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. 2026 Feb 18;15(2):bio062212. doi: 10.1242/bio.062212

Gelatin-methacryloyl hydrogel stiffness influences epithelial-mesenchymal transition in MCF7 but not MDA-MB-231 breast cancer cells in 3D culture

Jessika A Wise 1,2, Margaret J Currie 1, Tim B F Woodfield 2, Khoon S Lim 2,3,✉, Elisabeth Phillips 1,✉
PMCID: PMC12958301  PMID: 41705552

ABSTRACT

This study focuses on advancing the understanding of breast cancer through 3D in vitro models, which provide biomimetic environments superior to many 2D cultures and animal models. Ex vivo analyses show that malignant breast tissues exhibit increased stiffness with higher tumour grade. Tumour stiffening is associated with altered cell phenotype, promoting progression, invasion, and metastasis. This research aims to design 3D models that mimic the evolving tumour microenvironment to study how matrix stiffness affects breast cancer cell behaviour. Using gelatin-methacryloyl (GelMA) hydrogels, we investigated the phenotypic responses of MCF7 and MDA-MB-231 cells in 3D models of clinically relevant stiffness. A visible-light photoinitiation system enabled precise control of hydrogel mechanics while supporting biocompatibility and long-term cell viability. Over a 21-day culture period, MCF7 cells exhibited partial epithelial-mesenchymal transition in stiff hydrogels, showing altered morphology, downregulating E-cadherin and upregulating N-cadherin and Vimentin. Comparatively, MDA-MB-231 cells showed no such changes. Phenotype remained stable in soft hydrogels for both cell lines. This study demonstrates the impact of microenvironmental stiffness on breast cancer cell phenotype and highlights 3D GelMA hydrogels as a platform to investigate tumour microenvironment dynamics. The findings provide insights into how matrix stiffness influences EMT and breast cancer behaviour in biomimetic settings.

Keywords: Breast cancer, 3D cell culture, Hydrogel, Matrix stiffness, Epithelial-mesenchymal transition, MCF7

Summary: This study uses 3D cell culture in hydrogels to show how matrix stiffness affects breast cancer cells, including changes associated with epithelial-mesenchymal transition.

INTRODUCTION

The tumour microenvironment (TME) is a critical factor in breast cancer progression and consists of both cellular and acellular components (Pallegar and Christian, 2020). The acellular TME includes elements such as the extracellular matrix (ECM), soluble factors (e.g. cytokines, growth factors and chemokines), mechanical cues and biochemical (e.g. oxygen and nutrient) gradients. The ECM provides structural support and biochemical signals, while soluble factors regulate tumour cell behaviour and communication within the TME. Breast cancer cells interact with the TME, resulting in a supportive ‘reactive tumour stroma’, believed to promote cancer growth (Wiseman and Werb, 2002). The properties of the ECM significantly influence tumour biology, affecting breast cancer cell adhesion, metabolism, proliferation, differentiation, migration, and therapeutic resistance (Tang et al., 2021; Shah et al., 2022; Malandrino et al., 2018; Levental et al., 2009). The stiffness of the ECM is of particular significance, as it has been observed that human breast tumours are stiffer than healthy breast tissue, and increasing stiffness has been linked to higher tumour grade (Ramião et al., 2016; Samani et al., 2007; Van Houten et al., 2003; Krouskop et al., 1998; Wellman et al., 1999). Mechanical testing of ex vivo patient tissues has shown normal fibro-glandular breast tissue has a stiffness of roughly 3.2 kPa, while invasive ductal carcinomas (IDCs) increase in stiffness with the grade of cancer (ranging from 10.4 to 42.5 kPa from low to high grade IDC, respectively) (Ramião et al., 2016; Samani et al., 2007, 2003).

The development of 3D in vitro culture models for breast cancer offers a more realistic representation of the in vivo microenvironment than traditional 2D in vitro culture techniques (Yamada and Cukierman, 2007; Imamura et al., 2015). In these models, cells are cultured in a matrix that more closely resembles the in vivo tissue and directly impacts mechanical properties and cell-to-cell interactions (Duval et al., 2017). These models are also more cost effective and efficient for screening new therapeutic treatments than animal models (Langhans, 2018; Fang and Eglen, 2017).

Gelatin-methacryloyl (GelMA) hydrogels are an appealing biomaterial for 3D models due to their tuneable physico-mechanical properties (Kaemmerer et al., 2014; Klotz et al., 2016). For instance, hydrogel stiffness can be adjusted by varying the amount of macromer, while maintaining the hydrogel's ability to allow liquid diffusion (Kaemmerer et al., 2014). Research has shown that cells cultured in GelMA hydrogels exhibit high viability, metabolism, adhesion, and proliferation, as well as the formation of spheroids by some cell types (Kaemmerer et al., 2014; Yue et al., 2015; Lim et al., 2019; Krishnamoorthy et al., 2019). However, research on the effects of GelMA hydrogel culture on breast cancer cells is limited, with only a few studies conducted over a 14-day period, primarily focused on cell viability, metabolic activity, and migration (Loessner et al., 2016; Casey et al., 2017; Berger et al., 2019).

This study is the first to utilize GelMA hydrogels crosslinked with a visible light photoinitiator system in breast cancer research. We employed a photoinitiator system comprising ruthenium/sodium persulfate (Ru/SPS) and visible light (400-450 nm) to rapidly fabricate biocompatible 3D hydrogels that enhance light penetration and maintain high cell viability (Lim et al., 2019). The visible light photo-crosslinking used in this study offers an alternative to commonly used UV crosslinking approaches, which have been shown to lead to chromosomal damage and reduced cell viability (Loessner et al., 2016).

The aim of this study was to investigate the effects of matrix stiffness on breast cancer cell phenotype and behaviour using 3D visible light-crosslinked GelMA hydrogels encapsulated with two distinct breast cancer cell lines: MCF7 cells, representing the epithelial-like, Luminal A, hormone responsive breast cancer subtype; and MDA-MB-231 cells, representative of the mesenchymal-like triple receptor-negative breast cancer subtype. By comparing the responses of these cell lines to clinically relevant hydrogel stiffness, this study provides valuable insights into how breast cancer cells respond to matrix stiffness in a controlled 3D hydrogel model, modelling key mechanical aspects of the TME.

RESULTS AND DISCUSSION

Hydrogel characterization and cell incorporation

In previous studies, acellular hydrogels have been used to measure hydrogel properties (Pradhan and Slater, 2019; Nichol et al., 2010). However, it is well established that encapsulation of cells can influence the photo-crosslinking process and introduces an extra component that could affect the mechanical properties of the hydrogel through incomplete crosslinking.

Therefore, to create breast cancer cell-laden GelMA hydrogels of varying mechanical stiffness, 5 million cells/ml were encapsulated into hydrogels that contained 5%, 7.5%, and 10% GelMA macromer by weight. The concentration of 5 million cells/ml was selected as it falls within the reported range of concentrations used in 3D models, which typically range from 1 to 15 million cells/ml (Kaemmerer et al., 2014; Lim et al., 2019; Nichol et al., 2010; Zhu et al., 2019; Benton et al., 2009). The range of GelMA macromer concentrations (5%, 7.5%, and 10%) was selected based on previous research that used these macromer concentrations to produce hydrogels with mechanical stiffness similar to that of normal and malignant ex vivo patient breast tissues (Samani et al., 2007; Krouskop et al., 1998). The physical properties of the hydrogel were determined by measuring the hydrogel mass swelling ratio (q), soluble fraction (%), and compressive modulus (kPa).

The mass swelling ratio of hydrogels was measured to determine their swelling capacity. Cell-free GelMA hydrogel controls showed that increasing macromer concentration led to a decrease in mass swelling ratio (Fig. 1A). The addition of MDA-MB-231 cells slightly increased the mass swelling of 5 wt% hydrogels, but not MCF7 cells. The mass swelling ratio of hydrogels was not significantly impacted by the addition of either cell line in 7.5 wt% and 10 wt% GelMA hydrogels. MDA-MB-231- and MCF7-laden hydrogels exhibited a similar decrease in mass swelling ratio as cell-free hydrogels with increasing macromer concentration.

Fig. 1.

Fig. 1.

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Impact of breast cancer cells on GelMA hydrogel properties. (A-C) Mass swelling ratio (q) (n=3; A), soluble fraction (%) (n=3; B) and compressive modulus (kPa; C) of cell-free and breast cancer cell-laden (5 million cells/ml) GelMA hydrogels (n=6) (hydrogels were 2 mm high). (D,E) MDA-MB-231 (D) or MCF7 (E) breast cancer cells were encapsulated at 0, 1, 2, 5, 10 or 15 million cells/ml within GelMA hydrogels of 5, 7.5 or 10 wt% (n=3 for 1, 2, 10 and 15 million cells/ml data and n=6 for cell-free and 5 million cells/ml data). (F) Measurement of oxygen concentration (%) throughout the depth of cell-free GelMA hydrogels of different stiffness (hydrogels were 1 mm high). Bars represent means±s.d. ns, not significant; *P≤0.05, **P≤0.01, ***P≤0.001, ****P≤0.0001 by two-way ANOVA with Tukey's multiple comparisons test.

The soluble fraction of a hydrogel refers to the percentage of macromer that remains un-crosslinked and subsequently washes out of the hydrogel network. It was observed that the soluble fraction increased as the macromer concentration increased in cell-free GelMA hydrogels (Fig. 1B). In comparison, the addition of breast cancer cell lines did not significantly impact the soluble fraction of GelMA hydrogels.

As expected, the compressive modulus of GelMA hydrogels, both cell free and cell laden, increased significantly with increasing macromer concentration (Fig. 1C). The stiffness of 5 wt% and 7.5 wt% hydrogels did not change significantly with the addition of either MDA-MB-231 or MCF7 breast cancer cells. However, adding either cell type at a concentration of 5 million cells/ml reduced the stiffness of 10 wt% hydrogels significantly. There was no significant difference in the stiffness of 10 wt% hydrogels between those loaded with MDA-MB-231 or MCF7 cells.

In general, adding breast cancer cells at a concentration of 5 million cells/ml had little effect on the swelling and soluble fraction properties of GelMA hydrogels with 5, 7.5, and 10 wt% macromer, which is consistent with previously published literature (Kaemmerer et al., 2014; Lim et al., 2019; Nichol et al., 2010; Zhu et al., 2019; Benton et al., 2009). Only the 10 wt% hydrogels showed a decrease in stiffness with the addition of breast cancer cells at 5 million cells/ml.

To investigate whether the decrease in stiffness observed in 10 wt% GelMA hydrogels with 5 million cells/ml breast cancer cell encapsulation was influenced by cell concentration, a variety of breast cancer cell concentrations (0, 1, 2, 5, 10, and 15 million cells/ml) were introduced into GelMA hydrogels, and the corresponding compressive moduli were evaluated (Fig. 1D,E). The presence of MDA-MB-231 or MCF7 cells at various concentrations did not significantly affect the stiffness of 5 wt% and 7.5 wt% GelMA hydrogels. However, in the case of 10 wt% GelMA hydrogels, the addition of breast cancer cells at all concentrations led to a significant reduction in stiffness (Fig. 1D,E). Increasing cell concentration has been reported to reduce hydrogel stiffness (Mouser et al., 2016; Levett et al., 2014). In 10 wt% GelMA hydrogels, all tested cell concentrations (1-15 million cells/ml) led to a reduction in stiffness compared to acellular controls. However, the decrease was not concentration dependent, and higher cell concentrations did not further reduce stiffness. Based on these results, a density of 5 million cells/ml was chosen to balance hydrogel integrity with sufficient cell numbers for downstream analyses.

At each GelMA macromer concentration, MDA-MB-231-laden hydrogels had a mean stiffness of 11.7 kPa (5 wt%), 22.9 kPa (7.5 wt%), and 32.7 kPa (10 wt%), while MCF7-laden hydrogels had a mean stiffness of 11.3 kPa (5 wt%), 19.9 kPa (7.5 wt%), and 28.2 kPa (10 wt%). Therefore, the range of GelMA hydrogel stiffness produced in this current study provided a panel of hydrogels that mimic the stiffness observed in breast TMEs with increasing grade (ranging from 10.4 in low-grade to 42.5 kPa in high-grade IDC) (Ramião et al., 2016; Samani et al., 2007, 2003), allowing assessment of the way different breast cancer cell types respond to these microenvironments.

Solid tumours are known to contain oxygen gradients, which can have significant effects on breast cancer phenotype and behaviours, such as migration and invasion (Byrne et al., 2014; Campillo et al., 2019; Lewis et al., 2017; Milotti et al., 2017). To determine whether such gradients existed within the GelMA hydrogels, oxygen concentrations were measured in 5, 7.5, and 10 wt% hydrogels. Measurements were taken in a top-down manner throughout the depth of cell-free hydrogels, with 0 µm indicating the top and 1000 µm indicating the bottom of the hydrogel. Hydrogels with a height of 1 mm were assessed for direct comparison with subsequent cell response experiments. As expected, oxygen concentration decreased steadily with increasing hydrogel depth in all samples, with 10 wt% GelMA hydrogels exhibiting a significantly lower oxygen concentration than 5 wt% GelMA hydrogels at 200 µm and deeper (Fig. 1F). The lowest concentration detected was 17% O2 at the base of 10 wt% hydrogels, which does not reach levels that would be considered hypoxic in tumour tissue (<1% O2) (Tang et al., 2021; Campillo et al., 2019; Muz et al., 2015). In the current study, a regional separation into the ‘centre’ and ‘edge’ regions of the hydrogel was employed to assess cellular response to the different O2 concentrations that exist within these hydrogel regions (see Fig. 7 for a visual representation of this division). The porosity of hydrogels is an important parameter, as it influences the diffusion of nutrients, signalling molecules, and therapeutic agents within the tumour microenvironment. Exploring hydrogel porosity could provide further insights into how physical properties of the extracellular matrix impact cancer cell behaviour and may serve as a valuable future direction for this work.

Fig. 7.

Fig. 7.

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Schematic of regional image analysis in GelMA hydrogels. (1) Formalin-fixed and OCT embedded hydrogels were cryosectioned to produce 30 µm thick sections, which were cut in a top-down manner onto adhesive microscope slides. (2) These sections were then immunofluorescently stained for proteins of interest and imaged on a fluorescence microscope. (3) Images were quantified based on the region of the hydrogel, which were separated into centre and edge regions. The edge region was defined as 200 µm from the outer top and side edges of the hydrogels and the centre region as the remaining region from 200 µm into the hydrogel and deeper. Created in BioRender by Wise, J. A. (2026). https://BioRender.com/hi79lt6. This figure was sublicensed under CC-BY 4.0 terms.

Cell viability, metabolic activity and proliferation in 3D GelMA hydrogels

The response of both breast cancer cell lines to 5 wt% (soft), 7.5 wt% (medium) and 10 wt% (stiff) GelMA hydrogels were examined at day 1, 7, 14, and 21 of culture. MDA-MB-231 cells showed reduced viability in 7.5 wt% and 10 wt% hydrogels from day 7 onwards, while MCF7 cells only showed reduced viability in 10 wt% hydrogels at day 21 of culture (Fig. 2A,B). Breast cancer cellular metabolic activity increased between day 1 and day 21 in all % GelMA hydrogels (Fig. 2C,D). Cell proliferation, as measured by DNA content, was greatest in both breast cancer cell lines when cultured in 5 wt% (soft) hydrogels (Fig. 2E,F). Previously reported studies that used 3D hydrogel cultures with a stiffness of around 5-15 kPa yielded similar findings to the current study (Nichol et al., 2010; Jiang et al., 2020; Jabbari et al., 2015). Specifically, these studies demonstrated that softer hydrogel conditions are conducive to cell functionality, as determined by assays measuring viability, metabolism, proliferation, or migration (Nichol et al., 2010; Jiang et al., 2020; Jabbari et al., 2015). The 7.5 wt% (medium) stiffness hydrogels did not exhibit significant differences to soft or stiff hydrogels and were therefore not further examined in this study.

Fig. 2.

Fig. 2.

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Breast cancer cell behaviour in GelMA hydrogels of different stiffness. (A,C,E) MDA-MB-231 cells: cell viability (%) (n=4; A), metabolic activity (n=4; C) and fold change of DNA content (µg/sample) (n=3; E). (B,D,F) MCF7 cells: cell viability (%) (n=3; B), metabolic activity (n=3; D) and fold change of DNA content (µg/sample) (n=3; F) in soft (5 wt%), medium (7.5 wt%) and stiff (10 wt%) GelMA hydrogels over 21 days. Hydrogels were 1 mm high. Bars or data points represent means±s.d. *P≤0.05, **P≤0.01 by two-way ANOVA with Tukey's multiple comparisons test. rfu, relative fluorescence units.

Cell morphology and spatial growth patterns in 3D GelMA hydrogels

MDA-MB-231 cells demonstrated a spindle-like, elongated morphology and formed connected networks within GelMA hydrogels, with increased multilayer cell density observed at the outer edge of both soft and stiff hydrogels, shown by F-actin staining (Fig. 3A). Angiotool software was used to quantify the junction density per area of MDA-MB-231 cells measured within soft and stiff hydrogels, separated into ‘edge’ and ‘centre’ regions (Fig. 3B). MDA-MB-231 cells developed the highest number of connections between cells over time within the edge region of hydrogels irrespective of hydrogel stiffness. Additionally, the centre region of soft hydrogels displayed greater capacity for formation of cellular junctions than the centre region of stiff hydrogels. This difference in MDA-MB-231 cell growth pattern suggests that these cells may be more proliferative within the edge region of these GelMA hydrogels.

Fig. 3.

Fig. 3.

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Breast cancer cell growth patterns within GelMA hydrogels of different stiffness. (A) Representative images of MDA-MB-231 cells in soft (5 wt%) and stiff (10 wt%) GelMA hydrogels at days 1 and 21; zoomed inset images are of centre and edge regions of the hydrogel. (B) Quantification of mean MDA-MB-231 cell junction density normalized to area (junction density/area) within the centre and edge regions of soft (5 wt%) and stiff (10 wt%) GelMA hydrogels at day 1, 7, 14 and 21 in culture. (C) Representative images of MCF7 cells in soft (5 wt%) and stiff (10 wt%) GelMA hydrogels at days 1 and 21; zoomed inset images are of centre and edge regions of the hydrogel. (D,E) Quantification of mean MCF7 aggregate area (µm; D) and MCF7 cell coverage (%; E), within the centre and edge regions of soft (5 wt%) and stiff (10 wt%) GelMA hydrogels at day 1, 7, 14 and 21 in culture. Hydrogels were 1 mm high. F-actin filaments were stained with rhodamine phalloidin (red) and nuclei with DAPI (blue). Bars represent means±s.d. (n=3). ns, not significant; *P≤0.05, **P≤0.01, ***P≤0.001, ****P≤0.0001 by two-way ANOVA with Tukey's multiple comparisons test. Scale bars: 100 µm (20 µm in inset zoomed images).

F-actin staining revealed that MCF7 cells in stiff GelMA hydrogels adopted more elongated and protrusive morphologies, particularly at cluster peripheries, which were observed to be more irregular in shape. In contrast, cells in soft hydrogels at day 21 were rounded and clustered with strong cell-cell adhesion (Fig. 3C). The aggregate area (µm) and cell coverage percentage (%) were quantified within the centre and edge regions of soft and stiff hydrogels using ImageJ software (Fig. 3D,E). These results suggest that the MCF7 cells in the edge region of hydrogels grow in a similar pattern (aggregate size and cell coverage percentage) regardless of hydrogel stiffness (Fig. 3D,E). In addition, the centre region of both soft and stiff hydrogels showed similarly low aggregate size and cell coverage percentage, displaying no difference in response to stiffness. This highlights the ability of MCF7 cells to develop similar growth patterns despite hydrogel stiffness, but preferentially in the edge region of hydrogels, and this may also be due to a greater proliferation within the edge region.

Ki67 is a protein expressed by cells at every stage of proliferation in the cell cycle and is absent in G0 or quiescent cells (Juríková et al., 2016; Gerdes et al., 1983; Hashmi et al., 2019). Based on the American Joint Committee on Cancer (AJCC) 2018 and the International Ki67 in Breast Cancer Working Group (IKWG) 2021, the expression of Ki67 can be broadly separated into low (<10%), intermediate (10-20%), high (>20%) and very high (>30%) levels (Vissio et al., 2019; Nielsen et al., 2021). Higher rates of proliferation are associated with poorer outcomes, and triple-negative breast cancers have been shown to exhibit much higher levels of Ki67 expression compared to Luminal A breast cancers (Hashmi et al., 2019; Inwald and Klinkhammer-Schalke, 2013; Soliman and Yussif, 2016). The proliferative rate of MDA-MB-231 and MCF7 breast cancer cells were found to be similar when cultured in GelMA hydrogels (Fig. 4A,C), with both breast cancer cell lines displaying medium (10-20% Ki67-positive cells) to high (>20% Ki67-positive cells) proliferative rates (Fig. 4B,D). Results also showed that the proliferative rate of these cells was not greatly modified by the GelMA hydrogel stiffness or region within the hydrogel (Fig. 4B,D).

Fig. 4.

Fig. 4.

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Breast cancer cell proliferative rate within GelMA hydrogels of different stiffness. (A) Representative images of MDA-MB-231 cells in soft (5 wt%) and stiff (10 wt%) GelMA hydrogels at days 1 and 21; zoomed inset images are of centre and edge regions of the hydrogel. (B) Quantification of the percentage (%) of proliferative (Ki67+) MDA-MB-231 cells within the centre and edge regions of soft and stiff GelMA hydrogels. (C) Representative images of MCF7 cells in soft (5 wt%) and stiff (10 wt%) GelMA hydrogels at days 1 and 21; zoomed inset images are of centre and edge regions of the hydrogel. (D) Quantification of the percentage (%) of proliferative (Ki67+) MCF7 cells within the centre and edge regions of soft and stiff GelMA hydrogels. Nuclei are stained with DAPI (blue), and proliferative cells are stained for Ki67 (red). Bars represent means±s.d. (n=3). *P≤0.05, **P≤0.01, ****P≤0.0001 by two-way ANOVA with Tukey's multiple comparisons test. Scale bars: 100 µm (or, 20 µm in inset zoomed images).

The findings of this study suggest that the growth patterns observed in both MDA-MB-231 and MCF7 cells may not be solely due to cell proliferation, but could also be influenced by other mechanisms, such as cell migration within the hydrogel. MDA-MB-231 cells have previously been reported to be highly migratory in both 2D (Chao et al., 2010; Pai et al., 2013; Wang et al., 2004) and 3D (Peela et al., 2016) cultures, while MCF7 cells show limited migratory capacity in these systems (Peela et al., 2016; Tasdemir et al., 2018; Neve et al., 2006; Chen and Cho, 2011). Additionally, the differences in oxygen concentration within the hydrogels, especially the lower oxygen concentration in the centre region, may also play a role in the observed growth patterns. Previous studies have shown that MDA-MB-231 cells migrate towards regions of higher oxygen concentration (Yahara et al., 2016), which may explain the increased junction density observed in the edge region of the hydrogel. However, this cannot fully account for the higher aggregate area and cell coverage percentage observed in the edge regions of the hydrogel in MCF7 cells, which are not known to be migratory. Therefore, further investigation is needed to elucidate the mechanisms by which different stiffness GelMA hydrogel microenvironments influence cellular growth patterns, including whether oxygen gradients in combination with increased hydrogel stiffness or other factors, such as nutrient gradients, are responsible for the observed differences.

Matrix stiffness-dependent epithelial-mesenchymal transition marker expression

Epithelial-mesenchymal transition (EMT) refers to a multifaceted process that enables cancer cells to enhance their migratory and invasive properties, ultimately leading to metastatic spread from the primary tumour (Gilbert and Slingerland, 2013; Wang and Zhou, 2011; Lima et al., 2016). This intricate process involves the downregulation of cell-to-cell adhesions and the upregulation of migratory and invasive phenotypes (Mrozik et al., 2018; Vuoriluoto et al., 2011).

Results indicated that the mesenchymal-like MDA-MB-231 breast cancer cells did not exhibit changes in the expression of EMT-associated proteins E-cadherin (Fig. 5A,B), N-cadherin (Fig. 5E,F), or Vimentin (Fig. 5I,J) after 21 days of culture in either soft or stiff GelMA hydrogels, which was not unexpected given they are characterized as having already undergone partial-EMT (Pai et al., 2013; Liu et al., 2015; Ko et al., 2019; Bhandari et al., 2019). However, epithelial-like MCF7 breast cancer cells showed a decrease in the epithelial marker E-cadherin (Fig. 5C,D) and increases in the expression of mesenchymal markers N-cadherin (Fig. 5G,H) and Vimentin (Fig. 5K,L) when cultured in stiff (10 wt%) GelMA hydrogels. This change in phenotype was only observed in MCF7 cells cultured in stiff (10 wt%) GelMA hydrogels, while no changes in E-cadherin, N-cadherin, or Vimentin expression were observed in MCF7 cells cultured in soft (5 wt%) GelMA hydrogels, suggesting that increased matrix stiffness may promote EMT-associated phenotypic changes in breast cancer cells with an epithelial baseline phenotype, such as MCF7 cells (Ramião et al., 2016; Samani et al., 2007, 2003; Van Houten et al., 2003; Krouskop et al., 1998; Wellman et al., 1999). Intermediate stiffness hydrogels (7.5 wt%) were not assessed for EMT marker expression in this study. Future work including this condition could help clarify whether stiffness-induced phenotypic changes occur gradually or require a threshold.

Fig. 5.

Fig. 5.

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Breast cancer cell expression of E-cadherin, N-cadherin and Vimentin when cultured in GelMA hydrogels of different stiffness. (A,E,I) Representative images of MDA-MB-231 cells stained for E-cadherin (A), N-cadherin (E) and Vimentin (I), in soft (5 wt%) and stiff (10 wt%) hydrogels at days 1 and 21. (B,F,J) Quantification of mean MDA-MB-231 E-cadherin (B), N-cadherin (F) and Vimentin (J) staining intensity per cell in soft and stiff hydrogels at days 1 and 21. (C,G,K) Representative images of MCF7 cells stained for E-cadherin (C), N-cadherin (G) and Vimentin (K), in soft and stiff hydrogels at days 1 and 21. (D,H,L) Quantification of mean MCF7 E-cadherin (D), N-cadherin (H) and Vimentin (L) staining intensity per cell in soft and stiff hydrogels at days 1 and 21. Cells were stained with DAPI (nuclei, blue) and for E-cadherin, N-cadherin or Vimentin (red). Bars represent means±s.d. (n=3). *P≤0.05, **P≤0.01, ***P≤0.001, ****P≤0.0001 by two-way ANOVA with Tukey's multiple comparisons test. Scale bars: 100 µm. The data shown in this figure are also presented in Fig. S1 with regional zoomed inset images. (M) Graphical summary of major findings: culture of MDA-MB-231 and MCF7 breast cancer cells within soft (11 kPa) GelMA hydrogels maintained the EMT phenotypes of both cell lines over a 21-day culture, while culture within stiff (28 kPa) GelMA hydrogels resulted in MCF7 cells undergoing partial EMT (downregulation of E-cadherin and upregulation of N-cadherin and Vimentin), revealing a breast cancer cell line specific response to matrix stiffness. Created in BioRender by Wise, J. A. (2026). https://BioRender.com/ivd2fjj. This figure was sublicensed under CC-BY 4.0 terms.

While EMT markers were altered in MCF7 cells cultured in stiff hydrogels, cells retained some cluster organization, indicating a partial or hybrid EMT state. Morphological changes observed via F-actin staining (Fig. 3) (more elongated and protrusive cells in stiff hydrogels versus rounded clusters in soft hydrogels) support this interpretation. Altered hydrogel stiffness may regulate EMT through mechanotransduction pathways, whereby cells sense and respond to changes in the mechanical properties of their environment. Such mechanical cues can influence gene expression and phenotypic switching, contributing to the partial EMT phenotypes observed in these MCF7 cultures. Additional analyses, such as quantitative PCR or western blotting to assess EMT marker regulation, would provide further validation of the phenotypic changes observed. Definitive confirmation of EMT would require evaluation of additional epithelial markers, EMT transcription factors, relevant signalling pathways, and functional assays of cell motility or invasion. Therefore, these results should be interpreted as indicative of stiffness-associated partial EMT rather than full EMT induction.

Reduced viability (Fig. 2A,B) in stiff GelMA hydrogels, particularly for MDA-MB-231 cells, indicates that increased matrix stiffness imposed a greater physiological stress on cells over time. Importantly, despite this loss in viability, EMT marker expression in the surviving MDA-MB-231 population remained unchanged, suggesting that stiffness did not further drive EMT in this already mesenchymal-like line. This supports the interpretation that the absence of EMT marker changes is not masked by cell loss, but reflects phenotypic stability under mechanical stress. In contrast, MCF7 cells largely maintained viability and exhibited stiffness-associated EMT marker and morphological changes within the viable population, indicating a genuine stiffness-dependent phenotypic response rather than an artefact of reduced cell survival.

When centre and edge regional data were separated (Fig. S1, zoomed inset images), it was noted that the expression of E-cadherin or N-cadherin was not affected by the hydrogel region. However, the elevated expression of Vimentin at day 21 was observed only in the centre region of 10 wt% (stiff) hydrogels. Furthermore, the decrease in E-cadherin and increase in N-cadherin and Vimentin expression could facilitate the migratory behaviour of MCF7 cells, leading to their potential movement towards the edge region of stiff hydrogels. This could explain the larger aggregate area/cell coverage percentage detected in that region. However, it does not explain how the same trend in growth patterns was observed in soft hydrogels, where MCF7 cells maintain expression of E-cadherin and do not upregulate N-cadherin and Vimentin between day 1 and day 21. Previously published work using collagen gels showed that MCF7 cells underwent a reduction in E-cadherin expression and upregulation of EMT markers (Snail, Slug, TWIST1/2, Vimentin and β-catenin) (Chen et al., 2012); however, they performed no analyses of gel properties or mechanical stiffness. As a result, this is the first report to our knowledge of hydrogel stiffness differentially influencing the EMT status of encapsulated MCF7 breast cancer cells (see Fig. 5M for summary).

Although our 3D GelMA hydrogel model enables controlled investigation of stiffness-dependent phenotypic changes, it represents a reductionist system. In vivo, tumour cells experience heterogeneous stiffness and interactions with stromal and immune cells, which are not captured here. Future work incorporating additional tumour microenvironment components could enhance translational relevance. A potential application of this hydrogel system is the culture of patient-derived tumour cells under defined stiffness conditions. This approach could be used to investigate the capacity for EMT phenotypic switching in individual tumours and to explore therapeutic responses, highlighting the potential for a personalized medicine approach.

Conclusions

This study explored the use of a 3D GelMA hydrogel model and tuneable visible light crosslinking system, in which the stiffness of the hydrogel can be adjusted by altering the macromer concentration. The study aimed to investigate the impact of matrix stiffness on breast cancer cell behaviour and phenotype over a 21-day culture period using GelMA hydrogels of clinically relevant stiffness. The results showed that the response of breast cancer cells to varied hydrogel stiffness differed between cell lines of epithelial or mesenchymal phenotype. MCF7 (epithelial-like, hormone responsive, Luminal A) breast cancer cells exhibited an upregulation of mesenchymal markers N-cadherin and Vimentin, with downregulation of epithelial marker E-cadherin when cultured in stiff GelMA hydrogels (10 wt%; 28 kPa). However, stiff hydrogel culture (10 wt%; 33 kPa) had no impact on the expression of E-cadherin, N-cadherin, or Vimentin in MDA-MB-231 (mesenchymal-like, triple receptor-negative breast cancer) cells. Furthermore, maintaining the phenotype of MCF7 and MDA-MB-231 breast cancer cells for 21 days was achievable by culture in soft hydrogels (5 wt%; 11.3-11.7 kPa). This study emphasizes the importance of carefully controlling hydrogel mechanical properties to preserve or modify breast cancer cell phenotype during 3D in vitro culture. Moreover, it provides a novel platform for studying the impact of matrix stiffness on the phenotype of various tumour-associated cell types, as well as the molecular mechanisms underlying cancer cell EMT, invasion and metastasis.

MATERIALS AND METHODS

Cell culture

The human breast cancer cell lines MDA-MB-231 (HTB-26™) and MCF7 (HTB-22™) were obtained from the American Tissue Culture Collection (ATCC®; Manassas, VA, USA). The cells were cultured in high-glucose Dulbecco's Modified Eagle Medium (Gibco, USA) supplemented with 10% fetal bovine serum (Gibco, USA), 1% penicillin-streptomycin (Thermo Fisher Scientific, USA) and 0.1% amphotericin B solution (Sigma-Aldrich, USA) under aseptic conditions in a humidified 37°C incubator with 5% CO₂. Experiments were performed within the first 28 passages of cell culture, and cell lines tested negative for mycoplasma contamination.

GelMA hydrogel preparation

GelMA synthesis was carried out as previously described (Loessner et al., 2016). Briefly, a 10 w/v% solution was prepared by dissolving gelatin (from porcine skin) in 50°C 1× PBS solution and 0.6 g of methacrylic anhydride added per gram of gelatin. Following dialysis against deionized water, the solution was then pH adjusted to 7.4 and sterile filtered (0.2 μm pore size) before being frozen and lyophilized. This resulted in GelMA with a 58% degree of functionalization. To produce breast cancer cell-laden GelMA hydrogels, the lyophilized GelMA was dissolved in 1× PBS to produce 5%, 7.5%, and 10% wt% solutions, and pelleted MDA-MB-231 or MCF7 breast cancer cells were incorporated at the indicated final concentration of cells/ml. The photoinitiators Tris (2,2′-dipyridyl)dichloro-ruthenium(II) hexahydrate (Ru) and sodium persulfate (SPS) were added at 0.5 and 5 mM, respectively, and the resulting solution was pipetted into silicone moulds (1 mm deep and 5 mm diameter for biological studies, 2 mm deep and 5 mm diameter for mechanical testing). Crosslinking was performed using visible light (400-450 nm) with an intensity of 30 mW/cm² for 180 s (OmniCure S1500, Excelitas Technologies with a Rosco IR/UV filter). Cell-laden hydrogels were transferred to individual wells of a 48-well plate with 500 µl of cell culture media, which was refreshed every 3-4 days (Fig. 6).

Fig. 6.

Fig. 6.

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Schematic of GelMA hydrogel preparation with cell encapsulation. (1) Breast cancer cells were detached from the cell culture flask then pelleted to obtain the desired final concentration of live cells/ml. (2) Lyophilized GelMA macromer was weighed and dissolved in sterile 1× PBS solution to produce the GelMA solution of designed wt%. (3) Sodium persulfate (SPS) and ruthenium (Ru) were dissolved in sterile 1× PBS to produce solutions with final concentrations of 5 and 0.5 mM, respectively. (4) To produce the complete GelMA precursor solution; the dissolved GelMA solution, pelleted cells and photoinitiators (SPS and Ru) were combined and pipetted into 1 mm deep, 5 mm diameter moulds. (5) These were then crosslinked with 30 mW/cm² visible light for 180 s, before being transferred into individual wells of a 48-well plates with 500 µl cell appropriate media (6). Created in BioRender by Wise, J. A. (2026). https://BioRender.com/8yd72bj. This figure was sublicensed under CC-BY 4.0 terms.

Analysis of GelMA hydrogel properties

Hydrogels were weighed immediately following crosslinking to obtain the initial mass (minitial, t0), then either incubated overnight at 37°C in a humidified cell culture incubator in 1× PBS or immediately frozen in a −80°C freezer before freeze drying (mdry, t0). The hydrogels, which were swollen overnight, were then weighed again (mswollen), before being frozen in a −80°C freezer. All hydrogels were then freeze dried, and the final dry weight (mdry) was measured. These values were used to calculate the actual macromer fraction (Eqn 1), initial dry mass (Eqn 2), soluble fraction (%) (Eqn 3) and mass swelling ratio (q) of hydrogels (Eqn 4).

graphic file with name biolopen-15-062212-e1.jpg (1)
graphic file with name biolopen-15-062212-e2.jpg (2)
graphic file with name biolopen-15-062212-e3.jpg (3)
graphic file with name biolopen-15-062212-e4.jpg (4)

Hydrogels, 2 mm in height and 5 mm in diameter, underwent mechanical compression testing using an MTS Criterion machine (Model C42) fitted with a 5 N load cell to determine compressive modulus. The compressive modulus (E) was calculated (Eqn 5) to produce a stress (σe)-strain (εe) curve for each hydrogel using the compression testing data, hydrogel height and cross-sectional area measurements. The slope of the linear region of the stress-strain curve determined the mechanical stiffness (compressive modulus) of each hydrogel. The 10-20% strain region of the curve was found to show the highest R2 values representing the linear region of these hydrogels and was used for all experiments.

graphic file with name biolopen-15-062212-e5.jpg (5)

A Presens® oxygen microsensor probe was used to measure oxygen levels in a stepwise manner throughout the depth of cell-free GelMA hydrogels. The oxygen probe microsensor was mounted in the head of a computer-controlled 3D printer (Bioscaffolder, SYSEng) to allow for precise control over the z position of the probe tip within hydrogels. The sensor was positioned into the centre bottom of the hydrogel and allowed to equilibrate for 1 min, then retracted at 100 µm every 10 s (with ten measurements per second) to provide stepwise measurements throughout the depth of the 1 mm hydrogel. Measurements are denoted as 0 µm at the top of the hydrogel and 1000 µm at the bottom of the hydrogel.

Measurement of breast cancer cell viability, metabolic activity and DNA content

The study evaluated cellular response to 3D GelMA hydrogel culture by conducting Live/Dead staining to determine cell viability, AlamarBlue® (Thermo Fisher Scientific) to measure metabolic activity, and CyQUANT® (Thermo Fisher Scientific) to assess cellular proliferation on day 1, 7, 14, and 21 of the culture periods. Day 1 post-encapsulation was used as the reference state for all downstream analyses, providing a baseline to assess changes in viability, metabolic activity, proliferation, and phenotype over time. Each biological replicate represents the mean of three technical replicates (individual hydrogels). Separate sets of hydrogels were prepared for viability, metabolic activity, and proliferation assays at each time point. Minor variations in biological replicate numbers between cell lines arose from technical losses during culture or assay processing.

Briefly, Live/Dead staining was performed with calcein acetoxymethyl (Calcein-AM) and propidium iodide (PI). Hydrogels were washed with 1× PBS for 5 min, then incubated in Calcein-AM and PI (1 µg/ml) for 10 min. Hydrogels were then washed with PBS before fluorescent imaging on a Zeiss Axio Imager.Z1 microscope while hydrated. ImageJ software (National Institutes of Health) was used to count the number of live and dead cells and calculate the percentage viability (%) (Eqn 6).

graphic file with name biolopen-15-062212-e6.jpg (6)

The AlamarBlue™ cell viability assay was used to assess the metabolic activity of encapsulated cells. Breast cancer cell-laden hydrogels were incubated with 10% v/v AlamarBlue reagent in cell culture media for 6 h, after which the fluorescence intensity was measured at excitation of 545 nm and emission at 590 nm with the VarioSkan™ plate reader (Thermo Fisher Scientific). Results were normalized to negative controls (acellular hydrogels and media-only controls) and expressed as relative fluorescence units (rfu).

Breast cancer cell proliferation was measured using the CyQUANT™ direct cell proliferation assay. Cell-laden hydrogels were collected at indicated timepoints and washed with 1× PBS to eliminate residual Phenol Red from media. The hydrogels were then frozen at −80°C and subjected to freeze drying. The lyophilized hydrogels were then digested in proteinase K solution (1 mg/ml in Tris-EDTA) at 56°C for 12 h. The CyQUANT™ assay kit was used to quantify the DNA content of each hydrogel, following the manufacturer's protocols. The experimental measurements were normalized to negative controls, and results were extrapolated from the DNA standard curve.

Immunofluorescent staining

To prepare for staining, hydrogels containing cells were washed with 1× PBS and then fixed in 10% neutral buffered formalin at room temperature for 1 h. The hydrogels were then frozen at −80°C in optimal cutting temperature (OCT) compound before being cryosectioned into 30 µm sections. The cryosections were simultaneously blocked and permeabilized in 3% w/v bovine serum albumin and 0.1% v/v Triton™ X-100 before incubation with primary antibodies [anti-Ki67 (1: 500, Abcam, USA), anti-E-cad/N-cad/Vimentin (1:200, Cell Signaling Technology, USA), rhodamine phalloidin dye (6.6 µM, Thermo Fisher Scientific, USA)] at room temperature for 1 h. The sections were then washed with 1× PBS-T before incubation with the secondary antibody [goat anti-rabbit IgG (Alexa Fluor® 488); 1:1000, Abcam, USA] overnight at 4°C. The sections were counterstained with 4′,6-diamidino-2-phenylindole (DAPI; 0.02 mg/ml, Thermo Fisher Scientific, USA), mounted and cover slipped before being imaged with the Zeiss Axio Imager.Z1 microscope. Secondary-only immunostaining controls were performed to confirm specificity of fluorescent labelling. For each condition, three independent hydrogels were sectioned and stained. From each hydrogel, ten to 15 cryosections (30 µm thick) were imaged, with three to five fields of view per section in both the centre and edge regions.

Percentage proliferative (Ki67-expressing cells) was calculated using Eqn 7.

graphic file with name biolopen-15-062212-e7.jpg (7)

To evaluate growth patterns of MDA-MB-231 cells, the junction density per area was quantified using Angiotool software [National Cancer Institute Center for Cancer Research (CCR)] by measuring the number of cellular junctions in the explant area after staining cryosections with DAPI and rhodamine phalloidin. Comparatively, the size of cellular aggregates and the percentage of the hydrogel occupied by cells (cell coverage, %) were assessed for MCF7 cells using ImageJ. Difference in analyses were due to the difference in morphology between these two cell types.

Hydrogels were divided into two regions based on where the cells were located: the ‘centre’ and ‘edge’ regions. The edge region was defined as the area within 200 µm of the outer top and sides of the hydrogels, while the centre region was defined as the remaining area that was 200 µm into the hydrogel and deeper (see Fig. 7 for a visual representation of this division).

The relative expression levels of immunofluorescently stained proteins were quantified using the ImageJ software analyser tool. Images were analysed by separating them into single channels (FITC, Texas Red, DAPI) and determining the mean pixel density values for the appropriate antibody channel. For each image, the workflow in ImageJ included ‘background subtraction’, conversion to ‘16-bit’, ‘thresholding’, and ‘measurement’. The number of cells per image was determined using ImageJ analysis of the DAPI channel, involving conversion to ‘16-bit’, ‘thresholding’, ‘watershed’ segmentation for background removal, and ‘analysis’. All background removal, measurement, and analysis functions were standardized across all samples in the study. Staining intensity (pixel density) was normalized relative to the number of cells measured in each field.

Statistical analysis

Results were expressed as means±s.d. of the mean. GraphPad Prism software (version 9.2.0) was used to perform statistical analysis. Fold change data were calculated relative to the data on day 1 of analysis (no error bar). Data resulting from a minimum of three replicates within three independent biological repeats were evaluated (exact number shown in figure legends), and statistical significance was determined using two-way ANOVA with Tukey's multiple comparisons testing. A P-value less than 0.05 was considered significant, and the degree of significance was denoted as follows: ns, not significant; *P≤0.05, **P≤0.01, ***P≤0.001, and ****P≤0.0001.

Supplementary Material

biolopen-15-062212_review_history.pdf (910KB, pdf)
Supplementary information
biolopen-15-062212-s1.pdf (2.2MB, pdf)
DOI: 10.1242/biolopen.062212_sup1

Acknowledgements

The authors acknowledge the support of institutional core facilities and thank technical staff and members of the research group for access to shared laboratory facilities and equipment, as well as for helpful discussions that supported this work.

Footnotes

Author contributions

Conceptualization: M.J.C., T.B.F.W., K.S.L., E.P.; Data curation: J.A.W.; Formal analysis: J.A.W., K.S.L., E.P.; Funding acquisition: T.B.F.W., K.S.L., E.P.; Investigation: J.A.W., K.S.L., E.P.; Methodology: J.A.W., K.S.L., E.P.; Project administration: M.J.C., K.S.L., E.P.; Resources: M.J.C., K.S.L., E.P.; Supervision: M.J.C., T.B.F.W., K.S.L., E.P.; Writing – original draft: J.A.W.; Writing – review & editing: J.A.W., M.J.C., T.B.F.W., K.S.L., E.P.

Funding

This research received funding from the following sources: University of Otago, Maurice Wilkins Centre for Molecular Biodiscovery and the Cancer Society NZ-Canterbury West Coast Division. Open Access funding provided by University of Otago. Deposited in PMC for immediate release.

Data and resource availability

All relevant data and details of resources can be found within the article and its supplementary information.

Contributor Information

Khoon S. Lim, Email: khoon.lim@sydney.edu.au.

Elisabeth Phillips, Email: elisabeth.phillips@otago.ac.nz.

Peer review history

The peer review history is available online at https://journals.biologists.com/bio/lookup/doi/10.1242/bio.062212.reviewer-comments.pdf

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biolopen-15-062212-s1.pdf (2.2MB, pdf)
DOI: 10.1242/biolopen.062212_sup1

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