Metabolic CRISPR screening identifies RPE as a key regulator of acquired enzalutamide resistance through FKBP5 destabilization in prostate cancer.

Metabolic CRISPR screening identifies RPE as a key regulator of acquired enzalutamide resistance through FKBP5 destabilization in prostate cancer. | 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 Metabolic CRISPR screening identifies RPE as a key regulator of acquired enzalutamide resistance through FKBP5 destabilization in prostate cancer. Cheng Liu, Jintao Hu, Cong Lai, Yunfei Xiao, Zi Yan, Yongmei Tan, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9593389/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Enzalutamide is a cornerstone therapy for castration-resistant prostate cancer (CRPC), yet acquired resistance remains a major clinical challenge. Although metabolic enzymes are increasingly recognized as modulators of therapeutic response, their specific roles—particularly their non-enzymatic functions—in sustaining enzalutamide resistance remain incompletely understood. In this study, we performed an in vivo screen using a custom metabolic CRISPR library in enzalutamide-treated xenografts and identified the pentose phosphate pathway enzyme ribulose-5-phosphate 3-epimerase (RPE) as a critical driver of enzalutamide resistance. Silencing RPE markedly restored enzalutamide sensitivity, enhanced apoptosis in vitro, and significantly suppressed tumor growth in both cell line-derived and patient-derived xenograft models. Mechanistically, RPE promoted resistance independently of its canonical enzymatic activity. Instead, RPE physically interacted with FKBP5 and promoted its ubiquitin-proteasome-mediated degradation. Loss of FKBP5 subsequently hyperactivated AKT signaling, leading to increased p-BAD and BCL-xL levels and suppression of enzalutamide-induced cell death. Conversely, disrupting the RPE-FKBP5 interaction or silencing RPE in vivo using a PSMA-targeted lipid nanoparticle system effectively abrogated these resistance phenotypes. Together, these findings illustrate how CRPC cells hijack the non-enzymatic function of a metabolic enzyme to evade antiandrogen therapy, establishing the RPE-driven degradation of FKBP5 and consequent AKT hyperactivation as a targetable vulnerability for overcoming enzalutamide resistance. Biological sciences/Cancer/Cancer therapy/Cancer therapeutic resistance Biological sciences/Cancer/Urological cancer/Prostate cancer Health sciences/Biomarkers/Predictive markers Biological sciences/Cancer/Cancer models Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Prostate cancer remains one of the leading causes of cancer-related mortality in men worldwide( 1 , 2 ). While androgen deprivation therapy (ADT) is initially effective for advanced prostate cancer, the disease inevitably progresses to castration-resistant prostate cancer (CRPC)( 3 – 5 ). The development of next-generation androgen receptor (AR) pathway inhibitors, such as enzalutamide, has significantly improved outcomes for patients with CRPC( 6 , 7 ). However, the clinical efficacy of these therapies is severely constrained by the rapid emergence of acquired resistance, leading to lethal disease progression( 4 , 8 ). Although several mechanisms, including AR amplification, structural rearrangements, and lineage plasticity, have been implicated in mediating antiandrogen resistance( 9 – 11 ), targeting these classical pathways has yielded limited clinical success. Consequently, uncovering actionable, non-canonical molecular dependencies that sustain enzalutamide resistance remains an urgent clinical imperative. Metabolic reprogramming is a fundamental hallmark of CRPC, fueling the high proliferation rates and robust survival mechanisms required for cancer cells to adapt under the intense selective pressure of AR inhibition( 12 , 13 ). Recent efforts have highlighted the contribution of altered metabolic pathways—such as enhanced glycolysis and lipid metabolism—to the resistant phenotype( 14 – 18 ). However, our understanding of the specific metabolic vulnerabilities that drive enzalutamide resistance remains limited, in part because of the lack of systematic in vivo functional interrogation. Furthermore, while metabolic enzymes are conventionally studied for their catalytic roles in biochemical pathways, an emerging paradigm suggests that many of these proteins possess non-canonical functions—such as scaffolding protein complexes or regulating signal transduction—that operate independently of their enzymatic activities( 19 – 21 ). How CRPC cells exploit these non-enzymatic functions of metabolic enzymes to evade therapeutic pressure remains largely unexplored. To address this gap in knowledge, we performed an in vivo CRISPR-Cas9 loss-of-function screen using a custom metabolism-focused library in an enzalutamide-treated xenograft model. This strategy was designed to identify critical metabolic genes whose loss sensitizes CRPC cells to enzalutamide in a physiologically relevant in vivo context. From this screen, we identified ribulose-5-phosphate 3-epimerase (RPE), an enzyme traditionally known for catalyzing the reversible epimerization of ribulose-5-phosphate to xylulose-5-phosphate in the pentose phosphate pathway (PPP)( 22 , 23 ), as a top dependency required for the maintenance of enzalutamide resistance in CRPC. In this study, we demonstrate that RPE drives enzalutamide resistance not through its canonical enzymatic activity, but via a previously unrecognized non-enzymatic mechanism. Specifically, we found that RPE physically interacts with the co-chaperone protein FKBP5 and promotes its ubiquitin-proteasome-mediated degradation. Loss of FKBP5 subsequently hyperactivates the AKT survival signaling cascade, leading to increased p-BAD and BCL-xL levels and suppression of enzalutamide-induced apoptosis. Importantly, therapeutic intervention using a prostate-specific membrane antigen (PSMA)-targeted lipid nanoparticle (LNP) system to deliver RPE siRNA markedly re-sensitized resistant tumors to enzalutamide in vivo. Together, these findings reveal a mechanism by which CRPC cells exploit the non-enzymatic function of a metabolic enzyme to evade endocrine therapy, establishing the RPE-driven degradation of FKBP5 and consequent AKT hyperactivation as a targetable vulnerability for overcoming enzalutamide resistance. Results Metabolic CRISPR screening identifies RPE as a driver of enzalutamide resistance To systematically identify metabolic dependencies that sustain enzalutamide resistance in CRPC, we performed an in vivo pooled CRISPR-Cas9 loss-of-function screen. C4-2 cells transduced with a custom single guide RNA (sgRNA) library targeting human metabolic genes were subcutaneously implanted into surgically castrated immunodeficient mice. Following tumor establishment, mice were treated with vehicle or enzalutamide (20 mg/kg) for 4 weeks, and tumors were then collected for deep sequencing (Fig. 1 A). Comparison of sgRNA abundance between enzalutamide-treated and vehicle-treated tumors identified genes whose loss altered enzalutamide response, based on robust ranking aggregation (RRA) scoring. Negative and positive RRA score distributions revealed distinct sets of depleted and enriched genes, respectively (Fig. 1 B-C). In total, 66 genes were significantly depleted and 35 genes were enriched in enzalutamide-treated tumors. Among the top depleted metabolic candidates, RPE emerged as a prominent hit, suggesting that its loss compromises CRPC cell survival under enzalutamide treatment (Fig. 1 D). To validate the top hits from the screen, we selected the five most significantly depleted candidate genes (RPE, NAA50, PGK1, OGDH, and GRIK1) for individual siRNA-mediated knockdown in C4-2 EnzaR and 22Rv1 cells. RT-qPCR confirmed efficient silencing of each gene in both cell lines ( Supplementary Fig. 1A ). Among these candidates, RPE depletion produced the strongest sensitizing effect, markedly reducing the enzalutamide IC50 in C4-2 EnzaR cells (from 47.29 µM to 14.86 µM) and 22Rv1 cells (from 35.83 µM to 17.51 µM) (Fig. 1 E-F). We therefore prioritized RPE for further mechanistic studies. To confirm the role of RPE in sustaining enzalutamide resistance, we established stable shRPE cell lines. Efficient RPE depletion at both the mRNA and protein levels was accompanied by a marked reduction in enzalutamide IC50, consistent with the transient knockdown results (Fig. 1 G-I). Whereas RPE depletion alone had little effect on baseline proliferation, combining shRPE with enzalutamide markedly reduced cell viability over time (Fig. 1 J). Similarly, RPE knockdown alone did not impair clonogenic growth, but in the presence of enzalutamide it almost completely abolished colony formation in both CRPC cell lines (Fig. 1 K-L). These findings indicate that RPE is specifically required for CRPC cells to tolerate enzalutamide-induced cytotoxic stress. RPE deficiency sensitizes CRPC cells to enzalutamide-induced apoptosis Induction of apoptosis is a major mechanism by which enzalutamide suppresses prostate cancer cell growth; accordingly, resistance to enzalutamide-induced apoptosis represents an important basis of acquired enzalutamide resistance( 24 – 26 ). Because RPE knockdown selectively abolished the clonogenic survival of enzalutamide-treated cells, we hypothesized that RPE depletion restores sensitivity to enzalutamide by reinstating apoptotic cell death. To test this, we performed Annexin V/PI flow cytometry in both C4-2 EnzaR and 22Rv1 cells. Neither enzalutamide treatment nor RPE depletion alone induced substantial cell death. In contrast, the combination of shRPE and enzalutamide produced a marked increase in apoptosis in both resistant cell lines (Fig. 2 A-B). To investigate the underlying mechanism, we examined key apoptosis-related proteins by immunoblotting. Consistent with the flow cytometry results, combined RPE depletion and enzalutamide treatment markedly increased the levels of cleaved PARP and cleaved Caspase-3 (Fig. 2 C). At the same time, this combination suppressed survival signaling, as reflected by reduced BCL-xL expression and loss of p-BAD. Because RPE is a canonical enzyme in the non-oxidative branch of the pentose phosphate pathway (PPP), catalyzing the reversible interconversion of ribulose-5-phosphate (Ru5P) and xylulose-5-phosphate (Xu5P) (Fig. 2 D), we next assessed the metabolic consequences of its loss. Seahorse extracellular flux analysis showed that RPE depletion reduced both extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) in C4-2 EnzaR (Fig. 2 E) and 22Rv1 cells (Fig. 2 F). In addition, RPE deficiency decreased the intracellular NADPH/NADP + ratio. These metabolic changes were primarily attributable to RPE loss and were not substantially intensified by enzalutamide treatment. Importantly, although RPE knockdown measurably altered cellular bioenergetics, these changes alone were insufficient to induce overt cell death. This dissociation between the metabolic phenotype caused by RPE loss alone and the pronounced apoptosis observed only with combined enzalutamide treatment suggested that RPE may protect CRPC cells through mechanisms beyond its canonical metabolic function. We therefore next investigated whether apoptotic sensitization to enzalutamide depends strictly on the enzymatic activity of RPE. RPE depletion overcomes enzalutamide resistance in preclinical in vivo models To determine whether the apoptotic sensitization observed in vitro could be translated in vivo, we evaluated the therapeutic impact of targeting RPE in two independent preclinical models: a CDX model established from C4-2 EnzaR cells (Fig. 3 A) and a PDX model derived from a patient with clinically confirmed enzalutamide-resistant CRPC (Fig. 3 B). In the CDX model, consistent with the refractory nature of these cells, enzalutamide monotherapy failed to suppress tumor growth. Likewise, RPE knockdown alone did not significantly inhibit tumor progression. In contrast, the combination of RPE depletion and enzalutamide markedly suppressed tumor growth, resulting in substantially reduced final tumor volumes and weights (Fig. 3 C). To determine whether this antitumor effect was associated with the mechanisms identified in vitro, we performed Immunohistochemistry (IHC) analysis on excised CDX tumors. Staining confirmed sustained RPE knockdown in the corresponding groups. Notably, AR expression remained largely unchanged across groups, suggesting that RPE depletion does not restore enzalutamide sensitivity by reducing AR expression. Instead, quantitative IHC (H-score) analysis showed that tumors from the combination treatment group (shRPE + Enza) displayed increased apoptosis, as indicated by elevated Cleaved Caspase-3, together with reduced p-BAD and BCL-xL expression (Fig. 3 D-E). The therapeutic response in the PDX model closely recapitulated the findings in the CDX model. Whereas patient-derived tumors remained resistant to enzalutamide monotherapy and were minimally affected by RPE knockdown alone, the combination of enzalutamide with RPE depletion markedly suppressed tumor growth (Fig. 3 F). Histologic analysis of PDX tissues further supported activation of the apoptotic program predominantly in the combination treatment group ( Supplementary Fig. 2A-B ). Together, these data identify RPE as a critical dependency in enzalutamide-resistant CRPC and support its targeting as a strategy to restore sensitivity to enzalutamide in vivo. RPE drives enzalutamide resistance through an enzyme-independent mechanism Given the apparent dissociation between the metabolic alterations induced by RPE loss and the apoptotic phenotype observed under enzalutamide treatment, we hypothesized that RPE protects CRPC cells through a non-canonical, enzyme-independent mechanism. To test this, we generated a catalytically inactive mutant by introducing a point mutation at the highly conserved Ser10 residue (S10A). Previous biochemical and structural studies have shown that the S10A substitution abolishes the catalytic conversion of Ru5P to Xu5P while preserving the overall protein structure of RPE( 23 ). To confirm loss of enzymatic function, we used a coupled biochemical assay in which RPE activity was assessed indirectly through downstream NADH oxidation, monitored as a decrease in absorbance at 340 nm (Fig. 4 A). Using this assay, we confirmed that RPE S10A lacked catalytic activity relative to RPEWT (Fig. 4 B). We then reintroduced either shRNA-resistant RPE WT or RPE S10A into endogenous RPE-depleted C4-2 EnzaR and 22Rv1 cells. Both constructs were engineered with synonymous mutations rendering them resistant to shRPE. As expected, RPE WT restored intracellular enzymatic activity, whereas RPE S10A failed to rescue this metabolic function (Fig. 4 C). We next subjected these rescue cell lines to phenotypic analysis. Under vehicle treatment, neither RPE depletion nor ectopic expression of RPE WT or RPE S10A significantly altered baseline proliferation or clonogenic growth ( Supplementary Fig. 3A-C ). In contrast, under enzalutamide treatment, the catalytically inactive RPE S10A mutant restored the IC50 and rescued long-term cell viability to a similar extent as RPE WT (Fig. 4 D-E). This rescue was further supported by colony formation assays, in which RPE S10A restored clonogenic survival in enzalutamide-treated CRPC cells despite endogenous RPE depletion (Fig. 4 F-G). To determine whether this enzyme-independent rescue also extended to apoptosis, we examined apoptotic responses in these cells. Consistent with the viability data, expression of either RPE WT or RPE S10A markedly suppressed the apoptosis induced by combined shRPE and enzalutamide treatment (Fig. 4 H-I). Together, these rescue experiments demonstrate that the canonical enzymatic activity of RPE is dispensable for supporting CRPC cell survival under AR blockade. Instead, RPE promotes enzalutamide resistance and suppresses apoptosis through a previously unrecognized non-enzymatic function. To further determine whether the apoptotic rescue mediated by the S10A mutant occurs independently of metabolic restoration, we profiled the bioenergetic state of the RPE rescue cell lines under enzalutamide treatment. Re-expression of RPE WT reversed the metabolic defects caused by endogenous RPE depletion. In contrast, cells expressing the catalytically inactive RPE S10A mutant remained metabolically impaired, with persistently reduced ECAR, OCR, and intracellular NADPH/NADP⁺ ratio (Fig. 5 A-D). Despite this sustained metabolic deficiency, immunoblot analysis showed that both RPE WT and RPE S10A suppressed enzalutamide-induced apoptosis, as indicated by reduced PARP and Caspase-3 cleavage together with maintained p-BAD and BCL-xL expression (Fig. 5 E). We next asked whether this enzyme-independent survival mechanism also governs enzalutamide resistance in vivo. To this end, we established xenografts using C4-2 EnzaR rescue cell lines and treated the mice continuously with enzalutamide. Whereas tumors carrying the empty vector (shRPE + Vector) remained sensitive to AR blockade, ectopic expression of RPE WT restored tumor growth. Notably, RPE S10A closely recapitulated the effect of RPE WT , restoring final tumor volumes and weights to comparable levels (Fig. 5 F-G). Histologic analysis of excised tumors further supported these findings. IHC demonstrated that both wild-type and catalytically inactive RPE restored survival signaling in vivo, as evidenced by increased p-BAD and BCL-xL expression together with reduced Cleaved Caspase-3, without altering baseline AR expression (Fig. 5 H and Supplementary Fig. 4 ). Together, these molecular and in vivo data indicate that RPE promotes enzalutamide resistance and tumor progression through a non-enzymatic mechanism. RPE interacts with FKBP5 and promotes its proteasome-mediated degradation To identify downstream effectors mediating the non-enzymatic function of RPE, we sought to define its interacting partners. Flag-tagged RPE was immunoprecipitated from CRPC cells and subjected to silver staining followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) (Fig. 6 A). Analysis of the enriched proteins and peptide spectra identified the immunophilin FKBP5 as one of the most prominent RPE-associated candidates (Fig. 6 B and Supplementary Fig. 5A-B ). To validate this interaction in cells, we performed immunofluorescence (IF) staining, which showed substantial spatial colocalization of RPE and FKBP5, predominantly in the cytoplasm (Fig. 6 C-D). To define the structural basis of this interaction, we performed computational molecular docking, which predicted a binding interface between RPE and the C-terminal region of FKBP5 (Fig. 6 E). We then carried out a 100-ns molecular dynamics (MD) simulation to evaluate the stability of the predicted complex. Analyses of RMSD, SASA, RMSF, Rg, intermolecular hydrogen bonding, and the free energy landscape (FEL) supported a stable RPE-FKBP5 complex in solution ( Supplementary Fig. 5C-H ). To experimentally map the interaction region, we performed in vitro GST pulldown assays using a series of FKBP5 truncation mutants. Initial mapping localized the RPE-binding region to the C-terminal segment spanning amino acids 320–420 (Fig. 6 F). Further fine mapping using internal deletion mutants identified residues 331–342 as critical for the interaction (Fig. 6 G). Consistent with this result, co-immunoprecipitation assays showed that mutation of this region (FKBP5-MUT) largely abolished binding to RPE, further supporting the requirement of this sequence for complex formation (Fig. 6 H). We next examined the functional consequence of the RPE-FKBP5 interaction. Western blot analysis showed that RPE depletion increased endogenous FKBP5 protein levels, whereas ectopic expression of RPE reduced FKBP5 abundance (Fig. 6 I). In contrast, qRT-PCR analysis revealed that neither knockdown nor overexpression of RPE, with or without enzalutamide treatment, altered FKBP5 or AR mRNA levels ( Supplementary Fig. 6A ), arguing against transcriptional regulation and supporting a post-translational mechanism. Consistent with this, cycloheximide (CHX) chase assays showed that RPE depletion markedly prolonged the half-life of FKBP5 (Fig. 6 J). To determine the degradation pathway involved, cells were treated with either the proteasome inhibitor MG132 or the lysosome inhibitor chloroquine. MG132 abolished the difference in FKBP5 protein levels between shCtrl and shRPE cells, indicating proteasome-dependent turnover (Fig. 6 K). In parallel, ubiquitination assays showed that loss of RPE reduced FKBP5 polyubiquitination (Fig. 6 L). Together, these data indicate that RPE physically interacts with FKBP5 and promotes its ubiquitin-proteasome-mediated degradation, thereby reducing FKBP5 protein stability. Disruption of the RPE-FKBP5 interaction re-sensitizes CRPC cells to enzalutamide by suppressing AKT signaling Having established that RPE interacts with FKBP5 and promotes its degradation, we next asked whether disrupting this interaction could restore sensitivity to enzalutamide. To minimize interference from endogenous FKBP5, we used a knockdown-rescue strategy in C4-2 EnzaR and 22Rv1 cells. Endogenous FKBP5 was first depleted using stable shFKBP5, followed by re-expression of either wild-type FKBP5 (FKBP5 WT ) or an RPE-binding-deficient mutant (FKBP5 MUT ) harboring mutations within residues 331–342. Western blot analysis confirmed comparable steady-state expression of FKBP5 WT and FKBP5 MUT (Fig. 7 A). We hypothesized that FKBP5 MUT , by evading RPE-mediated recognition and subsequent proteasomal degradation, would persistently exert its downstream tumor-suppressive functions. Indeed, cell viability assays demonstrated that while cells expressing FKBP5 WT remained highly refractory to enzalutamide, the introduction of the interaction-defective FKBP5 MUT dramatically re-sensitized the cells, evidenced by a sharp reduction in IC50 values ( Fig. 7 B ) . This specific vulnerability was further corroborated by long-term functional assays, where the combination of enzalutamide and FKBP5 MUT —but not FKBP5 WT —markedly suppressed cell proliferation and virtually abolished clonogenic survival ( Fig. 7 C-E ) . To confirm that this restored drug sensitivity was driven by the reactivation of apoptotic pathways, we performed flow cytometry analysis. Consistent with the growth phenotypes, enzalutamide treatment failed to induce significant cell death in the FKBP5 WT -expressing cohorts. In striking contrast, cells harboring FKBP5 MUT exhibited a massive induction of apoptosis upon enzalutamide exposure ( Fig. 7 F-G ) . To decipher the ultimate downstream signaling network orchestrated by this uncoupled FKBP5, we examined the expression of critical survival kinases and apoptotic regulators under the shFKBP5 background. Mechanistically, FKBP5 is a well-established negative regulator of the AKT survival cascade; it functions as an essential scaffolding protein that recruits the phosphatase PHLPP to directly dephosphorylate AKT at Serine 473( 27 , 28 ). Although strong ectopic expression generated equivalent global protein levels, endogenous RPE possesses a high affinity for FKBP5 WT , continuously binding and targeting its active pool for ubiquitin-mediated turnover. This dynamic interference severely restricts the availability of free FKBP5 WT , preventing the stable formation of the functional phosphatase complex. Conversely, FKBP5 MUT evades RPE recognition and completely escapes this degradation machinery, remaining fully available to execute its function. As anticipated, only the expression of FKBP5 MUT combined with enzalutamide led to a profound and specific suppression of p-AKT (Ser473), while total AKT levels remained unchanged. This blockade of the AKT survival signal directly unleashed the intrinsic apoptotic cascade, characterized by the marked downregulation of the anti-apoptotic proteins p-BAD and BCL-xL, alongside the potent cleavage and activation of Caspase-3 and PARP ( Fig. 7 H ) . Collectively, these results definitively illustrate that the physical interaction between RPE and FKBP5 is indispensable for enzalutamide resistance. By dynamically binding and destroying the FKBP5-PHLPP phosphatase complex, RPE relieves the brake on AKT signaling, thereby granting CRPC cells an aggressive survival advantage under antiandrogen therapy. Clinical significance of RPE and PSMA-targeted LNP-mediated RPE silencing in overcoming enzalutamide resistance in vivo To assess the clinical relevance of our mechanistic findings, we examined RPE protein expression in paired clinical prostate cancer specimens collected before enzalutamide treatment and after acquisition of enzalutamide resistance. Immunoblotting showed that RPE was upregulated in post-resistance tumors relative to their pretreatment counterparts (Fig. 8 A). This observation was further supported by IHC, which demonstrated a significantly higher H-score for RPE in post-resistance specimens (Fig. 8 B), supporting a clinical association between elevated RPE expression and acquired enzalutamide resistance. Motivated by these clinical observations, we explored the therapeutic potential of targeting RPE in vivo. To overcome the physiological barriers of systemic siRNA delivery, we engineered a prostate-specific membrane antigen (PSMA)-targeted Lipid nanoparticles (LNP) system encapsulating RPE siRNA (PSMA-LNPs-siRPE) ( Fig. 8 C ) . Nanoparticle characterization via dynamic light scattering (DLS) and TEM showed that the PSMA-LNPs possessed a uniform spherical morphology with an average diameter of ~ 148.5 nm and an optimal slightly positive zeta potential ( Fig. 8 D-E ) . To verify their targeting efficacy, we performed in vivo and ex vivo fluorescence imaging. Compared to non-targeted LNPs, the PSMA-functionalized LNPs exhibited remarkably enhanced tumor homing and specific accumulation in the C4-2 EnzaR xenografts, demonstrating excellent precision for prostate cancer delivery ( Fig. 8 F-G ) . We then tested the therapeutic efficacy of this nanoplatform in surgically castrated nude mice bearing C4-2 EnzaR xenografts. Neither oral enzalutamide alone nor systemic PSMA-LNPs-siRPE alone significantly suppressed tumor growth compared with vehicle-treated controls. In contrast, the combination of PSMA-LNPs-siRPE and enzalutamide markedly inhibited tumor progression, resulting in reduced final tumor volume and tumor weight (Fig. 8 H). Histologic examination of major organs (heart, liver, spleen, lung, and kidney) by H&E staining revealed no obvious pathologic abnormalities, tissue necrosis, or significant inflammatory infiltration in any treatment group ( Supplementary Fig. 6B ), supporting the in vivo tolerability of the PSMA-targeted nanoplatform. Together, these in vivo data are consistent with our in vitro findings and indicate that RPE functions specifically to protect CRPC cells from antiandrogen-induced stress rather than as a general determinant of basal tumor growth. Based on these comprehensive results, we present a mechanistic schematic ( Fig. 8 I ) : under androgen deprivation and enzalutamide treatment, CRPC cells exploit the non-enzymatic function of RPE to interact with and promote the degradation of FKBP5, thereby relieving inhibition of AKT signaling and sustaining an anti-apoptotic survival program. Discussion Our findings identify RPE, discovered through an in vivo CRISPR-Cas9 metabolic screen, as a critical driver of enzalutamide resistance in CRPC. Canonically, RPE functions as a key metabolic enzyme in the pentose phosphate pathway, catalyzing the reversible interconversion of ribulose-5-phosphate and xylulose-5-phosphate to support nucleotide biosynthesis and redox homeostasis( 12 , 22 , 29 ). However, by using a catalytically inactive mutant, we demonstrate that the resistance-promoting effect of RPE is uncoupled from its classical enzymatic activity. These findings suggest that, under potent antiandrogen pressure, CRPC cells may become increasingly dependent on the non-canonical functions of metabolic enzymes rather than solely on their metabolic outputs. Consistent with this concept, metabolic enzymes have been shown in other tumor contexts to exert moonlighting functions, including roles in transcriptional regulation and signal transduction, thereby promoting malignant progression( 20 , 21 , 30 ). Our data extend this emerging paradigm to CRPC and identify a previously unrecognized dependency on the non-enzymatic function of RPE under antiandrogen stress, highlighting a targetable vulnerability in enzalutamide-resistant disease. Emerging evidence has highlighted the non-enzymatic roles of metabolic enzymes in modulating oncogenic signaling beyond their canonical metabolic functions. For example, several glycolytic and tricarboxylic acid cycle enzymes have been shown to translocate to the nucleus or interact with key kinases, thereby sustaining survival signaling under stress( 20 , 30 , 31 ). In the present study, we show that RPE exerts a similar but previously unrecognized non-enzymatic function. In the cytoplasm, elevated RPE directly interacts with FKBP5 and promotes its ubiquitin-proteasome-mediated degradation. As a result, RPE-mediated loss of FKBP5 relieves its inhibitory effect on AKT signaling( 27 , 28 ), leading to increased AKT phosphorylation, enhanced BAD phosphorylation, and elevated BCL-xL expression( 32 , 33 ). These findings establish a direct link between a non-enzymatic metabolic protein function and apoptotic rewiring in CRPC cells. They also nominate disruption of the RPE-FKBP5 interaction as a potential therapeutic strategy for restoring apoptotic sensitivity in enzalutamide-resistant tumors. The inherently adaptive nature of CRPC poses a major challenge to the efficacy of standard antiandrogen therapies( 4 , 12 ). Accordingly, strategies aimed at targeting metabolic vulnerabilities or other non-oncogene dependencies have attracted increasing interest. However, clinical translation of these mechanistic insights is often limited by the lack of selective inhibitors and by the toxicity or poor tumor specificity of non-targeted genetic interventions( 34 – 36 ). These limitations have driven the development of precision delivery strategies designed to selectively target tumor cells and thereby improve therapeutic efficacy( 37 , 38 ). In this study, we developed a prostate-specific membrane antigen (PSMA)-targeted LNP platform to deliver siRNA against RPE. Notably, selective RPE silencing using PSMA-LNPs, when combined with oral enzalutamide, produced a substantially greater antitumor effect than standard therapy alone in vivo, without evident systemic toxicity. The broader mechanisms by which RPE exerts non-enzymatic functions to reshape adaptive signaling networks in CRPC remain to be defined. Addressing these questions may further clarify how repurposed metabolic enzymes contribute to drug resistance and may help inform the design of rational combination strategies. This study has several limitations. Although we show that RPE promotes FKBP5 ubiquitin-proteasome-mediated degradation, the specific E3 ligase involved remains undefined. In addition, the clinical cohort was relatively limited, and the biomarker value of RPE for predicting enzalutamide response requires validation in larger patient sets. Finally, although PSMA-LNP-mediated RPE silencing showed promising activity in vivo, its long-term safety and performance in more advanced metastatic settings warrant further investigation. In our models, RPE did not function as a major determinant of basal proliferation. Instead, its principal role was to sustain CRPC cell survival under enzalutamide pressure, consistent with a context-dependent resistance mechanism rather than a general growth-promoting effect, the role and associated underlying mechanisms of RPE as a structural scaffold in solid tumors have remained largely unexplored. In this study, we show that RPE reshapes the survival dependency of CRPC under therapeutic stress. These findings suggest that targeting RPE may offer a selective strategy to treat CRPC by disrupting a non-enzymatic mechanism on which resistant cells rely to suppress apoptosis. More specifically, interference with the RPE-FKBP5-AKT axis restores endogenous apoptotic control, as reflected by increased cleavage of Caspase-3 and PARP. Consistent with this model, targeted delivery of siRPE by PSMA-LNPs, in combination with enzalutamide, effectively disrupted this survival program and induced apoptosis in vivo. Together, the identification of this non-enzymatic resistance mechanism and the demonstration of a tumor-targeted delivery strategy support RPE as a promising therapeutic target for overcoming enzalutamide resistance in CRPC. Materials and Methods Cell lines and reagents The human prostate cancer cell lines LNCaP C4-2 and 22Rv1 were obtained from the American Type Culture Collection (ATCC). The enzalutamide-resistant C4-2 cell line (C4-2 EnzaR) was established by continuously culturing parental LNCaP C4-2 cells in medium containing gradually increasing concentrations of enzalutamide for 6 months until a stable resistant phenotype was achieved. LNCaP C4-2 and C4-2 EnzaR cells were cultured in a 1:1 mixture of DMEM and DMEM/F-12 (Gibco) supplemented with 10% heat-inactivated fetal bovine serum (FBS, Gibco) and 1% penicillin/streptomycin. 22Rv1 cells were maintained in RPMI-1640 medium (Gibco) supplemented with 10% FBS and 1% penicillin/streptomycin. All cell lines were cultured at 37°C in a humidified incubator with 5% CO2. All cell lines were routinely tested for Mycoplasma contamination and authenticated by short tandem repeat (STR) profiling. Enzalutamide (Enza; Selleck Chemicals, CAS No. 915087-33-1), the proteasome inhibitor MG132 (Sigma-Aldrich, M8699), the lysosome inhibitor chloroquine (MedChemExpress, HY-17589A), and the protein synthesis inhibitor cycloheximide (CHX; Sigma-Aldrich, C7698-1G) were purchased from the indicated suppliers. Clinical prostate cancer specimens Paired tumor tissues were obtained from patients with CRPC before enzalutamide treatment and after acquisition of enzalutamide resistance, with written informed consent from all patients. The study protocol was approved by the Institutional Ethics Committee of Sun Yat-sen Memorial Hospital, Sun Yat-sen University (Approval No. SYSKY-2025-878-01) and was conducted in strict accordance with the Declaration of Helsinki. In vivo pooled CRISPR-Cas9 metabolic screening A custom-constructed sgRNA library targeting 3,162 human metabolism-related genes (Human CRISPRko Library-Metabolism Plus, Catalog: SSLP039) was customized and synthesized by Yomebio Co., Ltd. (Wuhan, China). The library contains a total of 16,460 sgRNAs, including non-targeting controls, with 5 independent sgRNAs targeting each gene, cloned into the LentiCRISPRv2-Puro backbone. The complete list of sgRNA sequences and their corresponding target metabolic genes is provided in Supplementary Table S1 . For the in vivo screen, C4-2 cells were stably transduced with the sgRNA library at a low multiplicity of infection (MOI < 0.3) to ensure a single sgRNA integration per cell. Following puromycin selection, 1×10^7 library-transduced cells per mouse were resuspended in a 1:1 mixture of PBS and Matrigel (Corning) and subcutaneously injected into the flanks of surgically castrated BALB/c nude mice. Once tumors became palpable, mice were randomized to receive vehicle or enzalutamide (20 mg/kg, PO, q2d) for 4 weeks. Genomic DNA was extracted from the harvested tumors, and the integrated sgRNA cassettes were amplified via PCR. The pooled libraries were subjected to next-generation sequencing on an Illumina platform. Depleted and enriched genes were identified, and robust RRA scores were calculated using the MAGeCK computational framework ( Supplementary Table S2 ). Plasmids, RNA interference, and lentiviral transduction Pooled target-specific small interfering RNAs (siRNAs) against RPE (sc-94945) and GRIK1 (sc-42487), as well as pooled short hairpin RNA (shRNA) plasmids targeting RPE (sc-94945-SH), were purchased from Santa Cruz Biotechnology. Gene-specific siRNAs targeting NAA50, PGK1, OGDH, and FKBP5 were synthesized by IGE Biotechnology (Guangzhou, China). The detailed sequences or catalog numbers of all siRNAs and shRNAs are provided in Supplementary Table S3 . Transient siRNA transfections were performed using Lipofectamine RNAiMAX (Invitrogen, 13778150) according to the manufacturer's instructions. For stable gene depletion, shRNAs targeting FKBP5 were cloned into lentiviral vectors. To generate the catalytically inactive RPE mutant, a point mutation at Ser10 (S10A) was introduced into the wild-type RPE coding sequence using the Hieff Mut Site-Directed Mutagenesis Kit (Yeasen, 11003ES10). For interaction-mapping studies, wild-type FKBP5 and an RPE-binding-deficient FKBP5 mutant harboring alterations within the 331–342 aa region were generated by gene synthesis. All rescue constructs were engineered to carry synonymous mutations rendering them resistant to shRNA-mediated knockdown. Lentiviral particles were produced in HEK293T cells by co-transfection with psPAX2 and pMD2.G. Stable cell lines were established after lentiviral infection and antibiotic selection with puromycin (Beyotime, ST551) or hygromycin B (Beyotime, ST1389). RNA extraction and quantitative real-time PCR (RT-qPCR) Total RNA was extracted from cultured cells or tissues using TRIzol reagent (Invitrogen, 15596026) according to the manufacturer's instructions. RNA concentration and purity were assessed using a NanoDrop spectrophotometer. Equal amounts of total RNA (1 µg) were reverse-transcribed into complementary DNA (cDNA) using the cDNA Synthesis Kit (Yeasen, 11141ES60). Quantitative real-time PCR was then performed using the SYBR Green qPCR Master Mix (Yeasen, 11185ES08) on a LightCycler 480 Real-Time PCR System (Roche Diagnostics). Relative mRNA expression levels were calculated using the 2^-△△Ct method. β-actin was used as an endogenous control for normalization. All reactions were performed with three biological replicates. The primer sequences used in this study are listed in Supplementary Table S4 . Cell viability, colony formation, and apoptosis assays For cell viability assays, cells were seeded in 96-well plates and treated with the indicated concentrations of enzalutamide. Cell viability was measured using the Cell Counting Kit-8 (CCK-8; APExBIO, K1018) by measuring absorbance at 450 nm, and IC50 values were determined. For cell proliferation assays, CCK-8 absorbance was measured daily for 5 consecutive days. For colony formation assays, cells were seeded at low density (1,000 cells/well) in 6-well plates and cultured in the presence of vehicle (0.1% DMSO) or 20 µM enzalutamide for 14 days. Colonies were then fixed with 4% paraformaldehyde, stained with 0.1% crystal violet, and quantified. For apoptosis analysis, cells were stained with Annexin V-FITC and propidium iodide (PI) using an Annexin V-FITC/PI Apoptosis Detection Kit (Elabscience, E-CK-A211) according to the manufacturer's instructions and analyzed by flow cytometry. Metabolic profiling and RPE enzymatic activity assay Real-time OCR and ECAR were measured using a Seahorse XFe96 Analyzer (Agilent Technologies) with the XF Cell Mito Stress Test Kit (Agilent, 103015-100) and the XF Glycolysis Stress Test Kit (Agilent, 103020-100), respectively. Briefly, cells were sequentially treated with oligomycin, FCCP, and rotenone/antimycin A for OCR measurements, or glucose, oligomycin, and 2-deoxy-D-glucose (2-DG) for ECAR measurements, according to the manufacturer's instructions. OCR and ECAR values were normalized to cell number. The intracellular NADPH/NADP + ratio was determined using a colorimetric assay kit (Abcam, ab65349) according to the manufacturer's instructions. To assess intracellular RPE catalytic activity (EC 5.1.3.1), cell lysates were subjected to a coupled enzymatic assay using reagents purchased from Sigma-Aldrich. In this assay, the epimerization of Ru5P to Xu5P was coupled to downstream reactions resulting in NADH oxidation. Enzymatic activity was monitored continuously by measuring the decrease in absorbance at 340 nm using a microplate reader. Immunoprecipitation (IP) and LC-MS/MS analysis Cells expressing Flag-tagged RPE were lysed using an Immunoprecipitation Kit (Thermo Fisher Scientific, 26149) supplemented with protease inhibitors. Cell lysates were incubated with ANTI-FLAG M2 Magnetic Beads (Sigma-Aldrich, M8823-1ML) overnight at 4°C with gentle rotation. The immunoprecipitated proteins were resolved by SDS-PAGE and visualized using a Silver Staining Kit (Beyotime, P0017S). Specific protein bands were excised, subjected to in-gel tryptic digestion, and analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) at PTM Biolabs (Hangzhou, China). MS/MS spectra were searched against the human UniProt database to identify RPE-interacting proteins. In vitro GST pulldown assay Recombinant His-tagged RPE and GST-tagged FKBP5 proteins, including wild-type and truncation/deletion mutants, were expressed in Escherichia coli BL21(DE3) cells. His-tagged RPE was purified using Ni-NTA Agarose (Qiagen, 30210) according to the manufacturer’s protocol. Equal amounts of purified GST-FKBP5 fusion proteins or GST control protein were immobilized on Glutathione Sepharose 4B beads (Cytiva, 17075601). The bead-bound proteins were incubated with purified His-RPE at 4°C with gentle rotation. After extensive washing with binding buffer to remove non-specific interactions, the bound protein complexes were eluted by boiling in SDS sample buffer, resolved by SDS-PAGE, and analyzed by immunoblotting using anti-His (Cell Signaling Technology, 12698) and anti-GST (Cell Signaling Technology, 2624S) antibodies. Molecular docking and molecular dynamics (MD) simulation The initial RPE-FKBP5 complex conformation was predicted using the HDOCK server. A 100-ns all-atom molecular dynamics (MD) simulation was performed using GROMACS (version 2021) with the AMBER99SB-ILDN force field in an explicit TIP3P water model. After energy minimization, NVT equilibration, and NPT equilibration, a 100-ns production run was carried out. Trajectory analyses, including root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), radius of gyration (Rg), and intermolecular hydrogen bonds, were performed using built-in GROMACS tools. The free energy landscape (FEL) was constructed using the first two principal components (PC1 and PC2). 4.11.Western blotting, CHX chase, and Ubiquitination assays Total protein was extracted using RIPA lysis buffer (Beyotime, P0013B) supplemented with protease and phosphatase inhibitor cocktails. Western blotting was performed according to standard procedures. For CHX chase assays to evaluate protein half-life, cells were treated with 50 µg/mL CHX, and protein lysates were collected at 0, 4, 8, 12, and 16 h after treatment. For endogenous ubiquitination assays, cells were pretreated with the proteasome inhibitor MG132 (10 µM) for 6 h before harvest. Endogenous FKBP5 was immunoprecipitated from cell lysates, and its polyubiquitination status was assessed by immunoblotting with an anti-ubiquitin antibody. A list of primary antibodies used in this study is provided in Supplementary Table S5 . Preparation and characterization of PSMA-LNPs-siRPE Lipid nanoparticles (LNPs) encapsulating siRPE were prepared using a microfluidic mixing system (NanoAssemblr Ignite, Precision NanoSystems). Briefly, a lipid mixture containing the ionizable cationic lipid G0-C14, DSPC, cholesterol, and PEG-lipid at a molar ratio of 50:10:38.5:1.5 was dissolved in ethanol. For PSMA-targeted LNPs (PSMA-LNPs), 0.5 mol% PSMA ligand-conjugated PEG-lipid was incorporated into the lipid phase in place of an equivalent molar amount of unconjugated PEG-lipid. siRPE was dissolved in an acidic aqueous buffer (pH 4.0), and the aqueous and organic phases were rapidly mixed in a microfluidic cartridge to allow nanoparticle self-assembly. The resulting nanoparticles were dialyzed against PBS to remove residual ethanol and neutralize the formulation. Particle size and zeta potential were measured by dynamic light scattering (DLS; Malvern Zetasizer), and morphology was examined by transmission electron microscopy (TEM). In vivo animal models and imaging All animal experiments were approved by the Institutional Animal Care and Use Committee of Sun Yat-sen Memorial Hospital, Sun Yat-sen University (Approval No. AP20250191) and were performed in accordance with the institutional guidelines for the care and use of laboratory animals. To establish the cell line-derived xenograft (CDX) model, 4-week-old male BALB/c nude mice underwent bilateral surgical castration. One week later, C4-2 EnzaR cells (1×10 6 ) mixed with Matrigel (Corning) at a 1:1 volume ratio were subcutaneously inoculated into the flanks. For the patient-derived xenograft (PDX) model, clinical CRPC tissues were cut into small fragments (~ 2×2×2 mm) and implanted subcutaneously into castrated immunodeficient NCG mice. When tumor volumes reached approximately 50 mm³, mice were randomized into different treatment groups. Enzalutamide was administered orally (20 mg/kg, every 2 days). For targeted nanotherapy, PSMA-LNPs-siRPE were injected intravenously via the tail vein (1.0 mg/kg based on siRNA content, once every 3 days for 3 doses). For intratumoral injection in the PDX model, siRNAs were complexed with in vivo transfection reagents and injected directly into the tumors. Tumor length (L) and width (W) were measured twice a week using digital calipers, and tumor volume was calculated as (L×W ^ 2)/2. At the experimental endpoint, mice were euthanized, and tumors together with major vital organs were excised, weighed, and processed for histological analysis. For biodistribution and targeting analysis, mice bearing C4-2 EnzaR tumors were intravenously injected with Cy5.5-labeled LNPs or Cy5.5-labeled PSMA-LNPs. Whole-body fluorescence imaging was performed at 0, 6, and 12 h post-injection using an IVIS Spectrum In Vivo Imaging System. Ex vivo fluorescence imaging of excised tumors and major organs was then conducted. Histology, Immunohistochemistry (IHC), and Immunofluorescence (IF) Excised tissues were fixed in 4% paraformaldehyde, paraffin-embedded, and sectioned at 4 µM. Hematoxylin and eosin (H&E) staining was performed to evaluate tissue morphology and, where applicable, systemic toxicity. For IHC, tissue sections were subjected to antigen retrieval, blocking, and overnight incubation with primary antibodies at 4°C, followed by incubation with secondary antibodies and DAB development. Staining intensity and the percentage of positive cells were semi-quantitatively assessed using the H-score method. For dual IF staining of RPE and FKBP5, a sequential multiplex staining protocol was performed using a Tyramide Signal Amplification (TSA) Kit (Absin, abs50012). After incubation with the first primary antibody and TSA-based signal visualization, sections were subjected to microwave treatment for antibody stripping. The second primary antibody and a distinct fluorophore were then applied, followed by DAPI counterstaining. Statistical analysis All in vitro experiments were performed with at least three independent biological replicates, unless otherwise indicated. Statistical analyses were performed using GraphPad Prism (version 10.3). Data are presented as mean ± standard deviation (SD). Comparisons between two independent groups were analyzed using an unpaired two-tailed Student’s t-test. For comparisons among multiple groups involving a single independent variable, statistical significance was determined by one-way ANOVA followed by either Tukey’s multiple-comparisons test (for all pairwise comparisons) or Dunnett’s multiple-comparisons test. Tumor growth curves and real-time cell proliferation curves were analyzed using two-way repeated-measures ANOVA. A P value < 0.05 was considered statistically significant (*P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001; ns, not significant). Declarations Ethics approval This study was approved by the Institutional Ethics Committee of Sun Yat-sen Memorial Hospital, Sun Yat-sen University (Approval No. SYSKY-2025-878-01). All human prostate cancer samples were collected with written informed consent from all participants. All animal experiments were performed according to procedures approved by the Institutional Animal Care and Use Committee of Sun Yat-sen Memorial Hospital, Sun Yat-sen University (Approval No. AP20250191), in accordance with institutional and national guidelines for the care and use of laboratory animals. CRediT authorship contribution statement Jintao Hu : Writing – original draft, Methodology, Investigation, Funding acquisition, Data curation, Formal analysis. Cong Lai : Writing – original draft, Methodology, Investigation, Validation, Data curation. Yunfei Xiao : Writing – original draft, Methodology, Investigation, Visualization, Formal analysis. Zi Yan : Methodology, Investigation, Validation, Data curation. Yongmei Tan : Methodology, Resources, Investigation, Data curation. Junjie Wang : Methodology, Investigation, Validation. Jiangping Qiu : Resources, Methodology, Investigation. Kuiqing Li : Methodology, Investigation, Data curation. Hao Yu : Methodology, Investigation, Formal analysis. Xutao Chen : Software, Formal analysis, Visualization. Jinli Han : Methodology, Investigation, Validation. Xiaolin Cai : Resources, Methodology, Investigation. Tianlong Luo : Methodology, Investigation, Data curation. Chunnuan Deng : Methodology, Investigation, Validation. Rong Na : Writing – review & editing, Supervision, Project administration, Conceptualization. Wang He : Writing – review & editing, Supervision, Project administration, Conceptualization. Kewei Xu : Writing – review & editing, Supervision, Project administration, Funding acquisition, Conceptualization. Cheng Liu : Writing – review & editing, Supervision, Project administration, Funding acquisition, Conceptualization. Data availability statement The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements This work was supported by the Guangdong S&T Program (No. 2023B1111030006), National Natural Science Foundation of China (No. 82560599 and 82372766), Guangdong Province Medical Science and Technology Research Fund (No. A2022541 and A2020571), Guangdong Province Medical Research Fund (No. A2026054), Yixian Clinical Research Project 5010 (No. SYS-5010-202503), and Shenzhen Key Industry Research and Development Program (No. ZDCY20250901102503004). Generative AI and AI-assisted technologies were NOT used in the preparation of this work. References Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. 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Supplementary Files SupplementaryTableS5.xlsx Supplementary Table S5 SupplementaryTableS1.xlsx Supplementary Table S1 SupplementaryTableS2.xlsx Supplementary Table S2 SupplementaryTableS3.xlsx Supplementary Table S3 SupplementaryTableS4.xlsx Supplementary Table S4 SupplementaryFig.1.tif Supplementary Fig. 1 SupplementaryFig.2.tif Supplementary Fig. 2 SupplementaryFig.3.tif Supplementary Fig. 3 SupplementaryFig.4.tif Supplementary Fig. 4 SupplementaryFig.5.tif Supplementary Fig. 5 SupplementaryFig.6.tif Supplementary Fig. 6 Cite Share Download PDF Status: Under Review Version 1 posted Review # 1 received at journal 11 May, 2026 Reviewer # 1 agreed at journal 10 May, 2026 Reviewers invited by journal 05 May, 2026 Submission checks completed at journal 05 May, 2026 Editor assigned by journal 02 May, 2026 First submitted to journal 02 May, 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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He","email":"","orcid":"https://orcid.org/0000-0002-3765-3991","institution":"Sun Yat-Sen Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wang","middleName":"","lastName":"He","suffix":""},{"id":635139531,"identity":"8e95e808-64b7-4a88-a027-73e544f5aba2","order_by":17,"name":"Kewei Xu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Kewei","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2026-05-02 11:35:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9593389/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9593389/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109296763,"identity":"77ffa7ae-4f17-4061-b985-8e4c40080491","added_by":"auto","created_at":"2026-05-15 08:51:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":10002843,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIn vivo CRISPR screening identifies RPE as a key driver of enzalutamide resistance in castration-resistant prostate cancer.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA, \u003c/strong\u003eSchematic of the in vivometabolic CRISPR-Cas9 knockout screen. Surgically castrated BALB/c nude mice bearing subcutaneous C4-2xenografts transduced with a human metabolic sgRNA library were treated with vehicle or enzalutamide (20 mg/kg) for 4 weeks, followed by tumor collection and deep sequencing. \u003cstrong\u003eB\u003c/strong\u003e and \u003cstrong\u003eC,\u003c/strong\u003eDistribution of robust ranking aggregation (RRA) scores for negatively selected (\u003cstrong\u003eB\u003c/strong\u003e, depleted) and positively selected (\u003cstrong\u003eC\u003c/strong\u003e, enriched) metabolic genes in enzalutamide-treated tumors relative to vehicle-treated tumors. Top candidate genes are indicated. \u003cstrong\u003eD,\u003c/strong\u003e Volcano plot showing significantly depleted (blue) and enriched (red) metabolic genes identified in the in vivo CRISPR screen. RPE emerged as a top depleted candidate. \u003cstrong\u003eE\u003c/strong\u003e and \u003cstrong\u003eF, \u003c/strong\u003eCell viability assays in C4-2 EnzaR (\u003cstrong\u003eE\u003c/strong\u003e) and 22Rv1 (\u003cstrong\u003eF\u003c/strong\u003e) cells transfected with control siRNA (siCtrl) or siRNAs targeting the five top depleted candidate genes. Cells were treated with the indicated concentrations of enzalutamide for 72 h. Corresponding IC50 values are shown. \u003cstrong\u003eG\u003c/strong\u003e, Cell viability assays confirming the re-sensitization of C4-2 EnzaR and 22Rv1 cells to enzalutamide upon stable knockdown of RPE (shCtrl vs. shRPE). \u003cstrong\u003eH\u003c/strong\u003e and \u003cstrong\u003eI,\u003c/strong\u003eValidation of RPE knockdown efficiency at the mRNA (\u003cstrong\u003eH\u003c/strong\u003e) and protein (\u003cstrong\u003eI\u003c/strong\u003e) levels in the indicated cell lines. β-actin was used as the loading control. Statistical analysis in H was performed using a two-tailed Student unpaired t test. \u003cstrong\u003eJ, \u003c/strong\u003eCCK-8 proliferation assays of C4-2 EnzaR and 22Rv1 cells harboring shCtrl or shRPE treated with vehicle or enzalutamide over a 5-day period. Statistical analysis was performed using two-way ANOVA. \u003cstrong\u003eK \u003c/strong\u003eand \u003cstrong\u003eL, \u003c/strong\u003eRepresentative images (\u003cstrong\u003eK\u003c/strong\u003e) and quantification (\u003cstrong\u003eL\u003c/strong\u003e) of colony formation assays in the indicated cells treated with vehicle or enzalutamide for 14 days. Statistical analysis was performed using one-way ANOVA. For all quantitative data (\u003cstrong\u003eH\u003c/strong\u003e, \u003cstrong\u003eJ\u003c/strong\u003e, and \u003cstrong\u003eL\u003c/strong\u003e), data represent the mean ± SD; n = 3 biologically independent replicates. ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001; ns, not significant.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/dab9ba68ef5610c93aa648a5.png"},{"id":109296846,"identity":"3fec1445-990e-4bf4-ab43-c64245082438","added_by":"auto","created_at":"2026-05-15 08:51:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":9908286,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRPE knockdown sensitizes CRPC cells to enzalutamide-induced apoptosis and metabolic reprogramming.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e and \u003cstrong\u003eB,\u003c/strong\u003e Flow cytometry analysis of apoptosis in C4-2 EnzaR (\u003cstrong\u003eA\u003c/strong\u003e) and 22Rv1 (\u003cstrong\u003eB\u003c/strong\u003e) cells harboring shCtrl or shRPE. Cells were treated with vehicle or enzalutamide for the indicated duration, followed by Annexin V-FITC and propidium iodide (PI) staining. The right panels show the quantification of the total apoptosis rate. \u003cstrong\u003eC,\u003c/strong\u003e Western blot analysis of apoptosis-associated markers in C4-2 EnzaR and 22Rv1 cells across the indicated treatment groups. β-actin served as the loading control. Three independent replicates produced similar results. \u003cstrong\u003eD, \u003c/strong\u003eSchematic illustration of the canonical enzymatic role of RPE in the pentose phosphate pathway (PPP) and its relationship to glycolysis and the tricarboxylic acid (TCA) cycle. \u003cstrong\u003eE\u003c/strong\u003e and \u003cstrong\u003eF, \u003c/strong\u003eMetabolic characterization of C4-2 EnzaR (\u003cstrong\u003eE\u003c/strong\u003e) and 22Rv1 (\u003cstrong\u003eF\u003c/strong\u003e) cells. Real-time ECAR and OCR were continuously measured using a Seahorse XFe96 analyzer following sequential injections of the indicated metabolic modulators (Oligomycin, 2-DG, or FCCP, Rot/AA). The calculated glycolytic capacity and the intracellular NADPH/NADP\u003csup\u003e+\u003c/sup\u003e ratio for each treatment group are also presented. For all quantitative data (\u003cstrong\u003eA\u003c/strong\u003e, \u003cstrong\u003eB\u003c/strong\u003e, \u003cstrong\u003eE\u003c/strong\u003e, and \u003cstrong\u003eF\u003c/strong\u003e), statistical analysis was performed using one-way ANOVA. Data represent the mean ± SD; n = 3 biologically independent replicates. ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001; ns, not significant.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/ff4f92154c90d9b352d7edd4.png"},{"id":109296845,"identity":"e5c365ec-ad8b-4dfc-8ba7-6857a29c6b7b","added_by":"auto","created_at":"2026-05-15 08:51:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":27532834,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTargeting RPE overcomes enzalutamide resistance in CDX and PDX models.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e and \u003cstrong\u003eB,\u003c/strong\u003e Schematic illustrations of the experimental designs for the cell line-derived xenograft (CDX) (\u003cstrong\u003eA\u003c/strong\u003e) and patient-derived xenograft (PDX) (\u003cstrong\u003eB\u003c/strong\u003e) models. In the CDX model, surgically castrated nude mice were subcutaneously implanted with C4-2 EnzaR cells stably expressing shCtrl or shRPE, followed by treatment with vehicle or enzalutamide (20 mg/kg, every 2 days) for 4 weeks. In the PDX model, surgically castrated NCG mice bearing established CRPC tumors received intratumoral siCtrl or siRPE together with oral vehicle or enzalutamide, generating four treatment groups.. \u003cstrong\u003eC,\u003c/strong\u003e In vivo therapeutic efficacy in the CDX model. Representative images of excised tumors (left), tumor growth trajectories over 5 weeks (middle), and final tumor volume and weight analysis (right) across the indicated treatment groups (n = 6 mice per group). \u003cstrong\u003eD\u003c/strong\u003eand \u003cstrong\u003eE,\u003c/strong\u003e Representative hematoxylin and eosin (H\u0026amp;E) and immunohistochemistry (IHC) staining images (\u003cstrong\u003eD\u003c/strong\u003e) and corresponding H-score quantification (\u003cstrong\u003eE\u003c/strong\u003e) of RPE, AR, and downstream apoptosis-associated markers in the excised CDX tumor tissues. Scale bars, 100 μm. \u003cstrong\u003eF,\u003c/strong\u003eTherapeutic response in the CRPC PDX model. Left, representative images of excised tumors. Middle, tumor growth curves over 6 weeks. Right, final tumor volume and tumor weight in the indicated groups (n = 5 mice per group). For tumor growth curves (\u003cstrong\u003eC\u003c/strong\u003e and \u003cstrong\u003eF\u003c/strong\u003e, middle panels), statistical significance was determined using two-way repeated measures ANOVA. For all quantitative bar graphs (\u003cstrong\u003eC\u003c/strong\u003e, \u003cstrong\u003eE\u003c/strong\u003e, and \u003cstrong\u003eF\u003c/strong\u003e), statistical analysis was performed using two-way ANOVA followed by Tukey's multiple comparisons test. Data represent the mean ± SD. **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001; ns, not significant.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/cd672a1ba093accf039ce32b.png"},{"id":109296810,"identity":"5127d4fd-4d79-4917-ad1b-f535ad7ac944","added_by":"auto","created_at":"2026-05-15 08:51:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":10305122,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRPE confers enzalutamide resistance through a non-enzymatic mechanism independent of its canonical catalytic activity.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA,\u003c/strong\u003e Schematic diagram of the coupled enzymatic assay utilized to determine intracellular RPE catalytic activity by continuously monitoring the oxidation of NADH at an absorbance of 340 nm. \u003cstrong\u003eB,\u003c/strong\u003e Relative enzymatic activity of wild-type RPE (RPE\u003csup\u003eWT\u003c/sup\u003e) and the catalytically dead mutant RPE\u003csup\u003eS10A\u003c/sup\u003e transiently expressed in C4-2 EnzaR and 22Rv1 cells. Statistical significance was determined using a two-tailed Student unpaired t test. \u003cstrong\u003eC,\u003c/strong\u003e RPE enzymatic activity in endogenous RPE-depleted CRPC cells (shRPE) reconstituted with empty vector, RPE\u003csup\u003eWT\u003c/sup\u003e\u003csub\u003erescue\u003c/sub\u003e, or RPE\u003csup\u003eS10A\u003c/sup\u003e\u003csub\u003erescue\u003c/sub\u003e. \u003cstrong\u003eD,\u003c/strong\u003e Cell viability curves and corresponding IC50 values of the indicated genetically modified cell lines treated with varying concentrations of enzalutamide for 72 hours. \u003cstrong\u003eE,\u003c/strong\u003e CCK-8 proliferation trajectories of the indicated cells continuously exposed to 20 μM enzalutamide over a 5-day period. Statistical significance for the growth curves was determined using two-way repeated measures ANOVA. \u003cstrong\u003eF\u003c/strong\u003e and \u003cstrong\u003eG,\u003c/strong\u003e Representative images (\u003cstrong\u003eF\u003c/strong\u003e) and quantification (\u003cstrong\u003eG\u003c/strong\u003e) of colony formation assays for the indicated cell lines cultured in the presence of 20 μM enzalutamide for 14 days. \u003cstrong\u003eH\u003c/strong\u003e and \u003cstrong\u003eI,\u003c/strong\u003e Flow cytometric analysis of apoptosis in the indicated C4-2 EnzaR (\u003cstrong\u003eH\u003c/strong\u003e) and 22Rv1 (\u003cstrong\u003eI\u003c/strong\u003e) rescue cell lines treated with 20 μM enzalutamide. Cells were stained with Annexin V-FITC and propidium iodide (PI). Right, quantification of total apoptotic cells. For all quantitative bar graphs with multiple groups (\u003cstrong\u003eC\u003c/strong\u003e, \u003cstrong\u003eE\u003c/strong\u003e, \u003cstrong\u003eG\u003c/strong\u003e, \u003cstrong\u003eH\u003c/strong\u003e and \u003cstrong\u003eI\u003c/strong\u003e), statistical analysis was performed using one-way ANOVA followed by Tukey's multiple comparisons test. Data represent the mean ± SD; n = 3 biologically independent replicates. ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001; ns, not significant.\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/c2aa3bb78793cc0f8aeaa384.png"},{"id":109297308,"identity":"1d224d06-7a5f-4807-b8fd-35513fb7fc0e","added_by":"auto","created_at":"2026-05-15 08:55:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":29027814,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe non-enzymatic function of RPE modulates metabolism and tumor survival in vivo.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e and \u003cstrong\u003eB,\u003c/strong\u003e Metabolic characterization utilizing real-time ECAR (\u003cstrong\u003eA\u003c/strong\u003e) and OCR (\u003cstrong\u003eB\u003c/strong\u003e) in endogenous RPE-depleted C4-2 EnzaR and 22Rv1 cells reconstituted with empty vector, wild-type RPE (RPE\u003csup\u003eWT\u003c/sup\u003e\u003csub\u003erescue\u003c/sub\u003e), or the catalytically dead mutant (RPE\u003csup\u003eS10A\u003c/sup\u003e\u003csub\u003erescue\u003c/sub\u003e). All cells were maintained in the presence of 20 μM enzalutamide. \u003cstrong\u003eC\u003c/strong\u003e and \u003cstrong\u003eD,\u003c/strong\u003e Quantification of the glycolytic capacity (\u003cstrong\u003eC\u003c/strong\u003e) and intracellular NADPH/NADP\u003csup\u003e+\u003c/sup\u003e ratio (\u003cstrong\u003eD\u003c/strong\u003e). \u003cstrong\u003eE,\u003c/strong\u003e Western blot analysis of apoptosis-associated proteins in the indicated rescue cell lines treated with 20 μM enzalutamide. Both RPE\u003csup\u003eWT\u003c/sup\u003e and RPE\u003csup\u003eS10A\u003c/sup\u003e suppressed the pro-apoptotic signaling induced by RPE depletion. Flag-tag blotting confirmed successful and equal reconstitution. β-actin served as a loading control. \u003cstrong\u003eF\u003c/strong\u003e and \u003cstrong\u003eG,\u003c/strong\u003e In vivo tumor rescue experiments. Surgically castrated nude mice were subcutaneously injected with the indicated C4-2 EnzaR rescue cell lines and concurrently treated with oral enzalutamide (20 mg/kg, q2d) for 5 weeks. Representative images of excised tumors and final tumor weight measurements (\u003cstrong\u003eF\u003c/strong\u003e), alongside tumor growth trajectories and end-point tumor volumes (\u003cstrong\u003eG\u003c/strong\u003e), are shown (n = 6). \u003cstrong\u003eH,\u003c/strong\u003e Representative H\u0026amp;E and IHC staining for RPE, AR, and downstream apoptotic markers (p-BAD, BCL-xL, and Cleaved Caspase-3) in the corresponding xenograft tumor tissues. Scale bars, 100 μm. For tumor growth curves (\u003cstrong\u003eG\u003c/strong\u003e, left panel), statistical significance was determined using two-way repeated measures ANOVA. For all quantitative bar graphs (\u003cstrong\u003eC\u003c/strong\u003e, \u003cstrong\u003eD\u003c/strong\u003e, \u003cstrong\u003eF\u003c/strong\u003e, and \u003cstrong\u003eG\u003c/strong\u003e), statistical analysis was performed using one-way ANOVA followed by Tukey's multiple comparisons test. Data represent the mean ± SD. ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001; ns, not significant.\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/f183c6197f2885145ee27e27.png"},{"id":109296766,"identity":"04dac45e-d0ad-4dd0-9b2e-1f485eb38712","added_by":"auto","created_at":"2026-05-15 08:51:40","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":12858089,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRPE directly interacts with FKBP5 and prevents its ubiquitin-mediated degradation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e and \u003cstrong\u003eB,\u003c/strong\u003e Identification of RPE-interacting proteins. Silver staining of Flag-RPE immunoprecipitates from CRPC cells (\u003cstrong\u003eA\u003c/strong\u003e) and ranked plot of enriched proteins identified by LC-MS/MS (\u003cstrong\u003eB\u003c/strong\u003e). FKBP5 emerged as a prominent RPE-associated candidate. \u003cstrong\u003eC\u003c/strong\u003eand \u003cstrong\u003eD,\u003c/strong\u003e Representative double immunofluorescence (IF) images (\u003cstrong\u003eC\u003c/strong\u003e) and fluorescence intensity profiles (\u003cstrong\u003eD\u003c/strong\u003e) showing colocalization of RPE (green) and FKBP5 (red) predominantly in the cytoplasm. Nuclei were counterstained with DAPI (blue). Scale bar, 10 μm. \u003cstrong\u003eE,\u003c/strong\u003e Computational molecular docking model predicting the binding interface between RPE and FKBP5. Insets indicate the predicted intermolecular hydrogen-bonding residues. \u003cstrong\u003eF\u003c/strong\u003e and \u003cstrong\u003eG,\u003c/strong\u003eIn vitro GST pulldown assays using a series of FKBP5 truncation mutants (\u003cstrong\u003eF\u003c/strong\u003e) and internal deletion mutants (\u003cstrong\u003eG\u003c/strong\u003e) to map the RPE-binding region. The critical interaction region was localized to residues 331-342 aa of FKBP5. \u003cstrong\u003eH,\u003c/strong\u003eCo-immunoprecipitation assay confirming that the specific mutation of the identified binding motif (FKBP5-MUT 331-342aa) virtually abolishes its physical interaction with RPE. \u003cstrong\u003eI,\u003c/strong\u003e Immunoblot analysis evaluating endogenous FKBP5 protein abundance in C4-2 EnzaR and 22Rv1 cells following RPE knockdown or ectopic overexpression. \u003cstrong\u003eJ,\u003c/strong\u003e Cycloheximide (CHX) chase assays assessing the half-life of FKBP5 protein. Indicated cells were treated with the protein synthesis inhibitor CHX for 0, 4, 8, 12, or 16 hours. \u003cstrong\u003eK,\u003c/strong\u003e Western blot analysis of FKBP5 in shCtrl and shRPE cells treated with DMSO, the proteasome inhibitor MG132, or the lysosome inhibitor chloroquine, demonstrating a proteasome-dependent degradation mechanism. \u003cstrong\u003eL,\u003c/strong\u003e Ubiquitination assay assessing endogenous FKBP5 polyubiquitination. Cells were pretreated with MG132, followed by FKBP5 immunoprecipitation and immunoblotting with an anti-ubiquitin antibody. Data are representative of n = 3 biologically independent replicates.\u003c/p\u003e","description":"","filename":"Fig.6.png","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/f27bfe4cbf7e415d22142ab0.png"},{"id":109296803,"identity":"239db0b1-813b-48d5-9e85-f9743de1ca73","added_by":"auto","created_at":"2026-05-15 08:51:47","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":10906595,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDisruption of the RPE-FKBP5 interaction re-sensitizes CRPC cells to enzalutamide by suppressing AKT signaling.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e, Immunoblot validation of endogenous FKBP5 depletion and subsequent reconstitution with either wild-type FKBP5 (FKBP5\u003csup\u003eWT\u003c/sup\u003e) or the RPE-binding-deficient mutant (FKBP5\u003csup\u003eMUT\u003c/sup\u003e) in C4-2 EnzaR and 22Rv1 cells. \u003cstrong\u003eB\u003c/strong\u003e, Cell viability curves and corresponding IC50 values of the indicated reconstituted cells treated with increasing concentrations of enzalutamide for 72 hours. \u003cstrong\u003eC\u003c/strong\u003e, CCK-8 proliferation trajectories of the indicated rescue cell lines treated with vehicle or 20 μM enzalutamide over a 5-day period. \u003cstrong\u003eD\u003c/strong\u003e and \u003cstrong\u003eE\u003c/strong\u003e, Representative images (D) and quantification (E) of colony formation assays in the indicated cell lines treated with 20 μM enzalutamide for 14 days. \u003cstrong\u003eF\u003c/strong\u003e and \u003cstrong\u003eG\u003c/strong\u003e, Flow cytometric analysis of apoptosis in C4-2 EnzaR (\u003cstrong\u003eF\u003c/strong\u003e) and 22Rv1 (\u003cstrong\u003eG\u003c/strong\u003e) rescue cell lines across the indicated treatment groups. Cells were double-stained with Annexin V-FITC and PI. Quantitative bar graphs of the total apoptosis rates are shown on the right. \u003cstrong\u003eH\u003c/strong\u003e, Western blot analysis assessing the AKT signaling (AKT, p-AKT) and downstream apoptosis-associated markers in cells subjected to the indicated genetic modifications and pharmacological treatments. β-actin served as the loading control. For CCK-8 growth curves (\u003cstrong\u003eC\u003c/strong\u003e), statistical significance was determined using two-way repeated measures ANOVA. For all quantitative bar graphs (\u003cstrong\u003eE\u003c/strong\u003e, \u003cstrong\u003eF\u003c/strong\u003e, and \u003cstrong\u003eG\u003c/strong\u003e right panels), statistical analysis was performed using one-way ANOVA followed by Tukey's multiple comparisons test. Data represent the mean ± SD; n = 3 biologically independent replicates. ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001; ns, not significant. Representative immunoblots from 3 biologically independent experiments are shown.\u003c/p\u003e","description":"","filename":"Fig.7.png","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/b77ba72b77c4a2535c3e0af2.png"},{"id":109296804,"identity":"113f99b2-8f74-493a-b5af-8d9836dc0d0c","added_by":"auto","created_at":"2026-05-15 08:51:47","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":13497198,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClinical relevance of RPE and PSMA-targeted LNP delivery of siRPE to overcome enzalutamide resistance.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e and \u003cstrong\u003eB, \u003c/strong\u003eClinical validation of RPE upregulation. A, Western blot analysis of RPE protein levels in paired prostate cancer specimens collected before enzalutamide treatment (Pretreatment) and after acquisition of enzalutamide resistance (Post-resistance). B, Representative IHC images and H-score quantification of RPE expression in the same paired pretreatment and post-resistance specimens. Statistical significance was determined using a paired two-tailed Student’s t test. \u003cstrong\u003eC\u003c/strong\u003e, Schematic illustration of the in vivo nanotherapy strategy. C4-2 EnzaR xenograft-bearing mice were treated with systemic PSMA-targeted lipid nanoparticles encapsulating siRPE (PSMA-LNP-siRPE) by intravenous injection (every 3 days for 3 doses) in combination with oral enzalutamide. \u003cstrong\u003eD\u003c/strong\u003eand \u003cstrong\u003eE\u003c/strong\u003e, Physicochemical characterization of the nanocarriers. Size distribution and representative electron microscopy morphology (\u003cstrong\u003eD\u003c/strong\u003e, insets) alongside zeta potential measurements (\u003cstrong\u003eE\u003c/strong\u003e) for the untargeted LNPs and PSMA-LNPs. \u003cstrong\u003eF\u003c/strong\u003e, Ex vivo fluorescence imaging of major organs and excised tumors, demonstrating the enhanced and specific tumor accumulation of PSMA-LNPs compared to non-targeted LNPs. \u003cstrong\u003eG\u003c/strong\u003e, Real-time in vivo whole-body fluorescence imaging at 0, 6, and 12 hours post-injection, tracking the dynamic biodistribution and comparing the tumor-targeting efficacy between empty PSMA-LNPs and siRNA-loaded nanoparticles. \u003cstrong\u003eH\u003c/strong\u003e, In vivo therapeutic efficacy of the nanomedicine combination. Representative images of excised tumors, tumor growth curves over 5 weeks, and end-point tumor volume and weight measurements across the indicated treatment groups (n = 5). \u003cstrong\u003eI\u003c/strong\u003e, Schematic summary illustrating how RPE confers enzalutamide resistance. For tumor growth curves (\u003cstrong\u003eH\u003c/strong\u003e), statistical significance was determined using two-way repeated measures ANOVA. For quantitative bar graphs (\u003cstrong\u003eH\u003c/strong\u003e), statistical analysis was performed using one-way ANOVA followed by Tukey's multiple comparisons test. Data represent the mean ± SD unless otherwise noted. **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001; ns, not significant.\u003c/p\u003e","description":"","filename":"Fig.8.png","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/2389c796108b876bd21d5fd0.png"},{"id":109264373,"identity":"21ab425d-1b9f-4313-9e65-36cd537e6431","added_by":"auto","created_at":"2026-05-14 12:09:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":241148,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/b1b2c208-764d-4d3d-a317-65a4233b95ab.pdf"},{"id":109296843,"identity":"06465074-e0ce-47f5-aba3-f54fb6e5d586","added_by":"auto","created_at":"2026-05-15 08:51:59","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":11163,"visible":true,"origin":"","legend":"Supplementary Table S5","description":"","filename":"SupplementaryTableS5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/ca8d950e6aa8714a3314558d.xlsx"},{"id":109296832,"identity":"627ccc9d-8fc0-4c2c-bc23-ec766712bde9","added_by":"auto","created_at":"2026-05-15 08:51:53","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":565954,"visible":true,"origin":"","legend":"Supplementary Table S1","description":"","filename":"SupplementaryTableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/396b5ae588f4cc8fc190cec5.xlsx"},{"id":109296795,"identity":"2750464e-0bcf-473b-ba89-51c6a657b858","added_by":"auto","created_at":"2026-05-15 08:51:46","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":320022,"visible":true,"origin":"","legend":"Supplementary Table S2","description":"","filename":"SupplementaryTableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/434cccf93a45cf092ed5cd53.xlsx"},{"id":109297300,"identity":"89f02043-e9df-4ce7-b7a8-5291ae01d55f","added_by":"auto","created_at":"2026-05-15 08:55:51","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":10397,"visible":true,"origin":"","legend":"Supplementary Table S3","description":"","filename":"SupplementaryTableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/cf5abdaa8f3005f86975e2b6.xlsx"},{"id":109296702,"identity":"6b55d41a-29f6-4da9-aebc-9b06e33cd79b","added_by":"auto","created_at":"2026-05-15 08:51:11","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":10788,"visible":true,"origin":"","legend":"Supplementary Table S4","description":"","filename":"SupplementaryTableS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/0a4b4c2e1197c3f8c6352d2d.xlsx"},{"id":109296699,"identity":"5f0a9b11-3117-4e73-8df2-f38d2a325012","added_by":"auto","created_at":"2026-05-15 08:51:07","extension":"tif","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":370204,"visible":true,"origin":"","legend":"Supplementary Fig. 1","description":"","filename":"SupplementaryFig.1.tif","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/10318c5f5e1adb50ec5d899a.tif"},{"id":109296813,"identity":"e0febda3-f38f-4b6e-ac8d-b6cd988a4efd","added_by":"auto","created_at":"2026-05-15 08:51:49","extension":"tif","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":9774584,"visible":true,"origin":"","legend":"Supplementary Fig. 2","description":"","filename":"SupplementaryFig.2.tif","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/54ddb79912c72a1a3e255b70.tif"},{"id":109296840,"identity":"e4807554-f891-4efe-bf32-abcb4ca124df","added_by":"auto","created_at":"2026-05-15 08:51:59","extension":"tif","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":2825448,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Fig. 3\u003c/p\u003e","description":"","filename":"SupplementaryFig.3.tif","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/5f132094977a3ff6bb425b4b.tif"},{"id":109296703,"identity":"93a7e1a9-9d41-4829-b828-821b6e9c29b2","added_by":"auto","created_at":"2026-05-15 08:51:13","extension":"tif","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":809012,"visible":true,"origin":"","legend":"Supplementary Fig. 4","description":"","filename":"SupplementaryFig.4.tif","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/5efc83f120843b0b32fdfbd2.tif"},{"id":109296848,"identity":"ff021256-2d81-4441-b0ac-9b37e56a0279","added_by":"auto","created_at":"2026-05-15 08:51:59","extension":"tif","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":3721956,"visible":true,"origin":"","legend":"Supplementary Fig. 5","description":"","filename":"SupplementaryFig.5.tif","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/950b53f02d676084f540d668.tif"},{"id":109405606,"identity":"e7008ff7-c576-48b2-b8e3-bf98672cdd79","added_by":"auto","created_at":"2026-05-17 13:19:21","extension":"tif","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":9994432,"visible":true,"origin":"","legend":"Supplementary Fig. 6","description":"","filename":"SupplementaryFig.6.tif","url":"https://assets-eu.researchsquare.com/files/rs-9593389/v1/93c89903d0566f75d59aa31c.tif"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Metabolic CRISPR screening identifies RPE as a key regulator of acquired enzalutamide resistance through FKBP5 destabilization in prostate cancer.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eProstate cancer remains one of the leading causes of cancer-related mortality in men worldwide(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). While androgen deprivation therapy (ADT) is initially effective for advanced prostate cancer, the disease inevitably progresses to castration-resistant prostate cancer (CRPC)(\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). The development of next-generation androgen receptor (AR) pathway inhibitors, such as enzalutamide, has significantly improved outcomes for patients with CRPC(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). However, the clinical efficacy of these therapies is severely constrained by the rapid emergence of acquired resistance, leading to lethal disease progression(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Although several mechanisms, including AR amplification, structural rearrangements, and lineage plasticity, have been implicated in mediating antiandrogen resistance(\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), targeting these classical pathways has yielded limited clinical success. Consequently, uncovering actionable, non-canonical molecular dependencies that sustain enzalutamide resistance remains an urgent clinical imperative.\u003c/p\u003e \u003cp\u003eMetabolic reprogramming is a fundamental hallmark of CRPC, fueling the high proliferation rates and robust survival mechanisms required for cancer cells to adapt under the intense selective pressure of AR inhibition(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Recent efforts have highlighted the contribution of altered metabolic pathways\u0026mdash;such as enhanced glycolysis and lipid metabolism\u0026mdash;to the resistant phenotype(\u003cspan additionalcitationids=\"CR15 CR16 CR17\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). However, our understanding of the specific metabolic vulnerabilities that drive enzalutamide resistance remains limited, in part because of the lack of systematic in vivo functional interrogation. Furthermore, while metabolic enzymes are conventionally studied for their catalytic roles in biochemical pathways, an emerging paradigm suggests that many of these proteins possess non-canonical functions\u0026mdash;such as scaffolding protein complexes or regulating signal transduction\u0026mdash;that operate independently of their enzymatic activities(\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). How CRPC cells exploit these non-enzymatic functions of metabolic enzymes to evade therapeutic pressure remains largely unexplored.\u003c/p\u003e \u003cp\u003eTo address this gap in knowledge, we performed an in vivo CRISPR-Cas9 loss-of-function screen using a custom metabolism-focused library in an enzalutamide-treated xenograft model. This strategy was designed to identify critical metabolic genes whose loss sensitizes CRPC cells to enzalutamide in a physiologically relevant in vivo context. From this screen, we identified ribulose-5-phosphate 3-epimerase (RPE), an enzyme traditionally known for catalyzing the reversible epimerization of ribulose-5-phosphate to xylulose-5-phosphate in the pentose phosphate pathway (PPP)(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), as a top dependency required for the maintenance of enzalutamide resistance in CRPC.\u003c/p\u003e \u003cp\u003eIn this study, we demonstrate that RPE drives enzalutamide resistance not through its canonical enzymatic activity, but via a previously unrecognized non-enzymatic mechanism. Specifically, we found that RPE physically interacts with the co-chaperone protein FKBP5 and promotes its ubiquitin-proteasome-mediated degradation. Loss of FKBP5 subsequently hyperactivates the AKT survival signaling cascade, leading to increased p-BAD and BCL-xL levels and suppression of enzalutamide-induced apoptosis. Importantly, therapeutic intervention using a prostate-specific membrane antigen (PSMA)-targeted lipid nanoparticle (LNP) system to deliver RPE siRNA markedly re-sensitized resistant tumors to enzalutamide in vivo. Together, these findings reveal a mechanism by which CRPC cells exploit the non-enzymatic function of a metabolic enzyme to evade endocrine therapy, establishing the RPE-driven degradation of FKBP5 and consequent AKT hyperactivation as a targetable vulnerability for overcoming enzalutamide resistance.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMetabolic CRISPR screening identifies RPE as a driver of enzalutamide resistance\u003c/h2\u003e \u003cp\u003eTo systematically identify metabolic dependencies that sustain enzalutamide resistance in CRPC, we performed an in vivo pooled CRISPR-Cas9 loss-of-function screen. C4-2 cells transduced with a custom single guide RNA (sgRNA) library targeting human metabolic genes were subcutaneously implanted into surgically castrated immunodeficient mice. Following tumor establishment, mice were treated with vehicle or enzalutamide (20 mg/kg) for 4 weeks, and tumors were then collected for deep sequencing (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eComparison of sgRNA abundance between enzalutamide-treated and vehicle-treated tumors identified genes whose loss altered enzalutamide response, based on robust ranking aggregation (RRA) scoring. Negative and positive RRA score distributions revealed distinct sets of depleted and enriched genes, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB-C). In total, 66 genes were significantly depleted and 35 genes were enriched in enzalutamide-treated tumors. Among the top depleted metabolic candidates, RPE emerged as a prominent hit, suggesting that its loss compromises CRPC cell survival under enzalutamide treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003eTo validate the top hits from the screen, we selected the five most significantly depleted candidate genes (RPE, NAA50, PGK1, OGDH, and GRIK1) for individual siRNA-mediated knockdown in C4-2 EnzaR and 22Rv1 cells. RT-qPCR confirmed efficient silencing of each gene in both cell lines (\u003cb\u003eSupplementary Fig.\u0026nbsp;1A\u003c/b\u003e). Among these candidates, RPE depletion produced the strongest sensitizing effect, markedly reducing the enzalutamide IC50 in C4-2 EnzaR cells (from 47.29 \u0026micro;M to 14.86 \u0026micro;M) and 22Rv1 cells (from 35.83 \u0026micro;M to 17.51 \u0026micro;M) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE-F). We therefore prioritized RPE for further mechanistic studies.\u003c/p\u003e \u003cp\u003eTo confirm the role of RPE in sustaining enzalutamide resistance, we established stable shRPE cell lines. Efficient RPE depletion at both the mRNA and protein levels was accompanied by a marked reduction in enzalutamide IC50, consistent with the transient knockdown results (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG-I). Whereas RPE depletion alone had little effect on baseline proliferation, combining shRPE with enzalutamide markedly reduced cell viability over time (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ). Similarly, RPE knockdown alone did not impair clonogenic growth, but in the presence of enzalutamide it almost completely abolished colony formation in both CRPC cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eK-L). These findings indicate that RPE is specifically required for CRPC cells to tolerate enzalutamide-induced cytotoxic stress.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRPE deficiency sensitizes CRPC cells to enzalutamide-induced apoptosis\u003c/h3\u003e\n\u003cp\u003eInduction of apoptosis is a major mechanism by which enzalutamide suppresses prostate cancer cell growth; accordingly, resistance to enzalutamide-induced apoptosis represents an important basis of acquired enzalutamide resistance(\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Because RPE knockdown selectively abolished the clonogenic survival of enzalutamide-treated cells, we hypothesized that RPE depletion restores sensitivity to enzalutamide by reinstating apoptotic cell death. To test this, we performed Annexin V/PI flow cytometry in both C4-2 EnzaR and 22Rv1 cells. Neither enzalutamide treatment nor RPE depletion alone induced substantial cell death. In contrast, the combination of shRPE and enzalutamide produced a marked increase in apoptosis in both resistant cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-B). To investigate the underlying mechanism, we examined key apoptosis-related proteins by immunoblotting. Consistent with the flow cytometry results, combined RPE depletion and enzalutamide treatment markedly increased the levels of cleaved PARP and cleaved Caspase-3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). At the same time, this combination suppressed survival signaling, as reflected by reduced BCL-xL expression and loss of p-BAD.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBecause RPE is a canonical enzyme in the non-oxidative branch of the pentose phosphate pathway (PPP), catalyzing the reversible interconversion of ribulose-5-phosphate (Ru5P) and xylulose-5-phosphate (Xu5P) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD), we next assessed the metabolic consequences of its loss. Seahorse extracellular flux analysis showed that RPE depletion reduced both extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) in C4-2 EnzaR (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE) and 22Rv1 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). In addition, RPE deficiency decreased the intracellular NADPH/NADP\u003csup\u003e+\u003c/sup\u003e ratio. These metabolic changes were primarily attributable to RPE loss and were not substantially intensified by enzalutamide treatment. Importantly, although RPE knockdown measurably altered cellular bioenergetics, these changes alone were insufficient to induce overt cell death. This dissociation between the metabolic phenotype caused by RPE loss alone and the pronounced apoptosis observed only with combined enzalutamide treatment suggested that RPE may protect CRPC cells through mechanisms beyond its canonical metabolic function. We therefore next investigated whether apoptotic sensitization to enzalutamide depends strictly on the enzymatic activity of RPE.\u003c/p\u003e\n\u003ch3\u003eRPE depletion overcomes enzalutamide resistance in preclinical in vivo models\u003c/h3\u003e\n\u003cp\u003eTo determine whether the apoptotic sensitization observed in vitro could be translated in vivo, we evaluated the therapeutic impact of targeting RPE in two independent preclinical models: a CDX model established from C4-2 EnzaR cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA) and a PDX model derived from a patient with clinically confirmed enzalutamide-resistant CRPC (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). In the CDX model, consistent with the refractory nature of these cells, enzalutamide monotherapy failed to suppress tumor growth. Likewise, RPE knockdown alone did not significantly inhibit tumor progression. In contrast, the combination of RPE depletion and enzalutamide markedly suppressed tumor growth, resulting in substantially reduced final tumor volumes and weights (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo determine whether this antitumor effect was associated with the mechanisms identified in vitro, we performed Immunohistochemistry (IHC) analysis on excised CDX tumors. Staining confirmed sustained RPE knockdown in the corresponding groups. Notably, AR expression remained largely unchanged across groups, suggesting that RPE depletion does not restore enzalutamide sensitivity by reducing AR expression. Instead, quantitative IHC (H-score) analysis showed that tumors from the combination treatment group (shRPE\u0026thinsp;+\u0026thinsp;Enza) displayed increased apoptosis, as indicated by elevated Cleaved Caspase-3, together with reduced p-BAD and BCL-xL expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD-E).\u003c/p\u003e \u003cp\u003eThe therapeutic response in the PDX model closely recapitulated the findings in the CDX model. Whereas patient-derived tumors remained resistant to enzalutamide monotherapy and were minimally affected by RPE knockdown alone, the combination of enzalutamide with RPE depletion markedly suppressed tumor growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). Histologic analysis of PDX tissues further supported activation of the apoptotic program predominantly in the combination treatment group (\u003cb\u003eSupplementary Fig.\u0026nbsp;2A-B\u003c/b\u003e). Together, these data identify RPE as a critical dependency in enzalutamide-resistant CRPC and support its targeting as a strategy to restore sensitivity to enzalutamide in vivo.\u003c/p\u003e\n\u003ch3\u003eRPE drives enzalutamide resistance through an enzyme-independent mechanism\u003c/h3\u003e\n\u003cp\u003eGiven the apparent dissociation between the metabolic alterations induced by RPE loss and the apoptotic phenotype observed under enzalutamide treatment, we hypothesized that RPE protects CRPC cells through a non-canonical, enzyme-independent mechanism. To test this, we generated a catalytically inactive mutant by introducing a point mutation at the highly conserved Ser10 residue (S10A). Previous biochemical and structural studies have shown that the S10A substitution abolishes the catalytic conversion of Ru5P to Xu5P while preserving the overall protein structure of RPE(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). To confirm loss of enzymatic function, we used a coupled biochemical assay in which RPE activity was assessed indirectly through downstream NADH oxidation, monitored as a decrease in absorbance at 340 nm (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Using this assay, we confirmed that RPE\u003csup\u003eS10A\u003c/sup\u003e lacked catalytic activity relative to RPEWT (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). We then reintroduced either shRNA-resistant RPE\u003csup\u003eWT\u003c/sup\u003e or RPE\u003csup\u003eS10A\u003c/sup\u003e into endogenous RPE-depleted C4-2 EnzaR and 22Rv1 cells. Both constructs were engineered with synonymous mutations rendering them resistant to shRPE. As expected, RPE\u003csup\u003eWT\u003c/sup\u003e restored intracellular enzymatic activity, whereas RPE\u003csup\u003eS10A\u003c/sup\u003e failed to rescue this metabolic function (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe next subjected these rescue cell lines to phenotypic analysis. Under vehicle treatment, neither RPE depletion nor ectopic expression of RPE\u003csup\u003eWT\u003c/sup\u003e or RPE\u003csup\u003eS10A\u003c/sup\u003e significantly altered baseline proliferation or clonogenic growth (\u003cb\u003eSupplementary Fig.\u0026nbsp;3A-C\u003c/b\u003e). In contrast, under enzalutamide treatment, the catalytically inactive RPE\u003csup\u003eS10A\u003c/sup\u003e mutant restored the IC50 and rescued long-term cell viability to a similar extent as RPE\u003csup\u003eWT\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD-E). This rescue was further supported by colony formation assays, in which RPE\u003csup\u003eS10A\u003c/sup\u003e restored clonogenic survival in enzalutamide-treated CRPC cells despite endogenous RPE depletion (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF-G).\u003c/p\u003e \u003cp\u003eTo determine whether this enzyme-independent rescue also extended to apoptosis, we examined apoptotic responses in these cells. Consistent with the viability data, expression of either RPE\u003csup\u003eWT\u003c/sup\u003e or RPE\u003csup\u003eS10A\u003c/sup\u003e markedly suppressed the apoptosis induced by combined shRPE and enzalutamide treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH-I). Together, these rescue experiments demonstrate that the canonical enzymatic activity of RPE is dispensable for supporting CRPC cell survival under AR blockade. Instead, RPE promotes enzalutamide resistance and suppresses apoptosis through a previously unrecognized non-enzymatic function.\u003c/p\u003e \u003cp\u003eTo further determine whether the apoptotic rescue mediated by the S10A mutant occurs independently of metabolic restoration, we profiled the bioenergetic state of the RPE rescue cell lines under enzalutamide treatment. Re-expression of RPE\u003csup\u003eWT\u003c/sup\u003e reversed the metabolic defects caused by endogenous RPE depletion. In contrast, cells expressing the catalytically inactive RPE\u003csup\u003eS10A\u003c/sup\u003e mutant remained metabolically impaired, with persistently reduced ECAR, OCR, and intracellular NADPH/NADP⁺ ratio (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-D). Despite this sustained metabolic deficiency, immunoblot analysis showed that both RPE\u003csup\u003eWT\u003c/sup\u003e and RPE\u003csup\u003eS10A\u003c/sup\u003e suppressed enzalutamide-induced apoptosis, as indicated by reduced PARP and Caspase-3 cleavage together with maintained p-BAD and BCL-xL expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe next asked whether this enzyme-independent survival mechanism also governs enzalutamide resistance in vivo. To this end, we established xenografts using C4-2 EnzaR rescue cell lines and treated the mice continuously with enzalutamide. Whereas tumors carrying the empty vector (shRPE\u0026thinsp;+\u0026thinsp;Vector) remained sensitive to AR blockade, ectopic expression of RPE\u003csup\u003eWT\u003c/sup\u003e restored tumor growth. Notably, RPE\u003csup\u003eS10A\u003c/sup\u003e closely recapitulated the effect of RPE\u003csup\u003eWT\u003c/sup\u003e, restoring final tumor volumes and weights to comparable levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF-G). Histologic analysis of excised tumors further supported these findings. IHC demonstrated that both wild-type and catalytically inactive RPE restored survival signaling in vivo, as evidenced by increased p-BAD and BCL-xL expression together with reduced Cleaved Caspase-3, without altering baseline AR expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH and \u003cb\u003eSupplementary Fig.\u0026nbsp;4\u003c/b\u003e). Together, these molecular and in vivo data indicate that RPE promotes enzalutamide resistance and tumor progression through a non-enzymatic mechanism.\u003c/p\u003e\n\u003ch3\u003eRPE interacts with FKBP5 and promotes its proteasome-mediated degradation\u003c/h3\u003e\n\u003cp\u003eTo identify downstream effectors mediating the non-enzymatic function of RPE, we sought to define its interacting partners. Flag-tagged RPE was immunoprecipitated from CRPC cells and subjected to silver staining followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Analysis of the enriched proteins and peptide spectra identified the immunophilin FKBP5 as one of the most prominent RPE-associated candidates (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB and \u003cb\u003eSupplementary Fig.\u0026nbsp;5A-B\u003c/b\u003e). To validate this interaction in cells, we performed immunofluorescence (IF) staining, which showed substantial spatial colocalization of RPE and FKBP5, predominantly in the cytoplasm (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC-D).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo define the structural basis of this interaction, we performed computational molecular docking, which predicted a binding interface between RPE and the C-terminal region of FKBP5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). We then carried out a 100-ns molecular dynamics (MD) simulation to evaluate the stability of the predicted complex. Analyses of RMSD, SASA, RMSF, Rg, intermolecular hydrogen bonding, and the free energy landscape (FEL) supported a stable RPE-FKBP5 complex in solution (\u003cb\u003eSupplementary Fig.\u0026nbsp;5C-H\u003c/b\u003e). To experimentally map the interaction region, we performed in vitro GST pulldown assays using a series of FKBP5 truncation mutants. Initial mapping localized the RPE-binding region to the C-terminal segment spanning amino acids 320\u0026ndash;420 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). Further fine mapping using internal deletion mutants identified residues 331\u0026ndash;342 as critical for the interaction (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG). Consistent with this result, co-immunoprecipitation assays showed that mutation of this region (FKBP5-MUT) largely abolished binding to RPE, further supporting the requirement of this sequence for complex formation (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003eWe next examined the functional consequence of the RPE-FKBP5 interaction. Western blot analysis showed that RPE depletion increased endogenous FKBP5 protein levels, whereas ectopic expression of RPE reduced FKBP5 abundance (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI). In contrast, qRT-PCR analysis revealed that neither knockdown nor overexpression of RPE, with or without enzalutamide treatment, altered FKBP5 or AR mRNA levels (\u003cb\u003eSupplementary Fig.\u0026nbsp;6A\u003c/b\u003e), arguing against transcriptional regulation and supporting a post-translational mechanism. Consistent with this, cycloheximide (CHX) chase assays showed that RPE depletion markedly prolonged the half-life of FKBP5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eJ). To determine the degradation pathway involved, cells were treated with either the proteasome inhibitor MG132 or the lysosome inhibitor chloroquine. MG132 abolished the difference in FKBP5 protein levels between shCtrl and shRPE cells, indicating proteasome-dependent turnover (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eK). In parallel, ubiquitination assays showed that loss of RPE reduced FKBP5 polyubiquitination (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eL). Together, these data indicate that RPE physically interacts with FKBP5 and promotes its ubiquitin-proteasome-mediated degradation, thereby reducing FKBP5 protein stability.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDisruption of the RPE-FKBP5 interaction re-sensitizes CRPC cells to enzalutamide by suppressing AKT signaling\u003c/h2\u003e \u003cp\u003eHaving established that RPE interacts with FKBP5 and promotes its degradation, we next asked whether disrupting this interaction could restore sensitivity to enzalutamide. To minimize interference from endogenous FKBP5, we used a knockdown-rescue strategy in C4-2 EnzaR and 22Rv1 cells. Endogenous FKBP5 was first depleted using stable shFKBP5, followed by re-expression of either wild-type FKBP5 (FKBP5\u003csup\u003eWT\u003c/sup\u003e) or an RPE-binding-deficient mutant (FKBP5\u003csup\u003eMUT\u003c/sup\u003e) harboring mutations within residues 331\u0026ndash;342. Western blot analysis confirmed comparable steady-state expression of FKBP5\u003csup\u003eWT\u003c/sup\u003e and FKBP5\u003csup\u003eMUT\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe hypothesized that FKBP5\u003csup\u003eMUT\u003c/sup\u003e, by evading RPE-mediated recognition and subsequent proteasomal degradation, would persistently exert its downstream tumor-suppressive functions. Indeed, cell viability assays demonstrated that while cells expressing FKBP5\u003csup\u003eWT\u003c/sup\u003e remained highly refractory to enzalutamide, the introduction of the interaction-defective FKBP5\u003csup\u003eMUT\u003c/sup\u003e dramatically re-sensitized the cells, evidenced by a sharp reduction in IC50 values \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. This specific vulnerability was further corroborated by long-term functional assays, where the combination of enzalutamide and FKBP5\u003csup\u003eMUT\u003c/sup\u003e\u0026mdash;but not FKBP5\u003csup\u003eWT\u003c/sup\u003e\u0026mdash;markedly suppressed cell proliferation and virtually abolished clonogenic survival \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC-E\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eTo confirm that this restored drug sensitivity was driven by the reactivation of apoptotic pathways, we performed flow cytometry analysis. Consistent with the growth phenotypes, enzalutamide treatment failed to induce significant cell death in the FKBP5\u003csup\u003eWT\u003c/sup\u003e-expressing cohorts. In striking contrast, cells harboring FKBP5\u003csup\u003eMUT\u003c/sup\u003e exhibited a massive induction of apoptosis upon enzalutamide exposure \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF-G\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eTo decipher the ultimate downstream signaling network orchestrated by this uncoupled FKBP5, we examined the expression of critical survival kinases and apoptotic regulators under the shFKBP5 background. Mechanistically, FKBP5 is a well-established negative regulator of the AKT survival cascade; it functions as an essential scaffolding protein that recruits the phosphatase PHLPP to directly dephosphorylate AKT at Serine 473(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Although strong ectopic expression generated equivalent global protein levels, endogenous RPE possesses a high affinity for FKBP5\u003csup\u003eWT\u003c/sup\u003e, continuously binding and targeting its active pool for ubiquitin-mediated turnover. This dynamic interference severely restricts the availability of free FKBP5\u003csup\u003eWT\u003c/sup\u003e, preventing the stable formation of the functional phosphatase complex. Conversely, FKBP5\u003csup\u003eMUT\u003c/sup\u003e evades RPE recognition and completely escapes this degradation machinery, remaining fully available to execute its function. As anticipated, only the expression of FKBP5\u003csup\u003eMUT\u003c/sup\u003e combined with enzalutamide led to a profound and specific suppression of p-AKT (Ser473), while total AKT levels remained unchanged. This blockade of the AKT survival signal directly unleashed the intrinsic apoptotic cascade, characterized by the marked downregulation of the anti-apoptotic proteins p-BAD and BCL-xL, alongside the potent cleavage and activation of Caspase-3 and PARP \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eH\u003cb\u003e)\u003c/b\u003e. Collectively, these results definitively illustrate that the physical interaction between RPE and FKBP5 is indispensable for enzalutamide resistance. By dynamically binding and destroying the FKBP5-PHLPP phosphatase complex, RPE relieves the brake on AKT signaling, thereby granting CRPC cells an aggressive survival advantage under antiandrogen therapy.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eClinical significance of RPE and PSMA-targeted LNP-mediated RPE silencing in overcoming enzalutamide resistance in vivo\u003c/h3\u003e\n\u003cp\u003eTo assess the clinical relevance of our mechanistic findings, we examined RPE protein expression in paired clinical prostate cancer specimens collected before enzalutamide treatment and after acquisition of enzalutamide resistance. Immunoblotting showed that RPE was upregulated in post-resistance tumors relative to their pretreatment counterparts (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA). This observation was further supported by IHC, which demonstrated a significantly higher H-score for RPE in post-resistance specimens (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB), supporting a clinical association between elevated RPE expression and acquired enzalutamide resistance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMotivated by these clinical observations, we explored the therapeutic potential of targeting RPE in vivo. To overcome the physiological barriers of systemic siRNA delivery, we engineered a prostate-specific membrane antigen (PSMA)-targeted Lipid nanoparticles (LNP) system encapsulating RPE siRNA (PSMA-LNPs-siRPE) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. Nanoparticle characterization via dynamic light scattering (DLS) and TEM showed that the PSMA-LNPs possessed a uniform spherical morphology with an average diameter of ~\u0026thinsp;148.5 nm and an optimal slightly positive zeta potential \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eD-E\u003cb\u003e)\u003c/b\u003e. To verify their targeting efficacy, we performed in vivo and ex vivo fluorescence imaging. Compared to non-targeted LNPs, the PSMA-functionalized LNPs exhibited remarkably enhanced tumor homing and specific accumulation in the C4-2 EnzaR xenografts, demonstrating excellent precision for prostate cancer delivery \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eF-G\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eWe then tested the therapeutic efficacy of this nanoplatform in surgically castrated nude mice bearing C4-2 EnzaR xenografts. Neither oral enzalutamide alone nor systemic PSMA-LNPs-siRPE alone significantly suppressed tumor growth compared with vehicle-treated controls. In contrast, the combination of PSMA-LNPs-siRPE and enzalutamide markedly inhibited tumor progression, resulting in reduced final tumor volume and tumor weight (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eH). Histologic examination of major organs (heart, liver, spleen, lung, and kidney) by H\u0026amp;E staining revealed no obvious pathologic abnormalities, tissue necrosis, or significant inflammatory infiltration in any treatment group (\u003cb\u003eSupplementary Fig.\u0026nbsp;6B\u003c/b\u003e), supporting the in vivo tolerability of the PSMA-targeted nanoplatform. Together, these in vivo data are consistent with our in vitro findings and indicate that RPE functions specifically to protect CRPC cells from antiandrogen-induced stress rather than as a general determinant of basal tumor growth.\u003c/p\u003e \u003cp\u003eBased on these comprehensive results, we present a mechanistic schematic \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eI\u003cb\u003e)\u003c/b\u003e: under androgen deprivation and enzalutamide treatment, CRPC cells exploit the non-enzymatic function of RPE to interact with and promote the degradation of FKBP5, thereby relieving inhibition of AKT signaling and sustaining an anti-apoptotic survival program.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings identify RPE, discovered through an in vivo CRISPR-Cas9 metabolic screen, as a critical driver of enzalutamide resistance in CRPC. Canonically, RPE functions as a key metabolic enzyme in the pentose phosphate pathway, catalyzing the reversible interconversion of ribulose-5-phosphate and xylulose-5-phosphate to support nucleotide biosynthesis and redox homeostasis(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). However, by using a catalytically inactive mutant, we demonstrate that the resistance-promoting effect of RPE is uncoupled from its classical enzymatic activity. These findings suggest that, under potent antiandrogen pressure, CRPC cells may become increasingly dependent on the non-canonical functions of metabolic enzymes rather than solely on their metabolic outputs. Consistent with this concept, metabolic enzymes have been shown in other tumor contexts to exert moonlighting functions, including roles in transcriptional regulation and signal transduction, thereby promoting malignant progression(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Our data extend this emerging paradigm to CRPC and identify a previously unrecognized dependency on the non-enzymatic function of RPE under antiandrogen stress, highlighting a targetable vulnerability in enzalutamide-resistant disease.\u003c/p\u003e \u003cp\u003eEmerging evidence has highlighted the non-enzymatic roles of metabolic enzymes in modulating oncogenic signaling beyond their canonical metabolic functions. For example, several glycolytic and tricarboxylic acid cycle enzymes have been shown to translocate to the nucleus or interact with key kinases, thereby sustaining survival signaling under stress(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). In the present study, we show that RPE exerts a similar but previously unrecognized non-enzymatic function. In the cytoplasm, elevated RPE directly interacts with FKBP5 and promotes its ubiquitin-proteasome-mediated degradation. As a result, RPE-mediated loss of FKBP5 relieves its inhibitory effect on AKT signaling(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), leading to increased AKT phosphorylation, enhanced BAD phosphorylation, and elevated BCL-xL expression(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). These findings establish a direct link between a non-enzymatic metabolic protein function and apoptotic rewiring in CRPC cells. They also nominate disruption of the RPE-FKBP5 interaction as a potential therapeutic strategy for restoring apoptotic sensitivity in enzalutamide-resistant tumors.\u003c/p\u003e \u003cp\u003eThe inherently adaptive nature of CRPC poses a major challenge to the efficacy of standard antiandrogen therapies(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Accordingly, strategies aimed at targeting metabolic vulnerabilities or other non-oncogene dependencies have attracted increasing interest. However, clinical translation of these mechanistic insights is often limited by the lack of selective inhibitors and by the toxicity or poor tumor specificity of non-targeted genetic interventions(\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). These limitations have driven the development of precision delivery strategies designed to selectively target tumor cells and thereby improve therapeutic efficacy(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). In this study, we developed a prostate-specific membrane antigen (PSMA)-targeted LNP platform to deliver siRNA against RPE. Notably, selective RPE silencing using PSMA-LNPs, when combined with oral enzalutamide, produced a substantially greater antitumor effect than standard therapy alone in vivo, without evident systemic toxicity. The broader mechanisms by which RPE exerts non-enzymatic functions to reshape adaptive signaling networks in CRPC remain to be defined. Addressing these questions may further clarify how repurposed metabolic enzymes contribute to drug resistance and may help inform the design of rational combination strategies.\u003c/p\u003e \u003cp\u003eThis study has several limitations. Although we show that RPE promotes FKBP5 ubiquitin-proteasome-mediated degradation, the specific E3 ligase involved remains undefined. In addition, the clinical cohort was relatively limited, and the biomarker value of RPE for predicting enzalutamide response requires validation in larger patient sets. Finally, although PSMA-LNP-mediated RPE silencing showed promising activity in vivo, its long-term safety and performance in more advanced metastatic settings warrant further investigation.\u003c/p\u003e \u003cp\u003eIn our models, RPE did not function as a major determinant of basal proliferation. Instead, its principal role was to sustain CRPC cell survival under enzalutamide pressure, consistent with a context-dependent resistance mechanism rather than a general growth-promoting effect, the role and associated underlying mechanisms of RPE as a structural scaffold in solid tumors have remained largely unexplored. In this study, we show that RPE reshapes the survival dependency of CRPC under therapeutic stress. These findings suggest that targeting RPE may offer a selective strategy to treat CRPC by disrupting a non-enzymatic mechanism on which resistant cells rely to suppress apoptosis. More specifically, interference with the RPE-FKBP5-AKT axis restores endogenous apoptotic control, as reflected by increased cleavage of Caspase-3 and PARP. Consistent with this model, targeted delivery of siRPE by PSMA-LNPs, in combination with enzalutamide, effectively disrupted this survival program and induced apoptosis in vivo. Together, the identification of this non-enzymatic resistance mechanism and the demonstration of a tumor-targeted delivery strategy support RPE as a promising therapeutic target for overcoming enzalutamide resistance in CRPC.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCell lines and reagents\u003c/h2\u003e \u003cp\u003eThe human prostate cancer cell lines LNCaP C4-2 and 22Rv1 were obtained from the American Type Culture Collection (ATCC). The enzalutamide-resistant C4-2 cell line (C4-2 EnzaR) was established by continuously culturing parental LNCaP C4-2 cells in medium containing gradually increasing concentrations of enzalutamide for 6 months until a stable resistant phenotype was achieved. LNCaP C4-2 and C4-2 EnzaR cells were cultured in a 1:1 mixture of DMEM and DMEM/F-12 (Gibco) supplemented with 10% heat-inactivated fetal bovine serum (FBS, Gibco) and 1% penicillin/streptomycin. 22Rv1 cells were maintained in RPMI-1640 medium (Gibco) supplemented with 10% FBS and 1% penicillin/streptomycin. All cell lines were cultured at 37\u0026deg;C in a humidified incubator with 5% CO2. All cell lines were routinely tested for Mycoplasma contamination and authenticated by short tandem repeat (STR) profiling. Enzalutamide (Enza; Selleck Chemicals, CAS No. 915087-33-1), the proteasome inhibitor MG132 (Sigma-Aldrich, M8699), the lysosome inhibitor chloroquine (MedChemExpress, HY-17589A), and the protein synthesis inhibitor cycloheximide (CHX; Sigma-Aldrich, C7698-1G) were purchased from the indicated suppliers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eClinical prostate cancer specimens\u003c/h2\u003e \u003cp\u003ePaired tumor tissues were obtained from patients with CRPC before enzalutamide treatment and after acquisition of enzalutamide resistance, with written informed consent from all patients. The study protocol was approved by the Institutional Ethics Committee of Sun Yat-sen Memorial Hospital, Sun Yat-sen University (Approval No. SYSKY-2025-878-01) and was conducted in strict accordance with the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eIn vivo pooled CRISPR-Cas9 metabolic screening\u003c/h2\u003e \u003cp\u003eA custom-constructed sgRNA library targeting 3,162 human metabolism-related genes (Human CRISPRko Library-Metabolism Plus, Catalog: SSLP039) was customized and synthesized by Yomebio Co., Ltd. (Wuhan, China). The library contains a total of 16,460 sgRNAs, including non-targeting controls, with 5 independent sgRNAs targeting each gene, cloned into the LentiCRISPRv2-Puro backbone. The complete list of sgRNA sequences and their corresponding target metabolic genes is provided in \u003cb\u003eSupplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e. For the in vivo screen, C4-2 cells were stably transduced with the sgRNA library at a low multiplicity of infection (MOI\u0026thinsp;\u0026lt;\u0026thinsp;0.3) to ensure a single sgRNA integration per cell. Following puromycin selection, 1\u0026times;10^7 library-transduced cells per mouse were resuspended in a 1:1 mixture of PBS and Matrigel (Corning) and subcutaneously injected into the flanks of surgically castrated BALB/c nude mice. Once tumors became palpable, mice were randomized to receive vehicle or enzalutamide (20 mg/kg, PO, q2d) for 4 weeks. Genomic DNA was extracted from the harvested tumors, and the integrated sgRNA cassettes were amplified via PCR. The pooled libraries were subjected to next-generation sequencing on an Illumina platform. Depleted and enriched genes were identified, and robust RRA scores were calculated using the MAGeCK computational framework (\u003cb\u003eSupplementary Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePlasmids, RNA interference, and lentiviral transduction\u003c/h2\u003e \u003cp\u003ePooled target-specific small interfering RNAs (siRNAs) against RPE (sc-94945) and GRIK1 (sc-42487), as well as pooled short hairpin RNA (shRNA) plasmids targeting RPE (sc-94945-SH), were purchased from Santa Cruz Biotechnology. Gene-specific siRNAs targeting NAA50, PGK1, OGDH, and FKBP5 were synthesized by IGE Biotechnology (Guangzhou, China). The detailed sequences or catalog numbers of all siRNAs and shRNAs are provided in \u003cb\u003eSupplementary Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e\u003c/b\u003e. Transient siRNA transfections were performed using Lipofectamine RNAiMAX (Invitrogen, 13778150) according to the manufacturer's instructions. For stable gene depletion, shRNAs targeting FKBP5 were cloned into lentiviral vectors. To generate the catalytically inactive RPE mutant, a point mutation at Ser10 (S10A) was introduced into the wild-type RPE coding sequence using the Hieff Mut Site-Directed Mutagenesis Kit (Yeasen, 11003ES10). For interaction-mapping studies, wild-type FKBP5 and an RPE-binding-deficient FKBP5 mutant harboring alterations within the 331\u0026ndash;342 aa region were generated by gene synthesis. All rescue constructs were engineered to carry synonymous mutations rendering them resistant to shRNA-mediated knockdown. Lentiviral particles were produced in HEK293T cells by co-transfection with psPAX2 and pMD2.G. Stable cell lines were established after lentiviral infection and antibiotic selection with puromycin (Beyotime, ST551) or hygromycin B (Beyotime, ST1389).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eRNA extraction and quantitative real-time PCR (RT-qPCR)\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted from cultured cells or tissues using TRIzol reagent (Invitrogen, 15596026) according to the manufacturer's instructions. RNA concentration and purity were assessed using a NanoDrop spectrophotometer. Equal amounts of total RNA (1 \u0026micro;g) were reverse-transcribed into complementary DNA (cDNA) using the cDNA Synthesis Kit (Yeasen, 11141ES60). Quantitative real-time PCR was then performed using the SYBR Green qPCR Master Mix (Yeasen, 11185ES08) on a LightCycler 480 Real-Time PCR System (Roche Diagnostics). Relative mRNA expression levels were calculated using the 2^-△△Ct method. β-actin was used as an endogenous control for normalization. All reactions were performed with three biological replicates. The primer sequences used in this study are listed in \u003cb\u003eSupplementary Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eCell viability, colony formation, and apoptosis assays\u003c/h2\u003e \u003cp\u003eFor cell viability assays, cells were seeded in 96-well plates and treated with the indicated concentrations of enzalutamide. Cell viability was measured using the Cell Counting Kit-8 (CCK-8; APExBIO, K1018) by measuring absorbance at 450 nm, and IC50 values were determined. For cell proliferation assays, CCK-8 absorbance was measured daily for 5 consecutive days. For colony formation assays, cells were seeded at low density (1,000 cells/well) in 6-well plates and cultured in the presence of vehicle (0.1% DMSO) or 20 \u0026micro;M enzalutamide for 14 days. Colonies were then fixed with 4% paraformaldehyde, stained with 0.1% crystal violet, and quantified. For apoptosis analysis, cells were stained with Annexin V-FITC and propidium iodide (PI) using an Annexin V-FITC/PI Apoptosis Detection Kit (Elabscience, E-CK-A211) according to the manufacturer's instructions and analyzed by flow cytometry.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eMetabolic profiling and RPE enzymatic activity assay\u003c/h2\u003e \u003cp\u003eReal-time OCR and ECAR were measured using a Seahorse XFe96 Analyzer (Agilent Technologies) with the XF Cell Mito Stress Test Kit (Agilent, 103015-100) and the XF Glycolysis Stress Test Kit (Agilent, 103020-100), respectively. Briefly, cells were sequentially treated with oligomycin, FCCP, and rotenone/antimycin A for OCR measurements, or glucose, oligomycin, and 2-deoxy-D-glucose (2-DG) for ECAR measurements, according to the manufacturer's instructions. OCR and ECAR values were normalized to cell number. The intracellular NADPH/NADP\u003csup\u003e+\u003c/sup\u003e ratio was determined using a colorimetric assay kit (Abcam, ab65349) according to the manufacturer's instructions. To assess intracellular RPE catalytic activity (EC 5.1.3.1), cell lysates were subjected to a coupled enzymatic assay using reagents purchased from Sigma-Aldrich. In this assay, the epimerization of Ru5P to Xu5P was coupled to downstream reactions resulting in NADH oxidation. Enzymatic activity was monitored continuously by measuring the decrease in absorbance at 340 nm using a microplate reader.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eImmunoprecipitation (IP) and LC-MS/MS analysis\u003c/h2\u003e \u003cp\u003eCells expressing Flag-tagged RPE were lysed using an Immunoprecipitation Kit (Thermo Fisher Scientific, 26149) supplemented with protease inhibitors. Cell lysates were incubated with ANTI-FLAG M2 Magnetic Beads (Sigma-Aldrich, M8823-1ML) overnight at 4\u0026deg;C with gentle rotation. The immunoprecipitated proteins were resolved by SDS-PAGE and visualized using a Silver Staining Kit (Beyotime, P0017S). Specific protein bands were excised, subjected to in-gel tryptic digestion, and analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) at PTM Biolabs (Hangzhou, China). MS/MS spectra were searched against the human UniProt database to identify RPE-interacting proteins.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eIn vitro GST pulldown assay\u003c/h2\u003e \u003cp\u003eRecombinant His-tagged RPE and GST-tagged FKBP5 proteins, including wild-type and truncation/deletion mutants, were expressed in Escherichia coli BL21(DE3) cells. His-tagged RPE was purified using Ni-NTA Agarose (Qiagen, 30210) according to the manufacturer\u0026rsquo;s protocol. Equal amounts of purified GST-FKBP5 fusion proteins or GST control protein were immobilized on Glutathione Sepharose 4B beads (Cytiva, 17075601). The bead-bound proteins were incubated with purified His-RPE at 4\u0026deg;C with gentle rotation. After extensive washing with binding buffer to remove non-specific interactions, the bound protein complexes were eluted by boiling in SDS sample buffer, resolved by SDS-PAGE, and analyzed by immunoblotting using anti-His (Cell Signaling Technology, 12698) and anti-GST (Cell Signaling Technology, 2624S) antibodies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eMolecular docking and molecular dynamics (MD) simulation\u003c/h2\u003e \u003cp\u003eThe initial RPE-FKBP5 complex conformation was predicted using the HDOCK server. A 100-ns all-atom molecular dynamics (MD) simulation was performed using GROMACS (version 2021) with the AMBER99SB-ILDN force field in an explicit TIP3P water model. After energy minimization, NVT equilibration, and NPT equilibration, a 100-ns production run was carried out. Trajectory analyses, including root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), radius of gyration (Rg), and intermolecular hydrogen bonds, were performed using built-in GROMACS tools. The free energy landscape (FEL) was constructed using the first two principal components (PC1 and PC2).\u003c/p\u003e \u003cp\u003e \u003cb\u003e4.11.Western blotting, CHX chase, and Ubiquitination assays\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTotal protein was extracted using RIPA lysis buffer (Beyotime, P0013B) supplemented with protease and phosphatase inhibitor cocktails. Western blotting was performed according to standard procedures. For CHX chase assays to evaluate protein half-life, cells were treated with 50 \u0026micro;g/mL CHX, and protein lysates were collected at 0, 4, 8, 12, and 16 h after treatment. For endogenous ubiquitination assays, cells were pretreated with the proteasome inhibitor MG132 (10 \u0026micro;M) for 6 h before harvest. Endogenous FKBP5 was immunoprecipitated from cell lysates, and its polyubiquitination status was assessed by immunoblotting with an anti-ubiquitin antibody. A list of primary antibodies used in this study is provided in \u003cb\u003eSupplementary Table \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003e\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003ePreparation and characterization of PSMA-LNPs-siRPE\u003c/h2\u003e \u003cp\u003eLipid nanoparticles (LNPs) encapsulating siRPE were prepared using a microfluidic mixing system (NanoAssemblr Ignite, Precision NanoSystems). Briefly, a lipid mixture containing the ionizable cationic lipid G0-C14, DSPC, cholesterol, and PEG-lipid at a molar ratio of 50:10:38.5:1.5 was dissolved in ethanol. For PSMA-targeted LNPs (PSMA-LNPs), 0.5 mol% PSMA ligand-conjugated PEG-lipid was incorporated into the lipid phase in place of an equivalent molar amount of unconjugated PEG-lipid. siRPE was dissolved in an acidic aqueous buffer (pH 4.0), and the aqueous and organic phases were rapidly mixed in a microfluidic cartridge to allow nanoparticle self-assembly. The resulting nanoparticles were dialyzed against PBS to remove residual ethanol and neutralize the formulation. Particle size and zeta potential were measured by dynamic light scattering (DLS; Malvern Zetasizer), and morphology was examined by transmission electron microscopy (TEM).\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eIn vivo animal models and imaging\u003c/h2\u003e \u003cp\u003e All animal experiments were approved by the Institutional Animal Care and Use Committee of Sun Yat-sen Memorial Hospital, Sun Yat-sen University (Approval No. AP20250191) and were performed in accordance with the institutional guidelines for the care and use of laboratory animals. To establish the cell line-derived xenograft (CDX) model, 4-week-old male BALB/c nude mice underwent bilateral surgical castration. One week later, C4-2 EnzaR cells (1\u0026times;10\u003csup\u003e6\u003c/sup\u003e) mixed with Matrigel (Corning) at a 1:1 volume ratio were subcutaneously inoculated into the flanks. For the patient-derived xenograft (PDX) model, clinical CRPC tissues were cut into small fragments (~\u0026thinsp;2\u0026times;2\u0026times;2 mm) and implanted subcutaneously into castrated immunodeficient NCG mice. When tumor volumes reached approximately 50 mm\u0026sup3;, mice were randomized into different treatment groups. Enzalutamide was administered orally (20 mg/kg, every 2 days). For targeted nanotherapy, PSMA-LNPs-siRPE were injected intravenously via the tail vein (1.0 mg/kg based on siRNA content, once every 3 days for 3 doses). For intratumoral injection in the PDX model, siRNAs were complexed with in vivo transfection reagents and injected directly into the tumors. Tumor length (L) and width (W) were measured twice a week using digital calipers, and tumor volume was calculated as (L\u0026times;W\u003csup\u003e^\u003c/sup\u003e2)/2. At the experimental endpoint, mice were euthanized, and tumors together with major vital organs were excised, weighed, and processed for histological analysis. For biodistribution and targeting analysis, mice bearing C4-2 EnzaR tumors were intravenously injected with Cy5.5-labeled LNPs or Cy5.5-labeled PSMA-LNPs. Whole-body fluorescence imaging was performed at 0, 6, and 12 h post-injection using an IVIS Spectrum In Vivo Imaging System. Ex vivo fluorescence imaging of excised tumors and major organs was then conducted.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eHistology, Immunohistochemistry (IHC), and Immunofluorescence (IF)\u003c/h2\u003e \u003cp\u003eExcised tissues were fixed in 4% paraformaldehyde, paraffin-embedded, and sectioned at 4 \u0026micro;M. Hematoxylin and eosin (H\u0026amp;E) staining was performed to evaluate tissue morphology and, where applicable, systemic toxicity. For IHC, tissue sections were subjected to antigen retrieval, blocking, and overnight incubation with primary antibodies at 4\u0026deg;C, followed by incubation with secondary antibodies and DAB development. Staining intensity and the percentage of positive cells were semi-quantitatively assessed using the H-score method. For dual IF staining of RPE and FKBP5, a sequential multiplex staining protocol was performed using a Tyramide Signal Amplification (TSA) Kit (Absin, abs50012). After incubation with the first primary antibody and TSA-based signal visualization, sections were subjected to microwave treatment for antibody stripping. The second primary antibody and a distinct fluorophore were then applied, followed by DAPI counterstaining.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll in vitro experiments were performed with at least three independent biological replicates, unless otherwise indicated. Statistical analyses were performed using GraphPad Prism (version 10.3). Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). Comparisons between two independent groups were analyzed using an unpaired two-tailed Student\u0026rsquo;s t-test. For comparisons among multiple groups involving a single independent variable, statistical significance was determined by one-way ANOVA followed by either Tukey\u0026rsquo;s multiple-comparisons test (for all pairwise comparisons) or Dunnett\u0026rsquo;s multiple-comparisons test. Tumor growth curves and real-time cell proliferation curves were analyzed using two-way repeated-measures ANOVA. A P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant (*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, ****P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; ns, not significant).\u003c/p\u003e "},{"header":"Declarations","content":"\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eEthics approval\u003c/h2\u003e \u003cp\u003e This study was approved by the Institutional Ethics Committee of Sun Yat-sen Memorial Hospital, Sun Yat-sen University (Approval No. SYSKY-2025-878-01). All human prostate cancer samples were collected with written informed consent from all participants. All animal experiments were performed according to procedures approved by the Institutional Animal Care and Use Committee of Sun Yat-sen Memorial Hospital, Sun Yat-sen University (Approval No. AP20250191), in accordance with institutional and national guidelines for the care and use of laboratory animals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eCRediT authorship contribution statement\u003c/h2\u003e \u003cp\u003e \u003cb\u003eJintao Hu\u003c/b\u003e: Writing \u0026ndash; original draft, Methodology, Investigation, Funding acquisition, Data curation, Formal analysis. \u003cb\u003eCong Lai\u003c/b\u003e: Writing \u0026ndash; original draft, Methodology, Investigation, Validation, Data curation. \u003cb\u003eYunfei Xiao\u003c/b\u003e: Writing \u0026ndash; original draft, Methodology, Investigation, Visualization, Formal analysis. \u003cb\u003eZi Yan\u003c/b\u003e: Methodology, Investigation, Validation, Data curation. \u003cb\u003eYongmei Tan\u003c/b\u003e: Methodology, Resources, Investigation, Data curation. \u003cb\u003eJunjie Wang\u003c/b\u003e: Methodology, Investigation, Validation. \u003cb\u003eJiangping Qiu\u003c/b\u003e: Resources, Methodology, Investigation. \u003cb\u003eKuiqing Li\u003c/b\u003e: Methodology, Investigation, Data curation. \u003cb\u003eHao Yu\u003c/b\u003e: Methodology, Investigation, Formal analysis. \u003cb\u003eXutao Chen\u003c/b\u003e: Software, Formal analysis, Visualization. \u003cb\u003eJinli Han\u003c/b\u003e: Methodology, Investigation, Validation. \u003cb\u003eXiaolin Cai\u003c/b\u003e: Resources, Methodology, Investigation. \u003cb\u003eTianlong Luo\u003c/b\u003e: Methodology, Investigation, Data curation. \u003cb\u003eChunnuan Deng\u003c/b\u003e: Methodology, Investigation, Validation. \u003cb\u003eRong Na\u003c/b\u003e: Writing \u0026ndash; review \u0026amp; editing, Supervision, Project administration, Conceptualization. \u003cb\u003eWang He\u003c/b\u003e: Writing \u0026ndash; review \u0026amp; editing, Supervision, Project administration, Conceptualization. \u003cb\u003eKewei Xu\u003c/b\u003e: Writing \u0026ndash; review \u0026amp; editing, Supervision, Project administration, Funding acquisition, Conceptualization. \u003cb\u003eCheng Liu\u003c/b\u003e: Writing \u0026ndash; review \u0026amp; editing, Supervision, Project administration, Funding acquisition, Conceptualization.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eData availability statement\u003c/h2\u003e \u003cp\u003eThe datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.\u003c/p\u003e \u003c/div\u003e\u003cp\u003e \u003ch2\u003eDeclaration of competing interest\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThis work was supported by the Guangdong S\u0026amp;T Program (No. 2023B1111030006), National Natural Science Foundation of China (No. 82560599 and 82372766), Guangdong Province Medical Science and Technology Research Fund (No. A2022541 and A2020571), Guangdong Province Medical Research Fund (No. A2026054), Yixian Clinical Research Project 5010 (No. SYS-5010-202503), and Shenzhen Key Industry Research and Development Program (No. ZDCY20250901102503004).\u003c/p\u003e \u003cp\u003eGenerative AI and AI-assisted technologies were NOT used in the preparation of this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians. 2024;74(3):229\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChakrabarti D, Albertsen P, Adkins A, Kishan A, Murthy V, Parker C, et al. The contemporary management of prostate cancer. CA: a cancer journal for clinicians. 2025;75(6):552\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeo MY, Rathkopf DE, Kantoff P. Treatment of Advanced Prostate Cancer. Annual review of medicine. 2019;70:479\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWatson PA, Arora VK, Sawyers CL. Emerging mechanisms of resistance to androgen receptor inhibitors in prostate cancer. Nature reviews Cancer. 2015;15(12):701\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLitwin MS, Tan HJ. The Diagnosis and Treatment of Prostate Cancer: A Review. Jama. 2017;317(24):2532\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScher HI, Fizazi K, Saad F, Taplin ME, Sternberg CN, Miller K, et al. Increased survival with enzalutamide in prostate cancer after chemotherapy. The New England journal of medicine. 2012;367(13):1187\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeer TM, Armstrong AJ, Rathkopf DE, Loriot Y, Sternberg CN, Higano CS, et al. Enzalutamide in metastatic prostate cancer before chemotherapy. The New England journal of medicine. 2014;371(5):424\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVasan N, Baselga J, Hyman DM. A view on drug resistance in cancer. Nature. 2019;575(7782):299\u0026ndash;309.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRobinson D, Van Allen EM, Wu YM, Schultz N, Lonigro RJ, Mosquera JM, et al. Integrative clinical genomics of advanced prostate cancer. Cell. 2015;161(5):1215\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAntonarakis ES, Lu C, Wang H, Luber B, Nakazawa M, Roeser JC, et al. AR-V7 and resistance to enzalutamide and abiraterone in prostate cancer. The New England journal of medicine. 2014;371(11):1028\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMu P, Zhang Z, Benelli M, Karthaus WR, Hoover E, Chen CC, et al. SOX2 promotes lineage plasticity and antiandrogen resistance in TP53- and RB1-deficient prostate cancer. Science (New York, NY). 2017;355(6320):84\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHanahan D. Hallmarks of Cancer: New Dimensions. Cancer Discov. 2022;12(1):31\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg effect: the metabolic requirements of cell proliferation. 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Nature nanotechnology. 2020;15(4):313\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"oncogene","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"onc","sideBox":"Learn more about [Oncogene](http://www.nature.com/onc/)","snPcode":"41388","submissionUrl":"https://mts-onc.nature.com/cgi-bin/main.plex","title":"Oncogene","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9593389/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9593389/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEnzalutamide is a cornerstone therapy for castration-resistant prostate cancer (CRPC), yet acquired resistance remains a major clinical challenge. Although metabolic enzymes are increasingly recognized as modulators of therapeutic response, their specific roles\u0026mdash;particularly their non-enzymatic functions\u0026mdash;in sustaining enzalutamide resistance remain incompletely understood. In this study, we performed an in vivo screen using a custom metabolic CRISPR library in enzalutamide-treated xenografts and identified the pentose phosphate pathway enzyme ribulose-5-phosphate 3-epimerase (RPE) as a critical driver of enzalutamide resistance. Silencing RPE markedly restored enzalutamide sensitivity, enhanced apoptosis in vitro, and significantly suppressed tumor growth in both cell line-derived and patient-derived xenograft models. Mechanistically, RPE promoted resistance independently of its canonical enzymatic activity. Instead, RPE physically interacted with FKBP5 and promoted its ubiquitin-proteasome-mediated degradation. Loss of FKBP5 subsequently hyperactivated AKT signaling, leading to increased p-BAD and BCL-xL levels and suppression of enzalutamide-induced cell death. Conversely, disrupting the RPE-FKBP5 interaction or silencing RPE in vivo using a PSMA-targeted lipid nanoparticle system effectively abrogated these resistance phenotypes. Together, these findings illustrate how CRPC cells hijack the non-enzymatic function of a metabolic enzyme to evade antiandrogen therapy, establishing the RPE-driven degradation of FKBP5 and consequent AKT hyperactivation as a targetable vulnerability for overcoming enzalutamide resistance.\u003c/p\u003e","manuscriptTitle":"Metabolic CRISPR screening identifies RPE as a key regulator of acquired enzalutamide resistance through FKBP5 destabilization in prostate cancer.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-14 12:09:04","doi":"10.21203/rs.3.rs-9593389/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-05-11T06:30:50+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-05-11T00:40:30+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2026-05-06T02:56:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-05-05T13:43:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-02T11:33:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"Oncogene","date":"2026-05-02T11:33:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"oncogene","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"onc","sideBox":"Learn more about [Oncogene](http://www.nature.com/onc/)","snPcode":"41388","submissionUrl":"https://mts-onc.nature.com/cgi-bin/main.plex","title":"Oncogene","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"99d6c200-6b13-4932-869b-0419b11356a6","owner":[],"postedDate":"May 14th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-05-11T06:30:50+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-05-11T00:40:30+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"6","date":"2026-05-06T02:56:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-05-05T13:43:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-02T11:33:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"Oncogene","date":"2026-05-02T11:33:39+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":67595540,"name":"Biological sciences/Cancer/Cancer therapy/Cancer therapeutic resistance"},{"id":67595541,"name":"Biological sciences/Cancer/Urological cancer/Prostate cancer"},{"id":67595542,"name":"Health sciences/Biomarkers/Predictive markers"},{"id":67595543,"name":"Biological sciences/Cancer/Cancer models"}],"tags":[],"updatedAt":"2026-05-14T12:09:04+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-14 12:09:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9593389","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9593389","identity":"rs-9593389","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}