Cargando…

Image-Based Quantification of Benzoporphyrin Derivative Uptake, Localization, and Photobleaching in 3D Tumor Models, for Optimization of PDT Parameters

Photodynamic therapy (PDT) is a light-based treatment modality in which wavelength specific activation of a photosensitizer (PS) generates cytotoxic response in the irradiated region. PDT response is critically dependent on several parameters including light dose, PS dose, uptake time, fluence rate,...

Descripción completa

Detalles Bibliográficos
Autores principales: Glidden, Michael D., Celli, Jonathan P., Massodi, Iqbal, Rizvi, Imran, Pogue, Brian W., Hasan, Tayyaba
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3475211/
https://www.ncbi.nlm.nih.gov/pubmed/23082096
http://dx.doi.org/10.7150/thno.4334
_version_ 1782246918332612608
author Glidden, Michael D.
Celli, Jonathan P.
Massodi, Iqbal
Rizvi, Imran
Pogue, Brian W.
Hasan, Tayyaba
author_facet Glidden, Michael D.
Celli, Jonathan P.
Massodi, Iqbal
Rizvi, Imran
Pogue, Brian W.
Hasan, Tayyaba
author_sort Glidden, Michael D.
collection PubMed
description Photodynamic therapy (PDT) is a light-based treatment modality in which wavelength specific activation of a photosensitizer (PS) generates cytotoxic response in the irradiated region. PDT response is critically dependent on several parameters including light dose, PS dose, uptake time, fluence rate, and the mode of light delivery. While the systematic optimization of these treatment parameters can be complex, it also provides multiple avenues for enhancement of PDT efficacy under diverse treatment conditions, provided that a rational framework is established to quantify the impact of parameter selection upon treatment response. Here we present a theranostic technique, combining the inherent ability of the PS to serve simultaneously as a therapeutic and imaging agent, with the use of image-based treatment assessment in three dimensional (3D) in vitro tumor models, to comprise a platform to evaluate the impact of PDT parameters on treatment outcomes. We use this approach to visualize and quantify the uptake, localization, and photobleaching of the PS benzoporphyrin derivative monoacid ring-A (BPD) in a range of treatment conditions with varying uptake times as well as continuous and fractionated light delivery regimens in 3D cultures of AsPC-1 and PANC-1 cells. Informed by photobleaching patterns and correlation with cytotoxic response, asymmetric fractionated light delivery at 4 hours BPD uptake was found to be the most effective regimen assessed. Quantification of the spatial profile of cell killing within multicellular nodules revealed that these conditions also achieve the highest depth of cytotoxicity along the radial axis of 3D nodules. The framework introduced here provides a means for systematic assessment of PDT treatment parameters in biologically relevant 3D tumor models with potential for broader application to other systems.
format Online
Article
Text
id pubmed-3475211
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher Ivyspring International Publisher
record_format MEDLINE/PubMed
spelling pubmed-34752112012-10-18 Image-Based Quantification of Benzoporphyrin Derivative Uptake, Localization, and Photobleaching in 3D Tumor Models, for Optimization of PDT Parameters Glidden, Michael D. Celli, Jonathan P. Massodi, Iqbal Rizvi, Imran Pogue, Brian W. Hasan, Tayyaba Theranostics Research Paper Photodynamic therapy (PDT) is a light-based treatment modality in which wavelength specific activation of a photosensitizer (PS) generates cytotoxic response in the irradiated region. PDT response is critically dependent on several parameters including light dose, PS dose, uptake time, fluence rate, and the mode of light delivery. While the systematic optimization of these treatment parameters can be complex, it also provides multiple avenues for enhancement of PDT efficacy under diverse treatment conditions, provided that a rational framework is established to quantify the impact of parameter selection upon treatment response. Here we present a theranostic technique, combining the inherent ability of the PS to serve simultaneously as a therapeutic and imaging agent, with the use of image-based treatment assessment in three dimensional (3D) in vitro tumor models, to comprise a platform to evaluate the impact of PDT parameters on treatment outcomes. We use this approach to visualize and quantify the uptake, localization, and photobleaching of the PS benzoporphyrin derivative monoacid ring-A (BPD) in a range of treatment conditions with varying uptake times as well as continuous and fractionated light delivery regimens in 3D cultures of AsPC-1 and PANC-1 cells. Informed by photobleaching patterns and correlation with cytotoxic response, asymmetric fractionated light delivery at 4 hours BPD uptake was found to be the most effective regimen assessed. Quantification of the spatial profile of cell killing within multicellular nodules revealed that these conditions also achieve the highest depth of cytotoxicity along the radial axis of 3D nodules. The framework introduced here provides a means for systematic assessment of PDT treatment parameters in biologically relevant 3D tumor models with potential for broader application to other systems. Ivyspring International Publisher 2012-09-05 /pmc/articles/PMC3475211/ /pubmed/23082096 http://dx.doi.org/10.7150/thno.4334 Text en © Ivyspring International Publisher. This is an open-access article distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by-nc-nd/3.0/). Reproduction is permitted for personal, noncommercial use, provided that the article is in whole, unmodified, and properly cited.
spellingShingle Research Paper
Glidden, Michael D.
Celli, Jonathan P.
Massodi, Iqbal
Rizvi, Imran
Pogue, Brian W.
Hasan, Tayyaba
Image-Based Quantification of Benzoporphyrin Derivative Uptake, Localization, and Photobleaching in 3D Tumor Models, for Optimization of PDT Parameters
title Image-Based Quantification of Benzoporphyrin Derivative Uptake, Localization, and Photobleaching in 3D Tumor Models, for Optimization of PDT Parameters
title_full Image-Based Quantification of Benzoporphyrin Derivative Uptake, Localization, and Photobleaching in 3D Tumor Models, for Optimization of PDT Parameters
title_fullStr Image-Based Quantification of Benzoporphyrin Derivative Uptake, Localization, and Photobleaching in 3D Tumor Models, for Optimization of PDT Parameters
title_full_unstemmed Image-Based Quantification of Benzoporphyrin Derivative Uptake, Localization, and Photobleaching in 3D Tumor Models, for Optimization of PDT Parameters
title_short Image-Based Quantification of Benzoporphyrin Derivative Uptake, Localization, and Photobleaching in 3D Tumor Models, for Optimization of PDT Parameters
title_sort image-based quantification of benzoporphyrin derivative uptake, localization, and photobleaching in 3d tumor models, for optimization of pdt parameters
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3475211/
https://www.ncbi.nlm.nih.gov/pubmed/23082096
http://dx.doi.org/10.7150/thno.4334
work_keys_str_mv AT gliddenmichaeld imagebasedquantificationofbenzoporphyrinderivativeuptakelocalizationandphotobleachingin3dtumormodelsforoptimizationofpdtparameters
AT cellijonathanp imagebasedquantificationofbenzoporphyrinderivativeuptakelocalizationandphotobleachingin3dtumormodelsforoptimizationofpdtparameters
AT massodiiqbal imagebasedquantificationofbenzoporphyrinderivativeuptakelocalizationandphotobleachingin3dtumormodelsforoptimizationofpdtparameters
AT rizviimran imagebasedquantificationofbenzoporphyrinderivativeuptakelocalizationandphotobleachingin3dtumormodelsforoptimizationofpdtparameters
AT poguebrianw imagebasedquantificationofbenzoporphyrinderivativeuptakelocalizationandphotobleachingin3dtumormodelsforoptimizationofpdtparameters
AT hasantayyaba imagebasedquantificationofbenzoporphyrinderivativeuptakelocalizationandphotobleachingin3dtumormodelsforoptimizationofpdtparameters