Fluorescence-Based Quantitative and Spatial Analysis of Tumour Spheroids: A Proposed Tool to Predict Patient-Specific Therapy Response

Tumour spheroids are widely used to pre-clinically assess anti-cancer treatments. They are an excellent compromise between the lack of microenvironment encountered in adherent cell culture conditions and the great complexity of in vivo animal models. Spheroids recapitulate intra-tumour microenvironm...

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Main Authors: Loredana Spoerri (Author), Gency Gunasingh (Author), Nikolas K. Haass (Author)
Format: Book
Published: Frontiers Media S.A., 2021-05-01T00:00:00Z.
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100 1 0 |a Loredana Spoerri  |e author 
700 1 0 |a Gency Gunasingh  |e author 
700 1 0 |a Nikolas K. Haass  |e author 
245 0 0 |a Fluorescence-Based Quantitative and Spatial Analysis of Tumour Spheroids: A Proposed Tool to Predict Patient-Specific Therapy Response 
260 |b Frontiers Media S.A.,   |c 2021-05-01T00:00:00Z. 
500 |a 2673-253X 
500 |a 10.3389/fdgth.2021.668390 
520 |a Tumour spheroids are widely used to pre-clinically assess anti-cancer treatments. They are an excellent compromise between the lack of microenvironment encountered in adherent cell culture conditions and the great complexity of in vivo animal models. Spheroids recapitulate intra-tumour microenvironment-driven heterogeneity, a pivotal aspect for therapy outcome that is, however, often overlooked. Likely due to their ease, most assays measure overall spheroid size and/or cell death as a readout. However, as different tumour cell subpopulations may show a different biology and therapy response, it is paramount to obtain information from these distinct regions within the spheroid. We describe here a methodology to quantitatively and spatially assess fluorescence-based microscopy spheroid images by semi-automated software-based analysis. This provides a fast assay that accounts for spatial biological differences that are driven by the tumour microenvironment. We outline the methodology using detection of hypoxia, cell death and PBMC infiltration as examples, and we propose this procedure as an exploratory approach to assist therapy response prediction for personalised medicine. 
546 |a EN 
690 |a tumour spheroid 
690 |a tumour micro-environment 
690 |a spatial analysis 
690 |a intra-tumoural heterogeneity 
690 |a anti-cancer drug response 
690 |a hypoxia 
690 |a Medicine 
690 |a R 
690 |a Public aspects of medicine 
690 |a RA1-1270 
690 |a Electronic computers. Computer science 
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786 0 |n Frontiers in Digital Health, Vol 3 (2021) 
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