RT Journal Article SR Electronic T1 Quantifying the Morphology and Mechanisms of Cancer Progression in 3D in-vitro environments: Integrating Experiments, Multiscale Models, and Spatial Validation JF bioRxiv FD Cold Spring Harbor Laboratory SP 2021.11.16.468856 DO 10.1101/2021.11.16.468856 A1 Nikolaos M. Dimitriou A1 Salvador Flores-Torres A1 Joseph Matthew Kinsella A1 Georgios D. Mitsis YR 2021 UL http://biorxiv.org/content/early/2021/11/22/2021.11.16.468856.abstract AB Throughout the years, mathematical models of cancer growth have become increasingly more accurate in terms of the description of cancer growth in both space and time. However, the limited amount of data typically available has resulted in a larger number of qualitative rather than quantitative studies. In this study, we provide an integrated experimental-computational framework for the quantification of the morphological characteristics and the mechanistic modelling of cancer progression in 3D environments. The proposed framework allows for the calibration of multiscale-spatiotemporal models of cancer growth using 3D cell culture data, and their validation based on the morphological patterns. The implementation of this framework enables us to pursue two goals; first, the quantitative description of the morphology of cancer progression in 3D cultures, and second, the relation of tumour morphology with underlying biophysical mechanisms that govern cancer growth. We apply this framework to the study of the spatiotemporal progression of Triple Negative Breast Cancer (TNBC) cells cultured in 3D Matrigel scaffolds, under the hypothesis of chemotactic migration using a multiscale Keller-Segel model. The results reveal transient, non-random spatial distributions of cancer cells that consist of clustered patterns across a wide range of neighbourhood distances, as well as dispersion for larger distances. Overall, the proposed model was able to describe the general characteristics of the experimental observations and suggests that cancer cells exhibited chemotactic migration and cell accumulation, as well as random motion throughout the period of development. To our knowledge, this is the first time a framework attempts to quantify the relationship between the spatial patterns and the underlying mechanisms of cancer growth in 3D environments.Competing Interest StatementThe authors have declared no competing interest.