Role of Hepatic Stellate Cells on Morphometric Dynamics in a Three-dimensional Hepatocellular Carcinoma Coculture Model

Role of Hepatic Stellate Cells on Morphometric Dynamics in a Three-dimensional Hepatocellular Carcinoma Coculture Model | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Role of Hepatic Stellate Cells on Morphometric Dynamics in a Three-dimensional Hepatocellular Carcinoma Coculture Model Jessica Obelar, Joao Garcia Vasconcellos, Natalia Baltazar do Nascimento, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9417634/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Hepatocellular carcinoma (HCC) remains a leading cause of cancer mortality worldwide. While three-dimensional (3D) spheroid models better recapitulate tumor architecture than conventional two-dimensional systems, the contribution of stromal components to spheroid organization and viability remains incompletely understood. In particular, the relationship between spheroid morphology and cell death dynamics in the presence of hepatic stellate cells (HSCs) has not been fully characterized. This study aimed to investigate how stromal cells influence spheroid architecture and survival in a 3D HCC model. Methods and Results Spheroids were generated using HepG2 cells, LX-2 cells (HSCs), and a 1:1 co-culture system (CCS) and monitored over 96 hours (n = 3 independent experiments). Morphometric parameters, including area, perimeter, circularity, aspect ratio, geometric and normalized solidity, and mean gray value, were quantified using ImageJ. Cell death was assessed by Annexin V/propidium iodide staining. CCS spheroids exhibited reduced area and perimeter compared to HepG2 monocultures (p < 0.05), along with increased circularity and normalized solidity, indicating enhanced structural organization and compaction. HepG2 spheroids showed higher necrosis levels, whereas CCS spheroids displayed reduced necrosis and a trend toward increased early apoptosis, suggesting improved viability in the presence of stromal cells. Conclusions Hepatic stellate cells modulate spheroid architecture and cell death dynamics, promoting more compact and viable tumor structures. These findings highlight the role of tumor–stroma interactions in HCC and support co-culture spheroids as more physiologically relevant preclinical models. HCC spheroids tumor microenvironment cell death hepatocytes hepatic stellate cells Figures Figure 1 Figure 2 Figure 3 Figure 4 Highlights Coculture spheroids show greater compactness than HepG2 monocultures. LX-2 inclusion enhances spheroid solidity and structural organization. Normalized solidity reveals stromal-driven compaction in mixed spheroids. Stromal cells modulate spheroid viability and cell-death patterns. Summary Cancer cells behave differently when they grow in three-dimensional structures instead of flat laboratory dishes. By measuring how tumor spheroids change their size and shape over time, the authors demonstrated 3D spheroids made of different cell types grow and change shape in distinct ways. These differences can help scientists choose better laboratory models to study cancer behavior and test treatments. 1. Introduction Hepatocellular carcinoma (HCC) is the most common primary liver cancer and ranks as the third leading cause of cancer-related death globally [ 1 ]. Despite advances in diagnosis and treatment, HCC remains a challenging disease, partly due to its molecular and cellular heterogeneity and its complex interaction with the tumor microenvironment (TME)[ 2 ]. Traditionally, in vitro studies have relied on two-dimensional (2D) monocultures of HCC cell lines such as HepG2. While useful, these models fail to recapitulate the structural and cellular complexity of tumors, especially in terms of cell–cell and cell–matrix interactions [ 3 ]. As a result, 2D models often fall short in predicting drug responses or mimicking tumor progression [ 4 ]. Three-dimensional (3D) cell culture systems, such as spheroids, have gained prominence in cancer research. These models better simulate the physiological architecture of solid tumors, including gradients of oxygen, nutrients, and metabolites. Compared to monolayers, 3D cultures more accurately reflect key cellular behaviors, such as extracellular matrix deposition, cellular polarity, and resistance to therapy [ 5 ], [ 6 ]. An essential component of the HCC microenvironment is the hepatic stellate cell (HSC). In a healthy liver, HSCs remain quiescent and store vitamin A in lipid droplets. Upon liver injury, they become activated, acquiring a myofibroblastic phenotype and contributing to fibrogenesis through excessive extracellular matrix secretion [ 7 ]. Persistent activation of HSCs not only leads to liver fibrosis but also promotes tumor progression by enhancing tissue remodeling and facilitating cancer cell invasion [ 7 ]. Given their critical role, co-culture models combining HCC cells and HSCs can provide a more realistic platform to study tumor behavior. These systems can also improve the predictive value of drug screening assays by more closely mimicking in vivo conditions [ 8 ]. However, studies that deeply explore the morphometric characteristics of these co-culture spheroids (e.g., shape, size, and compactness) remain limited. Notably, tumor morphology has been used as a non-invasive marker of malignancy in imaging-based studies of several cancers[ 9 ], [ 10 ], [ 11 ], [ 12 ], including the prediction of microvascular invasion in hepatocellular carcinoma [ 13 ]. Compact and round shapes often correlate with benign behavior, while irregular, lobulated forms are associated with malignancy [ 14 ]. Although shape analysis is already integrated into computer-aided diagnosis (CAD) for cancers such as breast and thyroid [ 15 ], its application to liver tumors remains underexplored [ 16 ]. In this study, we investigated the morphometric behavior and cell death dynamics of 3D spheroids composed of HepG2 cells (HCC, monoculture), LX-2 cells (HSC, monoculture), and a co-culture of both (CCS). By comparing parameters such as area, perimeter, circularity, solidity, and cell viability over time, we aim to better understand how spheroid architecture reflects the interplay between tumor and stromal components in HCC. Our findings provide insights into model selection for in vitro studies and offer potential implications for imaging analysis and drug testing platforms. 2. Methodology 2.1. Cell culture HepG2 cells were purchased from the Rio de Janeiro Cell Bank, and Dr. Karen C. Martinez de Moraes generously provided LX-2 cells from UNESP under the authorization of Prof. Scott Friedman. Both cell lines were maintained in Dulbecco’s Modified Essential Medium (DMEM) (Sigma Aldrich, St. Louis, MO, USA) low glucose, with 2% of fetal bovine serum (FBS), 1% of penicillin-streptomycin (10,000 U/mL penicillin and 10 mg/mL streptomycin) under 37ºC and 5% CO 2 in a controlled and humidified incubator. The cells were passaged using 0.25% trypsin-EDTA (Gibco, Grand Island, NY, USA). 2.2. Spheroid establishment The 96-well U-bottom plates were coated with a delicate layer of soft-agar (1.5%, pre-sterilized by autoclaving), and after solidification, the plates underwent UV light exposure for 30 minutes [ 17 ]. HepG2 and LX-2 monocultures were seeded with 5 x 10 4 cells/well in a 96-well plate (Fig. 1 A). To emulate the HCC TME, a CCS was established. LX-2 and HepG2 were concomitantly seeded in a 1:1 ratio in each well (2.5 x 10 4 cells/well of each lineage, totalizing 5 x 10 4 cells/well) [ 18 ], [ 19 ]. 2.3. Optical microscopy Spheroid evolution was monitored by phase-contrast inverted microscopy (Olympus IX40), and images were systematically captured at 24-hour intervals. This observational timeline spanned 96 hours, enabling a thorough examination of the dynamic changes and growth patterns exhibited by the spheroids across their developmental stages. 2.4. Morphometric Analysis To measure parameters such as area, density, aspect ratio, perimeter, circularity, roundness, and solidity in ImageJ (NIH, Bethesda, MD), a meticulous protocol was followed [ 20 ]. The image was converted to 8-bit, the scale was calibrated, and measurements were set to include area, mean gray value (MGV), centroid, perimeter, fit ellipse, shape descriptors, integrated density, limit to threshold, and display label. Subsequently, edges were defined, limits were adjusted, and a region of interest (ROI) was chosen using the ROI Manager. The process described above determines a ROI with specific coordinates for each sample. This coordinate (ROI) was then applied to the original image to measure previously defined parameters (Fig. 1 B) [ 21 ]. 2.4.1. Area To measure the growth and compactness of spheroids under different experimental conditions, the area of each spheroid was determined in ImageJ using the number of pixels within the defined ROI [ 22 ]. Upon calibration of the spatial scale in the software, the area values were automatically converted from pixel counts to physical units (µm²) using the following equation (Eq. 1 ): $$\:Area=nº\:of\:pixels\:\times\:\:(Pixel\:Width\:\times\:\:Pixel\:Height)$$ 1 2.4.2. Circularity Circularity was calculated to evaluate the contour regularity of the spheroids [ 23 ], [ 24 ]. This parameter integrates the area and perimeter of each object, providing a measure of how closely the shape approximates to a perfect circle. Values range from 0 (extremely elongated or irregular shapes) to 1.0 (perfect circle). The formula (Eq. 2 ) used by the software is: $$\:Circularity=(4\pi\:\:\times\:Area)/Perimeter²$$ 2 2.4.3. Roundness Roundness was assessed to determine the degree of elongation of the spheroids, independently of contour irregularities. Values close to 1.0 indicate spherical morphologies, whereas lower values suggest structural anisotropy or elongation [ 24 ], [ 25 ]. This descriptor considers the ratio between the area and the square of the major axis length, and was calculated using the following formula (Eq. 3 ): $$\:Roundness=(4\times\:Area)/(\pi\:\:\times\:Major\:axis\:²)$$ 3 2.4.4. Aspect ratio The aspect ratio of each spheroid was calculated from the Major and Minor axis measurements generated by ImageJ, which are based on an ellipse fitted to the selected ROI. Values close to 1 indicate a more symmetrical profile, while higher values reflect elongated or irregular morphologies [ 21 ], [ 26 ]. The aspect ratio was determined using the following formula (Eq. 4 ): $$\:Aspect\:ratio=\left(Major\:axis\right)/\left(Minor\:axis\right)$$ 4 2.4.5. Solidity Two different approaches were employed to assess solidity in spheroids: geometric solidity, based on shape descriptors; and normalized solidity, derived from grayscale intensity measurements [ 27 ], [ 28 ], [ 29 ]. Geometric solidity is a descriptor of morphological compactness. It quantifies how closely the spheroid's shape approximates that of a perfect convex structure. Values close to 1.0 indicate a smooth, compact shape with regular edges, while lower values suggest irregularity, fragmentation, or surface roughness [ 30 ]. This metric was calculated in ImageJ using the formula (Eq. 5 ): $$\:Geometric\:solidity=Area/\left(Convex\:area\right)$$ 5 To complement geometric assessment, we also evaluated spheroid internal density using gray-level pixel intensities obtained from brightfield images. The MGV of each spheroid was used as a proxy for internal compaction, assuming that darker spheroids (lower MGV) reflect higher cellular density or extracellular matrix accumulation. To facilitate interpretation and provide a measure that increases with biological compaction, the following normalization was applied (Eq. 6 ): $$\:Normalized\:solidity=(Max\:MGV-Current\:MGV)/(Max\:MGV-Min\:MGV)$$ 6 2.4.6. Density Spheroid density was assessed using the MGV, a parameter provided by ImageJ that reflects the average pixel intensity within a defined ROI. This measurement provides a straightforward quantitative estimate of grayscale density in brightfield images. Lower MGV corresponds to darker regions and may be indicative of increased biological density, such as greater cellular compaction, extracellular matrix (ECM) accumulation, or necrotic areas. Conversely, higher MGV suggest brighter, less dense regions, potentially associated with reduced cell packing or looser tissue organization. This parameter was used both as a standalone indicator of optical density and in the derivation of the normalized solidity index described above [ 31 ]. It was calculated using the following formula (Eq. 7 ): $$\:Mean\:Gray\:Value=(\sum\:Pixel\:intensity)/\left(nº\:of\:pixels\:in\:the\:ROI\right)$$ 7 2.5. Annexin/PI To measure the proportions of dead and viable cells, annexin V-FITC/propidium iodide (PI) was used for labeling. Ten spheroids of each group were collected, centrifuged (1,200 rpm for 10 min), washed once with 1 \(\:\times\:\) PBS, and dissociated with 300 µL of 0.25% Trypsin-EDTA. The cell suspension was centrifuged and then rewashed with 1 \(\:\times\:\) PBS. It was subsequently incubated with a solution of Annexin V-FITC (4 µg/mL, QuatroG) and PI (40 µg/mL, Invitrogen) for 15 minutes. The cells were rewashed with 1 \(\:\times\:\:\) PBS and then suspended in 300 µL of 1 \(\:\times\:\:\) PBS. Data were acquired using a FACS Calibur flow cytometer (BD Biosciences San Jose, CA, USA). The data was analyzed using FlowJo XV version 10 (FlowJo LLC). 2.6. Statistical analysis Data were analyzed using GraphPad Prism version 9.0.0. To compare morphometric analysis over time and cell death type across different types of spheroids, we performed a two-way analysis of variance (ANOVA), followed by Tukey post-hoc tests. Analysis of the size of the difference was also performed (mean difference size = Δd), and the means of the spheroid measurements at 2 hours were compared with those at other times using a one-way ANOVA followed by Sidak post-hoc . Data is expressed by mean ± standard error of the mean (S.E.M). For the Annexin V-FITC/PI assay, data from three or more experimental repeats are presented as the mean ± SD. Data were analyzed using a one‑way ANOVA, after which a Tukey's test was performed for multiple comparisons. 3. Results 3.1. Morphometric dynamic The spheroids of LX-2, HepG2, and CCS (1:1, LX-2, and HepG2) were generated (Fig. 1 a), and monitored by optical microscopy every 24 hours for 96 hours to observe their appearance (Fig. 1 b). Morphometric analysis of spheroids is essential for assessing tumor growth, evaluating viability and morphology, and serving as a normalization reference. We could observe that the type of culture (two-way ANOVA, F (2, 71) = 135.9; P < 0.0001) and the time (two-way ANOVA, F (4, 71) = 34.11; P < 0.0001) affects the spheroid area, and there is a significant interaction between these factors (two-way ANOVA, F (8, 71) = 2.752; P = 0.0105) (Fig. 2 a and b). The number of cells that were seeded in each well was the same for each group, but over time the compactness dynamics starts to reveal differences among the types of culture (Fig. 2 a). Within 2 hours, the HepG2 spheroids show a higher area than LX-2 and CCS spheroids (Fig. 2 a and b). Still, this difference among the groups is further enhanced over time, with the area of HepG2 spheroids being 4.8x higher than that of LX-2 spheroids (P < 0.0001) and 4.6x higher than that of CCS spheroids (P < 0.0001) (Fig. 2 b) (Table S1 ). The HepG2 spheroid area was reduced by 21,94% in 96 hours compared with the initial area (2 hours), from 1.718 ± 0.27 mm² to 1.341 ± 0.06 mm², but this difference is not statistically significant (P = 0.1002) (Fig. 2 c, Table S1 ). Differently, after 24 hours of seeding, both LX-2 and CCS spheroids had the area significantly reduced (Table 1S): the LX-2 spheroid area was decreased by 72% (P < 0.0001), and the CCS spheroid area was decreased by 71.66% (P < 0.0001, Fig. 2 c). After 96 hours, the total rate of area reduction in the LX-2 spheroids achieved 80.42%, from 1.419 ± 0.26 mm² to 0.2778 ± 0.02 mm² (P < 0.0001, Fig. 2 c). We could observe a similar behavior of area reduction in CCS spheroid, in 2 hours2 hours of culture the area counts with 1.303 ± 0.12 mm². After 96 hours of cultivation, it ends with 0.2882 ± 0.03 mm², comprehending a total reduction of 77.88% in the spheroid area (P < 0,0001, Fig. 2 c). We observed that both the time (two-way ANOVA, F (4, 71) = 15,17; P < 0,0001) and the type of culture (two-way ANOVA, F (2, 71) = 53.19; P < 0,0001) affected the perimeter of the spheroids, but there is no interaction between these factors (F (8, 71) = 0.7013, P = 0.6893) (Fig. 3 a). The perimeter of the LX-2 and CCS spheroids showed similar behavior throughout the time, reducing dramatically in the first 24 hours (LX-2 = 63.571%, P < 0.0001; CCS = 66.854%, P < 0.0001) (Table S4), and then maintaining the perimeter reduced without abrupt changes (Fig. 3 a). The HepG2 spheroids did not follow the perimeter reduction as in LX-2 and CCS spheroids. The total reduction (from 2 hours to 96 hours96 hours) of HepG2 spheroids’ perimeter was about 23.796%, but this observation was not statistically significant (P = 0.4939) (Fig. 3 b, Table S4). When comparing the types of culture, LX-2 spheroids had a lower perimeter than HepG2 at 24 hours (P < 0.0001), 48 hours (P = 0.0020), 72 hours (P < 0.0001), and 96 hours (P < 0.0001). This difference in the perimeter was also observed comparing HepG2 with CCS spheroids, with significant differences at 24 hours (P < 0,0001), 48 hours (P = 0,0068), 72 hours2 hours (P < 0,0001), and 96 hours (P < 0,0001) (Table S3 and S4). At the end of the 96 hours of culture, LX-2 and CCS spheroids had a decrease in the perimeter of 77.042% (P < 0.0001) and 70.82% (P < 0.0001), respectively (Fig. b). As spheroid culture progresses, cells tend to aggregate and form a spherical structure. However, the degree of circularity can vary depending on the cell type in the culture. The time and type of culture influence spheroid’s circularity, but there is no interaction between these two factors (P = 0.0087, P = 0.0001, and P = 0.7376, respectively). We observe that until 48h of culture, the groups do not differ in circularity, but in 72 hours HepG2 spheroids present less circularity than CCS (P = 0.0210), and at 96 hours HepG2 spheroids become less circular than LX-2 spheroids (P = 0.0256) and CCS spheroids (P = 0.0215) (Fig. 3 c). A perfect circle has a circularity value of 1. In contrast, more complex or jagged structures have circularity values closer to 0 (Fig. 3 c). This means that spheroids with smooth, well-defined edges will have higher circularity, whereas those with irregular or rough boundaries will have lower circularity. The HepG2 spheroid reaches a circularity of 0.1373 at 96 hours, the LX-2 spheroid reaches 0.4045, and CCS spheroid reaches 0.4112 (Fig. 3 d), but no statistical difference was observed when comparing the spheroids circularity at 2 hours vs 96 hours (HepG2 P = 0.9858; LX-2 P = 0.0927; CCS P = 0.0706). Roundness measures how close a shape is to a circle, but it is based on the major axis rather than the perimeter. For example, a perfect circle has a roundness of 1. We observed that the only factor which has an effect over spheroid roundness is the type of culture (two-way ANOVA, F (2, 70) = 4,462; P = 0.0150), but over time, the cultures do not present any significant differences (Fig. 3 e). The roundness of HepG2 spheroids starts at 0.8267 arbitrary units (AU) at 2 hours of culture and has only 1.911% of increase (96 hours = 0.8425 AU., P = 0.9733) (Fig. 3 f). On the other hand, the roundness of LX-2 spheroids starts within 0.5467 AU., and it increases over time, reaching 0.8514 AU. at 48h (versus 2 hours, P = 0.0005), 0.8797 AU. at 72 hours (versus 2 hours, P < 0,0001), and 0.8940 AU. at 96 hours (versus 2 hours, P < 0.0001, Fig. 3 f), culminating in an increase of 63.527% at the end of the culture (Table 10). CCS spheroids’ roundness behaves similarly to that of the HepG2 spheroids. Their roundness starts at 0.6900 AU. in 2 hours of culture, and by the end (96 hours), they reach 0.8473 AU. Although the increase is approximately 22.797% (Table 10), this is not statistically significant compared to 2 hours (P = 0.7547, Fig. 3 f). Roundness considers the major axis of the spheroid in the equation. The aspect ratio of the spheroid also includes the minor axis measures. A two-way ANOVA revealed that time was the sole significant factor influencing aspect ratio (F (4, 69) = 2.963, P = 0.0255), while type of culture (P = 0.2564), and the interaction between factors (P = 0.1013) were not significant (Fig. 3 g). However, despite the overall significance of time, post-hoc analysis indicated that the aspect ratio at the endpoint (96 hours) did not differ significantly from baseline (2 hours) for any group. Specifically, while HepG2, LX-2 and CCS spheroids exhibited reductions in aspect ratio of 4.1% (Fig. 6C), 17.0% (Fig. 6D), and 18.5% (Fig. 3 h) respectively, these changes did not reach statistical significance. In order to analyze if shape changes in spheroids or if the edges of a spheroid become more regular/smooth/compact, we used the parameter called geometric solidity. We observe no effect of time or type of culture in this parameter on the different types of spheroids (Fig. 3 i). Only at the first 24 hours HepG2 spheroids had significantly lower geometric solidity than CCS (26.819% lower, P = 0.0303). Although the geometric solidity of HepG2 spheroid increased 43.684% and of CCS spheroid increased 21.955% at 96 hours, those alterations were not statistically significant (HepG2 2 hours versus 96 hours, P = 0.23640; CCS 2 hours versus 96 hours, P = 0.08940) spheroids did not change significantly over time (Fig. 3 j) (Table S14). On the other hand, LX-2 spheroids start in 48h to significantly increase the geometric solidity by 28.935% (P = 0.02050, and at the end of the culture (96 hours), they sum 36.782% of increasing (P = 0.00450) (Fig. 3 j). As geometric solidity does not account for pixel intensity (gray values) - only shape, we accessed the normalized solidity. Normalized solidity shows us how compact spheroids appear and is based on the MGV. We observe that time (F (4, 72) = 35.39, P < 0.0001) and type of culture (F (2, 72) = 44.81, P < 0.0001) have an effect on the normalized solidity of spheroids. There is also an interaction between factors (F (8, 72) = 3.306, P = 0.0029) (Fig. 3 k). At the first 2 hours, all the types of cultures are similar, presenting similar normalized solidity (Table S11). In 24 hours, CCS spheroids are 33.407% more solid than HepG2 (P = 0.0001), as well as LX-2, which are 28.330% more solid than HepG2 (P = 0.0421). At the end of the culture, at 96 hours, the CCS spheroids are 37.132% more solid than HepG2 spheroid (P < 0.0001), and LX-2 spheroids are also 58.709% more solid than HepG2 spheroid (P < 0.0001) (Fig. 3 k) (Table S12). HepG2 spheroid does not statistically change the solidity over time, even the increase of the solidity being around of 43.404% at the end of the culture (96 hours) compared to the beginning (P = 0.19480) (Fig. 3 l). On the other hand, LX-2 spheroid increased by 102.640% the solidity in the first 24 hours (P < 0.0001) and ends the culture with an increase of 148.419% (P < 0,0001) compared with the 2 hours of culture (Fig. 3 l). The same occurs with the solidity of CCS spheroids. At the first 24 hours, they increased by around 90.081% (P < 0.0001) and, at the end of the culture, by 99.582% (P < 0.0001) (Fig. 3 l). As time passes, the spheroids become darker, AU indicating they are becoming more compact. Lower MGV and density reflect this, as shown in the AU of MGV. As the MGV increases, the spheroid becomes lighter, and the density decreases. We observe that time (F (4, 70) = 40,40, P < 0,0001) and type of culture (F (2, 70) = 62,53, P < 0,0001) had effect over spheroids density, and there is an interaction between factors as well (F (8, 70) = 4,136, P = 0,0004) (Fig. 3 m). During the first 2 hours of culture all the types of spheroids present no difference in the density parameter. At 24 hours, HepG2 spheroids have a higher MGV (18,294%) than LX-2 (P = 0.0176) and CCS (47,834%, P < 0,0001). This pattern is repeated over the next few hours of culture, but after 72 hours of culture, CCS have a higher MGV than LX-2 spheroids (27.197%, P = 0.0427). At the end, in 96 hours, HepG2 spheroids had still higher MGV than LX-2 (37.314%, P < 0.0001) and then of CCS spheroids (60.104%, P < 0.0001) (Fig. 3 m). The density of HepG2 spheroids does not change statistically over time, but LX-2 and CCS spheroid did (Fig. 3 n). LX-2 spheroids decrease the MGV in 29.21% (P < 0.0001) at 24 hours and 45.375% after 96 hours of culture (P < 0.0001) (Fig. 3 n). CCS spheroids also had a decrease on MGV after 24 hours of 40.424% (P < 0,0001) and of 44.667% at 96 hours (P < 0.0001) (Fig. 3 n). 3.2. Cell death Each culture type behaves in a particular way, as we observed in the morphometric analyses. These differences in the spheroid compactness may be related to differences in the cell death rates. To evaluate cell death patterns at the end of 96 hours of spheroid formation for each culture type, we performed an Annexin V-FITC/PI co-labeling assay. We first evaluated the viable cells in each culture type, selecting only the cells that were not labeled with either Annexin or PI (quadrant 4 = Q4, Fig. 4 a and b). No significant differences were observed in the viability across the culture types. Next, we assessed early apoptosis by selecting cells labeled with annexin (gate: Annexin+ cells and PI− cells ) (quadrant 3 = Q3, Fig. 4 a). The one-way ANOVA indicated that the type of culture tended to affect early apoptosis, but is not statistically different. HepG2 spheroids showed 3.6% higher levels of early apoptosis compared to LX-2 spheroids. CCS spheroids behaved quite differently, exhibiting higher levels of early apoptosis than LX-2 by approximately 54.35%, and higher than HepG2 by 52.65%, though these differences were not statistically significant (Fig. 4 c). We then examined late apoptosis, characterized by cells that were labeled with both Annexin and PI (quadrant 2 = Q2, Fig. 4 a). The data showed no significant differences in late apoptosis levels across the groups. Although CCS spheroids exhibited lower levels of late apoptosis than LX-2 (48.8315%) and HepG2 (92.9891%), these differences were not statistically significant (Fig. 4 d). Finally, we evaluate the necrosis by selecting all cells labeled with PI (gate: PI+ cells ) (Fig. 4 e). The one-way ANOVA showed that the type of culture had a significant effect on necrosis (Fig. 4 f). HepG2 spheroids had significantly higher levels of necrosis (50.5085%) compared to LX-2 spheroids and CCS spheroids (76.3299%). Although CCS spheroids had slightly higher levels of necrosis than LX-2 (12.7316%), this difference was not statistically significant. 4. Discussion Morphometric parameters such as area, perimeter, circularity, and roundness are commonly used to evaluate the size, shape, and regularity of biological structures, including adipocytes [ 32 ] and cell nuclei [ 33 ]. These measurements have also proven helpful in assessing spheroid formation across different 3D culture methodologies [ 21 ], [ 34 ], [ 35 ], as they offer quantitative insights into the structural organization of these models. Building upon this approach, we applied morphometric analysis to investigate the dynamic behavior of spheroids in an HCC context. While in vitro HCC models have advanced our understanding of tumor biology and therapeutic responses, their predictive value is often limited by the use of traditional 2D monocultures, which lack the complexity of the in vivo TME [ 36 ]. In contrast, 3D cultures systems (particularly co-cultures) offer more physiologically relevant tumor models, more accurately mimicking the TME [ 37 ], including cell–cell interactions and extracellular matrix (ECM) production [ 38 ]. In this study, we investigated the morphometric and cell death dynamics of spheroids derived from HepG2 and LX-2 cells, both as monocultures and in a CCS. By evaluating structural and functional parameters over 96 hours, we aimed to understand how the presence of stromal components influences spheroid architecture and viability in an HCC context. Our morphometric analysis encompassed multiple shape descriptors, including area, perimeter, circularity, roundness, aspect ratio, solidity (geometric and normalized), and density. While roundness, aspect ratio, and geometric solidity did not differ significantly across groups, circularity showed a distinct pattern: HepG2 spheroids exhibited significantly lower circularity than LX-2 and CCS spheroids. Although circularity and roundness are related, they describe different geometric attributes: circularity being more sensitive to contour irregularities and symmetry, while roundness predominantly reflects elongation [ 39 ]. The reduced circularity observed in HepG2 spheroids suggests greater structural irregularity or asymmetry, which could influence internal diffusion dynamics. It has been shown that spheroid geometry directly affects diffusion gradients. Circular and symmetric spheroids facilitate more uniform diffusion toward the center, while irregular or elongated shapes increase surface area and reduce the average diffusion distance, potentially leading to uneven distribution of oxygen, nutrients, or drug [ 40 ], [ 41 ]. Therefore, the altered geometry of HepG2 spheroids may contribute to the higher necrosis levels observed in this group, either by compromising central oxygenation or by hindering the clearance of waste products. Thus, although circularity alone does not define compactness, it reflects geometric properties that are functionally relevant in spheroid biology [ 42 ]. Distinct trends were also observed in size-related metrics. Both area and perimeter significantly decreased in LX-2 and CCS spheroids from 2 to 24 hours of culture and continued to decrease until 96 hours, suggesting rapid and sustained compaction. In contrast, HepG2 spheroids exhibited a significant increase in diameter between 2 and 24 hours, resulting in a larger overall size. While area is often interpreted as a growth indicator [ 43 ], it may reflect compactness. This nuance is critical for interpreting spheroid behavior in early culture phases. Compactness in LX-2 and CCS spheroids was further supported by increased normalized solidity and reduced MGV, as well as reduced area and perimeter, both of which suggest greater density and structural integrity. Their presence in CCS appears to enhance mechanical stability and compactness, likely through ECM production and stromal–tumor interactions [ 6 ], [ 44 ] HepG2 spheroids, in contrast, formed larger and looser aggregates, likely due to weaker cell–cell adhesion. Our results align with prior studies showing increased compactness and viability in HCC spheroids co-cultured with stromal cells, reinforcing the essential role of the microenvironment in spheroid maturation. Interestingly, while Taroncher et al. observed continued spheroid growth in co-cultures during the final 24 hours of a 96-hour culture. Our normalized area analysis from 72 to 96 hours did not reveal significant growth in any group (Fig. S1 ) [ 45 ]. A potential explanation lies in the methodological differences. Their use of centrifugation accelerates spheroid formation and compactness, while our spontaneous aggregation approach provides a slower but more accessible model. Discrepancy may reflect both technical differences and variations in cellular behavior under distinct culture conditions. Geometric solidity values in HepG2 spheroids here found (80,7%) were comparable to those reported in the literature (80–95%) [ 45 ]. However, normalized solidity and MGV were significantly improved in CCS and LX-2 spheroids, indicating a more stable structure. These normalized metrics, which account for inter-spheroid variability, proved more sensitive than geometric solidity alone, offering a better resolution of compaction differences between groups. Regarding viability, the only significant difference in cell death profiles was found in necrosis levels. HepG2 spheroids exhibited the highest level of necrosis, which is consistent with their larger size and lower compactness. Larger spheroids (> 500 µm) are more susceptible to hypoxia-induced necrosis due to impaired diffusion of oxygen and nutrients [ 24 ]. It is well established that in spheroids exceeding 500 µm in diameter, central regions can become severely hypoxic due to diffusion limitations [ 46 ]. This hypoxia leads to the stabilization of hypoxia-inducible factor 1-alpha (HIF-1α), triggering metabolic reprogramming such as the Warburg effect and promoting necrotic cell death in the spheroid core due to acidification and waste accumulation [ 47 ]. Notably, all spheroid groups in our study exceeded this size threshold throughout the culture period, but their structural evolution differed substantially. The pronounced compaction observed in LX-2 and CCS spheroids may have improved diffusion efficiency and reduced central necrosis. Crucially, co-cultured spheroids exhibited significantly lower necrosis than HepG2 monocultures, suggesting a protective role of LX-2 cells. These findings align with previous studies demonstrating that stellate cells support hepatocyte viability and spheroid integrity via the secretion of extracellular matrix and survival factors [ 48 ], [ 49 ]. By enhancing compactness and possibly contributing ECM components, LX-2 cells modulate the physical and biochemical environment, supporting cell survival [ 50 ]. This highlights the value of co-culture systems in recapitulating the tumor-stromal interplay seen in vivo [ 51 ]. Spheroids of HepG2 co-cultured with LX-2 exhibited reduced necrosis, suggesting a protective role of LX-2 cells. A study using a live/dead fluorescence assay showed similar results, with co-culture spheroids demonstrating significantly higher viability than HepG2 monocultures [ 45 ]. The authors attributed this to stellate cells improving hepatocyte viability and structural organization. Together, our findings demonstrate that spheroid morphology and viability are strongly influenced by cellular composition. Co-culture with LX-2 cells promoted more compact, symmetrical, and viable spheroids, better representing the TME. These insights support the use of co-culture systems as more robust 3D models for HCC studies. Although we evaluated spheroid compaction and structure using diverse morphometric parameters, we did not assess ECM deposition or stiffness directly. These could have provided further insight into stromal contributions. Also, a more comprehensive panel of cell death markers (e.g., caspase activity, autophagy) could reveal subtler phenotypic shifts. Despite these limitations, our approach provides a valuable foundation for future studies aiming to refine in vitro HCC models and probe tumor–stroma interactions. 5. Conclusion Our findings demonstrate that both morphometric and cell death profiles are strongly influenced by spheroid composition. The inclusion of LX-2 cells resulted in more compact, symmetrical, and viable spheroids, underscoring the critical role of stromal components in shaping tumor architecture and supporting cell survival. These results highlight the need to select appropriate 3D models based on the biological question at hand, particularly when investigating tumor structure, microenvironmental interactions, and diffusion-related phenomena. Co-culture systems, by mimicking the in vivo complexity of HCC, offer a more physiologically relevant platform for preclinical studies and therapeutic testing. Abbreviations HCC Hepatocellular carcinoma TME Tumor microenvironmental 2D two-dimensional 3D three-dimensional HSC hepatic stellate cells CAD computer-aided diagnosis CCS co-culture system DMEM Dulbecco’s Modified Essential Medium FBS fetal bovine serum UV ultraviolet light MGV mean gray value ROI region of interest PBS Phosphate-buffered saline EDTA ethylenediaminetetraacetic acid PI propidium iodide rpm = rotations per minute ANOVA analysis of variance Δd mean difference size SEM standard error of mean SD standard deviation PS phosphatidylserine ECM extracellular matrix HIF-1α hypoxia-inducible factor 1-alpha. Declarations Funding This work was supported by Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS) [grant number 24/25510001320-2, 2024]. Additional support was provided by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). Competing Interests The authors have no relevant financial or non-financial interests to disclose. Ethics approval This is an observational study. The UFRGS Research Ethics Committee has confirmed that no ethical approval is required. Funding: This work was supported by FAPERGS [grant number 24/25510001320-2, 2024]. Author Contribution J.O. and F.T.C.R.G. contributed to the conceptualization and design of the study. Methodology, material preparation, and data collection were performed by J.O., J.G.V., and N.B.N.. Formal analysis and investigation were conducted by J.O.. J.O. also performed data curation and wrote the original draft of the manuscript. Writing—review and editing were carried out by F.T.C.R.G., V.M.T.T., and J.deO.. Resources were provided by F.T.C.R.G., V.M.T.T., and J.deO.. 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Supplementary Files Supplementarydata.pdf Supplementarydata.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 19 May, 2026 Reviews received at journal 18 May, 2026 Reviewers agreed at journal 13 May, 2026 Reviewers agreed at journal 11 May, 2026 Reviewers agreed at journal 11 May, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers invited by journal 20 Apr, 2026 Editor assigned by journal 16 Apr, 2026 Submission checks completed at journal 16 Apr, 2026 First submitted to journal 14 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9417634","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":627004417,"identity":"c39cc4b8-67e8-473a-9283-a36a753c0ab4","order_by":0,"name":"Jessica Obelar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIiWNgGAWjYBACxgYgkQDEBgzMQGYFAz9IlJlILSDmGQbJBkJa4ACshbGNCC3M7e2PPzyosZMzZ29s/Fw577CEef/yB8yFe/A4rOeMmUTCsWRjy56DzZJntx2WkLnxxoB5xjM8WmbksDEkNjAnbriR2CDZuO1wnYTEGQZmngN4tMx//vhDYkN94ob7D5t/Ns45LCEhcfwBfi0zGAwkEhsOA21hbJNsbABq4W8wwK+lJwfkl+NAvyS2WTYcSwfawmNweAYeLYbtxx9//FFTDQyxw4dvNtRYA205/vBxAT4tDRhCEgkMeDQwMMhjCvHj1TAKRsEoGAUjEAAApF1Xhqbj9DcAAAAASUVORK5CYII=","orcid":"","institution":"Federal University of Rio Grande do Sul","correspondingAuthor":true,"prefix":"","firstName":"Jessica","middleName":"","lastName":"Obelar","suffix":""},{"id":627004418,"identity":"793903af-5bc2-4008-9cb5-75b445088f89","order_by":1,"name":"Joao Garcia Vasconcellos","email":"","orcid":"","institution":"Federal University of Rio Grande do Sul","correspondingAuthor":false,"prefix":"","firstName":"Joao","middleName":"Garcia","lastName":"Vasconcellos","suffix":""},{"id":627004419,"identity":"3a5395fc-5b09-4762-8161-cda2caae0735","order_by":2,"name":"Natalia Baltazar do Nascimento","email":"","orcid":"","institution":"Federal University of Rio Grande do Sul","correspondingAuthor":false,"prefix":"","firstName":"Natalia","middleName":"Baltazar do","lastName":"Nascimento","suffix":""},{"id":627004420,"identity":"1f999d5e-5dbd-4980-84fb-d4adfe5ad0ac","order_by":3,"name":"Jade de Oliveira","email":"","orcid":"","institution":"Federal University of Rio Grande do Sul","correspondingAuthor":false,"prefix":"","firstName":"Jade","middleName":"","lastName":"de Oliveira","suffix":""},{"id":627004421,"identity":"7a9f107b-4993-4a8b-b7d3-7409f3c2516a","order_by":4,"name":"Vera Maria Treis Trindade","email":"","orcid":"","institution":"Federal University of Rio Grande do Sul","correspondingAuthor":false,"prefix":"","firstName":"Vera","middleName":"Maria Treis","lastName":"Trindade","suffix":""},{"id":627004422,"identity":"c512aea7-9cd7-4bd0-8054-df3081342f4f","order_by":5,"name":"Fatima Theresinha Costa Rodrigues Guma","email":"","orcid":"","institution":"Federal University of Rio Grande do Sul","correspondingAuthor":false,"prefix":"","firstName":"Fatima","middleName":"Theresinha Costa Rodrigues","lastName":"Guma","suffix":""}],"badges":[],"createdAt":"2026-04-14 15:53:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9417634/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9417634/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108181107,"identity":"93261e9a-ace5-4078-b946-26bdd030c074","added_by":"auto","created_at":"2026-04-30 08:57:30","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":211790,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScheme of how to prepare the plate for spheroid formation and morphometric evaluation.\u003c/strong\u003e (a) Add 100 µL of Soft-agar 1.5% to each well using a multi-channel pipette and immediately remove it from the wells. After 30 min under the U.V. light the wells come with a thin and sterile layer of 1.5% soft-agar lining the surface. (b) Workflow for image processing and morphometric analysis in ImageJ: (01) convert the image to 8-bit; (02) detect edges; (03) adjust the threshold; (04) select the region of interest (ROI) using the wand tool; (05) apply the ROI to the original image and perform the measurements. Scale bar = 200µm.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9417634/v1/9fc1933d456dd5f8a01e6882.jpg"},{"id":108014446,"identity":"e92ce29d-897b-4f37-b14c-b8c44952f444","added_by":"auto","created_at":"2026-04-28 13:30:52","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":961681,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eArea analysis of 3D cell aggregates.\u003c/strong\u003e (a) Images of spheroids obtained from HepG2, LX-2, and CCS using the present methodology, at different culture times. (b) Comparison among the different types of spheroids over time. (c) Spheroid occupation area varying between 2, 24, 48, 72, and 96 hours of cultivation in HepG2 (blue), LX-2 (gray), and CCS (black) spheroids. *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, and ****p \u0026lt; 0.0001. Data are presented as mean ± standard error of mean.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9417634/v1/5b03ccdd5e7db0d4d900093d.jpg"},{"id":109203324,"identity":"81e55aaf-f3b3-4f7b-8c74-cd155fc2f111","added_by":"auto","created_at":"2026-05-13 14:30:25","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":571273,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMorphometric properties across time points in HepG2, LX-2, and CCS cell lines cultures in 3D. \u003c/strong\u003e(a-m) Quantification of various morphological properties of HepG2 (blue), LX-2 (gray), and CCS (black) cells at different time points (2h, 24h, 48h, 72h, 96h). Panel (a-b) shows perimeter (mm), (c-d) circularity (AU), (e-f) roundness (AU), (g-h) aspect ratio (AU), (i-j) geometric solidity (AU), (k-l) normalized solidity (AU), and (m-n) mean gray value (MGV). Significant differences are indicated by statistical annotations, with *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, and ****p \u0026lt; 0.0001. Data are presented as mean ± standard error of mean.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9417634/v1/bae6f145e47a5c19b523cc77.jpg"},{"id":108014449,"identity":"c6d7fe45-771a-4971-af03-9ee02e8e9f79","added_by":"auto","created_at":"2026-04-28 13:30:52","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":456323,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCell death analysis in LX-2, HepG2, and CCS cell lines cultured in 3D.\u003c/strong\u003e (a) Representative dot plots of flow cytometry analysis using Annexin V-FITC and propidium iodide (PI) staining\u003cstrong\u003e. \u003c/strong\u003eThe upper left quadrant (Q1) represents necrotic cells (Annexin⁻/PI⁺), the upper right quadrant (Q2) represents late apoptotic cells (Annexin⁺/PI⁺), the lower right quadrant (Q3) represents early apoptotic cells (Annexin⁺/PI⁻), and the lower left quadrant (Q4) represents viable cells (Annexin⁻/PI⁻). Unstained cells were used as negative control. (b-d) Quantification of viable cells, early and late apoptosis in the spheroids of LX-2, HepG2 and CCS at 96 hours. Panel (b) shows the percentage of viable cells, (c) early apoptosis, (d) late apoptosis. (e) Representative dot plots of flow cytometry analysis using propidium iodide (PI) staining\u003cstrong\u003e. \u003c/strong\u003e\u0026nbsp;(f) Quantification of necrotic cells (%). Data are presented as mean ± standard deviation.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9417634/v1/5b7a11344ed89a58c0c67e45.jpg"},{"id":109298389,"identity":"28957ae7-9887-4fd4-91d6-81d71c8f86b8","added_by":"auto","created_at":"2026-05-15 09:11:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2516214,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9417634/v1/65cac400-1ab1-408c-8501-4194e34de7bf.pdf"},{"id":108014454,"identity":"269bbc59-6ccd-46d7-8044-19779b7bd154","added_by":"auto","created_at":"2026-04-28 13:30:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":541948,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarydata.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9417634/v1/39f17564f3ef9bbe332b24a5.pdf"},{"id":108181389,"identity":"f91ca905-afcd-498c-be58-6dda28b186c3","added_by":"auto","created_at":"2026-04-30 08:58:36","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":172593,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarydata.docx","url":"https://assets-eu.researchsquare.com/files/rs-9417634/v1/923bd57e70dcddbc6769aa60.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Role of Hepatic Stellate Cells on Morphometric Dynamics in a Three-dimensional Hepatocellular Carcinoma Coculture Model","fulltext":[{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003eCoculture spheroids show greater compactness than HepG2 monocultures.\u003c/li\u003e\n \u003cli\u003eLX-2 inclusion enhances spheroid solidity and structural organization.\u003c/li\u003e\n \u003cli\u003eNormalized solidity reveals stromal-driven compaction in mixed spheroids.\u003c/li\u003e\n \u003cli\u003eStromal cells modulate spheroid viability and cell-death patterns.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Summary","content":"\u003cul\u003e\n \u003cli\u003eCancer cells behave differently when they grow in three-dimensional structures instead of flat laboratory dishes. By measuring how tumor spheroids change their size and shape over time, the authors demonstrated 3D spheroids made of different cell types grow and change shape in distinct ways. These differences can help scientists choose better laboratory models to study cancer behavior and test treatments.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eHepatocellular carcinoma (HCC) is the most common primary liver cancer and ranks as the third leading cause of cancer-related death globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Despite advances in diagnosis and treatment, HCC remains a challenging disease, partly due to its molecular and cellular heterogeneity and its complex interaction with the tumor microenvironment (TME)[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Traditionally, \u003cem\u003ein vitro\u003c/em\u003e studies have relied on two-dimensional (2D) monocultures of HCC cell lines such as HepG2. While useful, these models fail to recapitulate the structural and cellular complexity of tumors, especially in terms of cell\u0026ndash;cell and cell\u0026ndash;matrix interactions [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. As a result, 2D models often fall short in predicting drug responses or mimicking tumor progression [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThree-dimensional (3D) cell culture systems, such as spheroids, have gained prominence in cancer research. These models better simulate the physiological architecture of solid tumors, including gradients of oxygen, nutrients, and metabolites. Compared to monolayers, 3D cultures more accurately reflect key cellular behaviors, such as extracellular matrix deposition, cellular polarity, and resistance to therapy [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAn essential component of the HCC microenvironment is the hepatic stellate cell (HSC). In a healthy liver, HSCs remain quiescent and store vitamin A in lipid droplets. Upon liver injury, they become activated, acquiring a myofibroblastic phenotype and contributing to fibrogenesis through excessive extracellular matrix secretion [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Persistent activation of HSCs not only leads to liver fibrosis but also promotes tumor progression by enhancing tissue remodeling and facilitating cancer cell invasion [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Given their critical role, co-culture models combining HCC cells and HSCs can provide a more realistic platform to study tumor behavior. These systems can also improve the predictive value of drug screening assays by more closely mimicking \u003cem\u003ein vivo\u003c/em\u003e conditions [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, studies that deeply explore the morphometric characteristics of these co-culture spheroids (e.g., shape, size, and compactness) remain limited.\u003c/p\u003e \u003cp\u003eNotably, tumor morphology has been used as a non-invasive marker of malignancy in imaging-based studies of several cancers[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], including the prediction of microvascular invasion in hepatocellular carcinoma [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Compact and round shapes often correlate with benign behavior, while irregular, lobulated forms are associated with malignancy [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Although shape analysis is already integrated into computer-aided diagnosis (CAD) for cancers such as breast and thyroid [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], its application to liver tumors remains underexplored [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we investigated the morphometric behavior and cell death dynamics of 3D spheroids composed of HepG2 cells (HCC, monoculture), LX-2 cells (HSC, monoculture), and a co-culture of both (CCS). By comparing parameters such as area, perimeter, circularity, solidity, and cell viability over time, we aim to better understand how spheroid architecture reflects the interplay between tumor and stromal components in HCC. Our findings provide insights into model selection for \u003cem\u003ein vitro\u003c/em\u003e studies and offer potential implications for imaging analysis and drug testing platforms.\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Cell culture\u003c/h2\u003e \u003cp\u003eHepG2 cells were purchased from the Rio de Janeiro Cell Bank, and Dr. Karen C. Martinez de Moraes generously provided LX-2 cells from UNESP under the authorization of Prof. Scott Friedman. Both cell lines were maintained in Dulbecco\u0026rsquo;s Modified Essential Medium (DMEM) (Sigma Aldrich, St. Louis, MO, USA) low glucose, with 2% of fetal bovine serum (FBS), 1% of penicillin-streptomycin (10,000 U/mL penicillin and 10 mg/mL streptomycin) under 37\u0026ordm;C and 5% CO\u003csub\u003e2\u003c/sub\u003e in a controlled and humidified incubator. The cells were passaged using 0.25% trypsin-EDTA (Gibco, Grand Island, NY, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Spheroid establishment\u003c/h2\u003e \u003cp\u003eThe 96-well U-bottom plates were coated with a delicate layer of soft-agar (1.5%, pre-sterilized by autoclaving), and after solidification, the plates underwent UV light exposure for 30 minutes [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. HepG2 and LX-2 monocultures were seeded with 5 x 10\u003csup\u003e4\u003c/sup\u003e cells/well in a 96-well plate (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). To emulate the HCC TME, a CCS was established. LX-2 and HepG2 were concomitantly seeded in a 1:1 ratio in each well (2.5 x 10\u003csup\u003e4\u003c/sup\u003e cells/well of each lineage, totalizing 5 x 10\u003csup\u003e4\u003c/sup\u003e cells/well) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Optical microscopy\u003c/h2\u003e \u003cp\u003eSpheroid evolution was monitored by phase-contrast inverted microscopy (Olympus IX40), and images were systematically captured at 24-hour intervals. This observational timeline spanned 96 hours, enabling a thorough examination of the dynamic changes and growth patterns exhibited by the spheroids across their developmental stages.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Morphometric Analysis\u003c/h2\u003e \u003cp\u003eTo measure parameters such as area, density, aspect ratio, perimeter, circularity, roundness, and solidity in ImageJ (NIH, Bethesda, MD), a meticulous protocol was followed [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The image was converted to 8-bit, the scale was calibrated, and measurements were set to include area, mean gray value (MGV), centroid, perimeter, fit ellipse, shape descriptors, integrated density, limit to threshold, and display label. Subsequently, edges were defined, limits were adjusted, and a region of interest (ROI) was chosen using the ROI Manager. The process described above determines a ROI with specific coordinates for each sample. This coordinate (ROI) was then applied to the original image to measure previously defined parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1. Area\u003c/h2\u003e \u003cp\u003eTo measure the growth and compactness of spheroids under different experimental conditions, the area of each spheroid was determined in ImageJ using the number of pixels within the defined ROI [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Upon calibration of the spatial scale in the software, the area values were automatically converted from pixel counts to physical units (\u0026micro;m\u0026sup2;) using the following equation (Eq.\u0026nbsp;\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e):\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:Area=n\u0026ordm;\\:of\\:pixels\\:\\times\\:\\:(Pixel\\:Width\\:\\times\\:\\:Pixel\\:Height)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.4.2. Circularity\u003c/h2\u003e \u003cp\u003eCircularity was calculated to evaluate the contour regularity of the spheroids [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This parameter integrates the area and perimeter of each object, providing a measure of how closely the shape approximates to a perfect circle. Values range from 0 (extremely elongated or irregular shapes) to 1.0 (perfect circle). The formula (Eq.\u0026nbsp;\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) used by the software is:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:Circularity=(4\\pi\\:\\:\\times\\:Area)/Perimeter\u0026sup2;$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.4.3. Roundness\u003c/h2\u003e \u003cp\u003eRoundness was assessed to determine the degree of elongation of the spheroids, independently of contour irregularities. Values close to 1.0 indicate spherical morphologies, whereas lower values suggest structural anisotropy or elongation [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This descriptor considers the ratio between the area and the square of the major axis length, and was calculated using the following formula (Eq.\u0026nbsp;\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e):\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:Roundness=(4\\times\\:Area)/(\\pi\\:\\:\\times\\:Major\\:axis\\:\u0026sup2;)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.4.4. Aspect ratio\u003c/h2\u003e \u003cp\u003eThe aspect ratio of each spheroid was calculated from the Major and Minor axis measurements generated by ImageJ, which are based on an ellipse fitted to the selected ROI. Values close to 1 indicate a more symmetrical profile, while higher values reflect elongated or irregular morphologies [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The aspect ratio was determined using the following formula (Eq.\u0026nbsp;\u003cspan refid=\"Equ4\" class=\"InternalRef\"\u003e4\u003c/span\u003e):\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\:Aspect\\:ratio=\\left(Major\\:axis\\right)/\\left(Minor\\:axis\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.4.5. Solidity\u003c/h2\u003e \u003cp\u003eTwo different approaches were employed to assess solidity in spheroids: geometric solidity, based on shape descriptors; and normalized solidity, derived from grayscale intensity measurements [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Geometric solidity is a descriptor of morphological compactness. It quantifies how closely the spheroid's shape approximates that of a perfect convex structure. Values close to 1.0 indicate a smooth, compact shape with regular edges, while lower values suggest irregularity, fragmentation, or surface roughness [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This metric was calculated in ImageJ using the formula (Eq.\u0026nbsp;\u003cspan refid=\"Equ5\" class=\"InternalRef\"\u003e5\u003c/span\u003e):\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$$\\:Geometric\\:solidity=Area/\\left(Convex\\:area\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eTo complement geometric assessment, we also evaluated spheroid internal density using gray-level pixel intensities obtained from brightfield images. The MGV of each spheroid was used as a proxy for internal compaction, assuming that darker spheroids (lower MGV) reflect higher cellular density or extracellular matrix accumulation. To facilitate interpretation and provide a measure that increases with biological compaction, the following normalization was applied (Eq.\u0026nbsp;\u003cspan refid=\"Equ6\" class=\"InternalRef\"\u003e6\u003c/span\u003e):\u003cdiv id=\"Equ6\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ6\" name=\"EquationSource\"\u003e\n$$\\:Normalized\\:solidity=(Max\\:MGV-Current\\:MGV)/(Max\\:MGV-Min\\:MGV)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e6\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.4.6. Density\u003c/h2\u003e \u003cp\u003eSpheroid density was assessed using the MGV, a parameter provided by ImageJ that reflects the average pixel intensity within a defined ROI. This measurement provides a straightforward quantitative estimate of grayscale density in brightfield images. Lower MGV corresponds to darker regions and may be indicative of increased biological density, such as greater cellular compaction, extracellular matrix (ECM) accumulation, or necrotic areas. Conversely, higher MGV suggest brighter, less dense regions, potentially associated with reduced cell packing or looser tissue organization. This parameter was used both as a standalone indicator of optical density and in the derivation of the normalized solidity index described above [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. It was calculated using the following formula (Eq.\u0026nbsp;\u003cspan refid=\"Equ7\" class=\"InternalRef\"\u003e7\u003c/span\u003e):\u003cdiv id=\"Equ7\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ7\" name=\"EquationSource\"\u003e\n$$\\:Mean\\:Gray\\:Value=(\\sum\\:Pixel\\:intensity)/\\left(n\u0026ordm;\\:of\\:pixels\\:in\\:the\\:ROI\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e7\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Annexin/PI\u003c/h2\u003e \u003cp\u003eTo measure the proportions of dead and viable cells, annexin V-FITC/propidium iodide (PI) was used for labeling. Ten spheroids of each group were collected, centrifuged (1,200 rpm for 10 min), washed once with 1\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\times\\:\\)\u003c/span\u003e\u003c/span\u003e PBS, and dissociated with 300 \u0026micro;L of 0.25% Trypsin-EDTA. The cell suspension was centrifuged and then rewashed with 1\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\times\\:\\)\u003c/span\u003e\u003c/span\u003e PBS. It was subsequently incubated with a solution of Annexin V-FITC (4 \u0026micro;g/mL, QuatroG) and PI (40 \u0026micro;g/mL, Invitrogen) for 15 minutes. The cells were rewashed with 1\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\times\\:\\:\\)\u003c/span\u003e\u003c/span\u003ePBS and then suspended in 300 \u0026micro;L of 1\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\times\\:\\:\\)\u003c/span\u003e\u003c/span\u003ePBS. Data were acquired using a FACS Calibur flow cytometer (BD Biosciences San Jose, CA, USA). The data was analyzed using FlowJo XV version 10 (FlowJo LLC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Statistical analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using GraphPad Prism version 9.0.0. To compare morphometric analysis over time and cell death type across different types of spheroids, we performed a two-way analysis of variance (ANOVA), followed by Tukey \u003cem\u003epost-hoc\u003c/em\u003e tests. Analysis of the size of the difference was also performed (mean difference size\u0026thinsp;=\u0026thinsp;Δd), and the means of the spheroid measurements at 2 hours were compared with those at other times using a one-way ANOVA followed by Sidak \u003cem\u003epost-hoc\u003c/em\u003e. Data is expressed by mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of the mean (S.E.M). For the Annexin V-FITC/PI assay, data from three or more experimental repeats are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Data were analyzed using a one‑way ANOVA, after which a Tukey's test was performed for multiple comparisons.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Morphometric dynamic\u003c/h2\u003e \u003cp\u003eThe spheroids of LX-2, HepG2, and CCS (1:1, LX-2, and HepG2) were generated (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea), and monitored by optical microscopy every 24 hours for 96 hours to observe their appearance (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMorphometric analysis of spheroids is essential for assessing tumor growth, evaluating viability and morphology, and serving as a normalization reference. We could observe that the type of culture (two-way ANOVA, F (2, 71)\u0026thinsp;=\u0026thinsp;135.9; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and the time (two-way ANOVA, F (4, 71)\u0026thinsp;=\u0026thinsp;34.11; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) affects the spheroid area, and there is a significant interaction between these factors (two-way ANOVA, F (8, 71)\u0026thinsp;=\u0026thinsp;2.752; P\u0026thinsp;=\u0026thinsp;0.0105) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea and b). The number of cells that were seeded in each well was the same for each group, but over time the compactness dynamics starts to reveal differences among the types of culture (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Within 2 hours, the HepG2 spheroids show a higher area than LX-2 and CCS spheroids (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea and b). Still, this difference among the groups is further enhanced over time, with the area of HepG2 spheroids being 4.8x higher than that of LX-2 spheroids (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and 4.6x higher than that of CCS spheroids (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb) (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The HepG2 spheroid area was reduced by 21,94% in 96 hours compared with the initial area (2 hours), from 1.718\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27 mm\u0026sup2; to 1.341\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 mm\u0026sup2;, but this difference is not statistically significant (P\u0026thinsp;=\u0026thinsp;0.1002) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Differently, after 24 hours of seeding, both LX-2 and CCS spheroids had the area significantly reduced (Table\u0026nbsp;1S): the LX-2 spheroid area was decreased by 72% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and the CCS spheroid area was decreased by 71.66% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). After 96 hours, the total rate of area reduction in the LX-2 spheroids achieved 80.42%, from 1.419\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26 mm\u0026sup2; to 0.2778\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 mm\u0026sup2; (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). We could observe a similar behavior of area reduction in CCS spheroid, in 2 hours2 hours of culture the area counts with 1.303\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12 mm\u0026sup2;. After 96 hours of cultivation, it ends with 0.2882\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 mm\u0026sup2;, comprehending a total reduction of 77.88% in the spheroid area (P\u0026thinsp;\u0026lt;\u0026thinsp;0,0001, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe observed that both the time (two-way ANOVA, F (4, 71)\u0026thinsp;=\u0026thinsp;15,17; P\u0026thinsp;\u0026lt;\u0026thinsp;0,0001) and the type of culture (two-way ANOVA, F (2, 71)\u0026thinsp;=\u0026thinsp;53.19; P\u0026thinsp;\u0026lt;\u0026thinsp;0,0001) affected the perimeter of the spheroids, but there is no interaction between these factors (F (8, 71)\u0026thinsp;=\u0026thinsp;0.7013, P\u0026thinsp;=\u0026thinsp;0.6893) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). The perimeter of the LX-2 and CCS spheroids showed similar behavior throughout the time, reducing dramatically in the first 24 hours (LX-2\u0026thinsp;=\u0026thinsp;63.571%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; CCS\u0026thinsp;=\u0026thinsp;66.854%, P\u0026thinsp;\u003cem\u003e\u0026lt;\u003c/em\u003e\u0026thinsp;0.0001) (Table S4), and then maintaining the perimeter reduced without abrupt changes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). The HepG2 spheroids did not follow the perimeter reduction as in LX-2 and CCS spheroids. The total reduction (from 2 hours to 96 hours96 hours) of HepG2 spheroids\u0026rsquo; perimeter was about 23.796%, but this observation was not statistically significant (P\u0026thinsp;=\u0026thinsp;0.4939) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, Table S4). When comparing the types of culture, LX-2 spheroids had a lower perimeter than HepG2 at 24 hours (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), 48 hours (P\u0026thinsp;=\u0026thinsp;0.0020), 72 hours (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and 96 hours (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). This difference in the perimeter was also observed comparing HepG2 with CCS spheroids, with significant differences at 24 hours (P\u0026thinsp;\u0026lt;\u0026thinsp;0,0001), 48 hours (P\u0026thinsp;=\u0026thinsp;0,0068), 72 hours2 hours (P\u0026thinsp;\u0026lt;\u0026thinsp;0,0001), and 96 hours (P\u0026thinsp;\u0026lt;\u0026thinsp;0,0001) (Table S3 and S4). At the end of the 96 hours of culture, LX-2 and CCS spheroids had a decrease in the perimeter of 77.042% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and 70.82% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), respectively (Fig. b).\u003c/p\u003e \u003cp\u003eAs spheroid culture progresses, cells tend to aggregate and form a spherical structure. However, the degree of circularity can vary depending on the cell type in the culture. The time and type of culture influence spheroid\u0026rsquo;s circularity, but there is no interaction between these two factors (P\u0026thinsp;=\u0026thinsp;0.0087, P\u0026thinsp;=\u0026thinsp;0.0001, and P\u0026thinsp;=\u0026thinsp;0.7376, respectively). We observe that until 48h of culture, the groups do not differ in circularity, but in 72 hours HepG2 spheroids present less circularity than CCS (P\u0026thinsp;=\u0026thinsp;0.0210), and at 96 hours HepG2 spheroids become less circular than LX-2 spheroids (P\u0026thinsp;=\u0026thinsp;0.0256) and CCS spheroids (P\u0026thinsp;=\u0026thinsp;0.0215) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). A perfect circle has a circularity value of 1. In contrast, more complex or jagged structures have circularity values closer to 0 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). This means that spheroids with smooth, well-defined edges will have higher circularity, whereas those with irregular or rough boundaries will have lower circularity. The HepG2 spheroid reaches a circularity of 0.1373 at 96 hours, the LX-2 spheroid reaches 0.4045, and CCS spheroid reaches 0.4112 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed), but no statistical difference was observed when comparing the spheroids circularity at 2 hours vs 96 hours (HepG2 P\u0026thinsp;=\u0026thinsp;0.9858; LX-2 P\u0026thinsp;=\u0026thinsp;0.0927; CCS P\u0026thinsp;=\u0026thinsp;0.0706).\u003c/p\u003e \u003cp\u003eRoundness measures how close a shape is to a circle, but it is based on the major axis rather than the perimeter. For example, a perfect circle has a roundness of 1. We observed that the only factor which has an effect over spheroid roundness is the type of culture (two-way ANOVA, F (2, 70)\u0026thinsp;=\u0026thinsp;4,462; P\u0026thinsp;=\u0026thinsp;0.0150), but over time, the cultures do not present any significant differences (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee). The roundness of HepG2 spheroids starts at 0.8267 arbitrary units (AU) at 2 hours of culture and has only 1.911% of increase (96 hours\u0026thinsp;=\u0026thinsp;0.8425 AU., P\u0026thinsp;=\u0026thinsp;0.9733) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef). On the other hand, the roundness of LX-2 spheroids starts within 0.5467 AU., and it increases over time, reaching 0.8514 AU. at 48h (versus 2 hours, P\u0026thinsp;=\u0026thinsp;0.0005), 0.8797 AU. at 72 hours (versus 2 hours, P\u0026thinsp;\u0026lt;\u0026thinsp;0,0001), and 0.8940 AU. at 96 hours (versus 2 hours, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef), culminating in an increase of 63.527% at the end of the culture (Table\u0026nbsp;10). CCS spheroids\u0026rsquo; roundness behaves similarly to that of the HepG2 spheroids. Their roundness starts at 0.6900 AU. in 2 hours of culture, and by the end (96 hours), they reach 0.8473 AU. Although the increase is approximately 22.797% (Table\u0026nbsp;10), this is not statistically significant compared to 2 hours (P\u0026thinsp;=\u0026thinsp;0.7547, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef).\u003c/p\u003e \u003cp\u003eRoundness considers the major axis of the spheroid in the equation. The aspect ratio of the spheroid also includes the minor axis measures. A two-way ANOVA revealed that time was the sole significant factor influencing aspect ratio (F (4, 69)\u0026thinsp;=\u0026thinsp;2.963, P\u0026thinsp;=\u0026thinsp;0.0255), while type of culture (P\u0026thinsp;=\u0026thinsp;0.2564), and the interaction between factors (P\u0026thinsp;=\u0026thinsp;0.1013) were not significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg). However, despite the overall significance of time, \u003cem\u003epost-hoc\u003c/em\u003e analysis indicated that the aspect ratio at the endpoint (96 hours) did not differ significantly from baseline (2 hours) for any group. Specifically, while HepG2, LX-2 and CCS spheroids exhibited reductions in aspect ratio of 4.1% (Fig.\u0026nbsp;6C), 17.0% (Fig.\u0026nbsp;6D), and 18.5% (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eh) respectively, these changes did not reach statistical significance.\u003c/p\u003e \u003cp\u003eIn order to analyze if shape changes in spheroids or if the edges of a spheroid become more regular/smooth/compact, we used the parameter called geometric solidity. We observe no effect of time or type of culture in this parameter on the different types of spheroids (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ei). Only at the first 24 hours HepG2 spheroids had significantly lower geometric solidity than CCS (26.819% lower, P\u0026thinsp;=\u0026thinsp;0.0303). Although the geometric solidity of HepG2 spheroid increased 43.684% and of CCS spheroid increased 21.955% at 96 hours, those alterations were not statistically significant (HepG2 2 hours versus 96 hours, P\u0026thinsp;=\u0026thinsp;0.23640; CCS 2 hours versus 96 hours, P\u0026thinsp;=\u0026thinsp;0.08940) spheroids did not change significantly over time (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ej) (Table S14). On the other hand, LX-2 spheroids start in 48h to significantly increase the geometric solidity by 28.935% (P\u0026thinsp;=\u0026thinsp;0.02050, and at the end of the culture (96 hours), they sum 36.782% of increasing (P\u0026thinsp;=\u0026thinsp;0.00450) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ej).\u003c/p\u003e \u003cp\u003eAs geometric solidity does not account for pixel intensity (gray values) - only shape, we accessed the normalized solidity. Normalized solidity shows us how compact spheroids appear and is based on the MGV. We observe that time (F (4, 72)\u0026thinsp;=\u0026thinsp;35.39, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and type of culture (F (2, 72)\u0026thinsp;=\u0026thinsp;44.81, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) have an effect on the normalized solidity of spheroids. There is also an interaction between factors (F (8, 72)\u0026thinsp;=\u0026thinsp;3.306, P\u0026thinsp;=\u0026thinsp;0.0029) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ek). At the first 2 hours, all the types of cultures are similar, presenting similar normalized solidity (Table S11). In 24 hours, CCS spheroids are 33.407% more solid than HepG2 (P\u0026thinsp;=\u0026thinsp;0.0001), as well as LX-2, which are 28.330% more solid than HepG2 (P\u0026thinsp;=\u0026thinsp;0.0421). At the end of the culture, at 96 hours, the CCS spheroids are 37.132% more solid than HepG2 spheroid (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and LX-2 spheroids are also 58.709% more solid than HepG2 spheroid (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ek) (Table S12). HepG2 spheroid does not statistically change the solidity over time, even the increase of the solidity being around of 43.404% at the end of the culture (96 hours) compared to the beginning (P\u0026thinsp;=\u0026thinsp;0.19480) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003el). On the other hand, LX-2 spheroid increased by 102.640% the solidity in the first 24 hours (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and ends the culture with an increase of 148.419% (P\u0026thinsp;\u0026lt;\u0026thinsp;0,0001) compared with the 2 hours of culture (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003el). The same occurs with the solidity of CCS spheroids. At the first 24 hours, they increased by around 90.081% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and, at the end of the culture, by 99.582% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003el).\u003c/p\u003e \u003cp\u003eAs time passes, the spheroids become darker, AU indicating they are becoming more compact. Lower MGV and density reflect this, as shown in the AU of MGV. As the MGV increases, the spheroid becomes lighter, and the density decreases. We observe that time (F (4, 70)\u0026thinsp;=\u0026thinsp;40,40, P\u0026thinsp;\u0026lt;\u0026thinsp;0,0001) and type of culture (F (2, 70)\u0026thinsp;=\u0026thinsp;62,53, P\u0026thinsp;\u0026lt;\u0026thinsp;0,0001) had effect over spheroids density, and there is an interaction between factors as well (F (8, 70)\u0026thinsp;=\u0026thinsp;4,136, P\u0026thinsp;=\u0026thinsp;0,0004) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003em). During the first 2 hours of culture all the types of spheroids present no difference in the density parameter. At 24 hours, HepG2 spheroids have a higher MGV (18,294%) than LX-2 (P\u0026thinsp;=\u0026thinsp;0.0176) and CCS (47,834%, P\u0026thinsp;\u0026lt;\u0026thinsp;0,0001). This pattern is repeated over the next few hours of culture, but after 72 hours of culture, CCS have a higher MGV than LX-2 spheroids (27.197%, P\u0026thinsp;=\u0026thinsp;0.0427). At the end, in 96 hours, HepG2 spheroids had still higher MGV than LX-2 (37.314%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and then of CCS spheroids (60.104%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003em). The density of HepG2 spheroids does not change statistically over time, but LX-2 and CCS spheroid did (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003en). LX-2 spheroids decrease the MGV in 29.21% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) at 24 hours and 45.375% after 96 hours of culture (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003en). CCS spheroids also had a decrease on MGV after 24 hours of 40.424% (P\u0026thinsp;\u0026lt;\u0026thinsp;0,0001) and of 44.667% at 96 hours (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003en).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Cell death\u003c/h2\u003e \u003cp\u003eEach culture type behaves in a particular way, as we observed in the morphometric analyses. These differences in the spheroid compactness may be related to differences in the cell death rates. To evaluate cell death patterns at the end of 96 hours of spheroid formation for each culture type, we performed an Annexin V-FITC/PI co-labeling assay.\u003c/p\u003e \u003cp\u003eWe first evaluated the viable cells in each culture type, selecting only the cells that were not labeled with either Annexin or PI (quadrant 4\u0026thinsp;=\u0026thinsp;Q4, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea and b). No significant differences were observed in the viability across the culture types. Next, we assessed early apoptosis by selecting cells labeled with annexin (gate: \u003cem\u003eAnnexin+ cells\u003c/em\u003e and \u003cem\u003ePI\u0026minus; cells\u003c/em\u003e) (quadrant 3\u0026thinsp;=\u0026thinsp;Q3, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). The one-way ANOVA indicated that the type of culture tended to affect early apoptosis, but is not statistically different. HepG2 spheroids showed 3.6% higher levels of early apoptosis compared to LX-2 spheroids. CCS spheroids behaved quite differently, exhibiting higher levels of early apoptosis than LX-2 by approximately 54.35%, and higher than HepG2 by 52.65%, though these differences were not statistically significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). We then examined late apoptosis, characterized by cells that were labeled with both Annexin and PI (quadrant 2\u0026thinsp;=\u0026thinsp;Q2, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). The data showed no significant differences in late apoptosis levels across the groups. Although CCS spheroids exhibited lower levels of late apoptosis than LX-2 (48.8315%) and HepG2 (92.9891%), these differences were not statistically significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003eFinally, we evaluate the necrosis by selecting all cells labeled with PI (gate: \u003cem\u003ePI+ cells\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee). The one-way ANOVA showed that the type of culture had a significant effect on necrosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ef). HepG2 spheroids had significantly higher levels of necrosis (50.5085%) compared to LX-2 spheroids and CCS spheroids (76.3299%). Although CCS spheroids had slightly higher levels of necrosis than LX-2 (12.7316%), this difference was not statistically significant.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eMorphometric parameters such as area, perimeter, circularity, and roundness are commonly used to evaluate the size, shape, and regularity of biological structures, including adipocytes [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and cell nuclei [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. These measurements have also proven helpful in assessing spheroid formation across different 3D culture methodologies [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], as they offer quantitative insights into the structural organization of these models.\u003c/p\u003e \u003cp\u003eBuilding upon this approach, we applied morphometric analysis to investigate the dynamic behavior of spheroids in an HCC context. While \u003cem\u003ein vitro\u003c/em\u003e HCC models have advanced our understanding of tumor biology and therapeutic responses, their predictive value is often limited by the use of traditional 2D monocultures, which lack the complexity of the \u003cem\u003ein vivo\u003c/em\u003e TME [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In contrast, 3D cultures systems (particularly co-cultures) offer more physiologically relevant tumor models, more accurately mimicking the TME [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], including cell\u0026ndash;cell interactions and extracellular matrix (ECM) production [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In this study, we investigated the morphometric and cell death dynamics of spheroids derived from HepG2 and LX-2 cells, both as monocultures and in a CCS. By evaluating structural and functional parameters over 96 hours, we aimed to understand how the presence of stromal components influences spheroid architecture and viability in an HCC context.\u003c/p\u003e \u003cp\u003eOur morphometric analysis encompassed multiple shape descriptors, including area, perimeter, circularity, roundness, aspect ratio, solidity (geometric and normalized), and density. While roundness, aspect ratio, and geometric solidity did not differ significantly across groups, circularity showed a distinct pattern: HepG2 spheroids exhibited significantly lower circularity than LX-2 and CCS spheroids. Although circularity and roundness are related, they describe different geometric attributes: circularity being more sensitive to contour irregularities and symmetry, while roundness predominantly reflects elongation [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The reduced circularity observed in HepG2 spheroids suggests greater structural irregularity or asymmetry, which could influence internal diffusion dynamics.\u003c/p\u003e \u003cp\u003eIt has been shown that spheroid geometry directly affects diffusion gradients. Circular and symmetric spheroids facilitate more uniform diffusion toward the center, while irregular or elongated shapes increase surface area and reduce the average diffusion distance, potentially leading to uneven distribution of oxygen, nutrients, or drug [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Therefore, the altered geometry of HepG2 spheroids may contribute to the higher necrosis levels observed in this group, either by compromising central oxygenation or by hindering the clearance of waste products. Thus, although circularity alone does not define compactness, it reflects geometric properties that are functionally relevant in spheroid biology [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDistinct trends were also observed in size-related metrics. Both area and perimeter significantly decreased in LX-2 and CCS spheroids from 2 to 24 hours of culture and continued to decrease until 96 hours, suggesting rapid and sustained compaction. In contrast, HepG2 spheroids exhibited a significant increase in diameter between 2 and 24 hours, resulting in a larger overall size. While area is often interpreted as a growth indicator [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], it may reflect compactness. This nuance is critical for interpreting spheroid behavior in early culture phases.\u003c/p\u003e \u003cp\u003eCompactness in LX-2 and CCS spheroids was further supported by increased normalized solidity and reduced MGV, as well as reduced area and perimeter, both of which suggest greater density and structural integrity. Their presence in CCS appears to enhance mechanical stability and compactness, likely through ECM production and stromal\u0026ndash;tumor interactions [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] HepG2 spheroids, in contrast, formed larger and looser aggregates, likely due to weaker cell\u0026ndash;cell adhesion. Our results align with prior studies showing increased compactness and viability in HCC spheroids co-cultured with stromal cells, reinforcing the essential role of the microenvironment in spheroid maturation.\u003c/p\u003e \u003cp\u003eInterestingly, while Taroncher et al. observed continued spheroid growth in co-cultures during the final 24 hours of a 96-hour culture. Our normalized area analysis from 72 to 96 hours did not reveal significant growth in any group (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. A potential explanation lies in the methodological differences. Their use of centrifugation accelerates spheroid formation and compactness, while our spontaneous aggregation approach provides a slower but more accessible model. Discrepancy may reflect both technical differences and variations in cellular behavior under distinct culture conditions.\u003c/p\u003e \u003cp\u003eGeometric solidity values in HepG2 spheroids here found (80,7%) were comparable to those reported in the literature (80\u0026ndash;95%) [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. However, normalized solidity and MGV were significantly improved in CCS and LX-2 spheroids, indicating a more stable structure. These normalized metrics, which account for inter-spheroid variability, proved more sensitive than geometric solidity alone, offering a better resolution of compaction differences between groups.\u003c/p\u003e \u003cp\u003eRegarding viability, the only significant difference in cell death profiles was found in necrosis levels. HepG2 spheroids exhibited the highest level of necrosis, which is consistent with their larger size and lower compactness. Larger spheroids (\u0026gt;\u0026thinsp;500 \u0026micro;m) are more susceptible to hypoxia-induced necrosis due to impaired diffusion of oxygen and nutrients [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. It is well established that in spheroids exceeding 500 \u0026micro;m in diameter, central regions can become severely hypoxic due to diffusion limitations [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. This hypoxia leads to the stabilization of hypoxia-inducible factor 1-alpha (HIF-1α), triggering metabolic reprogramming such as the Warburg effect and promoting necrotic cell death in the spheroid core due to acidification and waste accumulation [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Notably, all spheroid groups in our study exceeded this size threshold throughout the culture period, but their structural evolution differed substantially. The pronounced compaction observed in LX-2 and CCS spheroids may have improved diffusion efficiency and reduced central necrosis.\u003c/p\u003e \u003cp\u003eCrucially, co-cultured spheroids exhibited significantly lower necrosis than HepG2 monocultures, suggesting a protective role of LX-2 cells. These findings align with previous studies demonstrating that stellate cells support hepatocyte viability and spheroid integrity via the secretion of extracellular matrix and survival factors [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. By enhancing compactness and possibly contributing ECM components, LX-2 cells modulate the physical and biochemical environment, supporting cell survival [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. This highlights the value of co-culture systems in recapitulating the tumor-stromal interplay seen \u003cem\u003ein vivo\u003c/em\u003e [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSpheroids of HepG2 co-cultured with LX-2 exhibited reduced necrosis, suggesting a protective role of LX-2 cells. A study using a live/dead fluorescence assay showed similar results, with co-culture spheroids demonstrating significantly higher viability than HepG2 monocultures [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The authors attributed this to stellate cells improving hepatocyte viability and structural organization.\u003c/p\u003e \u003cp\u003eTogether, our findings demonstrate that spheroid morphology and viability are strongly influenced by cellular composition. Co-culture with LX-2 cells promoted more compact, symmetrical, and viable spheroids, better representing the TME. These insights support the use of co-culture systems as more robust 3D models for HCC studies.\u003c/p\u003e \u003cp\u003eAlthough we evaluated spheroid compaction and structure using diverse morphometric parameters, we did not assess ECM deposition or stiffness directly. These could have provided further insight into stromal contributions. Also, a more comprehensive panel of cell death markers (e.g., caspase activity, autophagy) could reveal subtler phenotypic shifts. Despite these limitations, our approach provides a valuable foundation for future studies aiming to refine \u003cem\u003ein vitro\u003c/em\u003e HCC models and probe tumor\u0026ndash;stroma interactions.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eOur findings demonstrate that both morphometric and cell death profiles are strongly influenced by spheroid composition. The inclusion of LX-2 cells resulted in more compact, symmetrical, and viable spheroids, underscoring the critical role of stromal components in shaping tumor architecture and supporting cell survival. These results highlight the need to select appropriate 3D models based on the biological question at hand, particularly when investigating tumor structure, microenvironmental interactions, and diffusion-related phenomena. Co-culture systems, by mimicking the \u003cem\u003ein vivo\u003c/em\u003e complexity of HCC, offer a more physiologically relevant platform for preclinical studies and therapeutic testing.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHepatocellular carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTME\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTumor microenvironmental\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e2D\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etwo-dimensional\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e3D\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ethree-dimensional\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHSC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehepatic stellate cells\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCAD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecomputer-aided diagnosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eco-culture system\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDMEM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDulbecco\u0026rsquo;s Modified Essential Medium\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efetal bovine serum\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eultraviolet light\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMGV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emean gray value\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eregion of interest\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhosphate-buffered saline\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEDTA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eethylenediaminetetraacetic acid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epropidium iodide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003erpm\u0026thinsp;=\u0026thinsp;rotations per minute\u003c/div\u003e \u003cdiv class=\"Description\"\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eANOVA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eanalysis of variance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eΔd\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emean difference size\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSEM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estandard error of mean\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ephosphatidylserine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eECM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eextracellular matrix\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHIF-1α\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehypoxia-inducible factor 1-alpha.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS) [grant number 24/25510001320-2, 2024]. Additional support was provided by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).\u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting Interests\u003c/h2\u003e \u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthics approval\u003c/h2\u003e \u003cp\u003eThis is an observational study. The UFRGS Research Ethics Committee has confirmed that no ethical approval is required.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis work was supported by FAPERGS [grant number 24/25510001320-2, 2024].\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJ.O. and F.T.C.R.G. contributed to the conceptualization and design of the study. Methodology, material preparation, and data collection were performed by J.O., J.G.V., and N.B.N.. Formal analysis and investigation were conducted by J.O.. J.O. also performed data curation and wrote the original draft of the manuscript. Writing\u0026mdash;review and editing were carried out by F.T.C.R.G., V.M.T.T., and J.deO.. Resources were provided by F.T.C.R.G., V.M.T.T., and J.deO.. Supervision was performed by F.T.C.R.G. and V.M.T.T., and funding acquisition was secured by F.T.C.R.G.. All authors contributed to previous versions of the manuscript, read, and approved the final version.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to thank the colleagues from GumaLab and the Laboratory of Metabolic Disorders and Neurodegenerative Diseases (LABIMN) at the Federal University of Rio Grande do Sul for their valuable support and contributions to this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRumgay H et al (2022) Global, regional and national burden of primary liver cancer by subtype. 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Sci.\u003c/em\u003e, vol. 20, n\u003csup\u003eo\u003c/sup\u003e 7, pp. 1\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms20071629\u003c/span\u003e\u003cspan address=\"10.3390/ijms20071629\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoulouarn C, Cl\u0026eacute;ment eB Stellate cells and the development of liver cancer: Therapeutic potential of targeting the stroma, 2014. Elsevier B V \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhep.2014.02.003\u003c/span\u003e\u003cspan address=\"10.1016/j.jhep.2014.02.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"molecular-biology-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mole","sideBox":"Learn more about [Molecular Biology Reports](https://www.springer.com/journal/11033)","snPcode":"11033","submissionUrl":"https://submission.nature.com/new-submission/11033/3","title":"Molecular Biology Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"HCC, spheroids, tumor microenvironment, cell death, hepatocytes, hepatic stellate cells","lastPublishedDoi":"10.21203/rs.3.rs-9417634/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9417634/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHepatocellular carcinoma (HCC) remains a leading cause of cancer mortality worldwide. While three-dimensional (3D) spheroid models better recapitulate tumor architecture than conventional two-dimensional systems, the contribution of stromal components to spheroid organization and viability remains incompletely understood. In particular, the relationship between spheroid morphology and cell death dynamics in the presence of hepatic stellate cells (HSCs) has not been fully characterized. This study aimed to investigate how stromal cells influence spheroid architecture and survival in a 3D HCC model.\u003c/p\u003e\u003ch2\u003eMethods and Results\u003c/h2\u003e \u003cp\u003eSpheroids were generated using HepG2 cells, LX-2 cells (HSCs), and a 1:1 co-culture system (CCS) and monitored over 96 hours (n\u0026thinsp;=\u0026thinsp;3 independent experiments). Morphometric parameters, including area, perimeter, circularity, aspect ratio, geometric and normalized solidity, and mean gray value, were quantified using ImageJ. Cell death was assessed by Annexin V/propidium iodide staining. CCS spheroids exhibited reduced area and perimeter compared to HepG2 monocultures (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), along with increased circularity and normalized solidity, indicating enhanced structural organization and compaction. HepG2 spheroids showed higher necrosis levels, whereas CCS spheroids displayed reduced necrosis and a trend toward increased early apoptosis, suggesting improved viability in the presence of stromal cells.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eHepatic stellate cells modulate spheroid architecture and cell death dynamics, promoting more compact and viable tumor structures. These findings highlight the role of tumor\u0026ndash;stroma interactions in HCC and support co-culture spheroids as more physiologically relevant preclinical models.\u003c/p\u003e","manuscriptTitle":"Role of Hepatic Stellate Cells on Morphometric Dynamics in a Three-dimensional Hepatocellular Carcinoma Coculture Model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-28 13:30:44","doi":"10.21203/rs.3.rs-9417634/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-19T09:35:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-18T11:29:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"264482675500081618656411100656147182567","date":"2026-05-13T07:47:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"243356408639359646599204585655486226004","date":"2026-05-11T12:32:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"334471125228274509394732790953872076311","date":"2026-05-11T09:09:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"86409581928982831382176984433239446244","date":"2026-04-21T06:06:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-20T11:37:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-16T13:26:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-16T13:25:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Molecular Biology Reports","date":"2026-04-14T15:42:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"molecular-biology-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mole","sideBox":"Learn more about [Molecular Biology Reports](https://www.springer.com/journal/11033)","snPcode":"11033","submissionUrl":"https://submission.nature.com/new-submission/11033/3","title":"Molecular Biology Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"5d878c13-c86e-4863-870f-887cbdcc8dbd","owner":[],"postedDate":"April 28th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-19T09:35:03+00:00","index":27,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-18T11:29:51+00:00","index":26,"fulltext":""},{"type":"reviewerAgreed","content":"264482675500081618656411100656147182567","date":"2026-05-13T07:47:21+00:00","index":25,"fulltext":""},{"type":"reviewerAgreed","content":"243356408639359646599204585655486226004","date":"2026-05-11T12:32:32+00:00","index":24,"fulltext":""},{"type":"reviewerAgreed","content":"334471125228274509394732790953872076311","date":"2026-05-11T09:09:21+00:00","index":23,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T13:30:44+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-28 13:30:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9417634","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9417634","identity":"rs-9417634","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}