Preclinical humanized bone models reveal metabolic reprogramming and simvastatin benefits in castration-resistant prostate cancer in bone

Preclinical humanized bone models reveal metabolic reprogramming and simvastatin benefits in castration-resistant prostate cancer in bone | 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 Article Preclinical humanized bone models reveal metabolic reprogramming and simvastatin benefits in castration-resistant prostate cancer in bone Agathe Bessot, Sugandha Bhatia, Jennifer Gunter, Lea Badin, Judith Clements, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8720393/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract Although initially effective to treat prostate cancer (PCa), resistance to antiandrogen therapies is inevitable and leads to metastatic castration-resistant PCa. Bone marrow adipocytes (BMAs) may play a role in bone metastasis therapy resistance by promoting metabolic reprogramming, yet their value as a therapeutic target remains understudied due to a lack of relevant models. Here, we used multicellular, modular hydrogel models in advanced humanized settings to examine the value of BMA targeting in advanced PCa. Our in vitro and in vivo findings confirmed that BMAs induce lipid metabolism dysregulation and pro-inflammatory signaling, creating a tumor-supportive environment that fosters resistance to androgen deprivation. Combining enzalutamide with the anti-cholesterol drug simvastatin significantly reduced these effects, notably through ferroptosis and bone tumor microenvironment modulations, impairing cancer cell survival. This study suggests that targeting BMA-PCa interactions with simvastatin may enhance enzalutamide’s efficacy, emphasizing the synergistic value of human-specific multicellular preclinical models for assessing therapeutic strategies in bone metastasis. Biological sciences/Cancer/Bone cancer Health sciences/Diseases/Cancer/Bone cancer Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Prostate cancer (PCa) remains a significant health concern globally, ranking as the second most common male-specific cancer diagnosed. 1 A hallmark feature of this malignancy is its reliance on the androgen signaling pathway for growth and survival, making androgen deprivation therapy (ADT) a successful treatment strategy. 2 While initially effective, patients can develop ADT resistance, transitioning to a more aggressive state: castration-resistant PCa (CRPC). 2 CRPC cells exhibit increased metastatic potential, particularly towards the bone microenvironment, 3 which is associated with poorer outcomes. 4 , 5 The development of second-generation androgen therapies (androgen-targeted therapies (ATT), such as bicalutamide and enzalutamide) allow the inhibition of PCa growth by targeting the androgen receptor (AR). 2 Unfortunately, treatment failure through AR reactivation prohibits full treatment efficiency. 6 While effectively targeting PCa cells, androgen-deprivation induces as a side-effect a metabolic shift, leading to metabolic syndrome. 7 This shift is characterized by increased adiposity (systemic increase of fat storage), elevated circulating lipids, insulin resistance (hyperglycemia) and a rise in metabolic hormones (e.g., leptin), further fueling cancer cell growth. 8 – 10 Additionally, androgen deprivation leads to bone dysregulation associated with higher risks of fracture, 11 and increase of marrow adiposity. 12 , 13 While the role of white adipose tissue (adipocytes from subcutaneous and visceral tissue) in cancer progression is well established, 14,15 bone marrow adipocytes (BMAs) remain less studied despite being the main component of bone marrow in adults (> 70% of marrow volume). 16 Although similar to white adipocytes, notably in their metabolic and endocrine functions (lipid storage, adipokine and cytokine secretion), 17 BMAs differ significantly in origin, lipid composition, and secretory profiles; displaying smaller size, less lipolytic, and secreting distinct levels of adipokines and inflammatory mediators. 16 Recent research has shed light on the multifaceted role BMAs play in bone metastases. 18 These studies showed that cancer-associated BMAs (CA-BMAs, adipocytes found in close proximity to cancer cells) present dysregulated phenotypes (proinflammatory profile), characterized by an increase in protumoral factor secretion (free fatty acids, IL-6, leptin, CXCL1/2) 15,19,20 and reduced adiponectin (antitumoral) secretion, 18 modulating the bone microenvironment. 21 These factors support cancer cell growth within the bone microenvironment, and contribute to therapy resistance, through the activation of multiple pathways (i.e., HIF1α, MAPK, PI3K/Akt and Jak2/STAT3). 18,22–24 Despite the growing interest in the BMA-cancer cell crosstalk, the full picture of the pathway dysregulations remains elusive. However, the current findings strongly suggest that BMA-secreted factors, such as leptin, 25 and lipid transfer, 26 could be promising targets as therapeutic strategies to inhibit protumoral effects of BMAs in cancer. Metformin and statins, commonly used to treat metabolic conditions such as diabetes and hyperlipidemia, have shown promises in overcoming enzalutamide resistance. 27 , 28 Metformin, a biguanide, improves insulin sensitivity and decreases hyperglycemia, conditions exacerbated by androgen deprivation. 29 Additionally, metformin has been shown to directly inhibit adipogenesis, 30 present a multimodal inhibitory effects on PCa cells 31 and a capacity to lift enzalutamide resistance in PCa cells. 32 Similarly, statins demonstrated inhibitory effects on androgen-deprivation-induced adipogenesis, via cholesterol metabolism pathways, and on PCa progression within the bone microenvironment, by inducing cancer cell apoptosis. 12 Combining enzalutamide with statins, including simvastatin, has demonstrated preliminary efficacy in overcoming PCa cell resistance to enzalutamide and reducing disease progression in 2D cultures and PCa-derived xenograft models, by inhibiting the overactivated sterol synthesis in PCa cells under androgen deprivation conditions. 33 Although promising, these studies rely on murine xenograft models, which lack the human-specific processes and bone microenvironment context. Current models of bone metastasis, whether in vitro or in vivo , fail to fully recapitulate the complex human tumor bone microenvironment, limiting our understanding of the cellular and molecular mechanisms driving metastatic progression and therapeutic resistance. 34 – 36 While 3D models offer improvements over traditional 2D systems by incorporating extracellular matrix (ECM) components such as collagen, Matrigel, or silk-based scaffolds, 37,38 they are limited in replicating the dynamic biochemical and mechanical cues of the bone marrow niche. Moreover, they typically lack sufficient cellular heterogeneity, coculturing PCa cells with only one stromal cell type such as osteoblasts, macrophages, or adipocytes. 39 – 41 While there is a stronger focus on delineating the role of adipocytes in cancer, a limited number of models focuses on bone metastases and includes bone marrow adipocytes. 42 Despite offering systemic complexity, in vivo murine models are limited by a lack of species specificity. In xenograft models, human tumor cells must interact with a murine stroma that differs fundamentally in cell biology, 43,44 compromising the fidelity of tumor–microenvironment interactions. In particular, murine BMAs differ markedly from their human counterparts in metabolic activity, adipokine expression and signaling pathways, which could lead to discrepancies in how tumors respond to adipocyte-derived cues. 45 Furthermore, murine tumors often arise from mesenchymal tissues and display lower metastatic potential compared to human epithelial tumors. 46 These interspecies differences compromise clinical relevance and drug response predictability. In response to these challenges, our group previously developed both in vitro (indirect and direct 3D multicellular systems) and in vivo humanized models using gelatin methacryloyl (GelMA) hydrogels, incorporating primary BMAs and androgen receptor-expressing PCa cells (LNCaP, C4-2B). 47 , 48 GelMA is a photocrosslinkable, tunable, and biocompatible hydrogel derived from denatured collagen, offering a balance between biological activity (e.g., RGD motifs supporting cell adhesion) and mechanical stability. 49 Unlike natural ECM materials such as Matrigel, which suffer from batch variability and undefined composition, GelMA provides reproducibility and structural customization, with biological and mechanical properties specifically attuned to modeling the complex bone marrow environment. Our previous GelMA-based models revealed adipocyte delipidation upon coculture and BMA-induced resistance to enzalutamide on cancer cells, supporting a functional role of BMAs in therapy evasion. 47 , 48 Here we advanced physiological relevance by modular combination of human osteoblasts, BMAs, and PCa cells, used as in vitro and in vivo humanized platforms. These models offer increased cellular complexity and mimicry of the bone and fat cellular compartments of bone marrow, allowing the investigation of specific niche crosstalks. In this study, we extended this platform to model metastatic CRPC, incorporating a mineralized microenvironment to more accurately evaluate therapeutic response by transcriptomic profiling. To capture the diverse effects of human BMAs on different stages of PCa, we employed two distinct AR-expressing cell lines with varying dependence to androgen: LNCaP cells (androgen-dependent) and C4-2B cells (androgen-independent). We used these humanized models to test combination therapies with enzalutamide and repurposed metabolic drugs (metformin, simvastatin), aiming to co-target BMA-mediated tumor-supportive mechanisms and improve therapeutic outcomes in CRPC. Results Developing a multicellular paracrine in vitro model using primary bone cells to mimic a fat-enriched mineralized tumor microenvironment The development of multicellular models is crucial to decipher the specific interactions between cancer cells and their microenvironment. 50 Based on our previous coculture system, 48 we introduced an additional bone-like element by incorporating mineralized microtissues composed of primary human osteoblasts (Fig. 1 ). Osteoblasts not only are highly responsive to BMAs, 51,52 but also recapitulate important cellular and extracellular features of the mineralized bone environment that contribute to bone disease progression and therapy resistance. 53 , 54 We first validated that all three cell types, primary human adipocytes (derived from SGBS cells or BMSCs), primary human osteoblasts, and human PCa cells, could be cocultured in a reduced medium without compromising cell viability or function. Once primary human osteoprogenitors differentiated into osteoblasts, they were cultured in a coculture medium (CoM) previously validated for both adipocytes and PCa cell lines. 48 After one week in CoM, no significant impact on osteoblast metabolic activity or mineralization was observed compared to culture in OM, confirming compatibility of this coculture medium for all three cell types over this time frame ( Figure S1 ). As BMAs shares similarities with white adipocytes, 17 we then investigated how white adipocytes (SGBS-derived) and bone marrow adipocytes (BMSC-derived) behaved within the bone-like environment. Although white adipocytes are not native to bone, investigating their phenotypic plasticity is important: if they can adopt BMA-like traits in the bone environment, SGBS-derived adipocytes could offer a practical and scalable model for bone metastases, due to their ease of isolation and handling. 55 Additionally, their heightened insulin sensitivity and active insulin signaling make them especially relevant for studying the metabolic alterations associated with androgen deprivation therapy in advanced PCa. 56 To explore these possibilities, we performed RNA sequencing on adipocytes upon coculture with osteoblasts. Transcriptomic analyses revealed significant differences between BMAs and SGBS adipocytes, particularly in genes related to lipid metabolism (Fig. 2 ). Over 4,000 genes were differentially expressed between the two groups (Fig. 2 .A), encompassing pathways related to organismal system (321 genes), human diseases (431 genes including 212 genes related to pathways in cancer), and environment information processing (333 genes). Notably, steroid biosynthesis (11 genes), regulation of lipolysis (25 genes), and PPAR signaling (31 genes) were differentially enriched between the two populations (Fig. 2 .B). Consistent with these pathway-level differences, BMAs exhibited lower expression of several lipid metabolism-related genes, including LPL , MGLL , and LIPE , compared to SGBS-derived adipocytes (Fig. 2 .C). These findings align with previous observations by Attané et al., who reported a lipolytic defect in primary BMAs relative to white adipocytes. 57 Here, we developed an all-human, 3D multicellular model that mimicked a human fat-enriched, mineralized bone microenvironment by coculturing primary human osteoblasts and adipocytes. Transcriptomic analysis revealed distinct phenotypic differences between SGBS- and BMSC-derived adipocytes within the bone-like context, particularly in lipid metabolism and cancer-related pathways, highlighting the unique features of BMAs. Bone marrow adipocytes exhibit early signs of tumor-induced metabolic reprogramming compared to white adipocytes After observing the distinct lipid metabolism in BMAs compared to SGBS-derived adipocytes in the presence of mineralized osteoblasts, we investigated the effect of PCa cells on adipocyte phenotype. We hypothesized that, similar to SGBS-derived adipocytes, BMAs would undergo phenotypic reprogramming in the presence of PCa cells. Specifically, we predicted that BMAs would acquire characteristics of cancer-associated adipocytes (CAAs), such as delipidation and a protumoral gene expression profile, reflecting a shift toward a tumor-supportive phenotype, 15,19,20 even with their unique lipid metabolism. Gene expression analyses revealed that BMAs were less transcriptionally responsive to PCa-derived cues in the coculture system compared to SGBS adipocytes, as only 132 genes were significantly affected, against 347 genes in SGBS adipocytes (Fig. 3 . A-B ). KEGG pathway analyses indicated that LNCaP cells altered BMA metabolism by upregulating pathways involved in metabolic regulation, cellular stress responses and intercellular communication (e.g., APLN, BCO1, GLS2 , Fig. 3 .C-D). These changes reflect an important metabolic reprogramming of BMAs by cancer cells, consistent with prior observations. 48 , 58 , 59 Furthermore, downregulation of bone-related genes (e.g., FGF18, TNFRS11A ) suggests that BMAs may also contribute to remodeling the bone microenvironment in response to tumor signaling. In addition to transcriptional changes, morphological evidence of delipidation was observed in BMAs cocultured with LNCaP and C4-2B cells (Fig. 3 .E), aligning with previously reported characteristics of CA-BMAs. 47 , 48 , 60 , 61 In contrast to BMAs, SGBS-derived adipocytes exhibited different transcriptional responses to LNCaP cells ( Figure S2.A-B ). These changes primarily involved cellular components rather than molecular functions or biological processes, indicating that SGBS adipocytes undergo structural and compartmental remodeling. This remodeling may represent an early step in their phenotypic reprogramming, preceding functional adaptations such as lipid transfer, suggesting a delayed response compared to BMAs. Immunofluorescence analysis (Figure S2.C) revealed a slight, though not statistically significant, decrease in lipid content in response to LNCaP cells, whereas exposure to C4-2B cells led to an increase in intracellular lipid accumulation. This observation is consistent with previous reports indicating that tumor-exposed adipose tissue may initially undergo adipogenesis, followed by delipidation, thereby supplying free fatty acids to support cancer cell survival and proliferation in a tumor demand–dependent manner. 62 In summary, despite showing fewer affected genes compared to SGBS adipocytes, BMAs exhibited a significant transcriptional response to PCa cells, with upregulation of metabolic and stress-related pathways and evidence of delipidation, indicating phenotypic reprogramming in response to the tumor microenvironment. In contrast, SGBS adipocytes displayed slower and more structural changes, suggesting a distinct, less immediate response to PCa cells. This underscores the importance of considering adipocyte origin when studying their role in the bone metastatic niche. The crosstalk between cancer-associated bone marrow adipocytes and prostate cancer cells involves metabolic dysregulation To determine how CAAs influence prostate cancer progression, we examined their effects on LNCaP and C4-2B cells, representing hormone-sensitive and castration-resistant stages, respectively. We hypothesized that CAAs, particularly BMAs, which display a more tumor-supportive phenotype, would enhance lipid metabolism and energy production in cancer cells, thereby promoting proliferation within the bone microenvironment, as previously suggested. 48 RNA sequencing revealed that LNCaP cells exhibited distinct transcriptional responses depending on the adipocyte type in coculture with osteoblasts (Fig. 4 . A-B, Figure S3.A ), highlighting adipocyte-specific effects on tumor transcriptional programs. In the presence of BMAs, LNCaP cells upregulated multiple pathways implicated in tumor progression, including Wnt, VEGF, PPAR, AMPK, adipocytokine signaling, and cholesterol metabolism (Fig. 4 .C). Expression of key lipid-handling genes ( FABP4, CD36, PLIN1, LPL, ABCD2 , ABCA family) was markedly increased (Fig. 4 .D), suggesting enhanced fatty acid uptake, storage, and lipolysis to support survival within the mineralized microenvironment, consistent with prior PCa models. 63 BMA coculture also induced pro-inflammatory cytokines (e.g., CSF1 , IGF2 ) and therapy resistance pathways (ABC transporters) in LNCaP cells, consistent with activation of PI3K/Akt, MAPK/ERK and JAK/Stat signaling. 64 – 66 Similar, though less pronounced, transcriptional changes were observed in the androgen-independent C4-2B cell line (Fig. 4 .E), indicating that BMA-driven tumor-supportive signaling extends across disease stages, in contrast to prior studies emphasizing effects on androgen-dependent cells. 48 SGBS-derived adipocytes induced a narrower transcriptional response, primarily affecting complement and coagulation cascades, PPAR and IL-17 (Figure S3.B). Their weaker impact on PCa cells’ lipid metabolism and cytokine signaling (Figure S3.C–D), compared to BMAs, indicates a reduced capacity to create a protumoral microenvironment. This likely reflects the intrinsic phenotype of white adipocytes, which may acquire cancer-associated features more slowly, resulting in less robust tumor-supportive signaling compared to BMAs within one week of coculture. Morphometric analysis showed comparable spheroid sizes in cocultures with osteoblasts ± adipocytes for both PCa cell lines (Fig. 4 .F, Figure S3.E). This differs from earlier reports in non-mineralized systems, 48 emphasizing the importance of osteoblast mineralization in modulating tumor–stromal interactions. However, a higher density of nuclei was observed in PCa spheroids upon coculture with BMA and SGBS (Fig. 4 .G, Figure S3.F), indicating enhanced PCa cell proliferation. In tri-cultures, PCa cells expressed higher expression of KLK3 (PSA) and AR compared to adipocyte-only cocultures ( Figure S4.A vs Figure S4.B). Despite stronger modulation of metabolic pathways in the tri-culture model, spheroid size did not significantly increase compared to osteoblast-free cocultures, possibly due to the intrinsic pro-tumoral effects of osteoblasts themselves. 53 These findings underscore the importance of refining preclinical in vitro models by incorporating multiple cell types to more accurately mimic the tumor microenvironment in cancer research. By employing an all-human, 3D tri-culture model that integrates adipocytes, osteoblasts, and PCa cells, we provide a physiologically relevant platform for dissecting stromal–tumor interactions in bone metastasis. Overall, our advanced model reveals that BMA exert consistent tumor-supportive effects across both androgen-dependent and androgen-independent PCa stages. Within the mineralized osteoblastic microenvironment, BMAs drive a coordinated transcriptional reprogramming that enhances lipid uptake and utilization, activates inflammatory and pro-survival pathways, and upregulates mediators of therapy resistance. This metabolic and signaling crosstalk promotes PCa cell adaptation and persistence within the bone niche. Human adipocytes promote castration and enzalutamide resistance in a humanized bone tumor microenvironment via lipid metabolic reprogramming and microenvironmental signaling. Adipose tissue functions as a dynamic endocrine organ influencing systemic metabolism and bone homeostasis. 67 , 68 Beyond direct interactions with cancer cells, adipocytes can systemically modulate pathways such as insulin sensitivity and cholesterol metabolism, both frequently dysregulated in advanced PCa. 69 Moreover, adipocytes may shape the bone microenvironment to favor tumor survival, 70 as suggested by our transcriptional analyses (Fig. 4 ). To delineate species-specific effects of human BMAs on PCa bone metastases growth and survival, we used an innovative in vivo mouse model by enhancing our previously developed humanized fat-enriched bone tumor microenvironment. 47 We hypothesized that human adipocytes would enhance androgen-deprivation resistance of androgen-dependent (LNCaP) and androgen-independent (C4-2B) PCa xenografts within the humanized bone microenvironment. Following ectopic humanized bone formation, cancer cells were implanted into the humanized bone microenvironment, and tumors were monitored before and after surgical castration (Fig. 5 . A ). The presence of human adipocytes did not influence progression prior to castration (Fig. 5 .B) but significantly enhanced resistance to castration, particularly in C4-2B xenografts (Fig. 5 .C-D). Transcriptomic profiling of LNCaP tumors revealed adipocyte-driven upregulation of lipid metabolism and inflammatory signaling pathways (Fig. 5 .E), mirroring our in vitro findings. Notably, key genes regulating lipid uptake (FABP4, CD36, ACSL5) and cholesterol metabolism (ANPP7P1, APOA1, LDLRAD2) were upregulated, together with pro-inflammatory mediators (CXCLs, CCL2, TNF) ( Figure S5 ). Immunohistochemistry confirmed increased proliferation (Ki67), without changes in PSA expression (Fig. 5 .F, Figure S6 ), in the presence of human adipocytes, consistent with prior evidence linking adipocyte-derived signals to metabolic flexibility and cancer cell survival. 20 , 70 , 71 Given that human adipocytes enhanced castration resistance, we investigated whether they could similarly affect enzalutamide response in PCa cells. Following one week of enzalutamide (10 µM) treatment in vitro , both PCa cell lines exhibited increased growth in the presence of human BMAs. C4-2B cells formed larger spheroids with higher nuclear intensity, whereas LNCaP spheroids maintained a similar size to controls but displayed increased nuclear density ( Figure.6.A.i ). Transcriptomic analysis revealed increased expression of lipid metabolism-related genes (e.g., FABP4 and CD36 ) in cocultures with BMAs, without changes in KLK3 , AR and ABCC3 (gene coding for ATP binding cassette, responsible for drug influx within cells) (Fig. 6 .A.ii-iii). Similarly, coculture with SGBS-derived white adipocytes significantly increased enzalutamide resistance in both AR-positive cell lines, accompanied by elevated expression of AR , FABP4 , CD36 and ABCC3 ( Figure S7 ). Despite phenotypic differences, both adipocyte types promoted enzalutamide resistance, with a stronger effect observed in white adipocytes cocultures. To validate these observations, in vivo humanized models were used to include systemic effects of metabolic syndrome associated with androgen deprivation, which can also influence both adipocytes and PCa progression. In C4-2B xenografts, human adipocytes conferred significant resistance to enzalutamide, with tumor progression comparable to untreated xenografts lacking adipocytes (Fig. 6 . B.i ). In contrast, human adipocytes did not significantly affect LNCaP tumor growth under enzalutamide, although KEGG pathway analysis revealed extensive transcriptomic remodeling (Fig. 6 .B.ii). Pathways enriched in LNCaP tumors included TGF-β, PI3K/Akt, and MAPK signaling, pathways implicated in therapy resistance and tumor progression. Additionally, enrichment of ECM–receptor interactions, complement/coagulation cascades, and Rap1 signaling indicated microenvironmental remodeling and altered immune-adhesion dynamics, supported by increased expression of BMP2, PDGFs, TNC, CCLs, FTH1P7 , and SERPINE1 . Metabolic pathways, including PPAR signaling and lipolysis in adipocytes, were significantly modulated (upregulation of FABP4 , CD36 , LPL , and SLC27A6 and downregulation of AQP7 ), reinforcing the role of adipocytes in reshaping lipid metabolism within the tumor context. These transcriptomic shifts suggest that adipocytes foster a metabolically adaptive microenvironment that supports PCa cell survival under antiandrogen pressure. Although no significant effect on PCa progression or PSA levels after were detected after four weeks of treatment (Figure S6), immunohistochemistry confirmed decreased proliferation under enzalutamide (Fig. 6 .B.iii). Notably, macrophage infiltration increased compared to untreated xenografts, as previously reported, 72 particularly in adipocyte-rich tumors. Despite the absence of tumor growth changes, human adipocytes enhance protumoral signaling and immune infiltration in LNCaP xenografts, potentially diminishing therapy responsiveness over time. Collectively, findings from both 3D in vivo and in vitro humanized models demonstrated that human BMAs remodel both lipid metabolism and inflammatory signaling to promote resistance to androgen deprivation and enzalutamide. This adipocyte-mediated reprogramming generates a metabolically flexible and pro-survival microenvironment, underscoring the potential of targeting adipocyte–tumor interactions to overcome antiandrogen resistance in bone-metastatic CRPC. Combination of enzalutamide with anti-cholesterol simvastatin drug inhibits prostate cancer progression by enhancing ferroptosis and modulating the bone tumor microenvironment To evaluate whether repurposed metabolic drugs could mitigate enzalutamide-induced metabolic dysregulation and BMA-mediated protumoral effects, we treated 3D cocultures with enzalutamide (10 µM, Enz), metformin (1 mM, Met), simvastatin (5 µM, Sim), or their combinations (Enz + Met; Enz + Sim) for one week. In LNCaP spheroids, both repurposed drugs alone significantly inhibited growth by approximately 40%, relative to controls (Fig. 7 . A ), confirming their intrinsic antitumor activity, as previously suggested. 12 , 32 Unexpectedly, combining either drug with enzalutamide did not further reduced spheroid size beyond enzalutamide monotherapy. However, in the presence of human BMAs, the Enz + Sim combination markedly decreased LNCaP cell density, suggesting an inhibitory effect on cell proliferation. In C4-2B spheroids, simvastatin exhibited synergy with enzalutamide only under coculture with BMAs, reducing spheroid growth by ~ 37% compared to 24% with enzalutamide alone, without significantly reducing cell density. The enhanced anti-tumoral likely arises from simvastatin-mediated inhibition of cholesterol signaling within BMAs, thereby diminishing their protumoral influence on PCa cells. 73 Transcriptomic analyses revealed modest yet consistent alterations in cancer cell gene expression under combined treatments (Fig. 7 .B). Enzalutamide with either metformin or simvastatin reduced KLK3 and AR expression in androgen-dependent cells, particularly in mineralized cocultures without adipocytes. However, the presence of human adipocytes attenuated this downregulation, suggesting a protective microenvironmental effect. Secreted PSA levels measured in conditioned medium mirrored these trends, showing the greatest suppression under the Enz + Sim combination (Fig. 7 .C), consistent with previous 2D studies. 33 , 74 , 75 Combined treatments also modulated metabolic gene expression (Fig. 7 .B). Enz + Sim, and to a lesser extent Enz + Met, upregulated PPARγ , CD36 , PLIN1 upregulated PPARγ, CD36 , and PLIN1 , particularly in LNCaP cells, indicating a shift toward enhanced lipid utilization, potentially compensating for reduced glucose uptake under androgen signaling inhibition. 76 Coculture with human BMAs further amplified this lipid metabolic signature ( PNPLA2, LIPE, PLIN1 and FABP4 ) while suppressing glucose uptake (downregulation of SLC2A4 ), suggesting adipocyte-derived fatty acids support cancer cell survival under dual therapy. Notably, Enz + Sim reduced expression of protumoral and microenvironmental remodeling genes (AQP7, CSF1, FGF7, SERPINE1) compared with enzalutamide alone, implying partial reversal of BMA-induced signaling. Protein analyses confirmed reduced ferritin and PAI-1 (SERPINE1) levels under Enz + Sim ( Figure S8 ). This shift suggests that the combined therapies influenced BMAs-cancer cells interactions, leading the PCa cells toward a less resilient and potentially less aggressive phenotype compared to enzalutamide treatment alone. Using the human 3D in vitro coculture systems, we demonstrated that the combined treatment of enzalutamide with simvastatin significantly reduced enzalutamide resistance induced by BMAs in LNCaP and C4-2B spheroids in vitro suggesting a potential strategy to enhance enzalutamide’s efficacy in advanced prostate cancer. While 3D coculture models provide valuable insights into drug responses within the localized tumor microenvironment, they cannot recapitulate systemic physiological interactions that critically influence therapeutic efficacy. To address this, we evaluated whether metformin or simvastatin could overcome enzalutamide resistance in vivo using our humanized bone tumor model. Following surgical castration, mice were treated for four weeks (or until clinical endpoint, defined as tumor volume > 999 mm³) with enzalutamide ± metformin or simvastatin (Fig. 8 . A ). Tumor progression was monitored by serial measurement of tumor size after castration and throughout treatment (Fig. 8 .B). In the absence of human adipocytes, both combination treatments reduced LNCaP tumor progression compared to enzalutamide alone. Tumors treated with enzalutamide alone increased by 25% relative to their post-castration size, whereas those receiving Enz + Met showed only a 10% increase, and those treated with Enz + Sim exhibited a 10% reduction. These results confirm the intrinsic antitumoral activity of both repurposed agents. However, when human adipocytes were present, tumor progression under Enz + Met became comparable, indicating that adipocytes diminished metformin’s therapeutic benefit. Although this contrasts with some preclinical reports, 32 it aligns with clinical observations showing limited efficacy of metformin in advanced PCa. 77 By contrast, the combination of enzalutamide + simvastatin significantly reduced tumor progression compared to enzalutamide alone in the presence of human adipocytes, although the magnitude of inhibition was lower than in adipocyte-free conditions (5% reduction versus 10%). This outcome is consistent with prior preclinical 12 , 33 , 74 , 78 and clinical studies 79 , 80 reporting improved survival among patients receiving statins during androgen deprivation therapy. Mechanistically, this enhanced effect likely reflects simvastatin-mediated inhibition of cholesterol metabolism in both BMAs and PCa cells, which reduces lipid availability and pro-inflammatory cytokine signaling within the tumor microenvironment. 73 , 81 At endpoint, no statistically significant differences in ex vivo tumor volume, bioluminescence or PSA secretion were observed between treatment groups. Nevertheless, tumors from the Enz + Sim group tended to be smaller than those treated with enzalutamide alone, whereas Enz + Met, particularly in the presence of human adipocytes, was associated with larger tumors, suggesting enhanced tumor progression ( Figure S9 ). A pilot experiment using C4-2B xenografts confirmed similar synergistic effects of Enz + Sim, especially in adipocyte-rich tumors, while metformin again failed to reduce progression and increased growth in the absence of adipocytes ( Figure S10 ). Together, these data underscore the importance of incorporating human adipocytes into the humanized bone model to more accurately capture tumor–stroma interactions and systemic metabolic influences on therapy response. To elucidate the mechanisms underlying these effects, we performed transcriptomic analyses on LNCaP xenografts. Principal component analysis revealed clear separation between the simvastatin combination and enzalutamide-alone groups, indicating distinct transcriptional reprogramming (Fig. 8 .C). In contrast, tumors from the enzalutamide + metformin group clustered closely with those treated with enzalutamide alone. In tumors bearing human adipocytes, differential gene expression analysis identified that enzalutamide + simvastatin enhanced pathways associated with necroptosis and ferroptosis, along with significant dysregulation in mineral absorption, ECM-receptor interaction and complement and coagulation cascade (Fig. 8 .D). These transcriptomic alterations suggest activation of regulated cell death pathways and remodeling of the extracellular environment, collectively contributing to reduced tumor viability and resistance. Among the most significantly modulated genes (Fig. 8 .E), downregulation of FTH1 and its pseudogenes, key regulators of ferroptosis, may underlie the observed decrease in tumor proliferation and therapy resistance from the Enz + Sim group, as seen in breast cancer models. 82 , 83 Additionally, decreased expression of SERPINE1 implies reduced angiogenesis and macrophage M2 polarization, 84 supporting the concept that simvastatin attenuates the protumoral immune microenvironment. Notably, simvastatin also suppressed adhesion- and migration-related genes (e.g., ITGA7 , PLGLB2 ), suggesting diminished metastatic potential under combination therapy. Histological analyses further validated these transcriptomic findings. Human adipocytes enhanced vascularization in tumors (Fig. 9 . B ), an effect inhibited by enzalutamide + simvastatin. The combination therapy markedly reduced tumor cell proliferation (Ki67, Fig. 9 .C), while maintaining similar PSA levels (Figure S10.C), indicating proliferation arrest rather than cytotoxicity. Importantly, simvastatin significantly reduced macrophage recruitment within adipocyte-rich tumors (Fig. 9 .E), thereby limiting the pro-inflammatory microenvironment that supports tumor survival. Protein-level validation confirmed reduced expression of ferritin and plasminogen activator inhibitor-1 (PAI-1, encoded by SERPINE1) in tumors receiving the Enz + Sim treatment (Fig. 9 .D,F), reinforcing simvastatin’s impact on vascularization, immune infiltration, and tumor proliferation. These pronounced effects were specific to the enzalutamide + simvastatin combination; enzalutamide + metformin failed to inhibit BMA-induced protumoral effects or to further suppress proliferation and microenvironmental remodeling compared to enzalutamide alone ( Figure S11 ). These findings align with clinical observations, 77 yet diverge from prior in vivo studies using ectopic xenografts. 32 This highlights the critical need to incorporate a humanized bone microenvironment in preclinical models to accurately model metabolic therapy responses. Collectively, these in vivo studies demonstrate that simvastatin enhances the efficacy of enzalutamide by mitigating BMA-driven resistance mechanisms. The combination reduced tumor progression, suppressed expression of protumoral and metabolic adaptation markers, and limited macrophage recruitment and vascularization within the bone tumor niche. In contrast, metformin showed modest activity in adipocyte-depleted conditions but failed to counteract the supportive effects of BMAs. Thus, simvastatin emerges as a superior co-treatment strategy, acting through coordinated modulation of cholesterol metabolism, cell death pathways, and the tumor microenvironment to increase cancer cell susceptibility to antiandrogen therapy. Discussion Bone metastases mark an advanced and often fatal stage of prostate cancer where current ATTs such as enzalutamide fail, 85 largely because the bone microenvironment actively supports tumor persistence. 14 , 15 , 41 , 86 Although ADT is known to alter bone remodeling 11 and systemic metabolism, 7 mechanistic insights have primarily been derived from murine models that differ markedly from the human marrow niche, notably in adipokine secretion and lipid composition. 36 These interspecies discrepancies have long complicated translation of preclinical discoveries. Our study addresses this gap through a human-specific, multicellular bone model that enables direct examination of BMA-cancer interactions under physiologically relevant conditions. While recent 3D models capture important aspects of bone physiology (e.g., architecture, extracellular matrix, cellular multiplicity, soluble factors) and have advanced our understanding of tumor biology and therapy response, few yet include bone marrow fat cells. 87 Previous 3D approaches have focused on single stromal components of bone metastasis, including osteoblasts or adipocytes, 39,41,47,88 yet none (to the best of our knowledge) have incorporated both mineralized matrix and adipose tissue, two hallmarks of PCa cells within a modular GelMA hydrogel, our platform captures features of the microenvironment previously accessible only in vivo , while retaining experimental control. GelMA hydrogels, a widely accepted and characterized biomaterial for 3D cell culture, 89 were used here to develop modular coculture systems due to their collagen-derivative nature, innate biocompatibility, and ease of controlled gelation. 47 Using GelMA as a carrier, the major innovation of this study was the multicellular, modular nature of the coculture system present here incorporating not only human BMAs and PCa cells, but also human osteoblasts. This design also aligns with recent calls to replace animal-derived matrices such as Matrigel with reproducible, chemically defined biomaterials. 90 Importantly, it allows systematic dissection of human-specific crosstalk, overcoming the species mismatch that limits xenograft fidelity. Our findings align with earlier reports that adipocytes foster PCa progression metabolic reprogramming 48 and tumor microenvironment modulation, 21 but extend these observations by showing that human BMAs possess a distinct metabolic signature compared with subcutaneous white adipocytes. Prior transcriptomic analyses of murine marrow fat suggested a “beige-like” phenotype , 91 with reduced lipolytic capacity. 57 We observed a similar trend in human BMAs, supporting the notion that marrow fat constitutes a metabolically restrained yet highly reactive depot. In contrast to studies using 2D cocultures, which often report uniform adipocyte activation, our multicellular system revealed cell-type-specific responses: BMAs underwent delipidation and pro-inflammatory reprogramming, while SGBS-derived adipocytes demonstrated slower plasticity. The relationship between lipid metabolism and therapy resistance has been widely recognized. Cholesterol plays a critical role in maintaining intracellular homeostasis, 92 but in the context of cancer, it promotes immune evasion by upregulating inhibitory immune checkpoint genes, thereby impairing antitumor immune responses. 93 Moreover, our findings align with previous reports demonstrating that cholesterol synthesis contributes to enzalutamide resistance by interacting with the mTOR and AR signaling axes. 33 Beyond metabolism, our transcriptomic analyses indicated activation of prosurvival pathways (e.g., PI3K/Akt, MAPK, and AMPK), similar to prior observations. 18 , 22 – 24 The upregulation of ABC transporters such as ABCC3 aligns with earlier work implicating lipid-regulated efflux pumps in multidrug resistance. High ABCC3 expression has been associated with poor clinical outcomes across multiple cancer types, 65 due to its capacity to reduce intracellular drug concentrations and diminish therapeutic efficacy. 94 Notably, ABCC3 expression is regulated by Wnt signaling, 95 a pathway we found to be dysregulated in the presence of BMAs, further supporting the role of adipocyte-derived cues in driving a multidrug-resistant phenotype. Importantly, our system also reproduced immune-related changes previously described, including macrophage recruitment via CSF1 and CCL2 signaling. 96 , 97 Such cross-validation with independent models strengthens confidence that the observed mechanisms are not model artefacts but authentic hallmarks of the metastatic bone niche. Repurposed drugs provide a pragmatic approach to combination therapy as their pharmacodynamics and toxicology are well understood, making them attractive options for reducing the tumor-supportive activity of BMAs without extensive early-phase testing. 98 Repurposing drugs also opens avenues for more immediate translational impact, as these agents can quickly be integrated into clinical trials. Recent studies indicate that repurposing strategies may be particularly beneficial in targeting the metabolic dependencies of cancer cells within the bone marrow niche. 99 Several groups have explored metabolic interventions using metformin (AMPK inhibitors) or statins (cholesterol inhibitors) to overcome ATT resistance. In 2D and xenograft models, both drugs exhibited antitumor activity, by inhibiting autophagy, 78 reducing mitochondrial respiration, 100 angiogenesis, 101 and pro-inflammatory signaling. 102 Yet, clinical trials have yielded mixed results for metformin 77 and more consistent benefits for statins. 79 , 80 The divergent outcomes may reflect differences in microenvironmental complexity, precisely what our model accounts for. The enhanced effect of simvastatin observed in our system mirrors recent data linking cholesterol depletion to ferroptosis vulnerability. 103 Ferroptosis, a form of regulated cell death driven by iron-dependent lipid peroxidation, has gained recognition as a critical mechanism in cancer biology. 104 In bone-metastatic PCa especially, the fatty acid-rich bone environment, induced by BMAs, and altered iron metabolism further promote lipid peroxidation and oxidative damage, enhancing ferroptosis susceptibility and potentially disrupting bone homeostasis, which supports cancer progression. 103 The complementary effects of simvastatin on cholesterol metabolism, ferroptosis induction, and microenvironmental remodeling underscore its therapeutic potential when combined with enzalutamide. This convergence between clinical and preclinical observations underscores the translational value of humanized multicellular systems for decoding metabolic resistance pathways within a controlled human context. We acknowledge that our in vitro system primarily captures paracrine interactions, and that direct physical contact between mature BMAs and tumor cells could further enhance the model’s physiological relevance. Previous studies have shown that such direct interactions facilitate lipid transfer and alter gene expression patterns supporting tumor survival. 105 , 106 However, establishing direct cocultures remains technically demanding, as it requires efficient co-encapsulation of mature BMAs with cancer cells and precise attribution of cell-specific contributions. 47 , 88 Moreover, in vitro systems inherently lack systemic influences from BMAs, such as endocrine and metabolic signaling, that shape the bone microenvironment and therapeutic response in vivo . These factors limit the ability to fully reproduce the complex responses to combination therapies observed clinically, emphasizing the complementary value of in vivo modeling. While our humanized in vivo model recapitulated therapeutic behaviors consistent with clinical outcomes, it also presents certain limitations. The adipose component currently relies on SGBS-derived adipocytes, which, although metabolically responsive, 56 do not fully reflect the phenotype of primary BMAs. Nonetheless, the use of SGBS cells provides a practical advantage by enabling the generation of sufficient and standardized adipocyte populations for in vivo experiments, overcoming the scarcity of primary BMA yield. 55 Future refinements integrating primary or induced bone marrow adipocytes will further enhance model specificity, although isolation and culture of primary BMAs remain challenging. 107 Despite these constraints, the platform’s defining strength lies in its ability to deconstruct complex, human-specific interactions within the bone metastatic microenvironment with unprecedented control and reproducibility. The breadth of the results presented here powerfully reinforce and extend a growing body of evidence positioning bone marrow adiposity as a key determinant of therapeutic resistance in metastatic PCa. By situating these insights within an all-human, multicellular system, we provided a platform that combines mechanistic precision with translational realism. By focusing on the mechanisms of drug resistance and identifying synergistic drug combinations, humanized models serve as a robust preclinical platform for evaluating innovative therapeutic strategies. The ability of this model to reproduce known clinical drug responses and uncover lipid-driven resistance pathways exemplifies its potential as a next-generation preclinical tool. More broadly, it supports a paradigm shift, from descriptive murine studies to human-specific, modular systems capable of revealing how stromal metabolism shapes cancer evolution and treatment response within the bone niche. Consequently, the platform is not limited to PCa but adaptable to other malignancies that colonize bone, including breast and lung cancers. Material and Methods In vitro cell culture Cells : Human osteoprogenitors used for osteoblastic microtissues were isolated from bone samples (ethics approval: Queensland University of Technology (QUT) 1400001024), as previously described, 108 and cultured in basal growth medium ( Table S1 , GM). Human bone marrow mesenchymal stem cells (BM-MSCs, ATCC, PCS500012, USA, used at passage 3–4) and Simpson-Golabi-Behmel syndrome (SGBS, human preadipocytes, a gift from Dr Barclay from Mater Research, Australia, used at passages 15–17) were cultured in adipocyte proliferation medium ( Table S1 , APM). LNCaP and C4-2B cell lines, transduced to express luciferase (a gift from the Australian Prostate Cancer Research Centre-Queensland (APCRC-Q), ethical approval for genetically modified organisms (1700000184)) were used at passages 34–39 and cultured in cancer proliferation medium ( Table S1 , CM). All human cell use was approved by QUT ethics #LR 2023-5612-12871. Cell encapsulation in GelMA hydrogels and microtissue formation Cells encapsulation in GelMA precursor solution (porcine type A, 300 bloom, 80% degree of functionalization, purchased from Gelomics, Australia) was performed according to previously described protocol. 47 Briefly, a photoinitiator, Irgacure 2959 (1-[4-(2-hydroxyethoxy)-phenyl]-2-hydroxy-2-methyl-1-propanone, BASF, Germany), was added to the GelMA precursor solution at a concentration of 0.005% (w/v) prior to crosslinking. Hydrogel casting was done using Teflon (PTFE) molds of 5 mm × 3 mm (volume of 65 µL) and hydrogels were crosslinked for 15 min at 365 nm, with a light intensity of 2.6 mW.cm − 2 . After crosslinking, hydrogels were placed in 48 well-plates and rinsed with phosphate-buffered saline (PBS) before being cultured in their respective culture medium (1 mL medium/well). To generate osteoblastic mineralized microtissues, primary human osteoprogenitors were embedded and crosslinked in GelMA 5% w/v (final compressive modulus around 6 kPa, Fig. 1 . B ) at a cell density of 2×10 6 cells/mL, and cultured in osteogenic medium (OM, Table S1 ), with three days in mineralization medium (MM, Table S1 ) to boost mineral deposition. For adipose hydrogels, human preadipocytes (SGBS) and BM-MSCs were embedded and crosslinked in GelMA 4% w/v (final compressive modulus around 2.5 kPa, Fig. 1 .B) at a cell density of 4×10 6 cells/mL, and cultured in adipogenic induction medium (AIM, Table S1 ) for the first two days of differentiation followed by adipogenic medium (AM, Table S1 ) for the rest of the differentiation duration. PCa cells were embedded and crosslinked in GelMA 4% w/v hydrogels at a cell density of 0.5×10 6 LNCaP cells/mL and 0.35×10 6 C4-2B cells/mL, and cultured as spheroids in cancer proliferation medium until coculture (CM, Table S1 ). Coculture systems and treatments Prior to coculture, 3D microtissues were preconditioned in 50% coculture medium and 50% of their respective medium (AIM for adipocytes, CM for cancer cells and OM for osteoblasts) for three days. Mineralized, adipose, and tumor microtissues were cocultured in coculture medium (Table S1 , CoM, 2.5 mL medium/well), after cell differentiation and spheroid formation in 3D settings (Fig. 1 . A ). For treatments, cells were cocultured in the different treatment media; CoM with DMSO (control), enzalutamide (10 µM, Enz), metformin (1 mM, Met), simvastatin (5 µM, Sim), enzalutamide (10 µM) combined with metformin (1 mM, Enz + Met), and enzalutamide (10 µM) combined with simvastatin (5 µM, Enz + Sim). Medium was fully replenished at day 3 and 5 of coculture. Animal experiments and monitoring In vivo experiments were conducted under the approval of the University of Queensland Animal Ethics Committee (approval number 2021-AE000353) and in accordance with the Australian Code of Practice for the Care and Use of Animals for Scientific Purposes. Six-week-old male NSG mice (strain NOD.Cg- Prkdc scid IL2rg tm1Wjl /SzJ) were purchased from Ozgene (Perth, WA, Australia). Animals were held at the Biological Resources Facility (Translational Research Institute, Brisbane, QLD, Australia), housed in groups of up to four mice in individually ventilated cages on a 12-hour light-dark cycle and had unrestricted access to food and water. After one week of acclimatization, mineralized microtissues were embedded in 40 µL of fibrin glue (TISSEEL Fibrin Sealant, Baxter Healthcare International, USA) loaded with 22.5 µg of recombinant human bone morphogenetic protein-2 (BMP-2) and subcutaneously implanted in the flank of the mice. Prior to subcutaneous implantation, Temgesic (Buprenorphine, 0.05 mg.kg − 1 ) was subcutaneously administered, and animals were anaesthetized using isoflurane (induction with 4%, maintenance at 2%). Temgesic was administered every 12 hours for 48 hours post-surgery. Animals were monitored twice weekly (health check and body weight measurements). After six weeks of in vivo mineralization and bone formation, tumoral microtissues (LNCaP or C4-2B cells) ± adipose microtissues (SGBS cells differentiated into adipocytes for three weeks, 2 million cells per implant), were implanted within the same subcutaneous pocket to form a humanized bone tumoral microenvironment. Animals were monitored twice weekly until tumor formation (measurable), where mice were monitored three times per week (health check, body weight and tumors measurements). Additionally, tumor progression was monitored fortnightly using bioluminescence imaging (intraperitoneal injection of XenoLight D-Luciferin potassium salt (150 mg/kg, PerkinElmer), imaging using Xenogen IVIS Spectrum (PerkinElmer), as previously described 47 ). Human prostate specific antigen (PSA) serum level (serum collection from submandibular bleeding (< 0.5% weight)) was measured using PSA total ELISA kit (OriGene Technologies, USA). Once tumors reached a volume of ~ 250 mm 3 (total implant of ~ 450–500 mm 3 ), or a PSA level of ~ 30–50 ng/mL, mice were surgically castrated. One week post-castration, mice were randomized to treatment groups and were orally gavaged daily, five days per week, with the different treatment oral solutions: 1) vehicle, 2) enzalutamide (10mg/kg/day, Enz), 3) enzalutamide + metformin (10mg/kg/day Enz, 250 mg/kg/day metformin (Met)) or 4) enzalutamide + simvastatin (10mg/kg/day Enz, 40 mg/kg/day Simvastatin (Sim)). Treatment persisted until endpoint, determined by; 1) completion of four weeks of treatment, 2) tumor endpoint (maximum tumor volume 1000 mm 3 ) or, 3) ethical welfare assessment of a condition requiring euthanasia. At endpoint, animals were euthanized using carbon dioxide asphyxiation and humanized tissues were rapidly excised and measured. Ex vivo tissues were snap frozen in liquid nitrogen and stored at -80°C for RNA analyses or fixed with 4% w/v paraformaldehyde for histology analyses. Mice bones and organs were collected and analyzed by bioluminescence imaging following incubation with luciferin, to detect metastases. As no metastases were observed, only the humanized tissues were further analyzed. Gene expression analyses mRNA extraction : In vitro samples Hydrogels were washed twice for 5 min in PBS, and two hydrogels per condition were pooled together and stored in 500 µL of TRIZol reagent (ThermoFisher) at -80°C for at least 48 hours and until RNA extraction. Using 21G needles, hydrogels were mechanically broken into small pieces and centrifuged at 16,000 rpm for 1 min to remove cell and hydrogel debris. mRNA was extracted using Direct-zol RNA Miniprep Plus Kit (Zymo Research, USA) following the manufacturer’s protocol. In vivo samples Frozen samples (~ 10mg of sample in 1mL TRIZol) were homogenized using stainless-steel beads for 1 min at ~ 20 Hz. The homogenate was centrifuged at 4°C for 1 min at 12,000 rpm. Supernatant was collected and processed using Direct-zol RNA Miniprep Plus Kit (Zymo Research, USA) to extract mRNA following manufacturer’s protocol. RTqPCR mRNA (250 ng) was reverse transcribed into cDNA using SensiFast cDNA Synthesis Kit (Bioline, Australia). Quantitative PCR was performed using SYBR Green PCR Master Mix and QuantStudio 6 Flex System (Applied Biosystems). RPL32 and ACTB were used as housekeeping genes to normalize Cq values for each marker (primers used listed in Table S2 ,), and differential gene expression was calculated using the ΔΔCq method. mRNA Sequencing : RNA sequencing (RNAseq) was performed by Azenta. First, total RNA was assessed for quality and quantity, with quality cut-off at RNA integrity number > 7. Library preparation was then performed using 1 µg of total RNA after poly(A) mRNA isolation, and RNAseq using Illumina HiSeq instrument using a 2× 150 paired-end (PE) configuration according to the manufacturer’s instructions, yielding ~ 50M reads/samples. RNA quality was assessed using standard quality metrics including Q20/Q30 scores, GC content, and read length distribution. Raw data was processed to remove technical sequences using Cutadapt (V1.9.1, phred cutoff: 20, error rate: 0.1, adapter overlap: 1bp, min. length: 75, proportion of N: 0.1). Clean data were aligned to reference genome (human genome) using Hisat2 (V2.2.1) software. Differential expression (DE) between conditions was performed using DESeq2 Bioconductor package and defined by a false-discovery rate (FDR) corrected P -value ≤ 0.05. Functional gene annotation and gene network analyses were performed on DE transcripts using GEOSeq (V1.34.1) and TopGO (V2.18.0). Samples clustering by principal component analysis (PCA) were performed using Rstudio with FPKM values as the input. Heatmaps of log2FPKM values were created in GraphPad Prism (version 10). Protein analyses Immunofluorescenc e imaging and analysis : Hydrogels were washed twice in PBS for 5 min and fixed with 4% w/v paraformaldehyde for 30 min. Cells underwent permeabilization with a 0.2% v/v Triton solution for 15 min, followed by incubation in a 1% w/v bovine serum albumin (BSA, Sigma-Aldrich) solution for 15 min and a 2h incubation in 5% w/v BSA solution. Constructs were then incubated overnight at 4°C with primary antibody solutions (anti-PAI-1 (ThermoFisher #MA517171) and anti-ferritin (ThermoFisher #PA5120011), 1:200 dilution in 1% w/v BSA solution), followed by an overnight incubation in DAPI (10 µg/mL) and Phalloidin (2.6 µg/mL) solution at 4°C. Samples were washed twice for 15 min in 1% w/v BSA solution and a third time overnight before imaging. For lipid droplets detection, constructs were incubated in DAPI/phalloidin staining solution with Nile Red (10 µg/mL) overnight at 4°C after blocking solution (5% w/v BSA solution). Imaging was conducted using a Spectral Spinning Disc Confocal Microscope (Nikon, Minato, TYO, Japan) with blue (excitation 405 nm, exposure 500 ms), green (excitation 488 nm, exposure 500 ms), and red (excitation 561 nm, exposure 400 ms) filter sets. Maximal intensity projections were generated from z -stacks with a step size of 10 µm and a thickness of 200 to 250 µm for 4× and 10× magnifications, and a step size of 5 µm and a thickness of 100 µm for 20× magnification images. Quantitative analysis for lipid droplets was undertaken on 10× magnification images (3–4 images per hydrogel, 2 hydrogels per biological replicate (BR), 3 BRs) using Image J software (version 1.54j, National Institute of Health (NIH), USA). Spheroid measurements from 10× magnification images (3–4 images per hydrogel, 2 hydrogels per BR, 3 BRs) were conducted using QuPath software (version 0.4.4) and modified StarDist algorithm. Nuclei density was measured using DAPI signal intensity normalized to spheroid area from 20× magnification images (3 images per hydrogel, 2 hydrogels per BR, 3 BRs) using Image J software (version 1.54j, National Institute of Health (NIH), USA). Enzyme-linked immunosorbent assay (ELISA) Human total PSA level from conditioned medium was measured using human PSA total ELISA kit (ThermoFisher), following the manufacturer’s instructions. Histology and immunohistochemistry (IHC) Explants were decalcified for 10 days in 10% w/v EDTA solution (37°C, pH 7.4) using KOS Rapid microwave lab station (ABACUS, Brisbane, Australia). Decalcified tissues were embedded in paraffin and serial 5 µm thick sections were used for staining. Hematoxylin and eosin (H&E) staining was used to characterize tissue morphology and Masson’s trichrome staining to characterize extracellular matrix, as previously described. 47 IHC was performed on dewaxed and rehydrated sections, after antigen retrieval treatment, as outlined in Table S3 . Tissue sections were first treated to quench endogenous peroxidase activity by incubating them in 3% v/v hydrogen peroxide (Sigma-Aldrich) solution for 5 min. Following this, non-specific binding sites were blocked using a 2% w/v BSA solution for 30 min. Primary antibodies were appropriately diluted in the blocking buffer ( Table S3 ). Immunoreactivity was subsequently visualized using the EnVision + Dual Link System-HRP Rabbit/Mouse kit (Dako, Glostrup, Denmark), and the color was developed using liquid diaminobenzidine chromagen (Dako). Sections were counterstained with Mayer’s Hematoxylin (Sigma) prior to dehydration and mounting. Statistical analysis For each in vitro assay and analysis, three independent experiments were conducted, and each experiment included two to four technical replicates. For in vivo study, eight to nine mice were included per group (only four for the pilot study with C4-2B xenografts). Ex vivo RNAseq and histology analyses were conducted on four to five explants per group, each. Graphs were created using GraphPad Prism version 10, while statistical analyses were performed using IBM SPSS Statistics (version 29) software, employing a general linear model (univariate analysis). Posthoc Tukey test was used to assess parameter estimates when overall significance was achieved. In all statistical assessments, significance levels were set at * p < 0.05, ** p < 0.001, *** p < 0.001, and **** p < 0.0001. Experimental plan figures were created using BioRender. Declarations Competing interests The authors declare no competing interests. Data and materials availability All data needed to evaluate the conclusions are presented in the publication. Additional data related to this publication may be requested from A.B. directly ( [email protected] ), upon reasonable request. Ethical Statement Isolation of primary human osteoprogenitors was conducted in accordance with the ethical principles and guidelines provided by the QUT Human Research Ethics Committee (ethics approval number 1400001024). Written informed consent was obtained from all human participants involved in providing primary cells for research purposes prior to cell isolation. The use of human cells (primary hBM-MSCs, SGBS cells and cell lines) was covered by ethics approval (LR 2023-5612-12871) from QUT. All experimental procedures involving animals were performed in compliance with the Australian Code of Practice for the Care and Use of Animals for Scientific Purposes , and approved by the University of Queensland Animal Ethics Committee (approval number 2021-AE000353). Every effort was made to minimize animal suffering, and appropriate measures were taken to ensure the welfare and humane treatment of animals throughout the study. Funding N.B. acknowledges support from Cancer Australia & Cure Cancer (Priority-driven Collaborative Cancer Research Scheme APP1187030), Advance Queensland (AQIRF066-2019RD2), the Australian Research Council (DE240100128). A.B., J.M. and N.B. acknowledge support from the Max Planck Queensland Centre for the Materials Science of Extracellular Matrices. Author contributions All authors confirmed that they have contributed to the intellectual content of this paper and have made significant contributions to some of the following: conception and design, acquisition of data, analysis and interpretation of data, and drafting or revising the article. A.B. contributed to the conceptualization, methodology, formal analysis, investigation, data curation, visualization, project administration and wrote the original draft. S.B. and L.B. contributed to the investigation and data curation. J.M. and J.G. contributed to the conceptualization, methodology, investigation and supervision. D.W. contributed to scholarship provision and supervision. J.C. contributed to mentoring. N.B. contributed to conceptualization, methodology, investigation, project administration, funding acquisition and supervision. Finally, all authors contributed to reviewing and editing the draft. Acknowledgments Schematic diagrams depicting the experimental design were created using BioRender.com. We thank Baxter Healthcare for providing TISSEEL™ Fibrin Sealant (fibrin glue) and Arla Foods Ingredients for supplying the Lacprodan® OPN-10 samples. We acknowledge the precious support provided by the Preclinical Imaging, Biological Resources, Microscopy Core Facilities at the Translational Research Institute, and the Central Analytical Research Facility (CARF) at the Queensland University of Technology. We thank Dr Anja Rockstroh from the Australian Prostate Cancer Research Centre – Queensland (APCRC-Q) for her guidance in RNAseq data processing. References Organization, I. A. f. R. o. C.-W. H. 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DMM Disease Models and Mechanisms 7 , 299–309 (2014). https://doi.org/10.1242/dmm.014076 Additional Declarations There is no conflict of interest Supplementary Files Bessotetal.Supportinginformation.docx Supplementary figures Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: revise 07 May, 2026 Review # 4 received at journal 05 May, 2026 Review # 3 received at journal 03 May, 2026 Review # 2 received at journal 16 Apr, 2026 Reviewer # 4 agreed at journal 02 Apr, 2026 Reviewer # 3 agreed at journal 01 Apr, 2026 Reviewer # 2 agreed at journal 16 Mar, 2026 Reviewer # 1 agreed at journal 01 Mar, 2026 Reviewers invited by journal 05 Feb, 2026 Submission checks completed at journal 30 Jan, 2026 Editor assigned by journal 28 Jan, 2026 First submitted to journal 28 Jan, 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. 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Images: brightfield coculture (left), µCT image of the mineralized microtissue (middle), immunofluorescence (right) of the adipose (top) and the tumor (bottom) microtissues, at day 0 of coculture (red: lipids, green: actin, blue: nuclei). Abbreviations: BMA: BM-MSC-derived adipocytes, SGBS: Simpson-Golabi-Behmel syndrome (preadipocytes), OB: osteoblasts.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8720393/v1/3c619abfca0b158ae4fb55fb.png"},{"id":102397978,"identity":"677bd679-5af2-4b51-ad35-ecd40c384088","added_by":"auto","created_at":"2026-02-11 10:20:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":349636,"visible":true,"origin":"","legend":"\u003cp\u003eBM-MSC-derived adipocytes showed a different lipid metabolism compared to SGBS-derived adipocytes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e Primary human osteo- and adipose progenitors were embedded in hydrogels and cultured individually before indirect coculture for one week. Image: brightfield image of cocultured gels with osteoblasts (OB) and bone marrow adipocytes (BMA). RNAseq analyses on BM-MSC-derived adipocytes compared to SGBS-derived adipocytes after one week of coculture with osteoblast microtissues, with\u003cstrong\u003e B)\u003c/strong\u003e volcano plot, \u003cstrong\u003eC)\u003c/strong\u003e KEGG pathway analyses (pathways with the strongest significance are highlighted in red) and \u003cstrong\u003eD)\u003c/strong\u003eheatmap of the top 20 differentially expressed genes related to lipid metabolism and PPAR signaling in BMAs compared to SGBS-derived adipocytes (Log2(FPKM+0.1) shown, n = 3 per condition).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8720393/v1/ae8a12f1afda8dc4cb2bcacb.png"},{"id":102328965,"identity":"c3a72ba2-aa5a-48bd-b31f-c986367ff36b","added_by":"auto","created_at":"2026-02-10 14:56:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":433397,"visible":true,"origin":"","legend":"\u003cp\u003ePCa cells induce metabolic dysfunctions in bone marrow adipocytes, leading to a cancer-associated adipocyte phenotype.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA) \u003c/strong\u003eQuantification of the number of differentially expressed genes from BMA and SGBS adipocytes coculture with or without LNCaP cells\u003cstrong\u003e. \u003c/strong\u003eRNAseq analyses on BM-MSC-derived adipocytes (BMA) after one week of coculture with osteoblast microtissues ± LNCaP cells, with\u003cstrong\u003e B)\u003c/strong\u003e volcano plot, \u003cstrong\u003eC)\u003c/strong\u003e KEGG pathway and \u003cstrong\u003eD)\u003c/strong\u003e heatmap analyses of differentially expressed genes (Log2(FPKM+0.1) shown on heatmap, n = 2-3). \u003cstrong\u003eE)\u003c/strong\u003e Immunofluorescence and lipid quantification after one week of coculture with LNCaP or C4-2B cells (red: lipids, green: actin filaments, blue: nuclei). Graphs: Mean+SE, n = 3, General Linear Model (Univariate), ns: not significant, *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01.Abbreviations: BMA: BM-MSC-derived adipocytes, SGBS: Simpson-Golabi-Behmel syndrome (preadipocytes), OB: osteoblasts.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8720393/v1/b8a3df6604f043aba4079b40.png"},{"id":102328984,"identity":"bdd4f9f0-1ad6-419e-b497-76ad90c15084","added_by":"auto","created_at":"2026-02-10 14:56:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":438944,"visible":true,"origin":"","legend":"\u003cp\u003eMulticellular bone coculture reveals BMA-driven transcriptional programs supporting prostate cancer proliferation and adaptation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e Quantification of differentially expressed genes between LNCaP cells cocultured with or without BMA or SGBS adipocytes. RNAseq analyses on LNCaP cells after one week of coculture with osteoblast microtissues ± BM-MSC-derived adipocytes, with \u003cstrong\u003eB)\u003c/strong\u003e volcano plot, \u003cstrong\u003eC)\u003c/strong\u003e KEGG pathway and \u003cstrong\u003eD)\u003c/strong\u003eheatmap analyses of differentially expressed genes (Log2(FPKM+0.1) shown, n = 3). \u003cstrong\u003eE)\u003c/strong\u003e Heatmap analyses of differentially expressed genes from C4-2B cells after one week of coculture with osteoblast microtissues ± BM-MSC-derived adipocytes (DCq shown, n = 3). \u003cstrong\u003eF)\u003c/strong\u003e Spheroid size and \u003cstrong\u003eG)\u003c/strong\u003e nuclei intensity quantification from immunofluorescence images (OB: osteoblasts, BMA: BM-MSC-derived adipocytes). Graphs: Mean+SE, all data points, n = 3, General Linear Model (Univariate), ns: not significant, ****\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8720393/v1/94e130fe306c03218e7c3fc3.png"},{"id":102328973,"identity":"3f82d34e-dbea-4151-9ac9-1cfd3341be3b","added_by":"auto","created_at":"2026-02-10 14:56:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":509205,"visible":true,"origin":"","legend":"\u003cp\u003eHuman adipocytes enhance gene dysregulations leading to castration resistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e Experimental plan, \u003cstrong\u003eB)\u003c/strong\u003e time until mice were castrated depending on groups. Tumor progression from \u003cstrong\u003eC)\u003c/strong\u003e C4-2B and \u003cstrong\u003eD)\u003c/strong\u003eLNCaP xenografts after castration. \u003cstrong\u003eE) \u003c/strong\u003eKEGG pathways of differentially expressed genes between LNCaP tumors ± adipocytes and treated with vehicle for four weeks. \u003cstrong\u003eF)\u003c/strong\u003e IHC on LNCaP tumors ± adipocytes (blue circle: humanized bone, green circle: LNCaP tumor, yellow arrows: fat tissue), \u003cstrong\u003eG)\u003c/strong\u003eQuantification of Ki67- and PSA-positive cells from IHC images. Graphs: Mean+SE, n = 4, General Linear Model (Univariate), ns: not significant, *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01. Ads = SGBS-derived adipocytes.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8720393/v1/f10fe5389b52365aa18601d5.png"},{"id":102328964,"identity":"901afecf-d770-4710-84b8-324a466944a1","added_by":"auto","created_at":"2026-02-10 14:56:18","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":625745,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCancer-associated human bone marrow adipocytes enhance enzalutamide resistance in androgen-independent PCa cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e \u003cem\u003eIn vitro\u003c/em\u003e analyses on LNCaP and C4-2B spheroids in coculture with osteoblasts ± BMAs with \u003cstrong\u003ei.\u003c/strong\u003equantification of spheroid area and nuclei intensity from immunofluorescence images, \u003cstrong\u003eii.\u003c/strong\u003e Heatmap analyses of differentially expressed genes from C4-2B cells after one week of coculture with osteoblast microtissues ± BM-MSC-derived adipocytes (DCq) and \u003cstrong\u003eiii.\u003c/strong\u003emRNA fold change from \u003cem\u003eAR, FABP4, CD36 \u003c/em\u003eand\u003cem\u003e ABCC3\u003c/em\u003e under enzalutamide treatment in coculture with BMAs, normalized to enzalutamide treatment without BMAs. \u003cstrong\u003eB)\u003c/strong\u003e \u003cem\u003eIn vivo \u003c/em\u003eanalyses on LNCaP and C4-2B xenografts with \u003cstrong\u003ei.\u003c/strong\u003e tumor size progression after castration,\u003cstrong\u003e ii.\u003c/strong\u003eKEGG pathways of differentially expressed genes between LNCaP tumors ± adipocytes and treated with enzalutamide for four weeks, and \u003cstrong\u003eiii.\u003c/strong\u003erepresentative IHC images of LNCaP ± BMA tumors treated with enzalutamide and quantification of Ki67- and CD68-positive cells from IHC images. Graphs: Mean+SE, n = 4, General Linear Model (Univariate), ns: not significant, *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001, ****\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001. Ads = SGBS-derived adipocytes.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8720393/v1/10a8173a5310c7a054e50970.png"},{"id":102328969,"identity":"53f316cc-a475-4f68-9385-f8906b97429c","added_by":"auto","created_at":"2026-02-10 14:56:18","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":472240,"visible":true,"origin":"","legend":"\u003cp\u003eCombining enzalutamide with simvastatin overcome enzalutamide resistance from PCa spheroids.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e Quantification of spheroid size and nuclei intensity normalized to control (DMSO) from immunofluorescence images of LNCaP and C4-2B after one week of treatment in coculture with osteoblasts ± BMAs, and representative images of C4-2B spheroids. \u003cstrong\u003eB) \u003c/strong\u003eHeatmap of differentially expressed genes (mean \u003cem\u003eΔCq\u003c/em\u003e, n =\u003cem\u003e \u003c/em\u003e3) between LNCaP or C4-2B cells after coculture with osteoblast microtissues ± adipocytes and treated with enzalutamide ± metformin or simvastatin for one week. C) PSA concentration from condition medium after one week of treatment, normalized to control (DMSO). Graphs: Mean+SE, n = 3, General Linear Model (Univariate), ns: not significant, *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001, ****\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8720393/v1/4ea31a7f25d1746599f500bf.png"},{"id":102328972,"identity":"4787fe9d-248e-4210-8320-4a1180e72f17","added_by":"auto","created_at":"2026-02-10 14:56:18","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":481939,"visible":true,"origin":"","legend":"\u003cp\u003eCombining enzalutamide with simvastatin inhibits further LNCaP tumor progression by enhancing necroptosis, ferroptosis and tumor microenvironment modulation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e Experimental plan, \u003cstrong\u003eB)\u003c/strong\u003e Tumor progression after castration, under enzalutamide and combined treatments. Graphs: Mean+SE, n = 8-9, General Linear Model (Univariate), ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001, ****\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, \u003cstrong\u003eC)\u003c/strong\u003e 2D principal component (PC) analysis plots showing differences between single and combined treatments depending on their gene expression (ellipse: 95% confidence), \u003cstrong\u003eD)\u003c/strong\u003e KEGG pathways and \u003cstrong\u003eE)\u003c/strong\u003e Heatmap of differentially expressed genes between LNCaP tumors ± adipocytes and treated with enzalutamide± simvastatin for 4 weeks (Log2(FPKM+0.1) shown, n = 4).\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8720393/v1/36731b64ff0573b54b29673c.png"},{"id":102328971,"identity":"eb6de1a2-7cb4-4896-9cf4-bf7a14783012","added_by":"auto","created_at":"2026-02-10 14:56:18","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":946640,"visible":true,"origin":"","legend":"\u003cp\u003eCharacterization of LNCaP tumors treated with enzalutamide ± simvastatin using immunohistochemistry.\u003c/p\u003e\n\u003cp\u003eHistology analyses on LNCaP xenografts treated for 4 weeks with enzalutamide combined or not with simvastatin with \u003cstrong\u003eA)\u003c/strong\u003e representative images from LNCaP tumors implanted with human adipocytes and quantification of \u003cstrong\u003eB) \u003c/strong\u003evascularization (endothelial cells, vWf)\u003cstrong\u003e C)\u003c/strong\u003e proliferation (Ki67), \u003cstrong\u003eD)\u003c/strong\u003eplasminogen activator inhibitor-1 (PAI-1), \u003cstrong\u003eE)\u003c/strong\u003e macrophages (CD68) markers, and \u003cstrong\u003eF)\u003c/strong\u003e ferritin staining from immunohistochemistry. Graphs: Mean+SE, n = 8-9, General Linear Model (Univariate), ns: not significant, *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-8720393/v1/a26d2fe944ad22ecc8e339aa.png"},{"id":108491656,"identity":"0ddd05a6-b4a3-4a3a-9aa1-363907c9787b","added_by":"auto","created_at":"2026-05-05 09:55:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5318228,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8720393/v1/a4ba30e3-32e1-4cc1-bbab-1b218efcf579.pdf"},{"id":102397998,"identity":"7f5dc1e8-7e8e-4d6e-b0d3-1cba69349619","added_by":"auto","created_at":"2026-02-11 10:20:27","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":5488105,"visible":true,"origin":"","legend":"Supplementary figures","description":"","filename":"Bessotetal.Supportinginformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-8720393/v1/53fbb6985e1782f0bf99f155.docx"}],"financialInterests":"There is no conflict of interest","formattedTitle":"Preclinical humanized bone models reveal metabolic reprogramming and simvastatin benefits in castration-resistant prostate cancer in bone","fulltext":[{"header":"Introduction","content":"\u003cp\u003eProstate cancer (PCa) remains a significant health concern globally, ranking as the second most common male-specific cancer diagnosed.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e A hallmark feature of this malignancy is its reliance on the androgen signaling pathway for growth and survival, making androgen deprivation therapy (ADT) a successful treatment strategy.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e While initially effective, patients can develop ADT resistance, transitioning to a more aggressive state: castration-resistant PCa (CRPC).\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e CRPC cells exhibit increased metastatic potential, particularly towards the bone microenvironment,\u003csup\u003e3\u003c/sup\u003e which is associated with poorer outcomes.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e The development of second-generation androgen therapies (androgen-targeted therapies (ATT), such as bicalutamide and enzalutamide) allow the inhibition of PCa growth by targeting the androgen receptor (AR).\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Unfortunately, treatment failure through AR reactivation prohibits full treatment efficiency.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e While effectively targeting PCa cells, androgen-deprivation induces as a side-effect a metabolic shift, leading to metabolic syndrome.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e This shift is characterized by increased adiposity (systemic increase of fat storage), elevated circulating lipids, insulin resistance (hyperglycemia) and a rise in metabolic hormones (e.g., leptin), further fueling cancer cell growth.\u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e Additionally, androgen deprivation leads to bone dysregulation associated with higher risks of fracture,\u003csup\u003e11\u003c/sup\u003e and increase of marrow adiposity.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWhile the role of white adipose tissue (adipocytes from subcutaneous and visceral tissue) in cancer progression is well established,\u003csup\u003e14,15\u003c/sup\u003e bone marrow adipocytes (BMAs) remain less studied despite being the main component of bone marrow in adults (\u0026gt;\u0026thinsp;70% of marrow volume).\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Although similar to white adipocytes, notably in their metabolic and endocrine functions (lipid storage, adipokine and cytokine secretion),\u003csup\u003e17\u003c/sup\u003e BMAs differ significantly in origin, lipid composition, and secretory profiles; displaying smaller size, less lipolytic, and secreting distinct levels of adipokines and inflammatory mediators.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Recent research has shed light on the multifaceted role BMAs play in bone metastases.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e These studies showed that cancer-associated BMAs (CA-BMAs, adipocytes found in close proximity to cancer cells) present dysregulated phenotypes (proinflammatory profile), characterized by an increase in protumoral factor secretion (free fatty acids, IL-6, leptin, CXCL1/2)\u003csup\u003e15,19,20\u003c/sup\u003e and reduced adiponectin (antitumoral) secretion,\u003csup\u003e18\u003c/sup\u003e modulating the bone microenvironment.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e These factors support cancer cell growth within the bone microenvironment, and contribute to therapy resistance, through the activation of multiple pathways (i.e., HIF1α, MAPK, PI3K/Akt and Jak2/STAT3).\u003csup\u003e18,22\u0026ndash;24\u003c/sup\u003e Despite the growing interest in the BMA-cancer cell crosstalk, the full picture of the pathway dysregulations remains elusive. However, the current findings strongly suggest that BMA-secreted factors, such as leptin,\u003csup\u003e25\u003c/sup\u003e and lipid transfer,\u003csup\u003e26\u003c/sup\u003e could be promising targets as therapeutic strategies to inhibit protumoral effects of BMAs in cancer.\u003c/p\u003e \u003cp\u003eMetformin and statins, commonly used to treat metabolic conditions such as diabetes and hyperlipidemia, have shown promises in overcoming enzalutamide resistance.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e Metformin, a biguanide, improves insulin sensitivity and decreases hyperglycemia, conditions exacerbated by androgen deprivation.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Additionally, metformin has been shown to directly inhibit adipogenesis,\u003csup\u003e30\u003c/sup\u003e present a multimodal inhibitory effects on PCa cells\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e and a capacity to lift enzalutamide resistance in PCa cells.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e Similarly, statins demonstrated inhibitory effects on androgen-deprivation-induced adipogenesis, via cholesterol metabolism pathways, and on PCa progression within the bone microenvironment, by inducing cancer cell apoptosis.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Combining enzalutamide with statins, including simvastatin, has demonstrated preliminary efficacy in overcoming PCa cell resistance to enzalutamide and reducing disease progression in 2D cultures and PCa-derived xenograft models, by inhibiting the overactivated sterol synthesis in PCa cells under androgen deprivation conditions.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e Although promising, these studies rely on murine xenograft models, which lack the human-specific processes and bone microenvironment context.\u003c/p\u003e \u003cp\u003eCurrent models of bone metastasis, whether \u003cem\u003ein vitro\u003c/em\u003e or \u003cem\u003ein vivo\u003c/em\u003e, fail to fully recapitulate the complex human tumor bone microenvironment, limiting our understanding of the cellular and molecular mechanisms driving metastatic progression and therapeutic resistance.\u003csup\u003e\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e While 3D models offer improvements over traditional 2D systems by incorporating extracellular matrix (ECM) components such as collagen, Matrigel, or silk-based scaffolds,\u003csup\u003e37,38\u003c/sup\u003e they are limited in replicating the dynamic biochemical and mechanical cues of the bone marrow niche. Moreover, they typically lack sufficient cellular heterogeneity, coculturing PCa cells with only one stromal cell type such as osteoblasts, macrophages, or adipocytes.\u003csup\u003e\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e While there is a stronger focus on delineating the role of adipocytes in cancer, a limited number of models focuses on bone metastases and includes bone marrow adipocytes.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e Despite offering systemic complexity, \u003cem\u003ein vivo\u003c/em\u003e murine models are limited by a lack of species specificity. In xenograft models, human tumor cells must interact with a murine stroma that differs fundamentally in cell biology,\u003csup\u003e43,44\u003c/sup\u003e compromising the fidelity of tumor\u0026ndash;microenvironment interactions. In particular, murine BMAs differ markedly from their human counterparts in metabolic activity, adipokine expression and signaling pathways, which could lead to discrepancies in how tumors respond to adipocyte-derived cues.\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e Furthermore, murine tumors often arise from mesenchymal tissues and display lower metastatic potential compared to human epithelial tumors.\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e These interspecies differences compromise clinical relevance and drug response predictability.\u003c/p\u003e \u003cp\u003eIn response to these challenges, our group previously developed both \u003cem\u003ein vitro\u003c/em\u003e (indirect and direct 3D multicellular systems) and \u003cem\u003ein vivo\u003c/em\u003e humanized models using gelatin methacryloyl (GelMA) hydrogels, incorporating primary BMAs and androgen receptor-expressing PCa cells (LNCaP, C4-2B).\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e GelMA is a photocrosslinkable, tunable, and biocompatible hydrogel derived from denatured collagen, offering a balance between biological activity (e.g., RGD motifs supporting cell adhesion) and mechanical stability.\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e Unlike natural ECM materials such as Matrigel, which suffer from batch variability and undefined composition, GelMA provides reproducibility and structural customization, with biological and mechanical properties specifically attuned to modeling the complex bone marrow environment. Our previous GelMA-based models revealed adipocyte delipidation upon coculture and BMA-induced resistance to enzalutamide on cancer cells, supporting a functional role of BMAs in therapy evasion.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eHere we advanced physiological relevance by modular combination of human osteoblasts, BMAs, and PCa cells, used as \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e humanized platforms. These models offer increased cellular complexity and mimicry of the bone and fat cellular compartments of bone marrow, allowing the investigation of specific niche crosstalks. In this study, we extended this platform to model metastatic CRPC, incorporating a mineralized microenvironment to more accurately evaluate therapeutic response by transcriptomic profiling. To capture the diverse effects of human BMAs on different stages of PCa, we employed two distinct AR-expressing cell lines with varying dependence to androgen: LNCaP cells (androgen-dependent) and C4-2B cells (androgen-independent). We used these humanized models to test combination therapies with enzalutamide and repurposed metabolic drugs (metformin, simvastatin), aiming to co-target BMA-mediated tumor-supportive mechanisms and improve therapeutic outcomes in CRPC.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eDeveloping a multicellular paracrine\u003c/b\u003e \u003cb\u003ein vitro\u003c/b\u003e \u003cb\u003emodel using primary bone cells to mimic a fat-enriched mineralized tumor microenvironment\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe development of multicellular models is crucial to decipher the specific interactions between cancer cells and their microenvironment.\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e Based on our previous coculture system,\u003csup\u003e48\u003c/sup\u003e we introduced an additional bone-like element by incorporating mineralized microtissues composed of primary human osteoblasts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Osteoblasts not only are highly responsive to BMAs,\u003csup\u003e51,52\u003c/sup\u003e but also recapitulate important cellular and extracellular features of the mineralized bone environment that contribute to bone disease progression and therapy resistance.\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe first validated that all three cell types, primary human adipocytes (derived from SGBS cells or BMSCs), primary human osteoblasts, and human PCa cells, could be cocultured in a reduced medium without compromising cell viability or function. Once primary human osteoprogenitors differentiated into osteoblasts, they were cultured in a coculture medium (CoM) previously validated for both adipocytes and PCa cell lines.\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e After one week in CoM, no significant impact on osteoblast metabolic activity or mineralization was observed compared to culture in OM, confirming compatibility of this coculture medium for all three cell types over this time frame (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eAs BMAs shares similarities with white adipocytes, \u003csup\u003e17\u003c/sup\u003e we then investigated how white adipocytes (SGBS-derived) and bone marrow adipocytes (BMSC-derived) behaved within the bone-like environment. Although white adipocytes are not native to bone, investigating their phenotypic plasticity is important: if they can adopt BMA-like traits in the bone environment, SGBS-derived adipocytes could offer a practical and scalable model for bone metastases, due to their ease of isolation and handling.\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e Additionally, their heightened insulin sensitivity and active insulin signaling make them especially relevant for studying the metabolic alterations associated with androgen deprivation therapy in advanced PCa.\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e To explore these possibilities, we performed RNA sequencing on adipocytes upon coculture with osteoblasts. Transcriptomic analyses revealed significant differences between BMAs and SGBS adipocytes, particularly in genes related to lipid metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Over 4,000 genes were differentially expressed between the two groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.A), encompassing pathways related to organismal system (321 genes), human diseases (431 genes including 212 genes related to pathways in cancer), and environment information processing (333 genes). Notably, steroid biosynthesis (11 genes), regulation of lipolysis (25 genes), and PPAR signaling (31 genes) were differentially enriched between the two populations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.B). Consistent with these pathway-level differences, BMAs exhibited lower expression of several lipid metabolism-related genes, including \u003cem\u003eLPL\u003c/em\u003e, \u003cem\u003eMGLL\u003c/em\u003e, and \u003cem\u003eLIPE\u003c/em\u003e, compared to SGBS-derived adipocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.C). These findings align with previous observations by Attan\u0026eacute; et al., who reported a lipolytic defect in primary BMAs relative to white adipocytes.\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHere, we developed an all-human, 3D multicellular model that mimicked a human fat-enriched, mineralized bone microenvironment by coculturing primary human osteoblasts and adipocytes. Transcriptomic analysis revealed distinct phenotypic differences between SGBS- and BMSC-derived adipocytes within the bone-like context, particularly in lipid metabolism and cancer-related pathways, highlighting the unique features of BMAs.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eBone marrow adipocytes exhibit early signs of tumor-induced metabolic reprogramming compared to white adipocytes\u003c/h2\u003e \u003cp\u003eAfter observing the distinct lipid metabolism in BMAs compared to SGBS-derived adipocytes in the presence of mineralized osteoblasts, we investigated the effect of PCa cells on adipocyte phenotype. We hypothesized that, similar to SGBS-derived adipocytes, BMAs would undergo phenotypic reprogramming in the presence of PCa cells. Specifically, we predicted that BMAs would acquire characteristics of cancer-associated adipocytes (CAAs), such as delipidation and a protumoral gene expression profile, reflecting a shift toward a tumor-supportive phenotype,\u003csup\u003e15,19,20\u003c/sup\u003e even with their unique lipid metabolism.\u003c/p\u003e \u003cp\u003eGene expression analyses revealed that BMAs were less transcriptionally responsive to PCa-derived cues in the coculture system compared to SGBS adipocytes, as only 132 genes were significantly affected, against 347 genes in SGBS adipocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003cb\u003eA-B\u003c/b\u003e). KEGG pathway analyses indicated that LNCaP cells altered BMA metabolism by upregulating pathways involved in metabolic regulation, cellular stress responses and intercellular communication (e.g., \u003cem\u003eAPLN, BCO1, GLS2\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.C-D). These changes reflect an important metabolic reprogramming of BMAs by cancer cells, consistent with prior observations.\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e,\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e Furthermore, downregulation of bone-related genes (e.g., \u003cem\u003eFGF18, TNFRS11A\u003c/em\u003e) suggests that BMAs may also contribute to remodeling the bone microenvironment in response to tumor signaling. In addition to transcriptional changes, morphological evidence of delipidation was observed in BMAs cocultured with LNCaP and C4-2B cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.E), aligning with previously reported characteristics of CA-BMAs.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e,\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e In contrast to BMAs, SGBS-derived adipocytes exhibited different transcriptional responses to LNCaP cells (\u003cb\u003eFigure S2.A-B\u003c/b\u003e). These changes primarily involved cellular components rather than molecular functions or biological processes, indicating that SGBS adipocytes undergo structural and compartmental remodeling. This remodeling may represent an early step in their phenotypic reprogramming, preceding functional adaptations such as lipid transfer, suggesting a delayed response compared to BMAs. Immunofluorescence analysis (Figure S2.C) revealed a slight, though not statistically significant, decrease in lipid content in response to LNCaP cells, whereas exposure to C4-2B cells led to an increase in intracellular lipid accumulation. This observation is consistent with previous reports indicating that tumor-exposed adipose tissue may initially undergo adipogenesis, followed by delipidation, thereby supplying free fatty acids to support cancer cell survival and proliferation in a tumor demand\u0026ndash;dependent manner.\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn summary, despite showing fewer affected genes compared to SGBS adipocytes, BMAs exhibited a significant transcriptional response to PCa cells, with upregulation of metabolic and stress-related pathways and evidence of delipidation, indicating phenotypic reprogramming in response to the tumor microenvironment. In contrast, SGBS adipocytes displayed slower and more structural changes, suggesting a distinct, less immediate response to PCa cells. This underscores the importance of considering adipocyte origin when studying their role in the bone metastatic niche.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe crosstalk between cancer-associated bone marrow adipocytes and prostate cancer cells involves metabolic dysregulation\u003c/h3\u003e\n\u003cp\u003eTo determine how CAAs influence prostate cancer progression, we examined their effects on LNCaP and C4-2B cells, representing hormone-sensitive and castration-resistant stages, respectively. We hypothesized that CAAs, particularly BMAs, which display a more tumor-supportive phenotype, would enhance lipid metabolism and energy production in cancer cells, thereby promoting proliferation within the bone microenvironment, as previously suggested.\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eRNA sequencing revealed that LNCaP cells exhibited distinct transcriptional responses depending on the adipocyte type in coculture with osteoblasts (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003cb\u003eA-B, Figure S3.A\u003c/b\u003e), highlighting adipocyte-specific effects on tumor transcriptional programs. In the presence of BMAs, LNCaP cells upregulated multiple pathways implicated in tumor progression, including Wnt, VEGF, PPAR, AMPK, adipocytokine signaling, and cholesterol metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.C). Expression of key lipid-handling genes (\u003cem\u003eFABP4, CD36, PLIN1, LPL, ABCD2\u003c/em\u003e, \u003cem\u003eABCA\u003c/em\u003e family) was markedly increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.D), suggesting enhanced fatty acid uptake, storage, and lipolysis to support survival within the mineralized microenvironment, consistent with prior PCa models.\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e BMA coculture also induced pro-inflammatory cytokines (e.g., \u003cem\u003eCSF1\u003c/em\u003e, \u003cem\u003eIGF2\u003c/em\u003e) and therapy resistance pathways (ABC transporters) in LNCaP cells, consistent with activation of PI3K/Akt, MAPK/ERK and JAK/Stat signaling.\u003csup\u003e\u003cspan additionalcitationids=\"CR65\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e Similar, though less pronounced, transcriptional changes were observed in the androgen-independent C4-2B cell line (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.E), indicating that BMA-driven tumor-supportive signaling extends across disease stages, in contrast to prior studies emphasizing effects on androgen-dependent cells.\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSGBS-derived adipocytes induced a narrower transcriptional response, primarily affecting complement and coagulation cascades, PPAR and IL-17 (Figure S3.B). Their weaker impact on PCa cells\u0026rsquo; lipid metabolism and cytokine signaling (Figure S3.C\u0026ndash;D), compared to BMAs, indicates a reduced capacity to create a protumoral microenvironment. This likely reflects the intrinsic phenotype of white adipocytes, which may acquire cancer-associated features more slowly, resulting in less robust tumor-supportive signaling compared to BMAs within one week of coculture.\u003c/p\u003e \u003cp\u003eMorphometric analysis showed comparable spheroid sizes in cocultures with osteoblasts\u0026thinsp;\u0026plusmn;\u0026thinsp;adipocytes for both PCa cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.F, Figure S3.E). This differs from earlier reports in non-mineralized systems,\u003csup\u003e48\u003c/sup\u003e emphasizing the importance of osteoblast mineralization in modulating tumor\u0026ndash;stromal interactions. However, a higher density of nuclei was observed in PCa spheroids upon coculture with BMA and SGBS (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.G, Figure S3.F), indicating enhanced PCa cell proliferation. In tri-cultures, PCa cells expressed higher expression of \u003cem\u003eKLK3\u003c/em\u003e (PSA) and \u003cem\u003eAR\u003c/em\u003e compared to adipocyte-only cocultures (\u003cb\u003eFigure S4.A\u003c/b\u003e vs Figure S4.B). Despite stronger modulation of metabolic pathways in the tri-culture model, spheroid size did not significantly increase compared to osteoblast-free cocultures, possibly due to the intrinsic pro-tumoral effects of osteoblasts themselves.\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e These findings underscore the importance of refining preclinical \u003cem\u003ein vitro\u003c/em\u003e models by incorporating multiple cell types to more accurately mimic the tumor microenvironment in cancer research.\u003c/p\u003e \u003cp\u003eBy employing an all-human, 3D tri-culture model that integrates adipocytes, osteoblasts, and PCa cells, we provide a physiologically relevant platform for dissecting stromal\u0026ndash;tumor interactions in bone metastasis. Overall, our advanced model reveals that BMA exert consistent tumor-supportive effects across both androgen-dependent and androgen-independent PCa stages. Within the mineralized osteoblastic microenvironment, BMAs drive a coordinated transcriptional reprogramming that enhances lipid uptake and utilization, activates inflammatory and pro-survival pathways, and upregulates mediators of therapy resistance. This metabolic and signaling crosstalk promotes PCa cell adaptation and persistence within the bone niche.\u003c/p\u003e \u003cp\u003e \u003cb\u003eHuman adipocytes promote castration and enzalutamide resistance in a humanized bone tumor microenvironment via lipid metabolic reprogramming and microenvironmental signaling.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAdipose tissue functions as a dynamic endocrine organ influencing systemic metabolism and bone homeostasis.\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e,\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e Beyond direct interactions with cancer cells, adipocytes can systemically modulate pathways such as insulin sensitivity and cholesterol metabolism, both frequently dysregulated in advanced PCa.\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e Moreover, adipocytes may shape the bone microenvironment to favor tumor survival,\u003csup\u003e70\u003c/sup\u003e as suggested by our transcriptional analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo delineate species-specific effects of human BMAs on PCa bone metastases growth and survival, we used an innovative \u003cem\u003ein vivo\u003c/em\u003e mouse model by enhancing our previously developed humanized fat-enriched bone tumor microenvironment.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e We hypothesized that human adipocytes would enhance androgen-deprivation resistance of androgen-dependent (LNCaP) and androgen-independent (C4-2B) PCa xenografts within the humanized bone microenvironment. Following ectopic humanized bone formation, cancer cells were implanted into the humanized bone microenvironment, and tumors were monitored before and after surgical castration (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003cb\u003eA\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe presence of human adipocytes did not influence progression prior to castration (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.B) but significantly enhanced resistance to castration, particularly in C4-2B xenografts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.C-D). Transcriptomic profiling of LNCaP tumors revealed adipocyte-driven upregulation of lipid metabolism and inflammatory signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.E), mirroring our \u003cem\u003ein vitro\u003c/em\u003e findings. Notably, key genes regulating lipid uptake (FABP4, CD36, ACSL5) and cholesterol metabolism (ANPP7P1, APOA1, LDLRAD2) were upregulated, together with pro-inflammatory mediators (CXCLs, CCL2, TNF) (\u003cb\u003eFigure S5\u003c/b\u003e). Immunohistochemistry confirmed increased proliferation (Ki67), without changes in PSA expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.F, \u003cb\u003eFigure S6\u003c/b\u003e), in the presence of human adipocytes, consistent with prior evidence linking adipocyte-derived signals to metabolic flexibility and cancer cell survival.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e,\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eGiven that human adipocytes enhanced castration resistance, we investigated whether they could similarly affect enzalutamide response in PCa cells. Following one week of enzalutamide (10 \u0026micro;M) treatment \u003cem\u003ein vitro\u003c/em\u003e, both PCa cell lines exhibited increased growth in the presence of human BMAs. C4-2B cells formed larger spheroids with higher nuclear intensity, whereas LNCaP spheroids maintained a similar size to controls but displayed increased nuclear density (\u003cb\u003eFigure.6.A.i\u003c/b\u003e). Transcriptomic analysis revealed increased expression of lipid metabolism-related genes (e.g., \u003cem\u003eFABP4\u003c/em\u003e and \u003cem\u003eCD36\u003c/em\u003e) in cocultures with BMAs, without changes in \u003cem\u003eKLK3\u003c/em\u003e, \u003cem\u003eAR\u003c/em\u003e and \u003cem\u003eABCC3\u003c/em\u003e (gene coding for ATP binding cassette, responsible for drug influx within cells) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.A.ii-iii). Similarly, coculture with SGBS-derived white adipocytes significantly increased enzalutamide resistance in both AR-positive cell lines, accompanied by elevated expression of \u003cem\u003eAR\u003c/em\u003e, \u003cem\u003eFABP4\u003c/em\u003e, \u003cem\u003eCD36\u003c/em\u003e and \u003cem\u003eABCC3\u003c/em\u003e (\u003cb\u003eFigure S7\u003c/b\u003e). Despite phenotypic differences, both adipocyte types promoted enzalutamide resistance, with a stronger effect observed in white adipocytes cocultures.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo validate these observations, \u003cem\u003ein vivo\u003c/em\u003e humanized models were used to include systemic effects of metabolic syndrome associated with androgen deprivation, which can also influence both adipocytes and PCa progression. In C4-2B xenografts, human adipocytes conferred significant resistance to enzalutamide, with tumor progression comparable to untreated xenografts lacking adipocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003cb\u003eB.i\u003c/b\u003e). In contrast, human adipocytes did not significantly affect LNCaP tumor growth under enzalutamide, although KEGG pathway analysis revealed extensive transcriptomic remodeling (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.B.ii).\u003c/p\u003e \u003cp\u003ePathways enriched in LNCaP tumors included TGF-β, PI3K/Akt, and MAPK signaling, pathways implicated in therapy resistance and tumor progression. Additionally, enrichment of ECM\u0026ndash;receptor interactions, complement/coagulation cascades, and Rap1 signaling indicated microenvironmental remodeling and altered immune-adhesion dynamics, supported by increased expression of \u003cem\u003eBMP2, PDGFs, TNC, CCLs, FTH1P7\u003c/em\u003e, and \u003cem\u003eSERPINE1\u003c/em\u003e. Metabolic pathways, including PPAR signaling and lipolysis in adipocytes, were significantly modulated (upregulation of \u003cem\u003eFABP4\u003c/em\u003e, \u003cem\u003eCD36\u003c/em\u003e, \u003cem\u003eLPL\u003c/em\u003e, and \u003cem\u003eSLC27A6\u003c/em\u003e and downregulation of \u003cem\u003eAQP7\u003c/em\u003e), reinforcing the role of adipocytes in reshaping lipid metabolism within the tumor context. These transcriptomic shifts suggest that adipocytes foster a metabolically adaptive microenvironment that supports PCa cell survival under antiandrogen pressure. Although no significant effect on PCa progression or PSA levels after were detected after four weeks of treatment (Figure S6), immunohistochemistry confirmed decreased proliferation under enzalutamide (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.B.iii). Notably, macrophage infiltration increased compared to untreated xenografts, as previously reported,\u003csup\u003e72\u003c/sup\u003e particularly in adipocyte-rich tumors. Despite the absence of tumor growth changes, human adipocytes enhance protumoral signaling and immune infiltration in LNCaP xenografts, potentially diminishing therapy responsiveness over time.\u003c/p\u003e \u003cp\u003eCollectively, findings from both 3D \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e humanized models demonstrated that human BMAs remodel both lipid metabolism and inflammatory signaling to promote resistance to androgen deprivation and enzalutamide. This adipocyte-mediated reprogramming generates a metabolically flexible and pro-survival microenvironment, underscoring the potential of targeting adipocyte\u0026ndash;tumor interactions to overcome antiandrogen resistance in bone-metastatic CRPC.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCombination of enzalutamide with anti-cholesterol simvastatin drug inhibits prostate cancer progression by enhancing ferroptosis and modulating the bone tumor microenvironment\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo evaluate whether repurposed metabolic drugs could mitigate enzalutamide-induced metabolic dysregulation and BMA-mediated protumoral effects, we treated 3D cocultures with enzalutamide (10 \u0026micro;M, Enz), metformin (1 mM, Met), simvastatin (5 \u0026micro;M, Sim), or their combinations (Enz\u0026thinsp;+\u0026thinsp;Met; Enz\u0026thinsp;+\u0026thinsp;Sim) for one week. In LNCaP spheroids, both repurposed drugs alone significantly inhibited growth by approximately 40%, relative to controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003cb\u003eA\u003c/b\u003e), confirming their intrinsic antitumor activity, as previously suggested.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e Unexpectedly, combining either drug with enzalutamide did not further reduced spheroid size beyond enzalutamide monotherapy. However, in the presence of human BMAs, the Enz\u0026thinsp;+\u0026thinsp;Sim combination markedly decreased LNCaP cell density, suggesting an inhibitory effect on cell proliferation. In C4-2B spheroids, simvastatin exhibited synergy with enzalutamide only under coculture with BMAs, reducing spheroid growth by ~\u0026thinsp;37% compared to 24% with enzalutamide alone, without significantly reducing cell density. The enhanced anti-tumoral likely arises from simvastatin-mediated inhibition of cholesterol signaling within BMAs, thereby diminishing their protumoral influence on PCa cells.\u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTranscriptomic analyses revealed modest yet consistent alterations in cancer cell gene expression under combined treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.B). Enzalutamide with either metformin or simvastatin reduced \u003cem\u003eKLK3\u003c/em\u003e and \u003cem\u003eAR\u003c/em\u003e expression in androgen-dependent cells, particularly in mineralized cocultures without adipocytes. However, the presence of human adipocytes attenuated this downregulation, suggesting a protective microenvironmental effect. Secreted PSA levels measured in conditioned medium mirrored these trends, showing the greatest suppression under the Enz\u0026thinsp;+\u0026thinsp;Sim combination (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.C), consistent with previous 2D studies.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e,\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eCombined treatments also modulated metabolic gene expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.B). Enz\u0026thinsp;+\u0026thinsp;Sim, and to a lesser extent Enz\u0026thinsp;+\u0026thinsp;Met, upregulated \u003cem\u003ePPARγ\u003c/em\u003e, \u003cem\u003eCD36\u003c/em\u003e, \u003cem\u003ePLIN1\u003c/em\u003e upregulated \u003cem\u003ePPARγ, CD36\u003c/em\u003e, and \u003cem\u003ePLIN1\u003c/em\u003e, particularly in LNCaP cells, indicating a shift toward enhanced lipid utilization, potentially compensating for reduced glucose uptake under androgen signaling inhibition.\u003csup\u003e\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e Coculture with human BMAs further amplified this lipid metabolic signature (\u003cem\u003ePNPLA2, LIPE, PLIN1\u003c/em\u003e and \u003cem\u003eFABP4\u003c/em\u003e) while suppressing glucose uptake (downregulation of \u003cem\u003eSLC2A4\u003c/em\u003e), suggesting adipocyte-derived fatty acids support cancer cell survival under dual therapy. Notably, Enz\u0026thinsp;+\u0026thinsp;Sim reduced expression of protumoral and microenvironmental remodeling genes (AQP7, CSF1, FGF7, SERPINE1) compared with enzalutamide alone, implying partial reversal of BMA-induced signaling. Protein analyses confirmed reduced ferritin and PAI-1 (SERPINE1) levels under Enz\u0026thinsp;+\u0026thinsp;Sim (\u003cb\u003eFigure S8\u003c/b\u003e). This shift suggests that the combined therapies influenced BMAs-cancer cells interactions, leading the PCa cells toward a less resilient and potentially less aggressive phenotype compared to enzalutamide treatment alone.\u003c/p\u003e \u003cp\u003eUsing the human 3D \u003cem\u003ein vitro\u003c/em\u003e coculture systems, we demonstrated that the combined treatment of enzalutamide with simvastatin significantly reduced enzalutamide resistance induced by BMAs in LNCaP and C4-2B spheroids \u003cem\u003ein vitro\u003c/em\u003e suggesting a potential strategy to enhance enzalutamide\u0026rsquo;s efficacy in advanced prostate cancer.\u003c/p\u003e \u003cp\u003eWhile 3D coculture models provide valuable insights into drug responses within the localized tumor microenvironment, they cannot recapitulate systemic physiological interactions that critically influence therapeutic efficacy. To address this, we evaluated whether metformin or simvastatin could overcome enzalutamide resistance \u003cem\u003ein vivo\u003c/em\u003e using our humanized bone tumor model. Following surgical castration, mice were treated for four weeks (or until clinical endpoint, defined as tumor volume\u0026thinsp;\u0026gt;\u0026thinsp;999 mm\u0026sup3;) with enzalutamide\u0026thinsp;\u0026plusmn;\u0026thinsp;metformin or simvastatin (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003cb\u003eA\u003c/b\u003e). Tumor progression was monitored by serial measurement of tumor size after castration and throughout treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.B).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the absence of human adipocytes, both combination treatments reduced LNCaP tumor progression compared to enzalutamide alone. Tumors treated with enzalutamide alone increased by 25% relative to their post-castration size, whereas those receiving Enz\u0026thinsp;+\u0026thinsp;Met showed only a 10% increase, and those treated with Enz\u0026thinsp;+\u0026thinsp;Sim exhibited a 10% reduction. These results confirm the intrinsic antitumoral activity of both repurposed agents. However, when human adipocytes were present, tumor progression under Enz\u0026thinsp;+\u0026thinsp;Met became comparable, indicating that adipocytes diminished metformin\u0026rsquo;s therapeutic benefit. Although this contrasts with some preclinical reports,\u003csup\u003e32\u003c/sup\u003e it aligns with clinical observations showing limited efficacy of metformin in advanced PCa.\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e By contrast, the combination of enzalutamide\u0026thinsp;+\u0026thinsp;simvastatin significantly reduced tumor progression compared to enzalutamide alone in the presence of human adipocytes, although the magnitude of inhibition was lower than in adipocyte-free conditions (5% reduction versus 10%). This outcome is consistent with prior preclinical\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e,\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e and clinical studies \u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e,\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e reporting improved survival among patients receiving statins during androgen deprivation therapy. Mechanistically, this enhanced effect likely reflects simvastatin-mediated inhibition of cholesterol metabolism in both BMAs and PCa cells, which reduces lipid availability and pro-inflammatory cytokine signaling within the tumor microenvironment.\u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e,\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAt endpoint, no statistically significant differences in \u003cem\u003eex vivo\u003c/em\u003e tumor volume, bioluminescence or PSA secretion were observed between treatment groups. Nevertheless, tumors from the Enz\u0026thinsp;+\u0026thinsp;Sim group tended to be smaller than those treated with enzalutamide alone, whereas Enz\u0026thinsp;+\u0026thinsp;Met, particularly in the presence of human adipocytes, was associated with larger tumors, suggesting enhanced tumor progression (\u003cb\u003eFigure S9\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eA pilot experiment using C4-2B xenografts confirmed similar synergistic effects of Enz\u0026thinsp;+\u0026thinsp;Sim, especially in adipocyte-rich tumors, while metformin again failed to reduce progression and increased growth in the absence of adipocytes (\u003cb\u003eFigure S10\u003c/b\u003e). Together, these data underscore the importance of incorporating human adipocytes into the humanized bone model to more accurately capture tumor\u0026ndash;stroma interactions and systemic metabolic influences on therapy response.\u003c/p\u003e \u003cp\u003eTo elucidate the mechanisms underlying these effects, we performed transcriptomic analyses on LNCaP xenografts. Principal component analysis revealed clear separation between the simvastatin combination and enzalutamide-alone groups, indicating distinct transcriptional reprogramming (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.C). In contrast, tumors from the enzalutamide\u0026thinsp;+\u0026thinsp;metformin group clustered closely with those treated with enzalutamide alone.\u003c/p\u003e \u003cp\u003eIn tumors bearing human adipocytes, differential gene expression analysis identified that enzalutamide\u0026thinsp;+\u0026thinsp;simvastatin enhanced pathways associated with necroptosis and ferroptosis, along with significant dysregulation in mineral absorption, ECM-receptor interaction and complement and coagulation cascade (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.D). These transcriptomic alterations suggest activation of regulated cell death pathways and remodeling of the extracellular environment, collectively contributing to reduced tumor viability and resistance. Among the most significantly modulated genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.E), downregulation of \u003cem\u003eFTH1\u003c/em\u003e and its pseudogenes, key regulators of ferroptosis, may underlie the observed decrease in tumor proliferation and therapy resistance from the Enz\u0026thinsp;+\u0026thinsp;Sim group, as seen in breast cancer models.\u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e,\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e Additionally, decreased expression of \u003cem\u003eSERPINE1\u003c/em\u003e implies reduced angiogenesis and macrophage M2 polarization,\u003csup\u003e84\u003c/sup\u003e supporting the concept that simvastatin attenuates the protumoral immune microenvironment. Notably, simvastatin also suppressed adhesion- and migration-related genes (e.g., \u003cem\u003eITGA7\u003c/em\u003e, \u003cem\u003ePLGLB2\u003c/em\u003e), suggesting diminished metastatic potential under combination therapy.\u003c/p\u003e \u003cp\u003eHistological analyses further validated these transcriptomic findings. Human adipocytes enhanced vascularization in tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e.\u003cb\u003eB\u003c/b\u003e), an effect inhibited by enzalutamide\u0026thinsp;+\u0026thinsp;simvastatin. The combination therapy markedly reduced tumor cell proliferation (Ki67, Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e.C), while maintaining similar PSA levels (Figure S10.C), indicating proliferation arrest rather than cytotoxicity. Importantly, simvastatin significantly reduced macrophage recruitment within adipocyte-rich tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e.E), thereby limiting the pro-inflammatory microenvironment that supports tumor survival. Protein-level validation confirmed reduced expression of ferritin and plasminogen activator inhibitor-1 (PAI-1, encoded by SERPINE1) in tumors receiving the Enz\u0026thinsp;+\u0026thinsp;Sim treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e.D,F), reinforcing simvastatin\u0026rsquo;s impact on vascularization, immune infiltration, and tumor proliferation. These pronounced effects were specific to the enzalutamide\u0026thinsp;+\u0026thinsp;simvastatin combination; enzalutamide\u0026thinsp;+\u0026thinsp;metformin failed to inhibit BMA-induced protumoral effects or to further suppress proliferation and microenvironmental remodeling compared to enzalutamide alone (\u003cb\u003eFigure S11\u003c/b\u003e). These findings align with clinical observations,\u003csup\u003e77\u003c/sup\u003e yet diverge from prior \u003cem\u003ein vivo\u003c/em\u003e studies using ectopic xenografts.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e This highlights the critical need to incorporate a humanized bone microenvironment in preclinical models to accurately model metabolic therapy responses.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCollectively, these \u003cem\u003ein vivo\u003c/em\u003e studies demonstrate that simvastatin enhances the efficacy of enzalutamide by mitigating BMA-driven resistance mechanisms. The combination reduced tumor progression, suppressed expression of protumoral and metabolic adaptation markers, and limited macrophage recruitment and vascularization within the bone tumor niche. In contrast, metformin showed modest activity in adipocyte-depleted conditions but failed to counteract the supportive effects of BMAs. Thus, simvastatin emerges as a superior co-treatment strategy, acting through coordinated modulation of cholesterol metabolism, cell death pathways, and the tumor microenvironment to increase cancer cell susceptibility to antiandrogen therapy.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eBone metastases mark an advanced and often fatal stage of prostate cancer where current ATTs such as enzalutamide fail,\u003csup\u003e85\u003c/sup\u003e largely because the bone microenvironment actively supports tumor persistence.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u003c/sup\u003e Although ADT is known to alter bone remodeling\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e and systemic metabolism,\u003csup\u003e7\u003c/sup\u003e mechanistic insights have primarily been derived from murine models that differ markedly from the human marrow niche, notably in adipokine secretion and lipid composition.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e These interspecies discrepancies have long complicated translation of preclinical discoveries. Our study addresses this gap through a human-specific, multicellular bone model that enables direct examination of BMA-cancer interactions under physiologically relevant conditions.\u003c/p\u003e \u003cp\u003eWhile recent 3D models capture important aspects of bone physiology (e.g., architecture, extracellular matrix, cellular multiplicity, soluble factors) and have advanced our understanding of tumor biology and therapy response, few yet include bone marrow fat cells.\u003csup\u003e\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e\u003c/sup\u003e Previous 3D approaches have focused on single stromal components of bone metastasis, including osteoblasts or adipocytes, \u003csup\u003e39,41,47,88\u003c/sup\u003e yet none (to the best of our knowledge) have incorporated both mineralized matrix and adipose tissue, two hallmarks of PCa cells within a modular GelMA hydrogel, our platform captures features of the microenvironment previously accessible only \u003cem\u003ein vivo\u003c/em\u003e, while retaining experimental control. GelMA hydrogels, a widely accepted and characterized biomaterial for 3D cell culture,\u003csup\u003e89\u003c/sup\u003e were used here to develop modular coculture systems due to their collagen-derivative nature, innate biocompatibility, and ease of controlled gelation.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e Using GelMA as a carrier, the major innovation of this study was the multicellular, modular nature of the coculture system present here incorporating not only human BMAs and PCa cells, but also human osteoblasts. This design also aligns with recent calls to replace animal-derived matrices such as Matrigel with reproducible, chemically defined biomaterials.\u003csup\u003e\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e\u003c/sup\u003e Importantly, it allows systematic dissection of human-specific crosstalk, overcoming the species mismatch that limits xenograft fidelity.\u003c/p\u003e \u003cp\u003eOur findings align with earlier reports that adipocytes foster PCa progression metabolic reprogramming\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e and tumor microenvironment modulation,\u003csup\u003e21\u003c/sup\u003e but extend these observations by showing that human BMAs possess a distinct metabolic signature compared with subcutaneous white adipocytes. Prior transcriptomic analyses of murine marrow fat suggested a \u0026ldquo;beige-like\u0026rdquo; phenotype\u003csup\u003e,\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u003c/sup\u003e with reduced lipolytic capacity.\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e We observed a similar trend in human BMAs, supporting the notion that marrow fat constitutes a metabolically restrained yet highly reactive depot. In contrast to studies using 2D cocultures, which often report uniform adipocyte activation, our multicellular system revealed cell-type-specific responses: BMAs underwent delipidation and pro-inflammatory reprogramming, while SGBS-derived adipocytes demonstrated slower plasticity.\u003c/p\u003e \u003cp\u003eThe relationship between lipid metabolism and therapy resistance has been widely recognized. Cholesterol plays a critical role in maintaining intracellular homeostasis,\u003csup\u003e92\u003c/sup\u003e but in the context of cancer, it promotes immune evasion by upregulating inhibitory immune checkpoint genes, thereby impairing antitumor immune responses.\u003csup\u003e\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u003c/sup\u003e Moreover, our findings align with previous reports demonstrating that cholesterol synthesis contributes to enzalutamide resistance by interacting with the mTOR and AR signaling axes.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eBeyond metabolism, our transcriptomic analyses indicated activation of prosurvival pathways (e.g., PI3K/Akt, MAPK, and AMPK), similar to prior observations.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e The upregulation of ABC transporters such as ABCC3 aligns with earlier work implicating lipid-regulated efflux pumps in multidrug resistance. High ABCC3 expression has been associated with poor clinical outcomes across multiple cancer types,\u003csup\u003e65\u003c/sup\u003e due to its capacity to reduce intracellular drug concentrations and diminish therapeutic efficacy.\u003csup\u003e\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e\u003c/sup\u003e Notably, ABCC3 expression is regulated by Wnt signaling,\u003csup\u003e95\u003c/sup\u003e a pathway we found to be dysregulated in the presence of BMAs, further supporting the role of adipocyte-derived cues in driving a multidrug-resistant phenotype. Importantly, our system also reproduced immune-related changes previously described, including macrophage recruitment via CSF1 and CCL2 signaling.\u003csup\u003e\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e,\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e\u003c/sup\u003e Such cross-validation with independent models strengthens confidence that the observed mechanisms are not model artefacts but authentic hallmarks of the metastatic bone niche.\u003c/p\u003e \u003cp\u003eRepurposed drugs provide a pragmatic approach to combination therapy as their pharmacodynamics and toxicology are well understood, making them attractive options for reducing the tumor-supportive activity of BMAs without extensive early-phase testing.\u003csup\u003e\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e\u003c/sup\u003e Repurposing drugs also opens avenues for more immediate translational impact, as these agents can quickly be integrated into clinical trials. Recent studies indicate that repurposing strategies may be particularly beneficial in targeting the metabolic dependencies of cancer cells within the bone marrow niche.\u003csup\u003e\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e\u003c/sup\u003e Several groups have explored metabolic interventions using metformin (AMPK inhibitors) or statins (cholesterol inhibitors) to overcome ATT resistance. In 2D and xenograft models, both drugs exhibited antitumor activity, by inhibiting autophagy,\u003csup\u003e78\u003c/sup\u003e reducing mitochondrial respiration,\u003csup\u003e100\u003c/sup\u003e angiogenesis,\u003csup\u003e101\u003c/sup\u003e and pro-inflammatory signaling.\u003csup\u003e\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u003c/sup\u003e Yet, clinical trials have yielded mixed results for metformin\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e and more consistent benefits for statins.\u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e,\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e The divergent outcomes may reflect differences in microenvironmental complexity, precisely what our model accounts for. The enhanced effect of simvastatin observed in our system mirrors recent data linking cholesterol depletion to ferroptosis vulnerability.\u003csup\u003e\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e\u003c/sup\u003e Ferroptosis, a form of regulated cell death driven by iron-dependent lipid peroxidation, has gained recognition as a critical mechanism in cancer biology.\u003csup\u003e\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e\u003c/sup\u003e In bone-metastatic PCa especially, the fatty acid-rich bone environment, induced by BMAs, and altered iron metabolism further promote lipid peroxidation and oxidative damage, enhancing ferroptosis susceptibility and potentially disrupting bone homeostasis, which supports cancer progression.\u003csup\u003e\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e\u003c/sup\u003e The complementary effects of simvastatin on cholesterol metabolism, ferroptosis induction, and microenvironmental remodeling underscore its therapeutic potential when combined with enzalutamide. This convergence between clinical and preclinical observations underscores the translational value of humanized multicellular systems for decoding metabolic resistance pathways within a controlled human context.\u003c/p\u003e \u003cp\u003eWe acknowledge that our \u003cem\u003ein vitro\u003c/em\u003e system primarily captures paracrine interactions, and that direct physical contact between mature BMAs and tumor cells could further enhance the model\u0026rsquo;s physiological relevance. Previous studies have shown that such direct interactions facilitate lipid transfer and alter gene expression patterns supporting tumor survival.\u003csup\u003e\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e,\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e\u003c/sup\u003e However, establishing direct cocultures remains technically demanding, as it requires efficient co-encapsulation of mature BMAs with cancer cells and precise attribution of cell-specific contributions.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u003c/sup\u003e Moreover, \u003cem\u003ein vitro\u003c/em\u003e systems inherently lack systemic influences from BMAs, such as endocrine and metabolic signaling, that shape the bone microenvironment and therapeutic response \u003cem\u003ein vivo\u003c/em\u003e. These factors limit the ability to fully reproduce the complex responses to combination therapies observed clinically, emphasizing the complementary value of \u003cem\u003ein vivo\u003c/em\u003e modeling.\u003c/p\u003e \u003cp\u003eWhile our humanized \u003cem\u003ein vivo\u003c/em\u003e model recapitulated therapeutic behaviors consistent with clinical outcomes, it also presents certain limitations. The adipose component currently relies on SGBS-derived adipocytes, which, although metabolically responsive,\u003csup\u003e56\u003c/sup\u003e do not fully reflect the phenotype of primary BMAs. Nonetheless, the use of SGBS cells provides a practical advantage by enabling the generation of sufficient and standardized adipocyte populations for \u003cem\u003ein vivo\u003c/em\u003e experiments, overcoming the scarcity of primary BMA yield.\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e Future refinements integrating primary or induced bone marrow adipocytes will further enhance model specificity, although isolation and culture of primary BMAs remain challenging.\u003csup\u003e\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e\u003c/sup\u003e Despite these constraints, the platform\u0026rsquo;s defining strength lies in its ability to deconstruct complex, human-specific interactions within the bone metastatic microenvironment with unprecedented control and reproducibility.\u003c/p\u003e \u003cp\u003eThe breadth of the results presented here powerfully reinforce and extend a growing body of evidence positioning bone marrow adiposity as a key determinant of therapeutic resistance in metastatic PCa. By situating these insights within an all-human, multicellular system, we provided a platform that combines mechanistic precision with translational realism. By focusing on the mechanisms of drug resistance and identifying synergistic drug combinations, humanized models serve as a robust preclinical platform for evaluating innovative therapeutic strategies. The ability of this model to reproduce known clinical drug responses and uncover lipid-driven resistance pathways exemplifies its potential as a next-generation preclinical tool. More broadly, it supports a paradigm shift, from descriptive murine studies to human-specific, modular systems capable of revealing how stromal metabolism shapes cancer evolution and treatment response within the bone niche. Consequently, the platform is not limited to PCa but adaptable to other malignancies that colonize bone, including breast and lung cancers.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003e \u003cb\u003eIn vitro\u003c/b\u003e \u003cb\u003ecell culture\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eCells\u003c/em\u003e: Human osteoprogenitors used for osteoblastic microtissues were isolated from bone samples (ethics approval: Queensland University of Technology (QUT) 1400001024), as previously described,\u003csup\u003e108\u003c/sup\u003e and cultured in basal growth medium (\u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e, GM). Human bone marrow mesenchymal stem cells (BM-MSCs, ATCC, PCS500012, USA, used at passage 3\u0026ndash;4) and Simpson-Golabi-Behmel syndrome (SGBS, human preadipocytes, a gift from Dr Barclay from Mater Research, Australia, used at passages 15\u0026ndash;17) were cultured in adipocyte proliferation medium (\u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e, APM). LNCaP and C4-2B cell lines, transduced to express luciferase (a gift from the Australian Prostate Cancer Research Centre-Queensland (APCRC-Q), ethical approval for genetically modified organisms (1700000184)) were used at passages 34\u0026ndash;39 and cultured in cancer proliferation medium (\u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e, CM). All human cell use was approved by QUT ethics #LR 2023-5612-12871.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCell encapsulation in GelMA hydrogels and microtissue formation\u003c/strong\u003e \u003cp\u003eCells encapsulation in GelMA precursor solution (porcine type A, 300 bloom, 80% degree of functionalization, purchased from Gelomics, Australia) was performed according to previously described protocol.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e Briefly, a photoinitiator, Irgacure 2959 (1-[4-(2-hydroxyethoxy)-phenyl]-2-hydroxy-2-methyl-1-propanone, BASF, Germany), was added to the GelMA precursor solution at a concentration of 0.005% (w/v) prior to crosslinking. Hydrogel casting was done using Teflon (PTFE) molds of 5 mm \u0026times; 3 mm (volume of 65 \u0026micro;L) and hydrogels were crosslinked for 15 min at 365 nm, with a light intensity of 2.6 mW.cm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e. After crosslinking, hydrogels were placed in 48 well-plates and rinsed with phosphate-buffered saline (PBS) before being cultured in their respective culture medium (1 mL medium/well).\u003c/p\u003e \u003c/p\u003e \u003cp\u003eTo generate osteoblastic mineralized microtissues, primary human osteoprogenitors were embedded and crosslinked in GelMA 5% w/v (final compressive modulus around 6 kPa, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003cb\u003eB\u003c/b\u003e) at a cell density of 2\u0026times;10\u003csup\u003e6\u003c/sup\u003e cells/mL, and cultured in osteogenic medium (OM, \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e), with three days in mineralization medium (MM, \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e) to boost mineral deposition. For adipose hydrogels, human preadipocytes (SGBS) and BM-MSCs were embedded and crosslinked in GelMA 4% w/v (final compressive modulus around 2.5 kPa, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.B) at a cell density of 4\u0026times;10\u003csup\u003e6\u003c/sup\u003e cells/mL, and cultured in adipogenic induction medium (AIM, \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e) for the first two days of differentiation followed by adipogenic medium (AM, \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e) for the rest of the differentiation duration. PCa cells were embedded and crosslinked in GelMA 4% w/v hydrogels at a cell density of 0.5\u0026times;10\u003csup\u003e6\u003c/sup\u003e LNCaP cells/mL and 0.35\u0026times;10\u003csup\u003e6\u003c/sup\u003e C4-2B cells/mL, and cultured as spheroids in cancer proliferation medium until coculture (CM, \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCoculture systems and treatments\u003c/strong\u003e \u003cp\u003ePrior to coculture, 3D microtissues were preconditioned in 50% coculture medium and 50% of their respective medium (AIM for adipocytes, CM for cancer cells and OM for osteoblasts) for three days. Mineralized, adipose, and tumor microtissues were cocultured in coculture medium (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, CoM, 2.5 mL medium/well), after cell differentiation and spheroid formation in 3D settings (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003cb\u003eA\u003c/b\u003e). For treatments, cells were cocultured in the different treatment media; CoM with DMSO (control), enzalutamide (10 \u0026micro;M, Enz), metformin (1 mM, Met), simvastatin (5 \u0026micro;M, Sim), enzalutamide (10 \u0026micro;M) combined with metformin (1 mM, Enz\u0026thinsp;+\u0026thinsp;Met), and enzalutamide (10 \u0026micro;M) combined with simvastatin (5 \u0026micro;M, Enz\u0026thinsp;+\u0026thinsp;Sim). Medium was fully replenished at day 3 and 5 of coculture.\u003c/p\u003e \u003c/p\u003e\n\u003ch3\u003eAnimal experiments and monitoring\u003c/h3\u003e\n\u003cp\u003e\u003cem\u003eIn vivo\u003c/em\u003e experiments were conducted under the approval of the University of Queensland Animal Ethics Committee (approval number 2021-AE000353) and in accordance with the Australian Code of Practice for the Care and Use of Animals for Scientific Purposes. Six-week-old male NSG mice (strain NOD.Cg-\u003cem\u003ePrkdc\u003c/em\u003e\u003csup\u003e\u003cem\u003escid\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eIL2rg\u003c/em\u003e\u003csup\u003e\u003cem\u003etm1Wjl\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/SzJ)\u003c/em\u003e were purchased from Ozgene (Perth, WA, Australia). Animals were held at the Biological Resources Facility (Translational Research Institute, Brisbane, QLD, Australia), housed in groups of up to four mice in individually ventilated cages on a 12-hour light-dark cycle and had unrestricted access to food and water. After one week of acclimatization, mineralized microtissues were embedded in 40 \u0026micro;L of fibrin glue (TISSEEL Fibrin Sealant, Baxter Healthcare International, USA) loaded with 22.5 \u0026micro;g of recombinant human bone morphogenetic protein-2 (BMP-2) and subcutaneously implanted in the flank of the mice. Prior to subcutaneous implantation, Temgesic (Buprenorphine, 0.05 mg.kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) was subcutaneously administered, and animals were anaesthetized using isoflurane (induction with 4%, maintenance at 2%). Temgesic was administered every 12 hours for 48 hours post-surgery. Animals were monitored twice weekly (health check and body weight measurements). After six weeks of \u003cem\u003ein vivo\u003c/em\u003e mineralization and bone formation, tumoral microtissues (LNCaP or C4-2B cells) \u0026plusmn; adipose microtissues (SGBS cells differentiated into adipocytes for three weeks, 2\u0026nbsp;million cells per implant), were implanted within the same subcutaneous pocket to form a humanized bone tumoral microenvironment. Animals were monitored twice weekly until tumor formation (measurable), where mice were monitored three times per week (health check, body weight and tumors measurements). Additionally, tumor progression was monitored fortnightly using bioluminescence imaging (intraperitoneal injection of XenoLight D-Luciferin potassium salt (150 mg/kg, PerkinElmer), imaging using Xenogen IVIS Spectrum (PerkinElmer), as previously described\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e). Human prostate specific antigen (PSA) serum level (serum collection from submandibular bleeding (\u0026lt;\u0026thinsp;0.5% weight)) was measured using PSA total ELISA kit (OriGene Technologies, USA). Once tumors reached a volume of ~\u0026thinsp;250 mm\u003csup\u003e3\u003c/sup\u003e (total implant of ~\u0026thinsp;450\u0026ndash;500 mm\u003csup\u003e3\u003c/sup\u003e), or a PSA level of ~\u0026thinsp;30\u0026ndash;50 ng/mL, mice were surgically castrated. One week post-castration, mice were randomized to treatment groups and were orally gavaged daily, five days per week, with the different treatment oral solutions: 1) vehicle, 2) enzalutamide (10mg/kg/day, Enz), 3) enzalutamide\u0026thinsp;+\u0026thinsp;metformin (10mg/kg/day Enz, 250 mg/kg/day metformin (Met)) or 4) enzalutamide\u0026thinsp;+\u0026thinsp;simvastatin (10mg/kg/day Enz, 40 mg/kg/day Simvastatin (Sim)). Treatment persisted until endpoint, determined by; 1) completion of four weeks of treatment, 2) tumor endpoint (maximum tumor volume 1000 mm\u003csup\u003e3\u003c/sup\u003e) or, 3) ethical welfare assessment of a condition requiring euthanasia. At endpoint, animals were euthanized using carbon dioxide asphyxiation and humanized tissues were rapidly excised and measured. \u003cem\u003eEx vivo\u003c/em\u003e tissues were snap frozen in liquid nitrogen and stored at -80\u0026deg;C for RNA analyses or fixed with 4% w/v paraformaldehyde for histology analyses. Mice bones and organs were collected and analyzed by bioluminescence imaging following incubation with luciferin, to detect metastases. As no metastases were observed, only the humanized tissues were further analyzed.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGene expression analyses\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e\u003cem\u003emRNA extraction\u003c/em\u003e:\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eIn vitro samples\u003c/strong\u003e \u003cp\u003eHydrogels were washed twice for 5 min in PBS, and two hydrogels per condition were pooled together and stored in 500 \u0026micro;L of TRIZol reagent (ThermoFisher) at -80\u0026deg;C for at least 48 hours and until RNA extraction. Using 21G needles, hydrogels were mechanically broken into small pieces and centrifuged at 16,000 rpm for 1 min to remove cell and hydrogel debris. mRNA was extracted using Direct-zol RNA Miniprep Plus Kit (Zymo Research, USA) following the manufacturer\u0026rsquo;s protocol.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eIn vivo samples\u003c/strong\u003e \u003cp\u003eFrozen samples (~\u0026thinsp;10mg of sample in 1mL TRIZol) were homogenized using stainless-steel beads for 1 min at ~\u0026thinsp;20 Hz. The homogenate was centrifuged at 4\u0026deg;C for 1 min at 12,000 rpm. Supernatant was collected and processed using Direct-zol RNA Miniprep Plus Kit (Zymo Research, USA) to extract mRNA following manufacturer\u0026rsquo;s protocol.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eRTqPCR\u003c/strong\u003e \u003cp\u003emRNA (250 ng) was reverse transcribed into cDNA using SensiFast cDNA Synthesis Kit (Bioline, Australia). Quantitative PCR was performed using SYBR Green PCR Master Mix and QuantStudio 6 Flex System (Applied Biosystems). \u003cem\u003eRPL32\u003c/em\u003e and \u003cem\u003eACTB\u003c/em\u003e were used as housekeeping genes to normalize \u003cem\u003eCq\u003c/em\u003e values for each marker (primers used listed in \u003cb\u003eTable S2\u003c/b\u003e,), and differential gene expression was calculated using the ΔΔCq method.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003emRNA Sequencing\u003c/em\u003e: RNA sequencing (RNAseq) was performed by Azenta. First, total RNA was assessed for quality and quantity, with quality cut-off at RNA integrity number\u0026thinsp;\u0026gt;\u0026thinsp;7. Library preparation was then performed using 1 \u0026micro;g of total RNA after poly(A) mRNA isolation, and RNAseq using Illumina HiSeq instrument using a 2\u0026times; 150 paired-end (PE) configuration according to the manufacturer\u0026rsquo;s instructions, yielding ~\u0026thinsp;50M reads/samples. RNA quality was assessed using standard quality metrics including Q20/Q30 scores, GC content, and read length distribution. Raw data was processed to remove technical sequences using Cutadapt (V1.9.1, phred cutoff: 20, error rate: 0.1, adapter overlap: 1bp, min. length: 75, proportion of N: 0.1). Clean data were aligned to reference genome (human genome) using Hisat2 (V2.2.1) software. Differential expression (DE) between conditions was performed using DESeq2 Bioconductor package and defined by a false-discovery rate (FDR) corrected \u003cem\u003eP\u003c/em\u003e-value\u0026thinsp;\u0026le;\u0026thinsp;0.05. Functional gene annotation and gene network analyses were performed on DE transcripts using GEOSeq (V1.34.1) and TopGO (V2.18.0). Samples clustering by principal component analysis (PCA) were performed using Rstudio with FPKM values as the input. Heatmaps of log2FPKM values were created in GraphPad Prism (version 10).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eProtein analyses\u003c/h3\u003e\n\u003cp\u003e \u003cem\u003eImmunofluorescenc\u003c/em\u003ee \u003cem\u003eimaging and analysis\u003c/em\u003e: Hydrogels were washed twice in PBS for 5 min and fixed with 4% w/v paraformaldehyde for 30 min. Cells underwent permeabilization with a 0.2% v/v Triton solution for 15 min, followed by incubation in a 1% w/v bovine serum albumin (BSA, Sigma-Aldrich) solution for 15 min and a 2h incubation in 5% w/v BSA solution. Constructs were then incubated overnight at 4\u0026deg;C with primary antibody solutions (anti-PAI-1 (ThermoFisher #MA517171) and anti-ferritin (ThermoFisher #PA5120011), 1:200 dilution in 1% w/v BSA solution), followed by an overnight incubation in DAPI (10 \u0026micro;g/mL) and Phalloidin (2.6 \u0026micro;g/mL) solution at 4\u0026deg;C. Samples were washed twice for 15 min in 1% w/v BSA solution and a third time overnight before imaging.\u003c/p\u003e \u003cp\u003eFor lipid droplets detection, constructs were incubated in DAPI/phalloidin staining solution with Nile Red (10 \u0026micro;g/mL) overnight at 4\u0026deg;C after blocking solution (5% w/v BSA solution).\u003c/p\u003e \u003cp\u003eImaging was conducted using a Spectral Spinning Disc Confocal Microscope (Nikon, Minato, TYO, Japan) with blue (excitation 405 nm, exposure 500 ms), green (excitation 488 nm, exposure 500 ms), and red (excitation 561 nm, exposure 400 ms) filter sets. Maximal intensity projections were generated from \u003cem\u003ez\u003c/em\u003e-stacks with a step size of 10 \u0026micro;m and a thickness of 200 to 250 \u0026micro;m for 4\u0026times; and 10\u0026times; magnifications, and a step size of 5 \u0026micro;m and a thickness of 100 \u0026micro;m for 20\u0026times; magnification images.\u003c/p\u003e \u003cp\u003eQuantitative analysis for lipid droplets was undertaken on 10\u0026times; magnification images (3\u0026ndash;4 images per hydrogel, 2 hydrogels per biological replicate (BR), 3 BRs) using Image J software (version 1.54j, National Institute of Health (NIH), USA). Spheroid measurements from 10\u0026times; magnification images (3\u0026ndash;4 images per hydrogel, 2 hydrogels per BR, 3 BRs) were conducted using QuPath software (version 0.4.4) and modified StarDist algorithm. Nuclei density was measured using DAPI signal intensity normalized to spheroid area from 20\u0026times; magnification images (3 images per hydrogel, 2 hydrogels per BR, 3 BRs) using Image J software (version 1.54j, National Institute of Health (NIH), USA).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEnzyme-linked immunosorbent assay (ELISA)\u003c/strong\u003e \u003cp\u003eHuman total PSA level from conditioned medium was measured using human PSA total ELISA kit (ThermoFisher), following the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eHistology and immunohistochemistry (IHC)\u003c/h2\u003e \u003cp\u003eExplants were decalcified for 10 days in 10% w/v EDTA solution (37\u0026deg;C, pH 7.4) using KOS Rapid microwave lab station (ABACUS, Brisbane, Australia). Decalcified tissues were embedded in paraffin and serial 5 \u0026micro;m thick sections were used for staining. Hematoxylin and eosin (H\u0026amp;E) staining was used to characterize tissue morphology and Masson\u0026rsquo;s trichrome staining to characterize extracellular matrix, as previously described.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e IHC was performed on dewaxed and rehydrated sections, after antigen retrieval treatment, as outlined in \u003cb\u003eTable S3\u003c/b\u003e. Tissue sections were first treated to quench endogenous peroxidase activity by incubating them in 3% v/v hydrogen peroxide (Sigma-Aldrich) solution for 5 min. Following this, non-specific binding sites were blocked using a 2% w/v BSA solution for 30 min. Primary antibodies were appropriately diluted in the blocking buffer (\u003cb\u003eTable S3\u003c/b\u003e). Immunoreactivity was subsequently visualized using the EnVision\u0026thinsp;+\u0026thinsp;Dual Link System-HRP Rabbit/Mouse kit (Dako, Glostrup, Denmark), and the color was developed using liquid diaminobenzidine chromagen (Dako). Sections were counterstained with Mayer\u0026rsquo;s Hematoxylin (Sigma) prior to dehydration and mounting.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eFor each \u003cem\u003ein vitro\u003c/em\u003e assay and analysis, three independent experiments were conducted, and each experiment included two to four technical replicates. For \u003cem\u003ein vivo\u003c/em\u003e study, eight to nine mice were included per group (only four for the pilot study with C4-2B xenografts). \u003cem\u003eEx vivo\u003c/em\u003e RNAseq and histology analyses were conducted on four to five explants per group, each. Graphs were created using GraphPad Prism version 10, while statistical analyses were performed using IBM SPSS Statistics (version 29) software, employing a general linear model (univariate analysis). Posthoc Tukey test was used to assess parameter estimates when overall significance was achieved. In all statistical assessments, significance levels were set at *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, ***\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, and ****\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001. Experimental plan figures were created using BioRender.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eData and materials availability\u003c/h2\u003e \u003cp\u003eAll data needed to evaluate the conclusions are presented in the publication. Additional data related to this publication may be requested from A.B. directly ([email protected]), upon reasonable request.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical Statement\u003c/strong\u003e \u003cp\u003e Isolation of primary human osteoprogenitors was conducted in accordance with the ethical principles and guidelines provided by the QUT Human Research Ethics Committee (ethics approval number 1400001024). Written informed consent was obtained from all human participants involved in providing primary cells for research purposes prior to cell isolation. The use of human cells (primary hBM-MSCs, SGBS cells and cell lines) was covered by ethics approval (LR 2023-5612-12871) from QUT. All experimental procedures involving animals were performed in compliance with the \u003cem\u003eAustralian Code of Practice for the Care and Use of Animals for Scientific Purposes\u003c/em\u003e, and approved by the University of Queensland Animal Ethics Committee (approval number 2021-AE000353). Every effort was made to minimize animal suffering, and appropriate measures were taken to ensure the welfare and humane treatment of animals throughout the study.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eN.B. acknowledges support from Cancer Australia \u0026amp; Cure Cancer (Priority-driven Collaborative Cancer Research Scheme APP1187030), Advance Queensland (AQIRF066-2019RD2), the Australian Research Council (DE240100128). A.B., J.M. and N.B. acknowledge support from the Max Planck Queensland Centre for the Materials Science of Extracellular Matrices.\u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e \u003cp\u003eAll authors confirmed that they have contributed to the intellectual content of this paper and have made significant contributions to some of the following: conception and design, acquisition of data, analysis and interpretation of data, and drafting or revising the article. A.B. contributed to the conceptualization, methodology, formal analysis, investigation, data curation, visualization, project administration and wrote the original draft. S.B. and L.B. contributed to the investigation and data curation. J.M. and J.G. contributed to the conceptualization, methodology, investigation and supervision. D.W. contributed to scholarship provision and supervision. J.C. contributed to mentoring. N.B. contributed to conceptualization, methodology, investigation, project administration, funding acquisition and supervision. Finally, all authors contributed to reviewing and editing the draft.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eSchematic diagrams depicting the experimental design were created using BioRender.com. We thank Baxter Healthcare for providing TISSEEL\u0026trade; Fibrin Sealant (fibrin glue) and Arla Foods Ingredients for supplying the Lacprodan\u0026reg; OPN-10 samples. We acknowledge the precious support provided by the Preclinical Imaging, Biological Resources, Microscopy Core Facilities at the Translational Research Institute, and the Central Analytical Research Facility (CARF) at the Queensland University of Technology. We thank Dr Anja Rockstroh from the Australian Prostate Cancer Research Centre \u0026ndash; Queensland (APCRC-Q) for her guidance in RNAseq data processing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOrganization, I. A. f. R. o. C.-W. H. \u003cem\u003eCancer Today\u003c/em\u003e, \u0026lt;https://gco.iarc.fr/today/en/dataviz/pie?mode=cancer\u0026amp;group_populations=1\u0026amp;sexes=1\u0026amp;cancers=27\u0026amp;types=0\u0026amp;populations=900\u0026gt; (2024).\u003c/li\u003e\n\u003cli\u003eTeo, M. Y., Rathkopf, D. E. \u0026amp; Kantoff, P. 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Report of the Methodologies Working Group of the International Bone Marrow Adiposity Society. \u003cem\u003eFrontiers in Endocrinology\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e (2020). https://doi.org/10.3389/fendo.2020.00065\u003c/li\u003e\n\u003cli\u003eThibaudeau, L.\u003cem\u003e et al.\u003c/em\u003e A tissue-engineered humanized xenograft model of human breast cancer metastasis to bone. \u003cem\u003eDMM Disease Models and Mechanisms\u003c/em\u003e\u003cstrong\u003e7\u003c/strong\u003e, 299\u0026ndash;309 (2014). https://doi.org/10.1242/dmm.014076\u003c/li\u003e\n\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":"bone-research","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"boneres","sideBox":"Learn more about [Bone Research](http://www.nature.com/boneres/)","snPcode":"41413","submissionUrl":"https://mts-boneres.nature.com/cgi-bin/main.plex","title":"Bone Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8720393/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8720393/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAlthough initially effective to treat prostate cancer (PCa), resistance to antiandrogen therapies is inevitable and leads to metastatic castration-resistant PCa. Bone marrow adipocytes (BMAs) may play a role in bone metastasis therapy resistance by promoting metabolic reprogramming, yet their value as a therapeutic target remains understudied due to a lack of relevant models. Here, we used multicellular, modular hydrogel models in advanced humanized settings to examine the value of BMA targeting in advanced PCa. Our \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e findings confirmed that BMAs induce lipid metabolism dysregulation and pro-inflammatory signaling, creating a tumor-supportive environment that fosters resistance to androgen deprivation. Combining enzalutamide with the anti-cholesterol drug simvastatin significantly reduced these effects, notably through ferroptosis and bone tumor microenvironment modulations, impairing cancer cell survival. This study suggests that targeting BMA-PCa interactions with simvastatin may enhance enzalutamide\u0026rsquo;s efficacy, emphasizing the synergistic value of human-specific multicellular preclinical models for assessing therapeutic strategies in bone metastasis.\u003c/p\u003e","manuscriptTitle":"Preclinical humanized bone models reveal metabolic reprogramming and simvastatin benefits in castration-resistant prostate cancer in bone","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-10 14:55:33","doi":"10.21203/rs.3.rs-8720393/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2026-05-07T09:31:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-05-05T08:15:48+00:00","index":4,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-05-03T07:18:09+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-04-16T14:19:41+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-04-02T07:48:28+00:00","index":4,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-04-02T03:17:36+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-03-16T07:15:36+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-03-01T14:58:50+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2026-02-06T03:57:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-30T07:26:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-28T12:00:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"Bone Research","date":"2026-01-28T12:00:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bone-research","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"boneres","sideBox":"Learn more about [Bone Research](http://www.nature.com/boneres/)","snPcode":"41413","submissionUrl":"https://mts-boneres.nature.com/cgi-bin/main.plex","title":"Bone Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"00b4c927-7fb8-42a9-9a03-16ef048ae6f5","owner":[],"postedDate":"February 10th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"revise","date":"2026-05-07T09:31:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-05-05T08:15:48+00:00","index":4,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-05-03T07:18:09+00:00","index":3,"fulltext":"This content is not available."}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":62421193,"name":"Biological sciences/Cancer/Bone cancer"},{"id":62421194,"name":"Health sciences/Diseases/Cancer/Bone cancer"}],"tags":[],"updatedAt":"2026-05-07T09:35:47+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-10 14:55:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8720393","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8720393","identity":"rs-8720393","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}