The extracellular matrix (ECM) is a three-dimensional, acellular scaffold of living tissues. Incorporating the ECM into cell culture models is a goal of cell biology studies and requires biocompatible materials that can mimic the ECM. Among such materials are hydrogels: polymeric networks that derive most of their mass from water. With the tuning of their properties, these polymer networks can resemble living tissues. The microarchitectural properties of hydrogels, such as porosity, pore size, fiber length, and surface topology can determine cell plasticity. The adequate characterization of these parameters requires reliable and reproducible methods. However, most methods were historically standardized using other biological specimens, such as 2D cell cultures, biopsies, or even animal models. Therefore, their translation comes with technical limitations when applied to hydrogel-based cell culture systems. In our current work, we have reviewed the most common techniques employed in the characterization of hydrogel microarchitectures. Our review provides a concise description of the underlying principles of each method and summarizes the collective data obtained from cell-free and cell-loaded hydrogels. The advantages and limitations of each technique are discussed, and comparisons are made. The information presented in our current work will be of interest to researchers who employ hydrogels as platforms for cell culture, 3D bioprinting, and other fields within hydrogel-based research.

The tissue microenvironment is a major contributor to cellular functions, such as cell adhesion, migration and invasion. A critical physical parameter for determining the effect of the microenvironment on cellular functions is the average pore-size of filamentous scaffolds, such as 3D collagen fiber matrices, which are assembled by the polymerization of biopolymers. The scaffolds of these matrices can be analyzed easily by using state-of-the-art laser scanning confocal imaging. However, the generation of a quantitative estimate of the pore-size in a 3D microenvironment is not trivial. In this study, we present a reliable and fast analytical method, which relies on a two-step 3D pore-size analysis utilizing several state-of-the-art image analysis methods, such as total variation (TV) denoising and adaptive local thresholds, and another crucial parameter, such as pore-coverage. We propose an iterative approach of pore-size analysis to determine even the smallest and obscure pores in a collagen scaffold. Additionally, we propose a novel parameter, the pseudo-pore-size, which describes a virtual scaffold porosity. In order to validate the advanced two-step pore-size analysis different types of artificial collagens, such as a rat and bovine mixture with two different collagen concentrations have been utilized. Additionally, we compare a traditional approach with our method using an artificially generated network with predefined pore-size distributions. Indeed, our analytical method provides a precise, fast and parameter-free, user-independent and automatic analysis of 3D pore topology, such as pore-sizes and pore-coverage. Additionally, we are able to determine non-physiological network topologies by taking the pore-coverage as a goodness-of-fit parameter.

Cancer progression is caused by genetic changes and associated with various alterations in cell properties, which also affect a tumor's mechanical state. While an increasedstiffnesshas been well known for long for solid tumors, it has limited prognostic power. It is hypothesized that cancer progression is accompanied by tissuefluidization, where portions of the tissue can change position across different length scales. Supported by tabletop magnetic resonance elastography (MRE) on stroma mimicking collagen gels and microscopic analysis of live cells inside patient derived tumor explants, an overview is provided of how cancer associated mechanisms, including cellular unjamming, proliferation, microenvironment composition, and remodeling can alter a tissue'sfluidityandstiffness. In vivo, state‐of‐the‐art multifrequency MRE can distinguish tumors from their surrounding host tissue by their rheological fingerprints. Most importantly, a meta‐analysis on the currently available clinical studies is conducted and universal trends are identified. The results and conclusions are condensed into a gedankenexperiment about how a tumor can grow and eventually metastasize into its environment from a physics perspective to deduce corresponding mechanical properties. Based onstiffness, fluidity,spatial heterogeneity, andtextureof thetumor fronta roadmap for a prognosis of a tumor's aggressiveness and metastatic potential is presented.

Biopolymer blends are advantageous materials with novel properties that may show performances way beyond their individual constituents. Collagen elastin hybrid gels are a new representative of such materials as they employ elastin’s thermo switching behavior in the physiological temperature regime. Although recent studies highlight the potential applications of such systems, little is known about the interaction of collagen and elastin fibers during polymerization. In fact, the final network structure is predetermined in the early and mostly arbitrary association of the fibers. We investigated type I collagen polymerized with bovine neck ligament elastin with up to 33.3 weight percent elastin and showed, by using a plate reader, zeta potential and laser scanning microscopy (LSM) experiments, that elastin fibers bind in a lateral manner to collagen fibers. Our plate reader experiments revealed an elastin concentration-dependent increase in the polymerization rate, although the rate increase was greatest at intermediate elastin concentrations. As elastin does not significantly change the structural metrics pore size, fiber thickness or 2D anisotropy of the final gel, we are confident to conclude that elastin is incorporated homogeneously into the collagen fibers.

Purpose The remodeling of the extracellular matrix (ECM) is a key feature of tumor development in the liver, particularly in hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). Fibrosis and cirrhosis are risk factors for tumorigenesis and define serious structural changes in the ECM. Fibrotic-induced collagen and fibronectin alter the stiffness and heterogeneity of the ECM. A stiffened and heterogeneous ECM promotes the proliferation, migration, and invasion of tumor cells. Direct effects of structural changes in the ECM on HCC / iCCA cancer cells are insufficiently studied. Methods HCC and iCCA cells were examined in contact with varying structurally heterogeneous collagen and collagen-fibronectin networks. Heterogeneity of the networks was defined by the combination of stiffness and intrinsic properties. Network heterogeneity-related effects of cell-matrix interactions on cell stiffness, invasiveness, and the ability to interact with network structures by fiber displacements were determined. Results Increased network heterogeneity caused a decrease in cell stiffness, an increase in cell invasiveness, and altered fiber displacements. Different effects on HCC and iCCA cells depending on network heterogeneity were identified. High ECM heterogeneity resulted in low cell stiffness and high cell invasion across cancer cell types. Conclusions We present a model system that is applicable to identify structurally induced influences of the extracellular matrix on cancer cells and to investigate the risk factor of structural changes in the tumor environment.

Purpose: The remodeling of the extracellular matrix (ECM) is a key feature of tumor development in the liver, particularly in hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). Fibrosis and cirrhosis are risk factors for tumorigenesis and define serious structural changes in the ECM. Fibrotic-induced collagen and fibronectin alter the stiffness and heterogeneity of the ECM. A stiffened and heterogeneous ECM promotes the proliferation, migration, and invasion of tumor cells. Direct effects of structural changes in the ECM on HCC/iCCA cancer cells are insufficiently studied. Methods: HCC and iCCA cells were examined in contact with differently structured collagen and collagen-fibronectin networks. The structural architecture of the networks was defined by combining the normalized stiffness, pore size, and network distribution values as the ECM Architectural Index (EAI). The effects of cell-matrix interactions on cell stiffness, invasiveness, and the ability to interact with network structures through fiber displacement in relation to network architecture were determined. Results: Increased EAI caused a decrease in cell stiffness, an increase in cell invasiveness, and altered fiber displacements. Different effects on HCC and iCCA cells depending on the EAI were identified. High EAI resulted in low cell stiffness and high cell invasion across cancer cell types. Conclusions: We present a model system that is applicable to identify structurally induced influences of the extracellular matrix on cancer cells and to investigate the risk factor of structural changes in the tumor environment.