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3d tissue models as tools for radiotherapy screening for pancreatic cancer

The efficiency of radiotherapy treatment regimes varies from tumour to tumour and from patient to patient but it is generally highly influenced by the tumour microenvironment (TME). The TME can be described as a heterogeneous composition of biological, biophysical, biomechanical and biochemical mili...

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Autores principales: Wishart, Gabrielle, Gupta, Priyanka, Schettino, Giuseppe, Nisbet, Andrew, Velliou, Eirini
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The British Institute of Radiology. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8010544/
https://www.ncbi.nlm.nih.gov/pubmed/33684308
http://dx.doi.org/10.1259/bjr.20201397
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author Wishart, Gabrielle
Gupta, Priyanka
Schettino, Giuseppe
Nisbet, Andrew
Velliou, Eirini
author_facet Wishart, Gabrielle
Gupta, Priyanka
Schettino, Giuseppe
Nisbet, Andrew
Velliou, Eirini
author_sort Wishart, Gabrielle
collection PubMed
description The efficiency of radiotherapy treatment regimes varies from tumour to tumour and from patient to patient but it is generally highly influenced by the tumour microenvironment (TME). The TME can be described as a heterogeneous composition of biological, biophysical, biomechanical and biochemical milieus that influence the tumour survival and its’ response to treatment. Preclinical research faces challenges in the replication of these in vivo milieus for predictable treatment response studies. 2D cell culture is a traditional, simplistic and cost-effective approach to culture cells in vitro, however, the nature of the system fails to recapitulate important features of the TME such as structure, cell-cell and cell-matrix interactions. At the same time, the traditional use of animals (Xenografts) in cancer research allows realistic in vivo architecture, however foreign physiology, limited heterogeneity and reduced tumour mutation rates impairs relevance to humans. Furthermore, animal research is very time consuming and costly. Tissue engineering is advancing as a promising biomimetic approach, producing 3D models that capture structural, biophysical, biochemical and biomechanical features, therefore, facilitating more realistic treatment response studies for further clinical application. However, currently, the application of 3D models for radiation response studies is an understudied area of research, especially for pancreatic ductal adenocarcinoma (PDAC), a cancer with a notoriously complex microenvironment. At the same time, specific novel and/or more enhanced radiotherapy tumour-targeting techniques such as MRI-guided radiotherapy and proton therapy are emerging to more effectively target pancreatic cancer cells. However, these emerging technologies may have different biological effectiveness as compared to established photon-based radiotherapy. For example, for MRI-guided radiotherapy, the novel use of static magnetic fields (SMF) during radiation delivery is understudied and not fully understood. Thus, reliable biomimetic platforms to test new radiation delivery strategies are required to more accurately predict in vivo responses. Here, we aim to collate current 3D models for radiation response studies of PDAC, identifying the state of the art and outlines knowledge gaps. Overall, this review paper highlights the need for further research on the use of 3D models for pre-clinical radiotherapy screening including (i) 3D (re)-modeling of the PDAC hypoxic TME to allow for late effects of ionising radiation (ii) the screening of novel radiotherapy approaches and their combinations as well as (iii) a universally accepted 3D-model image quantification method for evaluating TME components in situ that would facilitate accurate post-treatment(s) quantitative comparisons.
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spelling pubmed-80105442021-10-18 3d tissue models as tools for radiotherapy screening for pancreatic cancer Wishart, Gabrielle Gupta, Priyanka Schettino, Giuseppe Nisbet, Andrew Velliou, Eirini Br J Radiol Review Article The efficiency of radiotherapy treatment regimes varies from tumour to tumour and from patient to patient but it is generally highly influenced by the tumour microenvironment (TME). The TME can be described as a heterogeneous composition of biological, biophysical, biomechanical and biochemical milieus that influence the tumour survival and its’ response to treatment. Preclinical research faces challenges in the replication of these in vivo milieus for predictable treatment response studies. 2D cell culture is a traditional, simplistic and cost-effective approach to culture cells in vitro, however, the nature of the system fails to recapitulate important features of the TME such as structure, cell-cell and cell-matrix interactions. At the same time, the traditional use of animals (Xenografts) in cancer research allows realistic in vivo architecture, however foreign physiology, limited heterogeneity and reduced tumour mutation rates impairs relevance to humans. Furthermore, animal research is very time consuming and costly. Tissue engineering is advancing as a promising biomimetic approach, producing 3D models that capture structural, biophysical, biochemical and biomechanical features, therefore, facilitating more realistic treatment response studies for further clinical application. However, currently, the application of 3D models for radiation response studies is an understudied area of research, especially for pancreatic ductal adenocarcinoma (PDAC), a cancer with a notoriously complex microenvironment. At the same time, specific novel and/or more enhanced radiotherapy tumour-targeting techniques such as MRI-guided radiotherapy and proton therapy are emerging to more effectively target pancreatic cancer cells. However, these emerging technologies may have different biological effectiveness as compared to established photon-based radiotherapy. For example, for MRI-guided radiotherapy, the novel use of static magnetic fields (SMF) during radiation delivery is understudied and not fully understood. Thus, reliable biomimetic platforms to test new radiation delivery strategies are required to more accurately predict in vivo responses. Here, we aim to collate current 3D models for radiation response studies of PDAC, identifying the state of the art and outlines knowledge gaps. Overall, this review paper highlights the need for further research on the use of 3D models for pre-clinical radiotherapy screening including (i) 3D (re)-modeling of the PDAC hypoxic TME to allow for late effects of ionising radiation (ii) the screening of novel radiotherapy approaches and their combinations as well as (iii) a universally accepted 3D-model image quantification method for evaluating TME components in situ that would facilitate accurate post-treatment(s) quantitative comparisons. The British Institute of Radiology. 2021-04-01 2021-03-08 /pmc/articles/PMC8010544/ /pubmed/33684308 http://dx.doi.org/10.1259/bjr.20201397 Text en © 2021 The Authors. Published by the British Institute of Radiology https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 Unported License http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) , which permits unrestricted non-commercial reuse, provided the original author and source are credited.
spellingShingle Review Article
Wishart, Gabrielle
Gupta, Priyanka
Schettino, Giuseppe
Nisbet, Andrew
Velliou, Eirini
3d tissue models as tools for radiotherapy screening for pancreatic cancer
title 3d tissue models as tools for radiotherapy screening for pancreatic cancer
title_full 3d tissue models as tools for radiotherapy screening for pancreatic cancer
title_fullStr 3d tissue models as tools for radiotherapy screening for pancreatic cancer
title_full_unstemmed 3d tissue models as tools for radiotherapy screening for pancreatic cancer
title_short 3d tissue models as tools for radiotherapy screening for pancreatic cancer
title_sort 3d tissue models as tools for radiotherapy screening for pancreatic cancer
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8010544/
https://www.ncbi.nlm.nih.gov/pubmed/33684308
http://dx.doi.org/10.1259/bjr.20201397
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