Abstract
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
milieus for predictable treatment response studies. 2D cell culture is a traditional, simplistic and cost-effective approach to culture cells
, 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
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
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
that would facilitate accurate post-treatment(s) quantitative comparisons.