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Discriminating Glioblastoma from Peritumoral Tissue by a Nanohole Array-Based Optical and Label-Free Biosensor

In glioblastoma (GBM) patients, maximal safe resection remains a challenge today due to its invasiveness and diffuse parenchymal infiltration. In this context, plasmonic biosensors could potentially help to discriminate tumor tissue from peritumoral parenchyma based on differences in their optical p...

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Autores principales: García-Milán, Víctor, Franco, Alfredo, Zvezdanova, Margarita Estreya, Marcos, Sara, Martin-Laez, Rubén, Moreno, Fernando, Velasquez, Carlos, Fernandez-Luna, José L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10296434/
https://www.ncbi.nlm.nih.gov/pubmed/37366956
http://dx.doi.org/10.3390/bios13060591
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author García-Milán, Víctor
Franco, Alfredo
Zvezdanova, Margarita Estreya
Marcos, Sara
Martin-Laez, Rubén
Moreno, Fernando
Velasquez, Carlos
Fernandez-Luna, José L.
author_facet García-Milán, Víctor
Franco, Alfredo
Zvezdanova, Margarita Estreya
Marcos, Sara
Martin-Laez, Rubén
Moreno, Fernando
Velasquez, Carlos
Fernandez-Luna, José L.
author_sort García-Milán, Víctor
collection PubMed
description In glioblastoma (GBM) patients, maximal safe resection remains a challenge today due to its invasiveness and diffuse parenchymal infiltration. In this context, plasmonic biosensors could potentially help to discriminate tumor tissue from peritumoral parenchyma based on differences in their optical properties. A nanostructured gold biosensor was used ex vivo to identify tumor tissue in a prospective series of 35 GBM patients who underwent surgical treatment. For each patient, two paired samples, tumor and peritumoral tissue, were extracted. Then, the imprint left by each sample on the surface of the biosensor was individually analyzed, obtaining the difference between their refractive indices. The tumor and non-tumor origins of each tissue were assessed by histopathological analysis. The refractive index (RI) values obtained by analyzing the imprint of the tissue were significantly lower (p = 0.0047) in the peritumoral samples (1.341, Interquartile Range (IQR) 1.339–1.349) compared with the tumor samples (1.350, IQR 1.344–1.363). The ROC (receiver operating characteristic) curve showed the capacity of the biosensor to discriminate between both tissues (area under the curve, 0.8779, p < 0.0001). The Youden index provided an optimal RI cut-off point of 0.003. The sensitivity and specificity of the biosensor were 81% and 80%, respectively. Overall, the plasmonic-based nanostructured biosensor is a label-free system with the potential to be used for real-time intraoperative discrimination between tumor and peritumoral tissue in patients with GBM.
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spelling pubmed-102964342023-06-28 Discriminating Glioblastoma from Peritumoral Tissue by a Nanohole Array-Based Optical and Label-Free Biosensor García-Milán, Víctor Franco, Alfredo Zvezdanova, Margarita Estreya Marcos, Sara Martin-Laez, Rubén Moreno, Fernando Velasquez, Carlos Fernandez-Luna, José L. Biosensors (Basel) Article In glioblastoma (GBM) patients, maximal safe resection remains a challenge today due to its invasiveness and diffuse parenchymal infiltration. In this context, plasmonic biosensors could potentially help to discriminate tumor tissue from peritumoral parenchyma based on differences in their optical properties. A nanostructured gold biosensor was used ex vivo to identify tumor tissue in a prospective series of 35 GBM patients who underwent surgical treatment. For each patient, two paired samples, tumor and peritumoral tissue, were extracted. Then, the imprint left by each sample on the surface of the biosensor was individually analyzed, obtaining the difference between their refractive indices. The tumor and non-tumor origins of each tissue were assessed by histopathological analysis. The refractive index (RI) values obtained by analyzing the imprint of the tissue were significantly lower (p = 0.0047) in the peritumoral samples (1.341, Interquartile Range (IQR) 1.339–1.349) compared with the tumor samples (1.350, IQR 1.344–1.363). The ROC (receiver operating characteristic) curve showed the capacity of the biosensor to discriminate between both tissues (area under the curve, 0.8779, p < 0.0001). The Youden index provided an optimal RI cut-off point of 0.003. The sensitivity and specificity of the biosensor were 81% and 80%, respectively. Overall, the plasmonic-based nanostructured biosensor is a label-free system with the potential to be used for real-time intraoperative discrimination between tumor and peritumoral tissue in patients with GBM. MDPI 2023-05-30 /pmc/articles/PMC10296434/ /pubmed/37366956 http://dx.doi.org/10.3390/bios13060591 Text en © 2023 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
García-Milán, Víctor
Franco, Alfredo
Zvezdanova, Margarita Estreya
Marcos, Sara
Martin-Laez, Rubén
Moreno, Fernando
Velasquez, Carlos
Fernandez-Luna, José L.
Discriminating Glioblastoma from Peritumoral Tissue by a Nanohole Array-Based Optical and Label-Free Biosensor
title Discriminating Glioblastoma from Peritumoral Tissue by a Nanohole Array-Based Optical and Label-Free Biosensor
title_full Discriminating Glioblastoma from Peritumoral Tissue by a Nanohole Array-Based Optical and Label-Free Biosensor
title_fullStr Discriminating Glioblastoma from Peritumoral Tissue by a Nanohole Array-Based Optical and Label-Free Biosensor
title_full_unstemmed Discriminating Glioblastoma from Peritumoral Tissue by a Nanohole Array-Based Optical and Label-Free Biosensor
title_short Discriminating Glioblastoma from Peritumoral Tissue by a Nanohole Array-Based Optical and Label-Free Biosensor
title_sort discriminating glioblastoma from peritumoral tissue by a nanohole array-based optical and label-free biosensor
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10296434/
https://www.ncbi.nlm.nih.gov/pubmed/37366956
http://dx.doi.org/10.3390/bios13060591
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