MicroRNA-216a is essential for cardiac angiogenesis.

While it is experimentally supported that impaired myocardial vascularization contributes to a mismatch between myocardial oxygen demand and supply, a mechanistic basis for disruption of coordinated tissue growth and angiogenesis in heart failure remains poorly understood. Silencing strategies that impair microRNA biogenesis have firmly implicated microRNAs in the regulation of angiogenesis, and individual microRNAs prove to be crucial in developmental or tumor angiogenesis. A high-throughput functional screening for the analysis of a whole-genome microRNA silencing library with regard to their phenotypic effect on endothelial cell proliferation as a key parameter, revealed several anti- and pro-proliferative microRNAs. Among those was miR-216a, a pro-angiogenic microRNA which is enriched in cardiac microvascular endothelial cells and reduced in expression under cardiac stress conditions. miR-216a null mice display dramatic cardiac phenotypes related to impaired myocardial vascularization and unbalanced autophagy and inflammation, supporting a model where microRNA regulation of microvascularization impacts the cardiac response to stress.

High-Throughput Methods in the Discovery and Study of Biomaterials and Materiobiology.

The complex interaction of cells with biomaterials (i.e., materiobiology) plays an increasingly pivotal role in the development of novel implants, biomedical devices, and tissue engineering scaffolds to treat diseases, aid in the restoration of bodily functions, construct healthy tissues, or regenerate diseased ones. However, the conventional approaches are incapable of screening the huge amount of potential material parameter combinations to identify the optimal cell responses and involve a combination of serendipity and many series of trial-and-error experiments. For advanced tissue engineering and regenerative medicine, highly efficient and complex bioanalysis platforms are expected to explore the complex interaction of cells with biomaterials using combinatorial approaches that offer desired complex microenvironments during healing, development, and homeostasis. In this review, we first introduce materiobiology and its high-throughput screening (HTS). Then we present an in-depth of the recent progress of 2D/3D HTS platforms (i.e., gradient and microarray) in the principle, preparation, screening for materiobiology, and combination with other advanced technologies. The Compendium for Biomaterial Transcriptomics and high content imaging, computational simulations, and their translation toward commercial and clinical uses are highlighted. In the final section, current challenges and future perspectives are discussed. High-throughput experimentation within the field of materiobiology enables the elucidation of the relationships between biomaterial properties and biological behavior and thereby serves as a potential tool for accelerating the development of high-performance biomaterials.

The Galapagos Chip Platform for High-Throughput Screening of Cell Adhesive Chemical Micropatterns.

In vivo cells reside in a complex extracellular matrix (ECM) that presents spatially distributed biochemical and -physical cues at the nano- to micrometer scales. Chemical micropatterning is successfully used to generate adhesive islands to control where and how cells attach and restore cues of the ECM in vitro. Although chemical micropatterning has become a powerful tool to study cell-material interactions, only a fraction of the possible micropattern designs was covered so far, leaving many other possible designs still unexplored. Here, a high-throughput screening platform called "Galapagos chip" is developed. It contains a library of 2176 distinct subcellular chemical patterns created using mathematical algorithms and a straightforward UV-induced two-step surface modification. This approach enables the immobilization of ligands in geometrically defined regions onto cell culture substrates. To validate the system, binary RGD/polyethylene glycol patterns are prepared on which human mesenchymal stem cells are cultured, and the authors observe how different patterns affect cell and organelle morphology. As proof of concept, the cells are stained for the mechanosensitive YAP protein, and, using a machine-learning algorithm, it is demonstrated that cell shape and YAP nuclear translocation correlate. It is concluded that the Galapagos chip is a versatile platform to screen geometrical aspects of cell-ECM interaction.

Data-analysis strategies for image-based cell profiling.

Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic differences among a variety of cell populations. It paves the way to studying biological systems on a large scale by using chemical and genetic perturbations. The general workflow for this technology involves image acquisition with high-throughput microscopy systems and subsequent image processing and analysis. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.

In-depth clinico-pathological examination of RNA foci in a large cohort of C9ORF72 expansion carriers.

A growing body of evidence suggests that a loss of chromosome 9 open reading frame 72 (C9ORF72) expression, formation of dipeptide-repeat proteins, and generation of RNA foci contribute to disease pathogenesis in amyotrophic lateral sclerosis and frontotemporal dementia. Although the levels of C9ORF72 transcripts and dipeptide-repeat proteins have already been examined thoroughly, much remains unknown about the role of RNA foci in C9ORF72-linked diseases. As such, we performed a comprehensive RNA foci study in an extensive pathological cohort of C9ORF72 expansion carriers (n = 63). We evaluated two brain regions using a newly developed computer-automated pipeline allowing recognition of cell nuclei and RNA foci (sense and antisense) supplemented by manual counting. In the frontal cortex, the percentage of cells with sense or antisense RNA foci was 26 or 12%, respectively. In the cerebellum, 23% of granule cells contained sense RNA foci and 1% antisense RNA foci. Interestingly, the highest percentage of cells with RNA foci was observed in cerebellar Purkinje cells (~70%). In general, more cells contained sense RNA foci than antisense RNA foci; however, when antisense RNA foci were present, they were usually more abundant. We also observed that an increase in the percentage of cells with antisense RNA foci was associated with a delayed age at onset in the frontal cortex (r = 0.43, p = 0.003), whereas no other associations with clinico-pathological features were seen. Importantly, our large-scale study is the first to provide conclusive evidence that RNA foci are not the determining factor of the clinico-pathological variability observed in C9ORF72 expansion carriers and it emphasizes that the distribution of RNA foci does not follow the pattern of neurodegeneration, stressing the complex interplay between different aspects of C9ORF72-related diseases.

Expanding Biomaterial Surface Topographical Design Space through Natural Surface Reproduction.

Surface topography is a tool to endow biomaterials with bioactive properties. However, the large number of possible designs makes it challenging to find the optimal surface structure to induce a specific cell response. The TopoChip platform is currently the largest collection of topographies with 2176 in silico designed microtopographies. Still, it is exploring only a small part of the design space due to design algorithm limitations and the surface engineering strategy. Inspired by the diversity of natural surfaces, it is assessed as to what extent the topographical design space and consequently the resulting cellular responses can be expanded using natural surfaces. To this end, 26 plant and insect surfaces are replicated in polystyrene and their surface properties are quantified using white light interferometry. Through machine-learning algorithms, it is demonstrated that natural surfaces extend the design space of the TopoChip, which coincides with distinct morphological and focal adhesion profiles in mesenchymal stem cells (MSCs) and Pseudomonas aeruginosa colonization. Furthermore, differentiation experiments reveal the strong potential of the holy lotus to improve osteogenesis in MSCs. In the future, the design algorithms will be trained with the results obtained by natural surface imprint experiments to explore the bioactive properties of novel surface topographies.

Discovery of synergistic material-topography combinations to achieve immunomodulatory osteoinductive biomaterials using a novel in vitro screening method: The ChemoTopoChip.

Human mesenchymal stem cells (hMSCs) are widely represented in regenerative medicine clinical strategies due to their compatibility with autologous implantation. Effective bone regeneration involves crosstalk between macrophages and hMSCs, with macrophages playing a key role in the recruitment and differentiation of hMSCs. However, engineered biomaterials able to simultaneously direct hMSC fate and modulate macrophage phenotype have not yet been identified. A novel combinatorial chemistry-topography screening platform, the ChemoTopoChip, is used here to identify materials suitable for bone regeneration by screening 1008 combinations in each experiment for human immortalized mesenchymal stem cell (hiMSCs) and human macrophage response. The osteoinduction achieved in hiMSCs cultured on the "hit" materials in basal media is comparable to that seen when cells are cultured in osteogenic media, illustrating that these materials offer a materials-induced alternative to osteo-inductive supplements in bone-regeneration. Some of these same chemistry-microtopography combinations also exhibit immunomodulatory stimuli, polarizing macrophages towards a pro-healing phenotype. Maximum control of cell response is achieved when both chemistry and topography are recruited to instruct the required cell phenotype, combining synergistically. The large combinatorial library allows us for the first time to probe the relative cell-instructive roles of microtopography and material chemistry which we find to provide similar ranges of cell modulation for both cues. Machine learning is used to generate structure-activity relationships that identify key chemical and topographical features enhancing the response of both cell types, providing a basis for a better understanding of cell response to micro topographically patterned polymers.

Evolutionary design of optimal surface topographies for biomaterials.

Natural evolution tackles optimization by producing many genetic variants and exposing these variants to selective pressure, resulting in the survival of the fittest. We use high throughput screening of large libraries of materials with differing surface topographies to probe the interactions of implantable device coatings with cells and tissues. However, the vast size of possible parameter design space precludes a brute force approach to screening all topographical possibilities. Here, we took inspiration from Nature to optimize materials surface topographies using evolutionary algorithms. We show that successive cycles of material design, production, fitness assessment, selection, and mutation results in optimization of biomaterials designs. Starting from a small selection of topographically designed surfaces that upregulate expression of an osteogenic marker, we used genetic crossover and random mutagenesis to generate new generations of topographies.

Mechanotransduction is a context-dependent activator of TGF-ß signaling in mesenchymal stem cells.

We previously found that surface topographies induce the expression of the Scxa gene, encoding Scleraxis in tenocytes. Because Scxa is a TGF-ß responsive gene, we investigated the link between mechanotransduction and TGF-ß signaling. We discovered that mesenchymal stem cells exposed to both micro-topographies and TGF-ß2 display synergistic induction of SMAD phosphorylation and transcription of the TGF-ß target genes SCX, a-SMA, and SOX9. Pharmacological perturbations revealed that Rho/ROCK/SRF signaling is required for this synergistic response. We further found an activation of the early response genes SRF and EGR1 during the early adaptation phase on micro-topographies, which coincided with higher expression of the TGF-ß type-II receptor gene. Of interest, PKC activators Prostratin and Ingenol-3, known for inducing actin reorganization and activation of serum response elements, were able to mimic the topography-induced TGF-ß response. These findings provide novel insights into the convergence of mechanobiology and TGF-ß signaling, which can lead to improved culture protocols and therapeutic applications.

MiR-337-3p Promotes Adipocyte Browning by Inhibiting TWIST1.

The prevalence of metabolic syndrome (MetS) and obesity is an alarming health issue worldwide. Obesity is characterized by an excessive accumulation of white adipose tissue (WAT), and it is associated with diminished brown adipose tissue (BAT) activity. Twist1 acts as a negative feedback regulator of BAT metabolism. Therefore, targeting Twist1 could become a strategy for obesity and metabolic disease. Here, we have identified miR-337-3p as an upstream regulator of Twist1. Increased miR-337-3p expression paralleled decreased expression of TWIST1 in BAT compared to WAT. Overexpression of miR-337-3p in brown pre-adipocytes provoked a reduction in Twist1 expression that was accompanied by increased expression of brown/mitochondrial markers. Luciferase assays confirmed an interaction between the miR-337 seed sequence and Twist1 3'UTR. The inverse relationship between the expression of TWIST1 and miR-337 was finally validated in adipose tissue samples from non-MetS and MetS subjects that demonstrated a dysregulation of the miR-337-Twist1 molecular axis in MetS. The present study demonstrates that adipocyte miR-337-3p suppresses Twist1 repression and enhances the browning of adipocytes.

On the correlation between material-induced cell shape and phenotypical response of human mesenchymal stem cells.

Learning rules by which cell shape impacts cell function would enable control of cell physiology and fate in medical applications, particularly, on the interface of cells and material of the implants. We defined the phenotypic response of human bone marrow-derived mesenchymal stem cells (hMSCs) to 2176 randomly generated surface topographies by probing basic functions such as migration, proliferation, protein synthesis, apoptosis, and differentiation using quantitative image analysis. Clustering the surfaces into 28 archetypical cell shapes, we found a very strict correlation between cell shape and physiological response and selected seven cell shapes to describe the molecular mechanism leading to phenotypic diversity. Transcriptomics analysis revealed a tight link between cell shape, molecular signatures, and phenotype. For instance, proliferation is strongly reduced in cells with limited spreading, resulting in down-regulation of genes involved in the G2/M cycle and subsequent quiescence, whereas cells with large filopodia are related to activation of early response genes and inhibition of the osteogenic process. In this paper we were aiming to identify a universal set of genes that regulate the material-induced phenotypical response of human mesenchymal stem cells. This will allow designing implants that can actively regulate cellular, molecular signalling through cell shape. Here we are proposing an approach to tackle this question.

Immune Modulation by Design: Using Topography to Control Human Monocyte Attachment and Macrophage Differentiation.

Macrophages play a central role in orchestrating immune responses to foreign materials, which are often responsible for the failure of implanted medical devices. Material topography is known to influence macrophage attachment and phenotype, providing opportunities for the rational design of "immune-instructive" topographies to modulate macrophage function and thus foreign body responses to biomaterials. However, no generalizable understanding of the inter-relationship between topography and cell response exists. A high throughput screening approach is therefore utilized to investigate the relationship between topography and human monocyte-derived macrophage attachment and phenotype, using a diverse library of 2176 micropatterns generated by an algorithm. This reveals that micropillars 5-10 µm in diameter play a dominant role in driving macrophage attachment compared to the many other topographies screened, an observation that aligns with studies of the interaction of macrophages with particles. Combining the pillar size with the micropillar density is found to be key in modulation of cell phenotype from pro to anti-inflammatory states. Machine learning is used to successfully build a model that correlates cell attachment and phenotype with a selection of descriptors, illustrating that materials can potentially be designed to modulate inflammatory responses for future applications in the fight against foreign body rejection of medical devices.

Identification of topographical architectures supporting the phenotype of rat tenocytes.

Tenocytes, the main cell type of the tendon, require mechanical stimuli for their proper function. When the tenocyte environment changes due to tissue damage or by transferring tenocytes from their native environment into cell culture, the signals from the tenocyte niche are lost, leading towards a decline of phenotypic markers. It is known that micro-topographies can influence cell fate by the physical cues they provide. To identify the optimal topography-induced biomechanical niche in vitro, we seeded tenocytes on the TopoChip, a micro-topographical screening platform, and measured expression of the tendon transcription factor Scleraxis. Through machine learning algorithms, we associated elevated Scleraxis levels with topological design parameters. Fabricating micro-topographies with optimal surface characteristics on larger surfaces allowed finding an improved expression of multiple tenogenic markers. However, long-term confluent culture conditions coincided with osteogenic marker expression and the loss of morphological characteristics. In contrast, passaging tenocytes which migrated from the tendon directly on the topography resulted in prolonged elongated morphology and elevated Scleraxis levels. This research provides new insights into how micro-topographies influence tenocyte cell fate, and supports the notion that micro-topographical design can be implemented in a new generation of tissue culture platforms for supporting the phenotype of tenocytes. STATEMENT OF SIGNIFICANCE: The challenge in controlling in vitro cell behavior lies in controlling the complex culture environment. Here, we present for the first time the use of micro-topographies as a biomechanical niche to support the phenotype of tenocytes. For this, we applied the TopoChip platform, a screening tool with 2176 unique micro-topographies for identifying feature characteristics associated with elevated Scleraxis expression, a tendon related marker. Large area fabrication of micro-topographies with favorable characteristics allowed us to find a beneficial influence on other tenogenic markers as well. Furthermore, passaging cells is more beneficial for Scleraxis marker expression and tenocyte morphology compared to confluent conditions. This study presents important insights for the understanding of tenocyte behavior in vitro, a necessary step towards tendon engineering.

Micro-scaled topographies direct differentiation of human epidermal stem cells.

Human epidermal stem cells initiate terminal differentiation when spreading is restricted on ECM-coated micropatterned islands, soft hydrogels or hydrogel-nanoparticle composites with high nanoparticle spacing. The effect of substrate topography, however, is incompletely understood. To explore this, primary human keratinocytes enriched for stem cells were seeded on a topographical library with over 2000 different topographies in the micrometre range. Twenty-four hours later the proportion of cells expressing the differentiation marker transglutaminase-1 was determined by high content imaging. As predicted, topographies that prevented spreading promoted differentiation. However, we also identified topographies that supported differentiation of highly spread cells. Topographies supporting differentiation of spread cells were more irregular than those supporting differentiation of round cells. Low topography coverage promoted differentiation of spread cells, whereas high coverage promoted differentiation of round cells. Based on these observations we fabricated a topography in 6-well plate format that supported differentiation of spread cells, enabling us to examine cell responses at higher resolution. We found that differentiated spread cells did not assemble significant numbers of hemidesmosomes, focal adhesions, adherens junctions, desmosomes or tight junctions. They did, however, organise the actin cytoskeleton in response to the topographies. Rho kinase inhibition and blebbistatin treatment blocked the differentiation of spread cells, whereas SRF inhibition did not. These observations suggest a potential role for actin polymerization and actomyosin contraction in the topography-induced differentiation of spread cells. STATEMENT OF SIGNIFICANCE: The epidermis is the outer covering of the skin. It is formed by layers of cells called keratinocytes. The basal cell layer contains stem cells, which divide to replace cells in the outermost layers that are lost through a process known as differentiation. In this manuscript we have developed surfaces that promote the differentiation of epidermal stem cells in order to understand the signals that control differentiation. The experimental tools we have developed have the potential to help us to devise new treatments that control diseases such as psoriasis and eczema in which epidermal stem cell proliferation and differentiation are disturbed.

Dynamic adaptation of mesenchymal stem cell physiology upon exposure to surface micropatterns.

Human mesenchymal stem (hMSCs) are defined as multi-potent colony-forming cells expressing a specific subset of plasma membrane markers when grown on flat tissue culture polystyrene. However, as soon as hMSCs are used for transplantation, they are exposed to a 3D environment, which can strongly impact cell physiology and influence proliferation, differentiation and metabolism. Strategies to control in vivo hMSC behavior, for instance in stem cell transplantation or cancer treatment, are skewed by the un-physiological flatness of the standard well plates. Even though it is common knowledge that cells behave differently in vitro compared to in vivo, only little is known about the underlying adaptation processes. Here, we used micrometer-scale defined surface topographies as a model to describe the phenotype of hMSCs during this adaptation to their new environment. We used well established techniques to compare hMSCs cultured on flat and topographically enhanced polystyreneand observed dramatically changed cell morphologies accompanied by shrinkage of cytoplasm and nucleus, a decreased overall cellular metabolism, and slower cell cycle progression resulting in a lower proliferation rate in cells exposed to surface topographies. We hypothesized that this reduction in proliferation rate effects their sensitivity to certain cancer drugs, which was confirmed by higher survival rate of hMSCs cultured on topographies exposed to paclitaxel. Thus, micro-topographies can be used as a model system to mimic the natural cell micro-environment, and be a powerful tool to optimize cell treatment in vitro.

Designed Surface Topographies Control ICAM-1 Expression in Tonsil-Derived Human Stromal Cells.

Fibroblastic reticular cells (FRCs), the T-cell zone stromal cell subtype in the lymph nodes, create a scaffold for adhesion and migration of immune cells, thus allowing them to communicate. Although known to be important for the initiation of immune responses, studies about FRCs and their interactions have been impeded because FRCs are limited in availability and lose their function upon culture expansion. To circumvent these limitations, stromal cell precursors can be mechanotranduced to form mature FRCs. Here, we used a library of designed surface topographies to trigger FRC differentiation from tonsil-derived stromal cells (TSCs). Undifferentiated TSCs were seeded on a TopoChip containing 2176 different topographies in culture medium without differentiation factors, then monitored cell morphology and the levels of ICAM-1, a marker of FRC differentiation. We identified 112 and 72 surfaces that upregulated and downregulated, respectively, ICAM-1 expression. By monitoring cell morphology, and expression of the FRC differentiation marker ICAM-1 via image analysis and machine learning, we discovered correlations between ICAM-1 expression, cell shape and design of surface topographies and confirmed our findings by using flow cytometry. Our findings confirmed that TSCs are mechano-responsive cells and identified particular topographies that can be used to improve FRC differentiation protocols.

How Not To Drown in Data: A Guide for Biomaterial Engineers.

High-throughput assays that produce hundreds of measurements per sample are powerful tools for quantifying cell-material interactions. With advances in automation and miniaturization in material fabrication, hundreds of biomaterial samples can be rapidly produced, which can then be characterized using these assays. However, the resulting deluge of data can be overwhelming. To the rescue are computational methods that are well suited to these problems. Machine learning techniques provide a vast array of tools to make predictions about cell-material interactions and to find patterns in cellular responses. Computational simulations allow researchers to pose and test hypotheses and perform experiments in silico. This review describes approaches from these two domains that can be brought to bear on the problem of analyzing biomaterial screening data.

NanoTopoChip: High-throughput nanotopographical cell instruction.

Surface topography is able to influence cell phenotype in numerous ways and offers opportunities to manipulate cells and tissues. In this work, we develop the Nano-TopoChip and study the cell instructive effects of nanoscale topographies. A combination of deep UV projection lithography and conventional lithography was used to fabricate a library of more than 1200 different defined nanotopographies. To illustrate the cell instructive effects of nanotopography, actin-RFP labeled U2OS osteosarcoma cells were cultured and imaged on the Nano-TopoChip. Automated image analysis shows that of many cell morphological parameters, cell spreading, cell orientation and actin morphology are mostly affected by the nanotopographies. Additionally, by using modeling, the changes of cell morphological parameters could by predicted by several feature shape parameters such as lateral size and spacing. This work overcomes the technological challenges of fabricating high quality defined nanoscale features on unprecedented large surface areas of a material relevant for tissue culture such as PS and the screening system is able to infer nanotopography - cell morphological parameter relationships. Our screening platform provides opportunities to identify and study the effect of nanotopography with beneficial properties for the culture of various cell types. STATEMENT OF SIGNIFICANCE: The nanotopography of biomaterial surfaces can be modified to influence adhering cells with the aim to improve the performance of medical implants and tissue culture substrates. However, the necessary knowledge of the underlying mechanisms remains incomplete. One reason for this is the limited availability of high-resolution nanotopographies on relevant biomaterials, suitable to conduct systematic biological studies. The present study shows the fabrication of a library of nano-sized surface topographies with high fidelity. The potential of this library, called the 'NanoTopoChip' is shown in a proof of principle HTS study which demonstrates how cells are affected by nanotopographies. The large dataset, acquired by quantitative high-content imaging, allowed us to use predictive modeling to describe how feature dimensions affect cell morphology.

TopoWellPlate: A Well-Plate-Based Screening Platform to Study Cell-Surface Topography Interactions.

The field of biomaterial engineering is increasingly using high-throughput approaches to investigate cell-material interactions. Because most material libraries are prepared as chips, immunofluorescence-based read-outs are used to uniquely image individual materials. This paper proposes to produce libraries of materials using a well-based strategy in which each material is physically separated, and thus compatible with standard biochemical assays. In this work, the TopoWellPlate, a novel system to study cell-surface topography interaction in high-throughput is presented. From a larger library of topographies, 87 uniquely defined bioactive surface topographies are identified, which induce a wide variety of cellular morphologies. Topographically enhanced polystyrene films are fabricated in a multistep cleanroom process and served as base for the TopoWellPlate. Thermal bonding of the films to bottomless 96-well plates results in a cell culture ready, topographically enhanced, 96-well plate. The overall metabolic activity of bone marrow-derived human mesenchymal stem cells is measured to show the functionality of the TopoWellPlate as a screening tool, which showed a 2.5-fold difference range in metabolic activity per cell. TopoWellPlates of this and other topographical designs can be used to analyze cells using the wealth of standardized molecular assays available and thus disclose the mechanisms of biomaterials-induced mechanotransduction.

Micro-Topographies Promote Late Chondrogenic Differentiation Markers in the ATDC5 Cell Line.

Chemical and mechanical cues are well-established influencers of in vitro chondrogenic differentiation of ATDC5 cells. Here, we investigate the role of topographical cues in this differentiation process, a study not been explored before. Previously, using a library of surface micro-topographies we found some distinct patterns that induced alkaline phosphatase (ALP) production in human mesenchymal stromal cells. ALP is also a marker for hypertrophy, the end stage of chondrogenic differentiation preceding bone formation. Thus, we hypothesized that these patterns could influence end-stage chondrogenic differentiation of ATDC5 cells. In this study, we randomly selected seven topographies among the ALP influencing hits. Cells grown on these surfaces displayed varying nuclear shape and actin filament structure. When stimulated with insulin-transferrin-selenium (ITS) medium, nodule formation occurred and in some cases showed alignment to the topographical patterns. Gene expression analysis of cells growing on topographical surfaces in the presence of ITS medium revealed a downregulation of early markers and upregulation of late markers of chondrogenic differentiation compared to cells grown on a flat surface. In conclusion, we demonstrated that surface topography in addition to other cues can promote hypertrophic differentiation suitable for bone tissue engineering.