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Chen Z, Li Y, Zhu R, Zhou Z, Yan Z, Chen S, Zhang G. Early differential diagnosis of pancytopenia related diseases based on serum surface-enhanced Raman spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 316:124335. [PMID: 38663130 DOI: 10.1016/j.saa.2024.124335] [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: 01/25/2024] [Revised: 04/17/2024] [Accepted: 04/22/2024] [Indexed: 05/15/2024]
Abstract
Pancytopenia is a common blood disorder defined as the decrease of red blood cells, white blood cells and platelets in the peripheral blood. Its genesis mechanism is typically complex and a variety of diseases have been found to be capable of causing pancytopenia, some of which are featured by their high mortality rates. Early judgement on the cause of pancytopenia can benefit timely and appropriate treatment to improve patient survival significantly. In this study, a serum surface-enhanced Raman spectroscopy (SERS) method was explored for the early differential diagnosis of three pancytopenia related diseases, i.e., aplastic anemia (AA), myelodysplastic syndrome (MDS) and spontaneous remission of pancytopenia (SRP), in which the patients with those pancytopenia related diseases at initial stage exhibited same pancytopenia symptom but cannot be conclusively diagnosed through conventional clinical examinations. The SERS spectral analysis results suggested that certain amino acids, protein substances and nucleic acids are expected to be potential biomarkers for their early differential diagnosis. In addition, a diagnostic model was established based on the joint use of partial least squares analysis and linear discriminant analysis (PLS-LDA), and an overall accuracy of 86.67 % was achieved to differentiate those pancytopenia related diseases, even at the time that confirmed diagnosis cannot be made by routine clinical examinations. Therefore, the proposed method has demonstrated great potential for the early differential diagnosis of pancytopenia related diseases, thus it has significant clinical importance for the timely and rational guidance on subsequent treatment to improve patient survival.
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Affiliation(s)
- Zhilin Chen
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, Liaoning, China
| | - Yang Li
- Department of Hematology, Shengjing Hospital of China Medical University, Shenyang 110022, China
| | - Ruochen Zhu
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, Liaoning, China
| | - Zheng Zhou
- School of Innovation and Entrepreneurship, Liaoning Institute of Science and Technology, Benxi 117004, China
| | - Zejun Yan
- Department of Urology, The First Affiliated Hospital of Ningbo University, Ningbo 315010, China
| | - Shuo Chen
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, Liaoning, China; Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China; Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Shenyang 110169, China.
| | - Guojun Zhang
- Department of Hematology, Shengjing Hospital of China Medical University, Shenyang 110022, China.
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Wang Y, Wang Y, Chen X, Zhu M, Xu Y, Wu Y, Gao S, Zhang M, Su L, Han W, Chi M. Label-Free Identification of AML1-ETO Positive Acute Myeloid Leukemia Using Single-Cell Raman Spectroscopy. APPLIED SPECTROSCOPY 2024; 78:863-873. [PMID: 38772561 DOI: 10.1177/00037028241254403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2024]
Abstract
Acute myeloid leukemia (AML) is a malignant hematological tumor disease. Chromosomal abnormality is an independent prognostic factor in AML. AML with t(8:21) (q22; q22)/AML1-ETO (AE) is an independent disease group. In this research, a new method based on Raman spectroscopy is reported for label-free single-cell identification and analysis of AE fusion genes in clinical AML patients. Raman spectroscopy reflects the intrinsic vibration information of molecules in a label-free and non-destructive manner, and the fingerprint Raman spectrum of cells characterizes intracellular molecular types and relative concentration information, so as to realize the identification and molecular metabolism analysis of different kinds of cells. We collected the Raman spectra of bone marrow cells from clinically diagnosed AML M2 patients with and without the AE fusion gene. Through comparison of the average spectra and identification analysis based on multivariate statistical methods such as principal component analysis and linear discriminant analysis, the distinction between AE positive and negative sample cells in M2 AML patients was successfully achieved, and the single-cell identification accuracy was more than 90%. At the same time, the Raman spectra of the two types of cells were analyzed by the multivariate curve resolution alternating least squares decomposition method. It was found that the presence of the AE fusion gene may lead to the metabolic changes of lipid and nucleic acid in AML cells, which was consistent with the results of genomic and metabolomic multi-omics studies. The above results indicate that single-cell Raman spectroscopy has the potential for early identification of AE-positive AML.
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Affiliation(s)
- Yang Wang
- Changchun Sci-Tech University, Shuangyang, Jilin Province, China
| | - Yimeng Wang
- National Science Library (Chengdu), Chinese Academy of Sciences, Chengdu, China
| | - Xing Chen
- Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin, China
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Applied Optics, Changchun, Jilin, China
- Key Laboratory of Optical System Advanced Manufacturing Technology, Chinese Academy of Sciences, Changchun, Jilin, China
| | - Mingyao Zhu
- Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin, China
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Applied Optics, Changchun, Jilin, China
- Key Laboratory of Optical System Advanced Manufacturing Technology, Chinese Academy of Sciences, Changchun, Jilin, China
| | - Yang Xu
- Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin, China
| | - Yihui Wu
- Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin, China
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Applied Optics, Changchun, Jilin, China
- Key Laboratory of Optical System Advanced Manufacturing Technology, Chinese Academy of Sciences, Changchun, Jilin, China
| | - Sujun Gao
- Department of Hematology, The First Bethune Hospital, Jilin University, Changchun, China
| | - Ming Zhang
- Department of Hematology, The First Bethune Hospital, Jilin University, Changchun, China
| | - Long Su
- Department of Hematology, The First Bethune Hospital, Jilin University, Changchun, China
| | - Wei Han
- Department of Hematology, The First Bethune Hospital, Jilin University, Changchun, China
| | - Mingbo Chi
- Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin, China
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Applied Optics, Changchun, Jilin, China
- Key Laboratory of Optical System Advanced Manufacturing Technology, Chinese Academy of Sciences, Changchun, Jilin, China
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Zhang J, Weng Y, Liu Y, Wang N, Feng S, Qiu S, Lin D. Molecular separation-assisted label-free SERS combined with machine learning for nasopharyngeal cancer screening and radiotherapy resistance prediction. JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY. B, BIOLOGY 2024; 257:112968. [PMID: 38955080 DOI: 10.1016/j.jphotobiol.2024.112968] [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: 11/24/2023] [Revised: 04/30/2024] [Accepted: 06/25/2024] [Indexed: 07/04/2024]
Abstract
Nasopharyngeal cancer (NPC) is a malignant tumor with high prevalence in Southeast Asia and highly invasive and metastatic characteristics. Radiotherapy is the primary strategy for NPC treatment, however there is still lack of effect method for predicting the radioresistance that is the main reason for treatment failure. Herein, the molecular profiles of patient plasma from NPC with radiotherapy sensitivity and resistance groups as well as healthy group, respectively, were explored by label-free surface enhanced Raman spectroscopy (SERS) based on surface plasmon resonance for the first time. Especially, the components with different molecular weight sizes were analyzed via the separation process, helping to avoid the possible missing of diagnostic information due to the competitive adsorption. Following that, robust machine learning algorithm based on principal component analysis and linear discriminant analysis (PCA-LDA) was employed to extract the feature of blood-SERS data and establish an effective predictive model with the accuracy of 96.7% for identifying the radiotherapy resistance subjects from sensitivity ones, and 100% for identifying the NPC subjects from healthy ones. This work demonstrates the potential of molecular separation-assisted label-free SERS combined with machine learning for NPC screening and treatment strategy guidance in clinical scenario.
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Affiliation(s)
- Jun Zhang
- Key Laboratory of OptoElectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou 350117, PR China
| | - Youliang Weng
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fujian Branch of Fudan University Shanghai Cancer Center, Fuzhou 350014, PR China
| | - Yi Liu
- Key Laboratory of OptoElectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou 350117, PR China
| | - Nan Wang
- Key Laboratory of OptoElectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou 350117, PR China
| | - Shangyuan Feng
- Key Laboratory of OptoElectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou 350117, PR China
| | - Sufang Qiu
- Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fujian Branch of Fudan University Shanghai Cancer Center, Fuzhou 350014, PR China.
| | - Duo Lin
- Key Laboratory of OptoElectronic Science and Technology for Medicine, Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou 350117, PR China.
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Li S, Gao S, Su L, Zhang M. Evaluating the accuracy of Raman spectroscopy in differentiating leukemia patients from healthy individuals: A systematic review and meta-analysis. Photodiagnosis Photodyn Ther 2024; 48:104260. [PMID: 38950876 DOI: 10.1016/j.pdpdt.2024.104260] [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: 04/21/2024] [Revised: 05/26/2024] [Accepted: 06/26/2024] [Indexed: 07/03/2024]
Abstract
PURPOSE To assess the accuracy of Raman spectroscopy in distinguishing between patients with leukemia and healthy individuals. METHOD PubMed, Embase, Web of Science, Cochrane Library, and CNKI databases were searched for relevant articles published from inception of the respective database to November 1, 2023. The pooled sensitivity (SEN), specificity (SPE), diagnostic odds ratio (DOR), positive likelihood ratio (PLR), negative likelihood ratio (NLR), were calculated along with their corresponding 95 % confidence intervals (CI). A summary comprehensive receiver operating characteristic curve (SROC) was constructed and the area under the curve (AUC) was calculated. The degree of heterogeneity was tested and analyzed. RESULTS Fifteen groups of original studies from 13 articles were included. The pooled SEN and SPE were 0.93 (95 % CI, [0.92 -0.93]) and 0.91(95 % CI, [0.90-0.92]), respectively. The DOR was 613.01 (95 %CI, [270.79-1387.75]), and the AUC was 0.99. The Deeks' funnel plot asymmetry test indicated no significant publication bias among the included studies (bias coefficient, 40.80; P = 0.13 < 0.10). The meta-regression analysis findings indicated that the observed heterogeneity could be attributed to variations in sample categories and Raman spectroscopy techniques. CONCLUSION We confirmed that Raman spectroscopy has good accuracy in differentiating patients with leukemia from healthy individuals, and may become a means of leukemia screening in clinical practice. In the case of analysis based on live cells using surface-enhanced Raman spectroscopy (SERS) improved diagnostic efficacy was observed.
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Affiliation(s)
- Shaotong Li
- Department of Hematology, The First Hospital of Jilin University, Changchun 130021, PR China
| | - Sujun Gao
- Department of Hematology, The First Hospital of Jilin University, Changchun 130021, PR China.
| | - Long Su
- Department of Hematology, The First Hospital of Jilin University, Changchun 130021, PR China
| | - Ming Zhang
- Department of Hematology, The First Hospital of Jilin University, Changchun 130021, PR China
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5
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Wu X, Wang F, Yang X, Gong Y, Niu T, Chu B, Qu Y, Qian Z. Advances in Drug Delivery Systems for the Treatment of Acute Myeloid Leukemia. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024:e2403409. [PMID: 38934349 DOI: 10.1002/smll.202403409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Revised: 06/06/2024] [Indexed: 06/28/2024]
Abstract
Acute myeloid leukemia (AML) is a common and catastrophic hematological neoplasm with high mortality rates. Conventional therapies, including chemotherapy, hematopoietic stem cell transplantation (HSCT), immune therapy, and targeted agents, have unsatisfactory outcomes for AML patients due to drug toxicity, off-target effects, drug resistance, drug side effects, and AML relapse and refractoriness. These intrinsic limitations of current treatments have promoted the development and application of nanomedicine for more effective and safer leukemia therapy. In this review, the classification of nanoparticles applied in AML therapy, including liposomes, polymersomes, micelles, dendrimers, and inorganic nanoparticles, is reviewed. In addition, various strategies for enhancing therapeutic targetability in nanomedicine, including the use of conjugating ligands, biomimetic-nanotechnology, and bone marrow targeting, which indicates the potential to reverse drug resistance, are discussed. The application of nanomedicine for assisting immunotherapy is also involved. Finally, the advantages and possible challenges of nanomedicine for the transition from the preclinical phase to the clinical phase are discussed.
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Affiliation(s)
- Xia Wu
- Department of Hematology and Institute of Hematology, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P. R. China
| | - Fangfang Wang
- Department of Hematology and Institute of Hematology, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P. R. China
| | - Xijing Yang
- The Experimental Animal Center of West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P. R. China
| | - Yuping Gong
- Department of Hematology and Institute of Hematology, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P. R. China
| | - Ting Niu
- Department of Hematology and Institute of Hematology, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P. R. China
| | - Bingyang Chu
- Department of Hematology and Institute of Hematology, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P. R. China
| | - Ying Qu
- Department of Hematology and Institute of Hematology, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P. R. China
| | - Zhiyong Qian
- Department of Hematology and Institute of Hematology, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, P. R. China
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6
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Yang Y, Gao X, Zhang H, Chao F, Jiang H, Huang J, Lin J. Multi-scale representation of surface-enhanced Raman spectroscopy data for deep learning-based liver cancer detection. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 308:123764. [PMID: 38134653 DOI: 10.1016/j.saa.2023.123764] [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: 10/11/2023] [Revised: 12/04/2023] [Accepted: 12/10/2023] [Indexed: 12/24/2023]
Abstract
The early detection of liver cancer greatly improves survival rates and allows for less invasive treatment options. As a non-invasive optical detection technique, Surface-Enhanced Raman Spectroscopy (SERS) has shown significant potential in early cancer detection, providing multiple advantages over conventional methods. The majority of existing cancer detection methods utilize multivariate statistical analysis to categorize SERS data. However, these methods are plagued by issues such as information loss during dimensionality reduction and inadequate ability to handle nonlinear relationships within the data. To overcome these problems, we first use wavelet transform with its multi-scale analysis capability to extract multi-scale features from SERS data while minimizing information loss compared to traditional methods. Moreover, deep learning is employed for classification, leveraging its strong nonlinear processing capability to enhance accuracy. In addition, the chosen neural network incorporates a data augmentation method, thereby enriching our training dataset and mitigating the risk of overfitting. Moreover, we acknowledge the significance of selecting the appropriate wavelet basis functions in SERS data processing, prompting us to choose six specific ones for comparison. We employ SERS data from serum samples obtained from both liver cancer patients and healthy volunteers to train and test our classification model, enabling us to assess its performance. Our experimental results demonstrate that our method achieved outstanding and healthy volunteers to train and test our classification model, enabling us to assess its performance. Our experimental results demonstrate that our method achieved outstanding performance, surpassing the majority of multivariate statistical analysis and traditional machine learning classification methods, with an accuracy of 99.38 %, a sensitivity of 99.8 %, and a specificity of 97.0 %. These results indicate that the combination of SERS, wavelet transform, and deep learning has the potential to function as a non-invasive tool for the rapid detection of liver cancer.
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Affiliation(s)
- Yang Yang
- School of Opto-Electronic and Communication Engineering, Xiamen University of Technology, Xiamen, China
| | - Xingen Gao
- School of Opto-Electronic and Communication Engineering, Xiamen University of Technology, Xiamen, China
| | - Hongyi Zhang
- School of Opto-Electronic and Communication Engineering, Xiamen University of Technology, Xiamen, China.
| | - Fei Chao
- Department of Artificial Intelligence, School of Informatics, Xiamen University, Xiamen, China
| | - Huali Jiang
- School of Opto-Electronic and Communication Engineering, Xiamen University of Technology, Xiamen, China
| | - Junqi Huang
- School of Opto-Electronic and Communication Engineering, Xiamen University of Technology, Xiamen, China
| | - Juqiang Lin
- School of Opto-Electronic and Communication Engineering, Xiamen University of Technology, Xiamen, China.
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7
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Janani G, Girigoswami A, Girigoswami K. Advantages of nanomedicine over the conventional treatment in Acute myeloid leukemia. JOURNAL OF BIOMATERIALS SCIENCE. POLYMER EDITION 2024; 35:415-441. [PMID: 38113194 DOI: 10.1080/09205063.2023.2294541] [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: 10/07/2023] [Accepted: 12/08/2023] [Indexed: 12/21/2023]
Abstract
Leukemia is a cancer of blood cells that mainly affects the white blood cells. In acute myeloid leukemia (AML) sudden growth of cancerous cells occurs in blood and bone marrow, and it disrupts normal blood cell production. Most patients are asymptomatic, but it spreads rapidly and can become fatal if left untreated. AML is the prevalent form of leukemia in children. Risk factors of AML include chemical exposure, radiation, genetics, etc. Conventional diagnostic methods of AML are complete blood count tests and bone marrow aspiration, while conventional treatment methods involve chemotherapy, radiation therapy, and bone marrow transplant. There is a risk of cancer cells spreading progressively to the other organs if left untreated, and hence, early diagnosis is required. The conventional diagnostic methods are time- consuming and have drawbacks like harmful side effects and recurrence of the disease. To overcome these difficulties, nanoparticles are employed in treating and diagnosing AML. These nanoparticles can be surface- modified and can be used against cancer cells. Due to their enhanced permeability effect and high surface-to-volume ratio they will be able to reach the tumour site which cannot be reached by traditional drugs. This review article talks about how nanotechnology is more advantageous over the traditional methods in the treatment and diagnosis of AML.
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Affiliation(s)
- Gopalarethinam Janani
- Medical Bionanotechnology, Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Chennai, Tamil Nadu, India
| | - Agnishwar Girigoswami
- Medical Bionanotechnology, Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Chennai, Tamil Nadu, India
| | - Koyeli Girigoswami
- Medical Bionanotechnology, Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Chennai, Tamil Nadu, India
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8
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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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Teixeira A, Carreira L, Abalde-Cela S, Sampaio-Marques B, Areias AC, Ludovico P, Diéguez L. Current and Emerging Techniques for Diagnosis and MRD Detection in AML: A Comprehensive Narrative Review. Cancers (Basel) 2023; 15:cancers15051362. [PMID: 36900154 PMCID: PMC10000116 DOI: 10.3390/cancers15051362] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 02/06/2023] [Accepted: 02/17/2023] [Indexed: 02/24/2023] Open
Abstract
Acute myeloid leukemia (AML) comprises a group of hematologic neoplasms characterized by abnormal differentiation and proliferation of myeloid progenitor cells. AML is associated with poor outcome due to the lack of efficient therapies and early diagnostic tools. The current gold standard diagnostic tools are based on bone marrow biopsy. These biopsies, apart from being very invasive, painful, and costly, have low sensitivity. Despite the progress uncovering the molecular pathogenesis of AML, the development of novel detection strategies is still poorly explored. This is particularly important for patients that check the criteria for complete remission after treatment, since they can relapse through the persistence of some leukemic stem cells. This condition, recently named as measurable residual disease (MRD), has severe consequences for disease progression. Hence, an early and accurate diagnosis of MRD would allow an appropriate therapy to be tailored, improving a patient's prognosis. Many novel techniques with high potential in disease prevention and early detection are being explored. Among them, microfluidics has flourished in recent years due to its ability at processing complex samples as well as its demonstrated capacity to isolate rare cells from biological fluids. In parallel, surface-enhanced Raman scattering (SERS) spectroscopy has shown outstanding sensitivity and capability for multiplex quantitative detection of disease biomarkers. Together, these technologies can allow early and cost-effective disease detection as well as contribute to monitoring the efficiency of treatments. In this review, we aim to provide a comprehensive overview of AML disease, the conventional techniques currently used for its diagnosis, classification (recently updated in September 2022), and treatment selection, and we also aim to present how novel technologies can be applied to improve the detection and monitoring of MRD.
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Affiliation(s)
- Alexandra Teixeira
- International Iberian Nanotechnology Laboratory (INL), Avda Mestre José Veiga, 4715-310 Braga, Portugal
- Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, 4710-057 Braga, Portugal
- ICVS/3B’s–PT Government Associate Laboratory, 4710-057 Braga, Portugal
| | - Luís Carreira
- International Iberian Nanotechnology Laboratory (INL), Avda Mestre José Veiga, 4715-310 Braga, Portugal
| | - Sara Abalde-Cela
- International Iberian Nanotechnology Laboratory (INL), Avda Mestre José Veiga, 4715-310 Braga, Portugal
| | - Belém Sampaio-Marques
- Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, 4710-057 Braga, Portugal
- ICVS/3B’s–PT Government Associate Laboratory, 4710-057 Braga, Portugal
| | - Anabela C. Areias
- Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, 4710-057 Braga, Portugal
- ICVS/3B’s–PT Government Associate Laboratory, 4710-057 Braga, Portugal
| | - Paula Ludovico
- Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, 4710-057 Braga, Portugal
- ICVS/3B’s–PT Government Associate Laboratory, 4710-057 Braga, Portugal
- Correspondence: (P.L.); (L.D.)
| | - Lorena Diéguez
- International Iberian Nanotechnology Laboratory (INL), Avda Mestre José Veiga, 4715-310 Braga, Portugal
- Correspondence: (P.L.); (L.D.)
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10
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Li C, Feng C, Xu R, Jiang B, Li L, He Y, Tu C, Li Z. The emerging applications and advancements of Raman spectroscopy in pediatric cancers. Front Oncol 2023; 13:1044177. [PMID: 36814817 PMCID: PMC9939836 DOI: 10.3389/fonc.2023.1044177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 01/18/2023] [Indexed: 02/09/2023] Open
Abstract
Although the survival rate of pediatric cancer has significantly improved, it is still an important cause of death among children. New technologies have been developed to improve the diagnosis, treatment, and prognosis of pediatric cancers. Raman spectroscopy (RS) is a non-destructive analytical technique that uses different frequencies of scattering light to characterize biological specimens. It can provide information on biological components, activities, and molecular structures. This review summarizes studies on the potential of RS in pediatric cancers. Currently, studies on the application of RS in pediatric cancers mainly focus on early diagnosis, prognosis prediction, and treatment improvement. The results of these studies showed high accuracy and specificity. In addition, the combination of RS and deep learning is discussed as a future application of RS in pediatric cancer. Studies applying RS in pediatric cancer illustrated good prospects. This review collected and analyzed the potential clinical applications of RS in pediatric cancers.
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Affiliation(s)
- Chenbei Li
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Central South University, Changsha, China
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Chengyao Feng
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Central South University, Changsha, China
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Ruiling Xu
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Central South University, Changsha, China
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Buchan Jiang
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Central South University, Changsha, China
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Lan Li
- Department of Pathology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yu He
- Department of Radiology, Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Chao Tu
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Central South University, Changsha, China
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Zhihong Li
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Central South University, Changsha, China
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
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11
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Abstract
In the last decade, there has been a rapid increase in the number of surface-enhanced Raman scattering (SERS) spectroscopy applications in medical research. In this article we review some recent, and in our opinion, most interesting and promising applications of SERS spectroscopy in medical diagnostics, including those that permit multiplexing within the range important for clinical samples. We focus on the SERS-based detection of markers of various diseases (or those whose presence significantly increases the chance of developing a given disease), and on drug monitoring. We present selected examples of the SERS detection of particular fragments of DNA or RNA, or of bacteria, viruses, and disease-related proteins. We also describe a very promising and elegant ‘lab-on-chip’ approach used to carry out practical SERS measurements via a pad whose action is similar to that of a pregnancy test. The fundamental theoretical background of SERS spectroscopy, which should allow a better understanding of the operation of the sensors described, is also briefly outlined. We hope that this review article will be useful for researchers planning to enter this fascinating field.
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