دورية أكاديمية
Low-abundance proteins-based label-free SERS approach for high precision detection of liver cancer with different stages.
| العنوان: | Low-abundance proteins-based label-free SERS approach for high precision detection of liver cancer with different stages. |
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| المؤلفون: | Sun T; School of Opto-electronic and Communication Engineering, Xiamen University of Technology, Xiamen, Fujian, 361024, China., Lin Y; MOE Key Laboratory of Opto Electronic Science and Technology for Medicine and Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou, Fujian, 350007, China., Yu Y; College of Integrative Medicine, Laboratory of Pathophysiology, Key Laboratory of Integrative Medicine on Chronic Diseases (Fujian Province University), Synthesized Laboratory of Integrative Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China. Electronic address: yuyunsatan@163.com., Gao S; Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and the Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China., Gao X; School of Opto-electronic and Communication Engineering, Xiamen University of Technology, Xiamen, Fujian, 361024, China., Zhang H; School of Opto-electronic and Communication Engineering, Xiamen University of Technology, Xiamen, Fujian, 361024, China., Lin K; Department of Hepatobiliary Surgery, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, China., Lin J; School of Opto-electronic and Communication Engineering, Xiamen University of Technology, Xiamen, Fujian, 361024, China. Electronic address: jqlin@t.xmut.edu.cn. |
| المصدر: | Analytica chimica acta [Anal Chim Acta] 2024 May 22; Vol. 1304, pp. 342518. Date of Electronic Publication: 2024 Mar 21. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0370534 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-4324 (Electronic) Linking ISSN: 00032670 NLM ISO Abbreviation: Anal Chim Acta Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: Amsterdam : Elsevier Original Publication: Amsterdam. |
| مواضيع طبية MeSH: | Blood Proteins* , Liver Neoplasms*/diagnosis, Humans ; Discriminant Analysis ; Biomarkers ; Spectrum Analysis, Raman/methods ; Principal Component Analysis |
| مستخلص: | Background: Surface-enhanced Raman scattering (SERS) technology have unique advantages of rapid, simple, and highly sensitive in the detection of serum, it can be used for the detection of liver cancer. However, some protein biomarkers in body fluids are often present at ultra-low concentrations and severely interfered with by the high-abundance proteins (HAPs), which will affect the detection of specificity and accuracy in cancer screening based on the SERS immunoassay. Clearly, there is a need for an unlabeled SERS method based on low abundance proteins, which is rapid, noninvasive, and capable of high precision detection and screening of liver cancer. Results: Serum samples were collected from 60 patients with liver cancer (27 patients with stage T1 and T2 liver cancer, 33 patients with stage T3 and T4 liver cancer) and 40 healthy volunteers. Herein, immunoglobulin and albumin were separated by immune sorption and Cohn ethanol fractionation. Then, the low abundance protein (LAPs) was enriched, and high-quality SERS spectral signals were detected and obtained. Finally, combined with the principal component analysis-linear discriminant analysis (PCA-LDA) algorithm, the SERS spectrum of early liver cancer (T1-T2) and advanced liver cancer (T3-T4) could be well distinguished from normal people, and the accuracy rate was 98.5% and 100%, respectively. Moreover, SERS technology based on serum LAPs extraction combined with the partial least square-support vector machine (PLS-SVM) successfully realized the classification and prediction of normal volunteers and liver cancer patients with different tumor (T) stages, and the diagnostic accuracy of PLS-SVM reached 87.5% in the unknown testing set. Significance: The experimental results show that the serum LAPs SERS detection combined with multivariate statistical algorithms can be used for effectively distinguishing liver cancer patients from healthy volunteers, and even achieved the screening of early liver cancer with high accuracy (T1 and T2 stage). These results showed that serum LAPs SERS detection combined with a multivariate statistical diagnostic algorithm has certain application potential in early cancer screening. Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (Copyright © 2024 Elsevier B.V. All rights reserved.) |
| فهرسة مساهمة: | Keywords: Liver cancer; Low-abundance proteins; Serum; Surface-enhanced Raman spectroscopy |
| المشرفين على المادة: | 0 (Biomarkers) 0 (Blood Proteins) |
| تواريخ الأحداث: | Date Created: 20240418 Date Completed: 20240422 Latest Revision: 20240422 |
| رمز التحديث: | 20240422 |
| DOI: | 10.1016/j.aca.2024.342518 |
| PMID: | 38637045 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1873-4324 |
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| DOI: | 10.1016/j.aca.2024.342518 |