The concept of cancer as a complex organ has led to research on other analytical techniques, with the quest of finding a more sensitive and cost-effective comprehensive approach. Furthermore, artificial intelligence has gained broader consensus in the oncology community as a powerful tool with the potential to revolutionize cancer diagnosis for physicians. We herein explore the relevance of the concept of cancer as a complex organ interacting with the bodily surroundings, and focus on promising emerging technologies seeking to diagnose cancer earlier, such as liquid biopsies. We highlight the importance of a comprehensive approach to encompass all the tumor and non-tumor derived information salient to earlier cancer detection.
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Affiliation(s)
| | | | - Paul M Brennan
- Translational Neurosurgery, Department of Clinical Neurosciences, Royal Infirmary of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Emma J Crosbie
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
- Division of Gynecology, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, M13 9WL, UK
| | - Tom Curran
- Children's Mercy Research Institute, Children's Mercy Kansas City, Kansas City, MO, 64108, USA
| | - Ewan Gray
- Independent Health Economics Consultant, Edinburgh, UK
| | - Pierre Martin-Hirsch
- Gynecological Oncology, Clinical Research Facility, Lancashire Teaching Hospitals, Preston, PR2 9HT, UK
| | - David S Palmer
- Dxcover Limited, Glasgow, G1 1XW, UK
- Department of Pure and Applied Chemistry, Thomas Graham Building, University of Strathclyde, Glasgow, G1 1XL, UK
| | - Ihtesham U Rehman
- School of Medicine, Faculty of Clinical and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK
| | - Nicholas J W Rattray
- Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS), University of Strathclyde, Glasgow, G4 0RE, UK
| | - Matthew J Baker
- Dxcover Limited, Glasgow, G1 1XW, UK.
- Department of Pure and Applied Chemistry, Thomas Graham Building, University of Strathclyde, Glasgow, G1 1XL, UK.
- School of Medicine, Faculty of Clinical and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK.
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Bures J, Kohoutova D, Skrha J, Bunganic B, Ngo O, Suchanek S, Skrha P, Zavoral M. Diabetes Mellitus in Pancreatic Cancer: A Distinct Approach to Older Subjects with New-Onset Diabetes Mellitus. Cancers (Basel) 2023; 15:3669. [PMID: 37509329 PMCID: PMC10377806 DOI: 10.3390/cancers15143669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Revised: 07/02/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023] Open
Abstract
BACKGROUND Pancreatic ductal adenocarcinoma (PDAC) is associated with a very poor prognosis, with near-identical incidence and mortality. According to the World Health Organization Globocan Database, the estimated number of new cases worldwide will rise by 70% between 2020 and 2040. There are no effective screening methods available so far, even for high-risk individuals. The prognosis of PDAC, even at its early stages, is still mostly unsatisfactory. Impaired glucose metabolism is present in about 3/4 of PDAC cases. METHODS Available literature on pancreatic cancer and diabetes mellitus was reviewed using a PubMed database. Data from a national oncology registry (on PDAC) and information from a registry of healthcare providers (on diabetes mellitus and a number of abdominal ultrasound investigations) were obtained. RESULTS New-onset diabetes mellitus in subjects older than 60 years should be an incentive for a prompt and detailed investigation to exclude PDAC. Type 2 diabetes mellitus, diabetes mellitus associated with chronic non-malignant diseases of the exocrine pancreas, and PDAC-associated type 3c diabetes mellitus are the most frequent types. Proper differentiation of particular types of new-onset diabetes mellitus is a starting point for a population-based program. An algorithm for subsequent steps of the workup was proposed. CONCLUSIONS The structured, well-differentiated, and elaborately designed approach to the elderly with a new onset of diabetes mellitus could improve the current situation in diagnostics and subsequent poor outcomes of therapy of PDAC.
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Affiliation(s)
- Jan Bures
- Institute of Gastrointestinal Oncology, Military University Hospital Prague, 169 02 Prague, Czech Republic
- Department of Medicine, First Faculty of Medicine, Charles University, Prague and Military University Hospital Prague, 169 02 Prague, Czech Republic
- Biomedical Research Centre, University Hospital Hradec Kralove, 500 03 Hradec Kralove, Czech Republic
| | - Darina Kohoutova
- Biomedical Research Centre, University Hospital Hradec Kralove, 500 03 Hradec Kralove, Czech Republic
- The Royal Marsden NHS Foundation Trust, London SW3 6JJ, UK
| | - Jan Skrha
- Third Department of Internal Medicine-Endocrinology and Metabolism, First Faculty of Medicine, Charles University, Prague and General University Hospital in Prague, 128 08 Prague, Czech Republic
| | - Bohus Bunganic
- Department of Medicine, First Faculty of Medicine, Charles University, Prague and Military University Hospital Prague, 169 02 Prague, Czech Republic
| | - Ondrej Ngo
- Institute of Health Information and Statistics of the Czech Republic, 128 01 Prague, Czech Republic
- Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, 602 00 Brno, Czech Republic
| | - Stepan Suchanek
- Institute of Gastrointestinal Oncology, Military University Hospital Prague, 169 02 Prague, Czech Republic
- Department of Medicine, First Faculty of Medicine, Charles University, Prague and Military University Hospital Prague, 169 02 Prague, Czech Republic
| | - Pavel Skrha
- Department of Medicine, Third Faculty of Medicine, Charles University, Prague and University Hospital Kralovske Vinohrady, 100 00 Prague, Czech Republic
| | - Miroslav Zavoral
- Institute of Gastrointestinal Oncology, Military University Hospital Prague, 169 02 Prague, Czech Republic
- Department of Medicine, First Faculty of Medicine, Charles University, Prague and Military University Hospital Prague, 169 02 Prague, Czech Republic
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9
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Variabilities in global DNA methylation and β-sheet richness establish spectroscopic landscapes among subtypes of pancreatic cancer. Eur J Nucl Med Mol Imaging 2023; 50:1792-1810. [PMID: 36757432 PMCID: PMC10119063 DOI: 10.1007/s00259-023-06121-7] [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: 09/27/2022] [Accepted: 01/21/2023] [Indexed: 02/10/2023]
Abstract
PURPOSE Knowledge about pancreatic cancer (PC) biology has been growing rapidly in recent decades. Nevertheless, the survival of PC patients has not greatly improved. The development of a novel methodology suitable for deep investigation of the nature of PC tumors is of great importance. Molecular imaging techniques, such as Fourier transform infrared (FTIR) spectroscopy and Raman hyperspectral mapping (RHM) combined with advanced multivariate data analysis, were useful in studying the biochemical composition of PC tissue. METHODS Here, we evaluated the potential of molecular imaging in differentiating three groups of PC tumors, which originate from different precursor lesions. Specifically, we comprehensively investigated adenocarcinomas (ACs): conventional ductal AC, intraductal papillary mucinous carcinoma, and ampulla of Vater AC. FTIR microspectroscopy and RHM maps of 24 PC tissue slides were obtained, and comprehensive advanced statistical analyses, such as hierarchical clustering and nonnegative matrix factorization, were performed on a total of 211,355 Raman spectra. Additionally, we employed deep learning technology for the same task of PC subtyping to enable automation. The so-called convolutional neural network (CNN) was trained to recognize spectra specific to each PC group and then employed to generate CNN-prediction-based tissue maps. To identify the DNA methylation spectral markers, we used differently methylated, isolated DNA and compared the observed spectral differences with the results obtained from cellular nuclei regions of PC tissues. RESULTS The results showed significant differences among cancer tissues of the studied PC groups. The main findings are the varying content of β-sheet-rich proteins within the PC cells and alterations in the relative DNA methylation level. Our CNN model efficiently differentiated PC groups with 94% accuracy. The usage of CNN in the classification task did not require Raman spectral data preprocessing and eliminated the need for extensive knowledge of statistical methodologies. CONCLUSIONS Molecular spectroscopy combined with CNN technology is a powerful tool for PC detection and subtyping. The molecular fingerprint of DNA methylation and β-sheet cytoplasmic proteins established by our results is different for the main PC groups and allowed the subtyping of pancreatic tumors, which can improve patient management and increase their survival. Our observations are of key importance in understanding the variability of PC and allow translation of the methodology into clinical practice by utilizing liquid biopsy testing.
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10
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Rutherford SH, Baker MJ, Hunt NT. 2D-IR spectroscopy of proteins in H 2O-A Perspective. J Chem Phys 2023; 158:030901. [PMID: 36681646 DOI: 10.1063/5.0129480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
The form of the amide I infrared absorption band provides a sensitive probe of the secondary structure and dynamics of proteins in the solution phase. However, the frequency coincidence of the amide I band with the bending vibrational mode of H2O has necessitated the widespread use of deuterated solvents. Recently, it has been demonstrated that ultrafast 2D-IR spectroscopy allows the detection of the protein amide I band in H2O-based fluids, meaning that IR methods can now be applied to study proteins in physiologically relevant solvents. In this perspective, we describe the basis of the 2D-IR method for observing the protein amide I band in H2O and show how this development has the potential to impact areas ranging from our fundamental appreciation of protein structural dynamics to new applications for 2D-IR spectroscopy in the analytical and biomedical sciences. In addition, we discuss how the spectral response of water, rather than being a hindrance, now provides a basis for new approaches to data pre-processing, standardization of 2D-IR data collection, and signal quantification. Ultimately, we visualize a direction of travel toward the creation of 2D-IR spectral libraries that can be linked to advanced computational methods for use in high-throughput protein screening and disease diagnosis.
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Affiliation(s)
- Samantha H Rutherford
- WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow G1 1RD, United Kingdom
| | - Matthew J Baker
- School of Medicine, Faculty of Clinical Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, United Kingdom
| | - Neil T Hunt
- Department of Chemistry and York Biomedical Research Institute, University of York, York YO10 5DD, United Kingdom
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Santos LLD, Silva ATF, Ferreira ICC, Souza AV, Justino AB, Santos DW, Goulart LR, Paiva CE, Espíndola FS, Maia YCP. A Lower Serum Antioxidant Capacity as a Distinctive Feature for Women with HER2+ Breast Cancer: A Preliminary Study. Cancers (Basel) 2022; 14:cancers14235973. [PMID: 36497455 PMCID: PMC9739610 DOI: 10.3390/cancers14235973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 11/23/2022] [Accepted: 11/29/2022] [Indexed: 12/11/2022] Open
Abstract
The overexpression of HER2 in breast cancer (BC) can contribute to redox imbalance, which is related to damage and structural modification in many biomolecules. To the best of our knowledge, this is the first study that has investigated the infrared spectrum wavenumbers obtained by ATR-FTIR and their relationship with the levels of redox status markers such as reduced glutathione, superoxide dismutase (SOD), catalase, Ferric Reducing Antioxidant Power (FRAP), and protein carbonyl among women with HER2+ BC, HER2- BC, and benign breast disease (BBD). The study was conducted with 25 women, 17 of whom were diagnosed with BC (6 HER2+ and 11 HER2-) and 8 with BBD. Our results indicate HER2+ BC cases could be distinguished from HER2- BC and BBD cases by their serum's antioxidant capacity [HER2+ BC vs. HER2- BC (AUC = 0.818; specificity = 81.82%; sensitivity = 66.67%); HER2+ BC vs. BBD (AUC = 0.875; specificity = 75%; sensitivity = 83.33%)]. The changes in biochemical terms that occur in serum as a result of the scarcity of antioxidants are related to a peculiar fingerprint in the infrared spectrum obtained by ATR-FTIR. In the serum of women with BBD, the SOD enzyme level is the highest, and this characteristic allowed us to distinguish them from HER2- BC. Finally, data regarding the serological antioxidant capacity of FRAP and the infrared spectrum by ATR-FTIR will allow us to assess biochemical changes that occur before clinical signs, indicating whether changes in therapy or interventions are necessary.
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Affiliation(s)
- Letícia L. D. Santos
- Laboratory of Nanobiotechnology Luiz Ricardo Goulart Filho, Institute of Biotechnology, Federal University of Uberlandia, Uberlandia 38402-022, Brazil
- Molecular Biology and Nutrition Research Group (BioNut), School of Medicine, Federal University of Uberlandia, Uberlandia 38405-320, Brazil
| | - Alinne T. F. Silva
- Laboratory of Nanobiotechnology Luiz Ricardo Goulart Filho, Institute of Biotechnology, Federal University of Uberlandia, Uberlandia 38402-022, Brazil
- Molecular Biology and Nutrition Research Group (BioNut), School of Medicine, Federal University of Uberlandia, Uberlandia 38405-320, Brazil
| | - Izabella C. C. Ferreira
- Laboratory of Nanobiotechnology Luiz Ricardo Goulart Filho, Institute of Biotechnology, Federal University of Uberlandia, Uberlandia 38402-022, Brazil
- Molecular Biology and Nutrition Research Group (BioNut), School of Medicine, Federal University of Uberlandia, Uberlandia 38405-320, Brazil
| | - Adriele V. Souza
- Laboratory of Biochemistry and Molecular Biology, Institute of Biotechnology, Federal University of Uberlandia, Uberlandia 38405-302, Brazil
| | - Allisson B. Justino
- Laboratory of Biochemistry and Molecular Biology, Institute of Biotechnology, Federal University of Uberlandia, Uberlandia 38405-302, Brazil
| | - Donizeti W. Santos
- Gynecologic Division, University Hospital, Federal University of Uberlandia, Uberlandia 38405-320, Brazil
| | - Luiz Ricardo Goulart
- Laboratory of Nanobiotechnology Luiz Ricardo Goulart Filho, Institute of Biotechnology, Federal University of Uberlandia, Uberlandia 38402-022, Brazil
| | - Carlos Eduardo Paiva
- Palliative Care and Quality of Life Research Group (GPQual), Learning and Research Institute, Barretos Cancer Hospital, Barretos 14784-400, Brazil
| | - Foued S. Espíndola
- Laboratory of Biochemistry and Molecular Biology, Institute of Biotechnology, Federal University of Uberlandia, Uberlandia 38405-302, Brazil
| | - Yara C. P. Maia
- Laboratory of Nanobiotechnology Luiz Ricardo Goulart Filho, Institute of Biotechnology, Federal University of Uberlandia, Uberlandia 38402-022, Brazil
- Molecular Biology and Nutrition Research Group (BioNut), School of Medicine, Federal University of Uberlandia, Uberlandia 38405-320, Brazil
- Correspondence:
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