Cargando…
Label-Free Surface Enhanced Raman Spectroscopy for Cancer Detection
SIMPLE SUMMARY: Blood is considered a rich reservoir of biomarkers for disease diagnosis. Surface-enhanced Raman scattering (SERS) is known for its high sensitivity and has been successfully employed to differentiate blood samples from cancer patients versus healthy individuals. Different from previ...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9600112/ https://www.ncbi.nlm.nih.gov/pubmed/36291805 http://dx.doi.org/10.3390/cancers14205021 |
_version_ | 1784816760312037376 |
---|---|
author | Avci, Ertug Yilmaz, Hulya Sahiner, Nurettin Tuna, Bilge Guvenc Cicekdal, Munevver Burcu Eser, Mehmet Basak, Kayhan Altıntoprak, Fatih Zengin, Ismail Dogan, Soner Çulha, Mustafa |
author_facet | Avci, Ertug Yilmaz, Hulya Sahiner, Nurettin Tuna, Bilge Guvenc Cicekdal, Munevver Burcu Eser, Mehmet Basak, Kayhan Altıntoprak, Fatih Zengin, Ismail Dogan, Soner Çulha, Mustafa |
author_sort | Avci, Ertug |
collection | PubMed |
description | SIMPLE SUMMARY: Blood is considered a rich reservoir of biomarkers for disease diagnosis. Surface-enhanced Raman scattering (SERS) is known for its high sensitivity and has been successfully employed to differentiate blood samples from cancer patients versus healthy individuals. Different from previous reports, this study aims at investigating the reliability of the observed results by varying several parameters influencing the observed spectra. Thus, blood taken from 30 healthy individuals as the control group, 30 patients with different types of cancers, and 15 patients with various types of chronic diseases were used in the study. The results revealed that spectral differences in the cancer group was directly related to the presence of cancer-related biomarkers. Although data were obtained from only small group of patients, the recorded sensitivity and specificity values clearly show the power of the technique to detect cancer. ABSTRACT: Blood is a vital reservoir housing numerous disease-related metabolites and cellular components. Thus, it is also of interest for cancer diagnosis. Surface-enhanced Raman spectroscopy (SERS) is widely used for molecular detection due to its very high sensitivity and multiplexing properties. Its real potential for cancer diagnosis is not yet clear. In this study, using silver nanoparticles (AgNPs) as substrates, a number of experimental parameters and scenarios were tested to disclose the potential for this technique for cancer diagnosis. The discrimination of serum samples from cancer patients, healthy individuals and patients with chronic diseases was successfully demonstrated with over 90% diagnostic accuracies. Moreover, the SERS spectra of the blood serum samples obtained from cancer patients before and after tumor removal were compared. It was found that the spectral pattern for serum from cancer patients evolved into the spectral pattern observed with serum from healthy individuals after the removal of tumors. The data strongly suggests that the technique has a tremendous potential for cancer detection and screening bringing the possibility of early detection onto the table. |
format | Online Article Text |
id | pubmed-9600112 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96001122022-10-27 Label-Free Surface Enhanced Raman Spectroscopy for Cancer Detection Avci, Ertug Yilmaz, Hulya Sahiner, Nurettin Tuna, Bilge Guvenc Cicekdal, Munevver Burcu Eser, Mehmet Basak, Kayhan Altıntoprak, Fatih Zengin, Ismail Dogan, Soner Çulha, Mustafa Cancers (Basel) Article SIMPLE SUMMARY: Blood is considered a rich reservoir of biomarkers for disease diagnosis. Surface-enhanced Raman scattering (SERS) is known for its high sensitivity and has been successfully employed to differentiate blood samples from cancer patients versus healthy individuals. Different from previous reports, this study aims at investigating the reliability of the observed results by varying several parameters influencing the observed spectra. Thus, blood taken from 30 healthy individuals as the control group, 30 patients with different types of cancers, and 15 patients with various types of chronic diseases were used in the study. The results revealed that spectral differences in the cancer group was directly related to the presence of cancer-related biomarkers. Although data were obtained from only small group of patients, the recorded sensitivity and specificity values clearly show the power of the technique to detect cancer. ABSTRACT: Blood is a vital reservoir housing numerous disease-related metabolites and cellular components. Thus, it is also of interest for cancer diagnosis. Surface-enhanced Raman spectroscopy (SERS) is widely used for molecular detection due to its very high sensitivity and multiplexing properties. Its real potential for cancer diagnosis is not yet clear. In this study, using silver nanoparticles (AgNPs) as substrates, a number of experimental parameters and scenarios were tested to disclose the potential for this technique for cancer diagnosis. The discrimination of serum samples from cancer patients, healthy individuals and patients with chronic diseases was successfully demonstrated with over 90% diagnostic accuracies. Moreover, the SERS spectra of the blood serum samples obtained from cancer patients before and after tumor removal were compared. It was found that the spectral pattern for serum from cancer patients evolved into the spectral pattern observed with serum from healthy individuals after the removal of tumors. The data strongly suggests that the technique has a tremendous potential for cancer detection and screening bringing the possibility of early detection onto the table. MDPI 2022-10-14 /pmc/articles/PMC9600112/ /pubmed/36291805 http://dx.doi.org/10.3390/cancers14205021 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Avci, Ertug Yilmaz, Hulya Sahiner, Nurettin Tuna, Bilge Guvenc Cicekdal, Munevver Burcu Eser, Mehmet Basak, Kayhan Altıntoprak, Fatih Zengin, Ismail Dogan, Soner Çulha, Mustafa Label-Free Surface Enhanced Raman Spectroscopy for Cancer Detection |
title | Label-Free Surface Enhanced Raman Spectroscopy for Cancer Detection |
title_full | Label-Free Surface Enhanced Raman Spectroscopy for Cancer Detection |
title_fullStr | Label-Free Surface Enhanced Raman Spectroscopy for Cancer Detection |
title_full_unstemmed | Label-Free Surface Enhanced Raman Spectroscopy for Cancer Detection |
title_short | Label-Free Surface Enhanced Raman Spectroscopy for Cancer Detection |
title_sort | label-free surface enhanced raman spectroscopy for cancer detection |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9600112/ https://www.ncbi.nlm.nih.gov/pubmed/36291805 http://dx.doi.org/10.3390/cancers14205021 |
work_keys_str_mv | AT avciertug labelfreesurfaceenhancedramanspectroscopyforcancerdetection AT yilmazhulya labelfreesurfaceenhancedramanspectroscopyforcancerdetection AT sahinernurettin labelfreesurfaceenhancedramanspectroscopyforcancerdetection AT tunabilgeguvenc labelfreesurfaceenhancedramanspectroscopyforcancerdetection AT cicekdalmunevverburcu labelfreesurfaceenhancedramanspectroscopyforcancerdetection AT esermehmet labelfreesurfaceenhancedramanspectroscopyforcancerdetection AT basakkayhan labelfreesurfaceenhancedramanspectroscopyforcancerdetection AT altıntoprakfatih labelfreesurfaceenhancedramanspectroscopyforcancerdetection AT zenginismail labelfreesurfaceenhancedramanspectroscopyforcancerdetection AT dogansoner labelfreesurfaceenhancedramanspectroscopyforcancerdetection AT culhamustafa labelfreesurfaceenhancedramanspectroscopyforcancerdetection |