IGFBP3-SphK1/S1P Signaling Axis Drives Enzalutamide Resistance in Advanced Prostate Cancer

Abstract

Enzalutamide resistance remains a significant challenge in the treatment of advanced prostate cancer. Identifying molecular drivers of enzalutamide resistance is crucial for developing effective therapeutic strategies. In this study, we identify insulin-like growth factor binding protein 3 (IGFBP3) as a key driver of enzalutamide resistance in castration-resistant prostate cancer (CRPC). We demonstrate that IGFBP3 expression is significantly upregulated in enzalutamide-resistant C4–2B MDVR cells compared to parental C4–2B cells. This upregulation was consistently observed across multiple enzalutamide-resistant CRPC models, including LNCaP-derived 42D and 42F cells, as well as long-term enzalutamide-resistant cell lines derived from LNCaP, VCaP, LAPC-4, and CWR-R1 cells. Additionally, Enzalutamide treatment directly induced IGFBP3 expression in sensitive cells. Elevated IGFBP3 expression was also observed in CRPC patient samples post-enzalutamide treatment and was associated with higher Gleason scores and reduced disease-free survival. Mechanistically, IGFBP3 activates the sphingosine kinase 1 (SphK1)/sphingosine-1-phosphate (S1P) signaling pathway, which promotes cell survival and resistance to enzalutamide. IGFBP3 knockdown decreased SphK1 expression, reduced S1P secretion, and enhanced enzalutamide sensitivity, whereas IGFBP3 overexpression induced SphK1 expression and S1P production, conferring enzalutamide resistance. Inhibition of IGFBP3 via siRNA reduced cell viability, induced apoptosis, and re-sensitized resistant models to enzalutamide. Similarly, targeting SphK1 with the inhibitor SKI-II suppressed SphK1 activity, reduced S1P production, enhanced enzalutamide sensitivity, and significantly inhibited resistant tumor growth while enhancing enzalutamide sensitivity. Collectively, these findings highlight IGFBP3-mediated SphK1 signaling as a critical mediator of enzalutamide resistance and suggest that targeting the IGFBP3/SphK1/S1P axis represents a promising therapeutic strategy to overcome resistance in advanced prostate cancer.

Introduction

Prostate cancer remains one of the most prevalent malignancies in men worldwide (1) (2). The incidence rates of prostate cancer have increased by 3% from 2015 to 2019 (3). This rise in prostate cancer incidences can be explained by the removal of prostate specific antigen (PSA) screening in 2012 (4,5). Back then, frequent PSA testing led to false positives and overdiagnosis (6). Thus, the U.S. Preventive Services Task Force changed the PSA screening guidelines. Without PSA detection, early-stage prostate cancer remains undetected and untreated (7). Androgen receptor (AR) signaling controls prostate cancer progression (8). The first line treatment for hormone-sensitive prostate cancer (HSPC) is androgen deprivation therapy (ADT) (9). Sadly, androgen responsiveness in early-stage prostate cancer is short-lived. Within 5 years, most HSPC patients will no longer respond to ADT and progress to castration-resistant prostate cancer (CRPC) (10). As CRPC evolves, this disease becomes androgen insensitive (11). CRPC represents the most aggressive and treatment-resistant form of the disease. Androgen receptor signaling inhibitors (ARSI), such as enzalutamide, have significantly improved clinical outcomes for patients with CRPC. However, resistance to enzalutamide frequently emerges, limiting its long-term efficacy and contributing to disease progression. Understanding the molecular mechanisms underlying enzalutamide resistance is therefore critical for the development of novel therapeutic strategies to enhance treatment response and improve patient outcomes. As CRPC becomes insensitive to AR signaling, lineage plasticity arises in a transdifferentiation manner leading to neuroendocrine prostate cancer (NEPC) (12–14). Treatment-induced resistance negates the effectiveness of enzalutamide, thus inevitably creating incurable CRPC (15,16). Identifying novel therapies to overcome enzalutamide resistance is therefore critical to improve mCRPC patient outcomes.

The mechanisms that drive enzalutamide resistance are incompletely understood. We have established the enzalutamide-resistant (MDVR) cells by chronically exposing C4–2B CRPC cells to enzalutamide to study acquired resistance (17–22). In addition, this study incorporated several independent enzalutamide-resistant models like 42D and 42F cells that were derived from the LNCaP castration-resistant 16D cells (23,24) and 22Rv1 cells which display intrinsic resistance to enzalutamide (25). Deciphering the molecular alterations using these resistant cellular models, patient-derived xenografts (PDXs), such as LTL331R and treatment-emergent patient tumor samples (26,27), several mechanisms associated with the development of resistance to enzalutamide were identified. These include reprogramed AR signaling (e.g., AR-V7) (28–30), Wnt signaling (e.g. Wnt5A) (31–33), Jak-Stat signaling (e.g. Stat3) (34,35), as well as multiple epigenetic and transcriptional factors (36), such as brain-specific homeobox/POU domain protein 2 (BRN2) and protein 4 (BRN4)(23,37), EZH2 (38,39), One Cut Homeobox 2 (ONECUT2)(40,41), and SRY-box transcription factor 2 (SOX2)(42).

Insulin-like growth factor-binding protein 3 (IGFBP3) has emerged as a key regulator of cancer progression and therapeutic resistance. Out of all 6 high-affinity IGFBPs, IGFBP3 is highest in adult circulation and regulates the Insulin Growth Factor (IGF) signaling pathway by binding to IGF-I and IGF-2. Elevated IGFBP3 expression correlates with poor prognosis across various cancers, including CRPC (43,44). Analysis of clinical prostate cancer specimens and TCGA datasets indicates that high IGFBP3 expression is associated with recurrence and poor patient survival (43,44). Our recent findings revealed IGFBP3 overexpression in Olaparib-resistant prostate cancer cell lines and demonstrated that IGFBP3 inhibition could re-sensitize these models to PARP inhibitors (45,46). However, IGFBP3’s specific role in ARSI resistance, particularly resistance to enzalutamide, has yet to be comprehensively characterized.

Emerging evidence implicates sphingosine-1-phosphate (S1P) signaling, regulated by sphingosine kinase 1 (SphK1), in mediating resistance to cancer therapies. S1P promotes cellular proliferation, survival, migration, and angiogenesis, with elevated S1P signaling linked to resistance against chemotherapy and targeted therapies in multiple malignancies. The SphK1/S1P signaling axis was found to transdifferentiate androgen-dependent prostate cancer (ADPC) into NEPC and enzalutamide resistance (47–50). In human umbilical vein endothelial cells (HUVEC), IGFBP3 can activate SphK1 to induce S1P production and reduce ceramide formation thereby inhibiting apoptosis (51). Furthermore, osteoblast-derived S1P induces proliferation and confers resistance to both chemo- and radio- therapeutics in bone metastasis-derived prostate cancer cells through S1P receptor 3 (S1PR3)(52). Notably, S1P signaling, regulated by sphingosine kinases, mediates resistance by counteracting ceramide-driven apoptosis, highlighting its potential importance in therapeutic resistance mechanisms. However, the functional role of IGFBP3-SphK1-S1P signaling pathway in ARSI resistance in prostate cancer remains poorly defined.

In this study, we examine the role of IGFBP3 in enzalutamide-resistant prostate cancer models and explore its functional link to SphK1/S1P signaling. We found that IGFBP3 is consistently upregulated in enzalutamide-resistant prostate cancer models—including C4–2B MDVR, 42D/42F, and long-term treated LNCaP, VCaP, and LAPC-4 cells—and that enzalutamide treatment induces IGFBP3 expression in parental lines. Mechanistically, IGFBP3 enhances SphK1 expression and activity, resulting in increased intracellular and extracellular S1P accumulation. Importantly, pharmacologic inhibition of SphK1 using SKI-II suppresses S1P production, restores enzalutamide sensitivity in resistant cells, and significantly reduces tumor growth in vivo. These results support a model in which IGFBP3 drives resistance by activating the SphK1–S1P survival axis, thereby promoting cellular survival under AR blockade.

Materials and Methods

Cell culture and reagents

C4–2B cells (RRID: CVCL_4784) were kindly provided and authenticated by Dr. Leland Chung (Cedars-Sinai Medical Center, Los Angeles, CA) in 2005. Enzalutamide-resistant (MDVR) were generated from parental C4–2B cells through chronic enzalutamide exposure as previously described (22). MDVR cells were maintained in 20μM enzalutamide. LNCaP (RRID: CVCL_0395) and 22Rv1 (RRID: CVCL_4Y35) were obtained from the American Type Culture Collection (ATCC) in 2008. ATCC uses short tandem repeat profiling for testing and authentication of cell lines. The 42D (RRID: CVCL_RW50), 42F (RRID: CVCL_RW51), and 16D cells were kindly provided and authenticated by Dr. Amina Zoubeidi (Vancouver Prostate Center, Vancouver, British Columbia, Canada) in 2022. The Enzalutamide-resistant 42D and 42F cells are maintained in 10μM enzalutamide as previously reported (23). All cell lines used in this study were of male origin and were not re-authenticated after purchase or acquisition. All cells were maintained in RPMI 1640 media supplemented with 10% fetal bovine serum (FBS), 100 units per ml penicillin, and 0.1 mg/ml streptomycin. Cell cultures were maintained at 37°C in a humidified incubator with 5% carbon dioxide. All cell lines are routinely tested (about every two month) for mycoplasma contamination using Applied Biological Materials (ABM) mycoplasma PCR detection kit (Cat#: G238). All cell lines used in this study remain mycoplasma negative. Enzalutamide (Cat#: S1250) was purchased from Selleck Chemicals while SKI-II (Cat#: HY-13822) was purchased from MedChemExpress.

Plasmid and cell transfection

Cells were seeded at a density of 25,000 cells per well in 24-well plates in complete RPMI-1640 media without any selection agent. After 24 hours, cells were subjected to indicated treatments. RNAi was performed using Dicer-Substrate siRNAs (DsiRNA) purchased from Integrated DNA Technologies and Opti-MEM (Cat#: 31985088) from Gibco. Transfection of DsiRNAs was performed using Lipofectamine RNAiMAX Transfection Reagent (Cat#: 13778150) purchased from Invitrogen according to the manufacturer’s protocol with 20nmol/L DsiRNA. The following DsiRNAs were used: Negative Control (NC) (Cat#: 51–01-14–04), IGFBP3 (Cat#: hs.Ri.IGFBP3.13.1), and SphK1 (Cat#: hs.Ri.SphK1.13.1 and Cat#: hs.Ri.SphK1.13.2). The DsiRNA targeted the following sequence: IGFBP3 (5’-rArArUrGrGrUrArArArCrUrUrGrArGrGrArUrCrUrUrUrUCA-3’, 5’rUrGrArArArArGrArUrGrCrUrCrArArGrUrUrUrArCrCrArUrUrCrA-3’).

SPHK13.1(5’-rGrGrGrUrGrArUrGrCrArUrCrUrGrUrUrCrUrArCrGrUrGCG-3’, 5’-rCrGrCrArCrGrUrArGrArArCrArGrArUrGrGrArUrGrArCrGrCrCrA-3’), SPHK13.2(5’-rCrCrUrGrArCrCrArArCrUrGrCrArGrGrGrUrArUrUrGrCTG-3’, 5’-rCrArGrCrArArUrArGrCrGrUrGrCrArGrUrUrGrGrUrCrArGrGrArG-3’).

IGFBP3 expression plasmid was generated by GenEZ ORF clone Plasmid IGFBP3_OHu23309C into PCDNA3.1 (+) vector (Lot#: U2605GF170–1/Q29854) from GenScript. Overexpression was performed by transfecting IGFBP3-expressing plasmids into C4–2B cells along with the vector control PCDNA3.1 (Cat #: 11608) obtained from Addgene using Lipofectamine 2000 (Cat #: 11668019) from Invitrogen.

Immunoblotting

Cells were harvested, washed with PBS, and lysed in RIPA buffer supplemented with 5 mmol/L EDTA, 1 mmol/L NaV, 10 mmol/L NaF, and 1X Halt Protease Inhibitor Cocktail (Cat#: 78430) purchased from Invitrogen. Protein concentration was determined Pierce Bradford Plus (Coomassie) Protein Assay Kit (Cat#: 23236) purchased from ThermoFisher Scientific. Protein extracts were resolved by SDS-PAGE, transferred to nitrocellulose membranes, blocked using 5% milk in PBS 0.1% Tween-20, and incubated using primary antibodies at 4°C overnight. IGFBP3 (SC-365936) (RRID: AB_10917037), SphK1 (SC-365401) (RRID: AB_10859210), and Alpha Tubulin (SC-5286) (RRID: AB_628411) were purchased from Santa Cruz Biotechnology. Cleaved PARP (Cat#: 9541) (RRID: AB_331426) was purchased from Cell Signaling Technology. Anti-Rabbit (Cat#: NC0161557) (RRID: AB_218567) and Anti-Mouse (Cat#: NC9575145) (RRID: AB_218457) were purchased from ThermoFisher Scientific. Alpha Tubulin was used as a loading control. Proteins were visualized with Immobilon Crescendo Western HRP substrate (Cat#: WBLUR0500) purchased from Millipore using a Bio-Rad ChemiDoc MP Imaging System.

RNA isolation and RT-qPCR

Total RNA was harvested using TRIzol reagent (Cat#: 15596018) purchased from ThermoFisher Scientific and the NanoDrop 2000 Spectrophotometer purchased from Fisher Scientific was used to measure the concentration and quality of RNA. The cDNA was prepared using qScript cDNA SuperMix (Cat#: 95048–500) purchased from Quanta Biosciences. The cDNAs were subjected to quantitative PCR (qPCR) using SsoFast EvaGreen Supermix (Cat#: 1725205) purchased from Bio-Rad according to the manufacturer’s instructions. Triplicates of samples were run on the default settings of the Bio-Rad CFX96 Real-Time PCR Detection System. Cq values of genes of interest were normalized to housekeeping gene ACTIN expression. Primers used for real-time qPCR were purchased from Integrated DNA Technologies. The primer sequences are the following: IGFBP3, 5’-ATGCAGCGGGCGCGAC -3’ (forward) and 3’-CTACTTGCTCTGCATGCTGTAGCA-5’ (reverse); SPHK1, 5’-GCTCTGGTGGTCATGTCTGG -3’ (forward) and 3’-CACAGCAATAGCGTGCAGT-5’ (reverse); ACTIN, 5’-CCCAGCCATGTACGTTGCTA-3’ (forward) and 3’-AGGGCATACCCCTCGTAGATG-5’ (reverse).

Spheroid assay

Cells (3000 per well) were seeded into 96-well ultra-low attachment BIOFLOAT plates (Cat#: 83.3925.400) purchased from Sarstedt containing complete RPMI-1640 media. Spheroids were maintained for 1 week with medium changed every 48 to 72 hours. The viability of spheroids was analyzed using Cell Titer-Glo 2.0 Cell Viability Assay purchased from Promega and visualized by immunofluorescence using LIVE/DEAD Viability/Cytotoxicity Kit (Cat#: L3224) purchased from Invitrogen. Microscopy was performed using a Keyence BZ-X810 imaging system. The fluorescence intensity of the spheroids was quantified using ImageJ software (RRID:SCR_003070) (National Institutes of Health).

Cell growth assay

Cells (25000 per well) were seeded into 24-well plates with complete RPMI-1640 media. After 24 hours, cells were subjected to indicated treatments. Transfections were performed 24 hours after plating and drugs were administered as indicated the following day. Cell count was determined using Cell Counting Kit-8 (Cat#: CK04) purchased from Dojindo Molecular Technologies. Data are displayed as percentage of control cell growth. All conditions were performed either in triplicate or quadruplicate. The 50% half maximal inhibitory concentration (IC50) is a quantitative measurement of a drug’s efficacy which indicates the concentration of drug needed to inhibit cancer cell viability. To determine synergism, the coefficient of drug interaction (CDI) is calculated as follows; CDI = AB/(A×B). The CDIs were analyzed to determine the synergism of the two drugs in combination (A CDI value < 1, = 1, or >1 indicates that the drugs are synergistic, additive, or antagonistic, respectively.

Clonogenic assay

To assess cell survival, colony formation assay was performed by seeding cells at an equal density of 1000 cells per 60mm plates. Subsequently, cells were treated as indicated and allowed to grow for 14 days. The colonies were rinsed with cold PBS before being fixed and stained with 4% paraformaldehyde and 0.1% crystal violet (Cat#: C581–25) for 30 min. The colonies were quantified using ImageJ software (RRID:SCR_003070) (National Institutes of Health). Microscopy was performed using a Keyence BZ-X810 imaging system.

ELISA

Human IGFBP3 Enzyme-Linked Immunosorbent Assay (ELISA) kit (Cat#: RAB0235) is an in vitro enzyme-linked immunosorbent assay for the quantitative measurement of human IGFBP-3 purchased from Sigma-Aldrich. Culture supernatants were collected and analyzed for IGFBP3 production by ELISA sandwich assay procedure. Samples and standards were assayed in duplicate according to the manufacturer’s protocol. The Sphingosine-1-Phosphate (S1P) ELISA Kit (Cat #: MBS2700637) was used for the quantification of the S1P levels purchased from MyBioSource following the manufacturer’s instructions.

RNA sequencing analysis

Transcriptomic analysis of the parental C4–2B cells and its resistant derivative line MDVR was performed with next-generation sequencing (NGS). Indexed RNA sequencing (RNA-seq) libraries were prepared from total RNA (1μg) using the KAPA Stranded mRNA-Seq Library Kit (Kapa Biosystems), according to the manufacturer’s instructions. Subsequently, libraries were combined for multiplex sequencing on an Illumina HiSeq 4000 System (2×150 bp, paired end, ~30 million reads/sample). Data analysis was performed with a HISAT-String Tie-Cuff norm pipeline for mapping/alignment of raw sequence reads (FASTQ format) to the reference human genome assembly (GRCh38/hg38), transcript assembly, and quantitation of gene and transcript expression as fragments per kilobase of transcript per million mapped (FPKM) reads. Gene set enrichment analysis (GSEA) using GSEA software {https://www.gsea-msigdb.org/gsea/index.jsp)(53) (RRID:SCR_003199) from the Broad Institute was used to identify biological function pathways based on the Molecular Signature Database (RRID:SCR_016863). Gene sets with normalized enrichment score (|NES| > 1) and a nominal P-value <0.05 and FDR q-value <0.25 were considered significant. The sequencing data have been deposited in GEO under accession number GSE64143.

Tumor xenografts

All animal experiments were approved by the Institutional Animal Care and Use Committee of UC Davis (Davis, CA). To assess the effects of SKI-II on tumor growth in vivo, 22Rv1 cells (3 X 10⁶) were mixed with Matrigel (1:1) and injected subcutaneously into the flanks of 3- to 4-week-old male C.B17/lcrHsd-Prkdc-SCID Lystbg mice (ENVIGO). Tumor-bearing mice (tumor volume around 50–100 mm³) were randomized into four groups (five to six mice in each group) and treated through oral gavage or intraperitoneal (i.p) injection three times per week as follows: (i) vehicle control (0.5% Methocel based upon weight/volume orally), (ii) enzalutamide (25mg/kg orally), (iii) SKI-II (50mg/kg SKI-II i.p.), and (iv) enzalutamide and SKI-II. The SKI-II was dissolved in 5% DMSO, then 95% corn oil for i.p. injection immediately before use. Tumors were measured using calipers twice a week and tumor volumes were calculated using the length X width X width X 0.52 formula. Tumor tissues were harvested and weighed at the end of treatment. Tumor samples were paraffin-embedded and subjected to immunohistochemistry (IHC) for hematoxylin and eosin (H&E) and Ki67 staining. Blood serum was collected for S1P measurements.

Clinical data analyses

Clinical datasets were analyzed using the cBioPortal for Cancer Genomics (http://www.cbioportal.org/)(54) (RRID:SCR_014555) and NCBI’s Gene Expression Omnibus (GEO) (RRID:SCR_005012). The mRNA levels of IGFBP3 and SphK1 in both normal prostate and PCa tissues were evaluated by analyzing multiple PCa mRNA datasets obtained from the cBioPortal database. Further analysis was performed by dividing the patients into groups based on Gleason Scores levels.

Statistical analyses

All quantitated data are displayed as a percentage of control mean ± standard deviation. Data analysis was performed using GraphPad Prism 10.0 software (https://www.graphpad.com/) (RRID:SCR_002798). Statistical analyses were performed using the two-tailed Student’s t test or one-way ANOVA with a post hoc Tukey’s honest significant difference (HSD) test when comparing at least three conditions. A p-value is considered statistically significant (*p < 0.05, **p < 0.01, ***p < 0.001). All experiments were repeated at least three times.

Data availability statement

The data collected in this research can be obtained by reaching out to the corresponding author upon request. The data analyzed in this study were obtained from Gene Expression Omnibus and the following accession numbers are GSE64143, GSE78201, GSE151083, GSE210847, GSE197780, GSE183100, GSE138460, and GSE205275.

Results

IGFBP3 expression is upregulated in enzalutamide-resistant prostate cancer

We have previously generated enzalutamide-resistant C4–2B MDVR cells through chronically exposing C4–2B cells to increasing doses of Enzalutamide (17–21). Our transcriptomic sequencing data revealed a remarkable increase in IGFBP3 gene expression in MDVR cells compared to parental C4–2B cells and significant enrichment of IGFBP-mediated gene pathways via Gene Set Enrichment Analysis (GSEA) (Figure 1A). Validation experiments confirmed that MDVR cells express significantly higher IGFBP3 protein levels than parental C4–2B cells (Figure 1B). To assess whether IGFBP3 abnormal overexpression is a general feature of enzalutamide resistance, we examined its expression in enzalutamide-resistant castration-resistant prostate cancer (CRPC) models derived from LNCaP xenografts according to GSE138460. Similar to the C4–2B MDVR model, transcriptomic analysis showed increased IGFBP3 expression in enzalutamide-resistant 42D, 42F, and 49F cell lines compared to the parental 16D CRPC and LNCaP CSPC cells (Figure 1C). These findings were validated via qPCR, which confirmed that IGFBP3 mRNA expression was significantly higher in resistant models (Figure 1D). Protein analysis further supported this observation, demonstrating increased IGFBP3 expression in 42D and 42F cells (Figure 1D). Extending these findings, genomic analyses of long-term enzalutamide-resistant cells (LNCaP, VCaP, LAPC-4, CWR-R1) revealed a consistent increase in IGFBP3 expression compared to their parental counterparts (Figure 1E). Independent C4–2B enzalutamide-resistant (C4–2B ENZR) cell models from GSE151083 and GSE210848 also exhibited significantly higher IGFBP3 expression (Figure 1F).

Figure 1. IGFBP3 is highly expressed in models of enzalutamide resistance.

(A) The IGFBP3 gene expression in MDVR compared to parental C4–2B cells was determined by RNAseq. GSEA plots were used to evaluate the significance of the IGFBP signaling pathway enrichment. (B) The IGFBP3 protein level in MDVR compared to parental C4–2B cells was determined by immunoblot. (C) The IGFBP3 gene expression in enza-resistant 42D, 42F, and 49F was compared to the 16D and LNCaP cell lines in the RNAseq dataset (GSE138460). (D) The IGFBP3 mRNA and protein in 42D and 42F vs. 16D and LNCaP cells were determined by RT-qPCR and immunoblot. (E) The IGFBP3 mRNA expression levels in both enza-treated and enza-resistant cells compared to parental in VCaP, LNCaP, LAPC-4, and CWR-R1 cells (GSE78201). (F) IGFBP3 mRNA levels in C4–2B enza-resistant cell lines compared to parental cells in datasets GSE151083 and GSE210847. P value less than 0.05 was considered significant (*, p < 0.05; **, p < 0.01; ***, p < 0.001; ****, p < 0.0001). Statistical analysis was performed using Student’s t test and one- way ANOVA.

Having demonstrated that IGFBP3 is overexpressed in the resistant models, we further determined whether enzalutamide treatment directly enhances IGFBP3 expression. We treated C4–2B cells with 20 μM enzalutamide for 48 hours and measured IGFBP3 mRNA and protein levels. Enzalutamide treatment significantly increased IGFBP3 expression compared to untreated controls (Figure 2A). Additionally, dose-response analysis revealed that 2.5 μM enzalutamide significantly induced IGFBP3 expression, which further increased at higher doses (Figure 2B). Consistent with these enzalutamide-resistant experimental models, IGFBP3 expression was significantly upregulated in CRPC patients following enzalutamide treatment compared to pre-treatment levels (Figure 2C–2D). Analysis of the TCGA PRAD clinical dataset indicated that patients with higher Gleason Scores exhibited elevated IGFBP3 mRNA expression (Figure 2E). Moreover, Kaplan-Meier survival curve analysis revealed that high IGFBP3 expression correlated with shorter disease-free survival (Figure 2F). Collectively, clinical evidence and experimental resistance models suggest that IGFBP3 expression is upregulated following enzalutamide treatment, and elevated IGFBP3 levels are associated with treatment resistance and poor survival.

Figure 2. Enzalutamide induces IGFBP3 expression in advanced PCa patients.

(A) The IGFBP3 mRNA and protein levels in C4–2B cells treated with or without 20 μM enzalutamide for 48 h by qPCR and immunoblot. (B) Enza treatment increases mRNA expression of IGFBP3 in C4–2B cells under the indicated doses by qPCR. (C) The IGFBP3 mRNA levels pre- and post-enzalutamide treatment in prostate cancer patients RNAseq data GSE197780 via paired t-test and Wilcoxon test. (D) The IGFBP3 mRNA levels in ADT and enzalutamide-treated prostate cancer in GSE183100 RNAseq data. (E) The IGFBP3 gene expression levels in tumor samples of different Gleason scores in the TCGA PRAD (Cell 2015). (F) Disease-free survival of IGFBP3 expression in MSCKK2010 cohorts (GSE21032) via Kaplan-Meier Survival analysis. P value less than 0.05 was considered significant (*, p < 0.05; **, p < 0.01; ***, p < 0.001; ****, p < 0.0001). Statistical analysis was performed using Student’s t test and one- way ANOVA.

Inhibition of IGFBP3 reduces cell growth and re-sensitizes resistant cells to Enzalutamide treatment

Given the strong association between IGFBP3 and enzalutamide resistance, we investigated whether small interfering RNA (siRNA)-mediated IGFBP3 knockdown affects the viability of enzalutamide-resistant prostate cancer cells. We found that silencing IGFBP3 decreases IGFBP3 mRNA and protein levels in C4–2B MDVR cells (Figure 3A). Notably, IGFBP3 depletion led to increased cleaved-PARP expression (Figure 3A), suggesting enhanced apoptotic cell death. Functional assays demonstrated that IGFBP3 knockdown significantly reduced C4–2B MDVR cell viability, with an even greater reduction observed when combined with enzalutamide treatment, which coincides with increased cleaved-PARP expression (Figure 3B–3C). Similar results were obtained in the additional two enzalutamide-resistant 42D and 42F models, where IGFBP3 knockdown induced cleaved-PARP expression and significantly reduced cell viability, with enhanced effects in combination with enzalutamide (Figure 3D–F). Colony formation assays supported these findings, as siRNA-mediated IGFBP3 silencing combined with enzalutamide treatment dramatically inhibited the ability of colonial formation in C4–2B MDVR cells (Figure 3G). To further validate these results in a 3D tumor-like environment, we assessed the impact of IGFBP3 inhibition on spheroids derived from C4–2B MDVR cells. Combination treatment with enzalutamide and IGFBP3 knockdown significantly reduced spheroid formation and viability (Figure 3H). Collectively, these results indicate that IGFBP3 inhibition suppresses cell growth and restores sensitivity to enzalutamide.

Figure 3. IGFBP3 depletion reduces growth and induces apoptosis in enza-resistant cells.

(A) Knocking down IGFBP3 in MDVR cells with siRNA-IGFBP3 was validated by RT-qPCR and immunoblot. (B) The cell growth assay was performed on MDVR cells with IGFBP3 silencing or in combination of enzalutamide treatment. (C) The protein expression of IGFBP3 and c-PARP in MDVR cells with IGFBP3 siRNA or combination with enzalutamide. (D) The IGFBP3 and c-PARP protein levels in IGFBP3 siRNA-transfected 42D and 42F cells via immunoblot. (E-F) The cell growth assay of IGFBP3 siRNA and enzalutamide in 42D and 42F cell lines. (G) Colony formation assay of MDVR cells treated with IGFBP3 siRNA or in combination with enzalutamide. (H) Spheroid formation assay of MDVR cells with indicated treatments visualized by LIVE/DEAD staining and measured by CellTiter-Glo^®. P value less than 0.05 was considered significant (*, p < 0.05; **, p < 0.01; ***, p < 0.001; ****, p < 0.0001). Statistical analysis was performed using Student’s t test and one- way ANOVA.

Silencing IGFBP3 suppresses SphK1/S1P signaling pathway

IGFBP3 has been implicated in sphingolipid metabolism by activating sphingosine kinase 1 (SphK1), which promotes sphingosine-1-phosphate (S1P) production and reduces ceramide accumulation (51,52,55–58). Given its role in enzalutamide resistance, we examined whether IGFBP3 regulates the SphK1/S1P pathway (59). RT-qPCR analyses confirmed that IGFBP3 knockdown significantly decreased SphK1 mRNA expression in MDVR cells (Figure 4A). Western blot analysis further demonstrated reduced SphK1 protein levels and increased PARP cleavage upon IGFBP3 depletion (Figure 4B). Additionally, IGFBP3 knockdown significantly decreased S1P secretion in MDVR cells via ELISA analysis (Figure 4C). GSEA revealed that the S1P pathway was significantly enriched in the MDVR control (NES=1.502, p<0.05) compared to IGFBP3 knockdown cells (Figure 4D), supporting the role of IGFBP3 in activating SphK1/S1P signaling and contributing to enzalutamide resistance. In intrinsically resistant 22Rv1 cells, similar findings have been shown that genetic modulation of IGFBP3 demonstrates a strong reduction in gene expression (Figure 4E and 4F) and S1P secretion (Figure 4G). Combination treatment with IGFBP3 knocking down resensitized 22Rv1 cells to enzalutamide (Figure 4H). Furthermore, we overexpressed IGFBP3 in C4–2B cells to determine whether IGFBP3 overexpression alters sensitivity to enzalutamide through the sphingolipid pathway. We transiently overexpressed an IGFBP3 plasmid (pIGFBP3), which led to increased mRNA expression of IGFBP3 and SphK1 in C4–2B cells (Figure 4I). Western blotting showed the upregulation of IGFBP3 and SphK1 protein expression, and reduced c-PARP level, indicating the mitigated apoptotic death in C4–2B cells (Figure 4J). Interestingly, ELISA reveals that pIGFBP3 C4–2B cells secreted higher levels of S1P compared to C4–2B cells transfected with the PCDNA3.1 vector control (Figure 4K). We also found that overexpression of IGFBP3 conferred partial resistance to enzalutamide in C4–2B cells (Figure 4L). Thus, these results indicate that targeting the SphK1-S1P signaling axis via inhibiting IGFBP3 or SphK1 could offer potential therapeutic strategies to overcome enzalutamide resistance.

Figure 4. IGFBP3 mediates enzalutamide resistance through SphK1.

(A) The SPHK1 mRNA level in IGFBP3 siRNA-transfected MDVR cells by qPCR. (B) The protein levels of IGFBP3, c-PARP, and SPHK1 were measured in MDVR cells after knocking down IGFBP3 by immunoblot. (C) The secretion level of S1P in MDVR cells after siRNA IGFBP3 transfection ELISA. (D) GSEA analysis of S1P/S1P1 pathway enrichment in MDVR cells with siIGFBP3 knockdown. (E) The mRNA levels of IGFBP3 (E) and SPHK1 (F) in 22Rv1 cells transfected with siIGFBP3. (G) The S1P secretion level was measured in siIGFBP3-transfected 22Rv1 cells by ELISA. (H) The cell growth assay of 22Rv1 cells with the indicated treatments. (I-J) Transient overexpression of IGFBP3 in C4–2B cells was examined via RT-qPCR and western blotting. (K) The IGFBP3-overexpressed C4–2B cells induced S1P secretion levels by ELISA. (L) The sensitivity to enzalutamide in IGFBP3-overexpressed C4–2B cells was measured by CCK-8. P value less than 0.05 was considered significant (*, p < 0.05; **, p < 0.01; ***, p < 0.001; ****, p < 0.0001). Statistical analysis was performed using Student’s t test and one- way ANOVA.

SphK1 knockdown enhances enzalutamide sensitivity in vitro

Since IGFBP3 inhibition re-sensitizes resistant cells to enzalutamide, we determined whether targeting IGFBP3-mediated SphK1 signaling would alter the sensitivity of resistant cells to enzalutamide treatment. The SphK1 inhibitor, SKI-II, has been shown to inhibit NEPC cell growth (49). We used both siRNA gene silencing and pharmacologic inhibition of SphK1 to test their effect on enzalutamide treatment. SKI-II inhibited the growth of MDVR cells in a dose-dependent manner with the IC₅₀ value of 11.14 μM (Figure 5A). We found that SKI-II treatment decreased SphK1 protein levels and increased cleaved PARP expression (Figure 5B). Since SphK1 catalyzes sphingosine into S1P, we examined if SKI-II can inhibit SphK1-mediated S1P production in MDVR cells. We found that SKI-II significantly reduced S1P secretion levels (Figure 5C). Next, we tested whether SKI-II can improve enzalutamide efficacy within the resistant models. The siRNAs of SphK1 also inhibited SphK1 protein levels while increasing cleaved-PARP (Figure 5D), diminished S1P secretion levels (Figure 5E), and enhanced enzalutamide sensitivity (Figure 5F). Notably, SKI-II treatment combined with enzalutamide led to a significant reduction in MDVR cell growth and colony formation (Figure 5G). Furthermore, we found that SKI-II combination with enzalutamide reduced both MDVR spheroid formation and viability (Figure 5H). In summary, these data suggest that targeting the IGFBP3-mediated SphK1 axis serves as a viable approach to overcome the resistance to enzalutamide treatment in CRPC.

Figure 5. Inhibition of SphK1 by small-molecule compound SKI-II re-sensitizes cells to enzalutamide.

(A) The IC₅₀ of SKI-II in MDVR cells with the indicated doses. (B) The protein levels of SPHK1 and c-PARP in SKI-II-treated MDVR cells were measured by immunoblot. (C) The SKI-II treatment reduced the S1P secretion levels quantified by ELISA. (D) Targeting effects of SKI-II compared with SphK1 siRNA treatment in MDVR cells were evaluated by immunoblot. (E) The S1P secretion in MDVR cells after SphK1 siRNA transfection by ELISA assay. (F) The cell viability of MDVR cells with single or combination treatment of siSphK1 or enzalutamide. (G) Cell viability and clonogenic formation of MDVR cells treated with either single or in combination of enza or SKI-II. Drug synergism was determined by the combination drug index (CDI). (H) The viability of the MDVR spheroids was determined by LIVE/DEAD staining and CellTiter-Glo^®. P value less than 0.05 was considered significant (*, p < 0.05; **, p < 0.01; ***, p < 0.001; ****, p < 0.0001). Statistical analysis was performed using Student’s t test and one- way ANOVA.

Targeting SphK1 signaling with SKI-II improves enzalutamide treatment in vivo

To examine whether targeting SphK1 enhances enzalutamide treatment can be translated into in vivo scenario. We first validated in the intrinsic 22Rv1 cells for the effectiveness of SKI-II in vitro and spheroid viability. Our data indicated a synergistic effect of SKI-II and enzalutamide in 22Rv1 cells in 2D cell proliferation (Figure 6A) and 3D spheroids formation assays (Figure 6B). Further, we subcutaneously implanted 22Rv1 cells into immunocompromised male mice to establish tumor xenografts and treated them with SKI-II in combination with enzalutamide. As shown in Figure 6C, 22Rv1 tumor xenografts were enzalutamide-resistant, as there is no significant difference in tumor volume or weight between the enzalutamide and vehicle treatment groups. In contrast, SKI-II treatment alone reduced 22Rv1 tumor growth (Figure 6C–6D). Notably, combining SKI-II with enzalutamide further suppressed both tumor growth and tumor weight, demonstrating significantly greater efficacy compared to SKI-II monotherapy (Figure 6C–6D). Mouse body weights were not affected by any treatment groups, indicating no spontaneous toxicity from the compounds (Figure 6E). Additionally, we observed decreased S1P secretion in serum harvested from both the SKI-II monotherapy and SKI-II plus enzalutamide combination treatment groups compared to the vehicle control group (Figure 6F). Immunohistochemical staining of Ki67 in tumors revealed that SKI-II treatment significantly reduced tumor cell proliferation, while SKI-II and ENZ combination treatment further reduced tumor cell proliferation in comparison to SKI-II alone (Figure 6G–6H). Consistently, terminal deoxynucleotidyl transferase dUTP nick-end labelling (TUNEL) staining showed an increase in the levels of apoptotic cell death within the ENZ and SKI-II combined group (Figure 6I). These results suggest that inhibition of SphK1 by SKI-II alone can suppress enzalutamide-resistant tumor growth, while the combination of SKI-II with enzalutamide further enhances treatment efficacy.

Figure 6. SKI-II synergizes with enzalutamide in vitro and in vivo.

(A) The viability and clonogenic formation to evaluate the synergism of enzalutamide and SKI-II in 22Rv1 cells. (B) The viability of the 22Rv1 spheroids was evaluated by LIVE/DEAD cell staining and CellTiter-Glo^®. (C) SKI-II and enzalutamide combined treatment decreased 22Rv1 tumor growth and (D) reduced tumor weight. (E) The body weight of the 22Rv1 xenograft mice treatment groups was observed. (F) The blood serum was collected from the 22Rv1 xenografts, and the S1P levels were measured by ELISA. (G) H&E staining and IHC staining of Ki67 and TUNEL were performed on fixed tumor tissues from the 22Rv1 xenograft. (H) Ki67 and (I) TUNEL positive stained cells were quantified by FIJI software. P value less than 0.05 was considered significant (*, p < 0.05; **, p < 0.01; ***, p < 0.001; ****, p < 0.0001). Statistical analysis was performed using Student’s t test and one- way ANOVA.

Discussion

Our study identifies IGFBP3 as a key mediator of enzalutamide resistance in prostate cancer and highlights the therapeutic potential of targeting IGFBP3 and its downstream SphK1/S1P signaling axis as depicted in Figure 7. We demonstrate that IGFBP3 expression is significantly upregulated in multiple enzalutamide-resistant prostate cancer models and that silencing IGFBP3 diminishes prostate cancer cell growth and triggers apoptotic cell death. Here, we determined that IGFBP3 expression directly potentiates SPHK1 signaling to induce S1P formation, thereby enabling cancer cell survival and resistance to enzalutamide. Targeting SphK1 with the inhibitor SKI-II suppressed SphK1 activity, reduced S1P production, enhanced enzalutamide sensitivity in vitro, and significantly inhibited resistant tumor growth while enhancing enzalutamide sensitivity in vivo.

Figure 7. IGFBP3–SphK1–S1P axis drives resistance to enzalutamide.

In treatment-sensitive prostate cancer, AR signaling drives tumor growth and is effectively blocked by enzalutamide. In resistant tumors, upregulation of IGFBP3 activates SphK1, increasing production of S1P, which engages S1PR to promote growth, survival, and resistance. The shift in the sphingolipid rheostat from ceramide to S1P (pro-survival) underlies ARSI resistance, which can be blocked by SphK1 inhibition (SKI-II) (Created with BioRender.com).

Our findings demonstrate that IGFBP3 is consistently overexpressed in multiple enzalutamide-resistant prostate cancer models, including C4–2B MDVR, LNCaP-derived 42D and 42F cells, and long-term resistant variants of LNCaP, VCaP, LAPC-4, and CWR-R1. We found that enzalutamide treatment itself induces IGFBP3 expression in parental C4–2B cells, suggesting a direct role of the drug in driving IGFBP3-mediated resistance. Clinically, IGFBP3 levels are elevated in CRPC patient samples post-enzalutamide treatment and are associated with high Gleason scores and shorter disease-free survival (43,44). The observed link between IGFBP3 overexpression and neuroendocrine differentiation underscores its potential role in aggressive prostate cancer phenotypes (60–63). Prior studies have shown that IGFBP3 enhances resistance to chemotherapy and radiotherapy by activating DNA repair pathways in triple-negative breast cancer (TNBC) and oral squamous cell carcinoma (55,64,65). In glioma models, IGFBP3 knockdown suppresses tumor growth by inducing G2/M cell cycle arrest and apoptosis (66). Consistent with these findings, we recently discovered that IGFBP3 is upregulated in Olaparib-resistant (OlapR) prostate cancer cells, and its inhibition re-sensitizes these models to PARP inhibition (45,46), further implicating IGFBP3 in therapy resistance. Together, our results highlight IGFBP3 as a key player in enzalutamide resistance and disease progression in prostate cancer.

Functional investigations confirm that IGFBP3 is not merely a marker of enzalutamide resistance but actively contributes to its development. Knockdown of IGFBP3 significantly reduces the viability of enzalutamide-resistant cell lines and enhances their sensitivity to enzalutamide. Mechanistically, IGFBP3 depletion promotes apoptosis, as evidenced by increased cleaved-PARP expression. We provide evidence that IGFBP3 is sufficient for enzalutamide resistance by demonstrating that IGFBP3 overexpression in parental C4–2B cells induces SphK1 expression and S1P production, which exerts pro-survival and anti-apoptotic affects in prostate cancer cells, thereby promoting resistance. These findings suggest that IGFBP3-driven enzalutamide resistance is mediated, at least in part, through the activation of the SphK1/S1P signaling pathway. Past studies have shown that SphK1/S1P signaling contributes to enzalutamide resistance and drives neuroendocrine transdifferentiation in CRPC (49,52). Our findings reveal, for the first time, that IGFBP3 directly activates the SphK1/S1P axis to fuel enzalutamide resistance. Without IGFBP3, the sphingolipid rheostat undergoes perturbations which forces ceramide levels to rise, thus halting the production of S1P and promoting apoptotic cell death. Hence, enzalutamide therapy imposes selective pressure that dysregulates sphingolipid composition, enhancing SphK1 expression and S1P production in resistant CRPC. Inhibiting IGFBP3 or SphK1 shifts the sphingolipid balance toward apoptosis, thus re-sensitizing resistant cells to enzalutamide.

Consistent with this hypothesis, our results indicate that IGFBP3 knockdown suppresses SphK1 expression and reduces S1P secretion in enzalutamide-resistant models. GSEA further supports the role of IGFBP3 in activating the SphK1/S1P pathway, revealing significant enrichment of S1P-related signaling in resistant cells. Importantly, pharmacologic inhibition of SphK1 using SKI-II effectively suppresses cell viability and enhances enzalutamide sensitivity in both in vitro and ex vivo models. SKI-II treatment reduces SphK1 protein levels, decreases S1P secretion, and promotes apoptosis, as indicated by increased cleaved-PARP and TUNEL expression. These effects are recapitulated in siRNA-mediated knockdown experiments, further validating the essential role of SphK1 in IGFBP3-driven resistance.

Our in vivo studies provide compelling evidence for the translational potential of targeting the IGFBP3/SphK1 axis. In 22Rv1 xenograft models, SKI-II monotherapy significantly suppresses tumor growth, and its combination with enzalutamide leads to even greater tumor inhibition. Notably, the combination treatment reduces S1P secretion in serum, indicating effective suppression of SphK1 activity. Importantly, SKI-II treatment is well tolerated, as no significant changes in body weight were observed across treatment groups. These findings strongly support the therapeutic potential of SphK1 inhibition in overcoming enzalutamide resistance.

In summary, our study provides mechanistic insights into the role of IGFBP3 in enzalutamide resistance and establishes its regulation of the SphK1/S1P signaling pathway as a critical contributor to this phenotype. Given that IGFBP3 overexpression is associated with poor clinical outcomes and neuroendocrine differentiation, targeting IGFBP3 or its downstream SphK1/S1P axis represents a promising strategy to enhance the efficacy of enzalutamide in resistant prostate cancer. Future investigations should focus on developing strategies selectively targeting IGFBP3-SphK1 signaling pathway and evaluating their therapeutic efficacy in preclinical and clinical settings.