Cancer cell sedimentation in 3D cultures reveals active migration regulated by self-generated gradients and adhesion sites.

Cell sedimentation in 3D hydrogel cultures refers to the vertical migration of cells towards the bottom of the space. Understanding this poorly examined phenomenon may allow us to design better protocols to prevent it, as well as provide insights into the mechanobiology of cancer development. We conducted a multiscale experimental and mathematical examination of 3D cancer growth in triple negative breast cancer cells. Migration was examined in the presence and absence of Paclitaxel, in high and low adhesion environments and in the presence of fibroblasts. The observed behaviour was modeled by hypothesizing active migration due to self-generated chemotactic gradients. Our results did not reject this hypothesis, whereby migration was likely to be regulated by the MAPK and TGF-ß pathways. The mathematical model enabled us to describe the experimental data in absence (normalized error<40%) and presence of Paclitaxel (normalized error<10%), suggesting inhibition of random motion and advection in the latter case. Inhibition of sedimentation in low adhesion and co-culture experiments further supported the conclusion that cells actively migrated downwards due to the presence of signals produced by cells already attached to the adhesive glass surface.

Quantifying the Morphology and Mechanisms of Cancer Progression in 3D In-Vitro Environments: Integrating Experiments and Multiscale Models.

Mathematical models of cancer growth have become increasingly more accurate both in the space and time domains. However, the limited amount of data typically available has resulted in a larger number of qualitative rather than quantitative studies. In the present 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 state-of-the-art 3D cell culture data, and their validation based on the resulting experimental morphological patterns using spatial point-pattern analysis techniques. We applied this framework to the study of the development of Triple Negative Breast Cancer cells cultured in Matrigel scaffolds, and validated the hypothesis of chemotactic migration using a multiscale, hybrid Keller-Segel model. The results revealed transient, non-random spatial distributions of cancer cells that consist of clustered, and dispersion patterns. The proposed model was able to describe the general characteristics of the experimental observations and suggests that chemotactic migration together with random motion was found to be a plausible mechanism leading to accumulation, during the examined time period of development. The developed framework enabled us to pursue two goals; first, the quantitative description of the morphology of cancer growth in 3D cultures using point-pattern analysis, and second, the relation of tumour morphology with underlying biophysical mechanisms that govern cancer growth and migration.

Detection and Spatiotemporal Analysis of In-vitro 3D Migratory Triple-Negative Breast Cancer Cells.

The invasion of cancer cells into the surrounding tissues is one of the hallmarks of cancer. However, a precise quantitative understanding of the spatiotemporal patterns of cancer cell migration and invasion still remains elusive. A promising approach to investigate these patterns are 3D cell cultures, which provide more realistic models of cancer growth compared to conventional 2D monolayers. Quantifying the spatial distribution of cells in these 3D cultures yields great promise for understanding the spatiotemporal progression of cancer. In the present study, we present an image processing and segmentation pipeline for the detection of 3D GFP-fluorescent triple-negative breast cancer cell nuclei, and we perform quantitative analysis of the formed spatial patterns and their temporal evolution. The performance of the proposed pipeline was evaluated using experimental 3D cell culture data, and was found to be comparable to manual segmentation, outperforming four alternative automated methods. The spatiotemporal statistical analysis of the detected distributions of nuclei revealed transient, non-random spatial distributions that consisted of clustered patterns across a wide range of neighbourhood distances, as well as dispersion for larger distances. Overall, the implementation of the proposed framework revealed the spatial organization of cellular nuclei with improved accuracy, providing insights into the 3 dimensional inter-cellular organization and its progression through time.

Effect of Cell Sex on Uptake of Nanoparticles: The Overlooked Factor at the Nanobio Interface.

Cellular uptake of nanoparticles (NPs) depends on the nature of the nanobio system including the solid nanocomponents ( e. g., physicochemical properties of NPs), nanobio interfaces ( e. g., protein corona composition), and the cellular characteristics ( e. g., cell type). In this study, we document the role of sex in cellular uptake of NPs as an "overlooked" factor in nanobio interface investigations. We demonstrate that cell sex leads to differences in NP uptake between male and female human amniotic stem cells (hAMSCs), with greater uptake by female cells. hAMSCs are one of the earliest sources of somatic stem cells. The experiments were replicated with primary fibroblasts isolated from the salivary gland of adult male and female donors of similar ages, and again the extent of NP uptake was altered by cell sex. However, in contrast to hAMSCs, uptake was greater in male cells. We also found out that female versus male amniotic stem cells exhibited different responses to reprogramming into induced pluripotent stem cells (iPSCs) by the Yamanaka factors. Thus, future studies should consider the effect of sex on the nanobio interactions to optimize clinical translation of NPs and iPSC biology and to help researchers to better design and produce safe and efficient therapeutic sex-specific NPs.