Experimental measurement and numerical modeling of deformation behavior of breast cancer cells passing through constricted microfluidic channels

During the multistep process of metastasis, cancer cells encounter various mechanical forces which make them deform drastically. Developing accurate in-silico models, capable of simulating the interactions between the mechanical forces and highly deformable cancer cells, can pave the way for the development of novel diagnostic and predictive methods for metastatic progression. Spring-network models of cancer cell, empowered by our recently proposed identification approach, promises a versatile numerical tool for developing experimentally validated models that can simulate complex interactions at cellular scale. Using this numerical tool, we presented spring-network models of breast cancer cells that can accurately replicate the experimental data of deformation behavior of the cells flowing in a fluidic domain and passing narrow constrictions comparable to microcapillary. First, using high-speed imaging, we experimentally studied the deformability of breast cancer cell lines with varying metastatic potential (MCF-7 (less invasive), SKBR-3 (medium-high invasive), and MDA-MB-231 (highly invasive)) in terms of their entry time to a constricted microfluidic channel. We observed that MDA-MB-231, that has the highest metastatic potential, is the most deformable cell among the three. Then, by focusing on this cell line, experimental measurements were expanded to two more constricted microchannel dimensions. The experimental deformability data in three constricted microchannel sizes for various cell sizes, enabled accurate identification of the unknown parameters of the spring-network model of the breast cancer cell line (MDA-MB-231). Our results show that the identified parameters depend on the cell size, suggesting the need for a systematic procedure for identifying the size-dependent parameters of spring-network models of cells. As the numerical results show, the presented cell models can simulate the entry process of the cell into constricted channels with very good agreements with the measured experimental data.

Controlled tumor heterogeneity in a co-culture system by 3D bio-printed tumor-on-chip model

Cancer treatment resistance is a caused by presence of various types of cells and heterogeneity within the tumor. Tumor cell-cell and cell-microenvironment interactions play a significant role in the tumor progression and invasion, which have important implications for diagnosis, and resistance to chemotherapy. In this study, we develop 3D bioprinted in vitro models of the breast cancer tumor microenvironment made of co-cultured cells distributed in a hydrogel matrix with controlled architecture to model tumor heterogeneity. We hypothesize that the tumor could be represented by a cancer cell-laden co-culture hydrogel construct, whereas its microenvironment can be modeled in a microfluidic chip capable of producing a chemical gradient. Breast cancer cells (MCF7 and MDA-MB-231) and non-tumorigenic mammary epithelial cells (MCF10A) were embedded in the alginate-gelatine hydrogels and printed using a multi-cartridge extrusion bioprinter. Our approach allows for precise control over position and arrangements of cells in a co-culture system, enabling the design of various tumor architectures. We created samples with two different types of cells at specific initial locations, where the density of each cell type was carefully controlled. The cells were either randomly mixed or positioned in sequential layers to create cellular heterogeneity. To study cell migration toward chemoattractant, we developed a chemical microenvironment in a chamber with a gradual chemical gradient. As a proof of concept, we studied different migration patterns of MDA-MB-231 cells toward the epithelial growth factor gradient in presence of MCF10A cells in different ratios using this device. Our approach involves the integration of 3D bioprinting and microfluidic devices to create diverse tumor architectures that are representative of those found in various patients. This provides an excellent tool for studying the behavior of cancer cells with high spatial and temporal resolution.

Numerical study on the adhesion of a circulating tumor cell in a curved microvessel

The adhesion of a circulating tumor cell (CTC) in a three-dimensional curved microvessel was numerically investigated. Simulations were first performed to characterize the differences in the dynamics and adhesion of a CTC in the straight and curved vessels. After that, a parametric study was performed to investigate the effects of the applied driven force density f (or the flow Reynolds number Re) and the CTC membrane bending modulus K_b on the CTC adhesion. Our simulation results show that the CTC prefers to adhere to the curved vessel as more bonds are formed around the transition region of the curved part due to the increased cell-wall contact by the centrifugal force. The parametric study also indicates that when the flow driven force f (or Re) increases or when the CTC becomes softer (K_b decreases), the bond formation probability increases and the bonds will be formed at more sites of a curved vessel. The increased f (or Re) brings a larger centrifugal force, while the decreased K_b generates more contact areas at the cell-wall interface, both of which are beneficial to the bond formation. In the curved vessel, it is found that the site where bonds are formed the most (hotspot) varies with the applied f and the K_b. For our vessel geometry, when f is small, the hotspot tends to be within the first bend of the vessel, while as f increases or K_b decreases, the hotspot may shift to the second bend of the vessel.

DNA Nanolithography Enables a Highly Ordered Recognition Interface in a Microfluidic Chip for the Efficient Capture and Release of Circulating Tumor Cells

Microfluidic chips with nano-scale structures have shown great potential, but the fabrication and cost issues restrict their application. Herein, we propose a conceptually new "DNA nanolithography in a microfluidic chip" by using sub-10 nm three-dimensional DNA structures (TDNs) as frameworks with a pendant aptamer at the top vertex (ApTDN-Chip). The nano-scale framework ensures that the aptamer is in a highly ordered upright orientation, avoiding the undesired orientation or crowding effects caused by conventional microfluidic interface fabrication processes. Compared with a monovalent aptamer modified chip, the capture efficiency of ApTDN-Chip was enhanced nearly 60 % due to the highly precise dimension and rigid framework of TDNs. In addition, the scaffolds make DNase I more accessible to the aptamer with up to 83 % release efficiency and 91 % cell viability, which is fully compatible with downstream molecular analysis. Overall, this strategy provides a novel perspective on engineering nano-scaffolds to achieve a more ordered nano-topography of microfluidic chips.

Single-Cell Mobility Analysis of Metastatic Breast Cancer Cells

Efforts have been taken to enhance the study of single-cells, however, the task remains challenging because most previous investigations cannot exclude the interactions between single cells or separately retrieved cells with specificity for further analyses. Here, a single-cell mobility analysis platform (SCM-Chip) is developed that can not only real-time monitor single-cell migration in independent niches but can also selectively recover target cells one by one. The design of each channel with a single-cell capture unit and an outlet enables the system to place single cells in different isolated niches with fluidic capture and to respectively collect target cells based on mobilities. SCM-Chip characterization of breast cancer cells reveals the presence of high- and low-migratory populations. Whole-cell transcriptome analysis establishes that monocyte chemotactic protein induced protein 1 (MCPIP1) is related with cell mobility; cells with a high expression of MCPIP1 exhibit low mobility in vitro and metastasis in vivo. The SCM platform provides a generic tool for accurate single-cell isolation and differentiation that can be readily adapted for the study of cancer and drug development.