Abnormal morphology biases hematocrit distribution in tumor vasculature and contributes to heterogeneity in tissue oxygenation

Bernabeu, M. O. et al. (2020) Abnormal morphology biases hematocrit distribution in tumor vasculature and contributes to heterogeneity in tissue oxygenation. Proceedings of the National Academy of Sciences of the United States of America, 117(45), pp. 27811-27819. (doi: 10.1073/pnas.2007770117) (PMID:33109723)

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Oxygen heterogeneity in solid tumors is recognized as a limiting factor for therapeutic efficacy. This heterogeneity arises from the abnormal vascular structure of the tumor, but the precise mechanisms linking abnormal structure and compromised oxygen transport are only partially understood. In this paper, we investigate the role that red blood cell (RBC) transport plays in establishing oxygen heterogeneity in tumor tissue. We focus on heterogeneity driven by network effects, which are challenging to observe experimentally due to the reduced fields of view typically considered. Motivated by our findings of abnormal vascular patterns linked to deviations from current RBC transport theory, we calculated average vessel lengths L⎯⎯ and diameters d⎯⎯ from tumor allografts of three cancer cell lines and observed a substantial reduction in the ratio λ=L⎯⎯/d⎯⎯ compared to physiological conditions. Mathematical modeling reveals that small values of the ratio λ (i.e., λ<6 ) can bias hematocrit distribution in tumor vascular networks and drive heterogeneous oxygenation of tumor tissue. Finally, we show an increase in the value of λ in tumor vascular networks following treatment with the antiangiogenic cancer agent DC101. Based on our findings, we propose λ as an effective way of monitoring the efficacy of antiangiogenic agents and as a proxy measure of perfusion and oxygenation in tumor tissue undergoing antiangiogenic treatment.

Item Type:Articles
Additional Information:Software development was sup- ported by Engineering and Physical Sciences Research Council (EPSRC) Grant eCSE-001-010. Supercomputing time on the ARCHER UK National Super- computing Service (http://www.archer.ac.uk) was provided by the UK Con- sortium on Mesoscale Engineering Sciences (UKCOMES) under EPSRC Grant EP/R029598/1. T.K. and M.O.B. contributions have been funded through two Chancellor’s Fellowships at The University of Edinburgh. M.O.B. is supported by EPSRC Grants EP/R029598/1 and EP/R021600/1; Fondation Leducq Grant 17 CVD 03; and the European Union’s Horizon 2020 research and inno- vation program under Grant Agreement 801423. The research leading to these results has received funding from the People Program (Marie Curie Actions) of the European Union’s Seventh Framework Program (FP7/2007- 2013) under Research Executive Agency Grant Agreement 625631 (obtained by B.M.). This work was also supported by Cancer Research UK (CRUK) Grants C5255/A18085 and C5255/A15935, through the CRUK Oxford Cen- ter. This work was supported by Biotechnology and Biological Sciences Research Council UK Multi-Scale Biology Network Grant BB/M025888/1. We acknowledge support from the UK Fluids Network (EPSRC Grant EP/N032861/1) for a Short Research Visit between the Edinburgh and Oxford teams.
Glasgow Author(s) Enlighten ID:Koery, Dr Jakub
Authors: Bernabeu, M. O., Köry, J., Grogan, J. A., Markelc, B., Beardo, A., d’Avezac, M., Enjalbert, R., Kaeppler, J., Daly, N., Hetherington, J., Krüger, T., Maini, P. K., Pitt-Francis, J. M., Muschel, R. J., Alarcón, T., and Byrne, H. M.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Mathematics
Journal Name:Proceedings of the National Academy of Sciences of the United States of America
Publisher:National Academy of Sciences
ISSN (Online):1091-6490
Published Online:27 October 2020

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