Targeting FGFR1 enhances olaparib sensitivity via MAPK-mediated BRCA2 downregulation in mCRPC

Introduction

Metastatic castration-resistant prostate cancer (mCRPC) represents a lethal stage of prostate cancer characterized by disease progression despite androgen deprivation therapy (ADT) (1-3). Although next-generation androgen receptor (AR)-targeted agents such as enzalutamide and abiraterone have improved clinical outcomes, resistance inevitably develops (4-8). As a result, mCRPC remains incurable, with a poor overall survival of only 30% at 5 years (9-11).

Genomic studies have revealed that a significant subset of mCRPC harbors defects in homologous recombination repair (HRR) pathways, with BRCA2 being the most frequently altered gene (11-13). These defects render tumor cells vulnerable to PARP inhibitors (PARPi), such as olaparib, through synthetic lethality (14-16). Clinical trials have demonstrated the efficacy of olaparib in patients with HRR mutations, particularly BRCA2 alterations, leading to its regulatory approval in this setting (17-20). Nevertheless, resistance to PARP inhibition remains a clinical challenge, and the molecular basis underlying variable responses in BRCA2 wild-type or high-expressing tumors is incompletely understood (21).

Recent transcriptomic analyses suggest that aberrant fibroblast growth factor (FGF) signaling is frequently activated in advanced prostate cancer, especially via overexpression or amplification of FGFR1 (22,23). FGFR1 plays a key role in tumor progression, metastasis, and therapeutic resistance (23-25). While its contributions to proliferation and survival are well established, the impact of FGFR1 signaling on DNA repair capacity and PARPi responsiveness has not been previously investigated (26,27).

In this study, we identify a previously unrecognized regulatory axis linking FGFR1 to BRCA2 expression in mCRPC. Through integrated analysis of public mCRPC datasets and functional validation in mCRPC cells, we demonstrate that FGFR1 expression is positively correlated with BRCA2 levels and that FGFR1 inhibition downregulates BRCA2 expression. Functionally, targeting FGFR1 enhances the antitumor activity of olaparib in vitro and in vivo. These findings not only reveal a novel mechanism of PARPi resistance but also provide a rationale for combinatorial treatment strategies and biomarker-guided patient stratification in mCRPC. We present this article in accordance with the ARRIVE reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-490/rc).

Methods

Bioinformatics analysis

We analyzed publicly available metastatic prostate cancer cohorts, including the SU2C/PCF-PolyA cohort (n=266), the SU2C/PCF-Capture cohort (n=208), and GSE118435 cohort (n=41). The SU2C/PCF-PolyA and SU2C/PCF-Capture datasets were obtained from https://www.cbioportal.org/, and the GSE118435 dataset was obtained from http://bioinfo.jialab-ucr.org/PCaDB/.

Somatic mutation data from the SU2C/PCF-PolyA cohort were used to evaluate the mutational spectrum. We performed gene set enrichment analysis (GSEA) analyses across three independent mCRPC transcriptomic cohorts (SU2C/PCF-PolyA, SU2C/PCF-Capture, and GSE118435), comparing BRCA2-high versus BRCA2-low groups. Expression profiles of FGFR1-4 were then compared between these groups. The correlation between BRCA2 and FGFR1 expression was examined by Pearson correlation analysis.

Finally, samples were stratified into BRCA2-high and BRCA2-low groups using the cohort-specific median for GSEA in each cohort. Enrichment was considered significant at FDR <0.25 with leading-edge analysis. Pathways were intersected with canonical FGFR1-downstream modules (MAPK/ERK, PI3K/AKT, PLCγ), which consistently converged on MAPK/ERK across all three datasets. Statistical significance was defined as a two-tailed P value <0.05. All analyses were performed in R (version 4.4.1) unless otherwise specified. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Cell culture

The cell lines used in this study were purchased from the American Type Culture Collection (ATCC, VA, USA). The primary cell lines involved include DU145, PC3 and human embryonic kidney (HEK) 293T cells. All cell lines were authenticated by ATCC through short tandem repeat (STR) profiling to confirm their identity and tested for the absence of mycoplasma contamination. The complete culture medium consisted of Dulbecco’s modified Eagle’s medium (DMEM) (Gibco, New York, USA; 10270-106) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin (10,000 U/mL). The cells were maintained in a 5% CO₂ incubator at 37 ℃.

Cell line construction

Short hairpin RNA (shRNA) plasmids were purchased from KeLai Biological Technology Co., Ltd. Lentiviral packaging was performed using the plasmids along with packaging vectors psPAX2 and pMD2.G, and the transfection reagent TransfectTurbo (Thermo Fisher Scientific, Waltham, MA, USA; 01300669) in HEK293T cells. After a 48-hour incubation for viral assembly, the medium supernatant was collected to infect the DU145 cells. Two days after lentiviral infection, the culture medium was replaced with puromycin-containing medium (2 µg/mL) to select transduced cells. Subsequently, individual clones were isolated, expanded, and validated by sequencing and functional assays. To achieve transient overexpression of FGFR1 in PC3 cells, we transfected cells with a pcDNA3.1-FGFR1 expression plasmid (empty pcDNA3.1 as control) according to the manufacturer’s instructions. The sequences of the shRNA are shown in Table S1.

Animal model construction

DU145 WT cells were prepared and subcutaneously injected into 4-week-old male BALB/c nude mice (GemPharmatech Guangdong, Foshan, China). Mice were acclimatized to the housing conditions for 1 week prior to experimentation to ensure robust health and suitability at a temperature of 20–25 ℃, and relative humidity of 50–60%, after which the follow-up experiment was conducted. A total of 2.4×10⁶ cells were injected into the left dorsal region of each mouse. Mice were randomly assigned to two groups (n=5) and marked accordingly. Tumor growth was monitored every 3 days and recorded by measuring tumor volume (length × width² × 0.52) and noting the time of injection. Three weeks post-cell inoculation, one group received olaparib (Selleckchem, Houston, USA; S1060, 30 mg/kg/day) via intraperitoneal injection, while the other group received a combination of olaparib (30 mg/kg/day) and PD173074 (Selleckchem, S1264, 20 mg/kg/day) for 2 weeks. The mice were euthanized 5 weeks (day 35) post-injection. All experiments involving animals were conducted according to the ethical policies and procedures approved by the South China University of Technology (No. S-2023-078-01).

Immunohistochemistry

Subcutaneous tumor tissues harvested 5 weeks after DU145 cells injection from nude mice were fixed in 4% paraformaldehyde at room temperature for 24 hours, followed by dehydration, deparaffinization, and embedding in paraffin. Tissues were sectioned into 4 µm-thick slices, mounted on glass slides, and dried at 60 ℃ for 2 hours. The sections were subjected to antigen retrieval via using citric acid buffer (pH 6.0). For immunohistochemical analysis, primary antibodies against Cleaved Caspase-3 and PCNA were used. Antibody concentrations were determined according to the manufacturer’s specifications. DAB staining (Fuzhou Maxin Biotech Development Co., Ltd., Fuzhou, China; DAB-0031) and hematoxylin counterstaining (Fuzhou Maxin Biotech Development Co., Ltd., DAB-0033) according to standard protocols. Finally, sections were mounted with neutral balsam (Fuzhou Maxin Biotech Development Co., Ltd., DAB-0033). Details of the antibodies used are provided in Table S2.

Western blot analysis

Cell lysates were prepared by homogenizing cells in Radioimmunoprecipitation (RIPA) Assay buffer containing phenylmethylsulfonyl fluoride (PMSF) proteinase inhibitor (100×, Beyotime, Shanghai, China; #ST506) and phosphatase inhibitor cocktail (50×, Bocai Biotechnology, Shanghai, China; #R0127). The lysates were mixed with 5× SDS loading buffer (Biosharp, Hefei, China; #BL502A) and boiled at 100 ℃ for 10 minutes to generate protein samples. Proteins were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred onto polyvinylidene fluoride (PVDF) membranes. The membranes were incubated with primary antibodies overnight at 4 ℃, followed by three 10-minute washes in TBST. Secondary antibodies were applied for 1-hour incubation at room temperature, with additional three 10-minute TBST washes. Protein signals were visualized using the ChemiDoc MP Imaging System (BIO-RAD, Hercules, California, USA, #12003154). Details of the antibodies used are provided in Table S2.

RNA sequencing

Total RNA was extracted from cells using TRIzol reagent (Invitrogen, CA, USA, #50175111). The quantity and purity of RNA were determined using a NanoDrop ND-1000 spectrophotometer (NanoDrop, Wilmington, DE, USA), with acceptable criteria defined as A260/A280 ratio ≥1.8 and A260/A230 ratio ≥2.0. The cDNA library was constructed from fragmented mRNA through reverse transcription. Paired-end sequencing (PE150) was performed on the Illumina NovaSeq 6000 (LC-Bio Technology Co., Ltd., Hangzhou, China) according to the manufacturer’s instructions. The execution of the entire RNA-seq process was carried out according to the overview of previous studies (28).

Quantitative real-time PCR

Total RNA was extracted from cells using TRIzol (Invitrogen, CA, USA, #50175111) reagent. The quantity and purity of RNA were determined using a NanoDrop ND-1000 spectrophotometer. Residual genomic DNA was removed using qPCR (+gDNA Wiper) Kit (Vazyme, Nanjing, China; #R323). cDNA was synthesized using HiScript^® III RT SuperMix (Vazyme, #R206). The cDNA, RNA-free H2O, and 2× ChamQ Universal SYBR qPCR Master Mix (Vazyme, #Q711) were mixed and added to qPCR 96-well plates containing primers. Amplification was performed using the Applied Biosystems QuantStudio™ 1 System (Thermo Fisher Scientific, Waltham, MA, USA, #A40427), and real-time fluorescence signals were monitored. Relative mRNA levels were normalized to β-actin (ACTB) expression. The primer sequences are shown in Table S3.

Cell Counting Kit-8 (CCK-8)

Cells were seeded into 96-well plates at a density of 800 cells/well (6 wells per sample). Plates were incubated in a humidified atmosphere containing 37 ℃ and 5% CO₂ for 24, 48, 72, 96, 120, and 144 hours. At each time point, 100 µL of CCK-8 solution was added to each well and incubated for 1 hour. Absorbance at 450 nm was measured using a microplate reader.

Apoptosis assay

Cells were stained with AnnexinV-APC/7-AAD apoptosis detection kit (MultiSciences, Hangzhou, China; #AP105) following the manufacturer’s instructions. A total of 1×10⁶ cells were analyzed using a flow cytometer (BD FACSCanto II, BD Biosciences, Franklin Lakes, NJ, USA). Apoptotic cell rates were quantified using FlowJo software (version 10.8).

Statistical analysis

All experiments were independently repeated at least three times. At each time point, each experiment was recorded from ≥3 technical replicates per condition. Data were analyzed using GraphPad software (version 9.5.1). Differences between groups were evaluated using independent two-tailed t-tests, and error bars represent mean ± standard deviation (SD). Statistical significance was defined as P<0.05.

Results

FGFR1 expression positively correlates with BRCA2 expression in mCRPC

To explore the relationship between FGFR1 and DNA repair pathways in mCRPC, we analyzed the SU2C/PCF-PolyA transcriptomic dataset (n=266). Among the top 12 most frequently altered pathways (29), HRR and FGF signaling ranked second (25.9%) and sixth (10.5%), respectively (Figure 1A). Within these categories, BRCA2 and FGFR1 emerged as the most frequently altered genes (Figure 1B). Stratification of three independent mCRPC transcriptomic datasets revealed a consistent, dataset-wide positive association between high FGFR1 expression and elevated BRCA2 expression (Figure 1C-1H). This correlation was not totally observed with FGFR2-4 or with BRCA1 expression (Figure 1C-1Q). Pearson correlation analyses confirmed a robust positive correlation between FGFR1 and BRCA2 expression across all datasets (Figure 1R-1T).

Figure 1 FGFR1 expression positively correlates with BRCA2 expression in mCRPC. (A,B) The most frequently altered signaling pathways in 266 mCRPC samples, as identified through genomic analysis of the SU2C/PCF-PolyA dataset (A), and the alteration frequencies of genes involved in HRR and FGF signaling (B). (C-E) Expression of BRCA1 and BRCA2 across three independent mCRPC datasets (SU2C/PCF-PolyA, SU2C/PCF-Capture, GSE118435), stratified by FGFR1 expression levels. (F-H) Expression levels of FGFR1-4 in indicated datasets, stratified by BRCA2 expression. (I-Q) Expression of BRCA1 and BRCA2 across three independent mCRPC datasets, stratified by FGFR2-4 expression levels. (R-T) Pearson correlation analyses between FGFR1 and BRCA2 expression across indicated datasets. PolyA, Capture and GSE118435 represent the SU2C/PCF-PolyA cohort, SU2C/PCF-Capture cohort, and GSE118435, respectively; 95% CIs were provided in Tables S4-S6. CI, confidence interval; FGF, fibroblast growth factor; HRR, homologous recombination repair; mCRPC, metastatic castration-resistant prostate cancer.

FGFR1 inhibition downregulates BRCA2 expression in DU145 cells

Transcriptomic and qPCR analysis showed markedly higher FGFR1 and BRCA2 mRNA levels in DU145 cells compared to PC3 cells (Figure 2A,2B). Western blotting confirmed elevated protein levels of FGFR1 and BRCA2 in DU145 cells (Figure 2C). Knocking down of FGFR1 significantly reduced BRCA2 mRNA and protein levels (Figure 2D,2E). Similarly, pharmacological inhibition of FGFR1 using PD173074 resulted in a notable decrease in BRCA2 mRNA and protein expression (Figure 2F,2G).

Figure 2 FGFR1 inhibition downregulates BRCA2 expression in DU145 cells. (A) Heatmap showed transcriptomic expression of FGFR1 and BRCA2 in DU145 and PC3 cells. (B) qPCR analysis of FGFR1 and BRCA2 mRNA levels in DU145 and PC3 cells. (C) Western blot analysis of FGFR1 and BRCA2 protein expression in DU145 and PC3 cells. (D,E) qPCR and Western blot analysis of BRCA2 protein levels in FGFR1 depleted DU145 cells. (F,G) qPCR and Western blot analysis of BRCA2 protein expression in DU145 cells treated with the FGFR1 inhibitor PD173074 (1 μM, 6 h). ***, P<0.001. qPCR, quantitative real-time polymerase chain reaction.

FGFR1 depletion enhances the anti-proliferative effect of olaparib in DU145 cells

The CCK-8 assay was conducted to assess cell viability and proliferation, and the absorbance values were used to compare the differences in proliferative capacity among different treatment groups. Dose-response experiments using CCK-8 assays demonstrated significant proliferation inhibition at olaparib concentrations ≥10 µM (Figure 3A). The anti-proliferative effect of olaparib in PC3 cells is significantly greater than in DU145 cells (Figure 3B). FGFR1 knockdown significantly potentiated the anti-proliferative effect of olaparib in DU145 cells. Co-treatment with PD173074 and olaparib induced greater inhibition of cell proliferation than either monotherapy (Figure 3C,3D, Figure S1A,S1B). A xenograft model showed that combination therapy significantly reduced tumor growth compared to olaparib alone (Figure 3E-3G). Immunohistochemistry confirmed reduced proliferation in tumor tissues following co-treatment (Figure 3H).

Figure 3 FGFR1 depletion enhances the anti-proliferative effect of olaparib in DU145 cells. (A) CCK-8 assay showing the cell proliferation of olaparib with indicated concentrations in DU145 cells. (B) CCK-8 assay evaluating the effect of olaparib (10 μM) in DU145 and PC3 cells. (C) CCK-8 assay evaluating the effect of olaparib (10 μM) in FGFR1 depleted DU145 cells. (D) CCK-8 assay of DU145 cells co-treated with olaparib (10 μM) and PD173074 (1 μM). (E-G) Representative images of tumor-bearing nude mice (E), excised tumors (F), and tumor volume curves (G) following intraperitoneal administration of olaparib (30 mg/kg/day) or/and PD173074 (20 mg/kg/day) for 14 consecutive days. (H) Immunohistochemical staining for the proliferation marker PCNA in tumor sections obtained from each treatment group. “NC + olaparib” denotes negative-control cells treated with olaparib. “shFGFR1 + olaparib” denotes FGFR1-knockdown cells treated with olaparib. *, P<0.05; **, P<0.01; ***, P<0.001. CCK-8, Cell Counting Kit-8; DMSO, dimethyl sulfoxide; OD, optical density; PCNA, proliferating cell nuclear antigen.

Combined FGFR1 and PARP inhibition synergistically induces apoptosis

Flow-cytometric analysis of AnnexinV-APC/7-AAD-stained DU145 cells revealed that either FGFR1 knockdown or pharmacologic FGFR1 inhibition (PD173074) significantly increased olaparib-induced apoptosis (Figure 4A-4D). Combination with olaparib produces greater apoptosis than FGFR1 inhibition alone (Figure S1C-S1F). Western blot analysis demonstrated increased expression of Cleaved Caspase-3 in both FGFR1-depleted and PD173074-treated DU145 cells than control groups (Figure 4E,4F). Immunohistochemistry confirmed enhanced apoptosis in tumor tissues following co-treatment (Figure 4G).

Figure 4 Combined FGFR1 and PARP inhibition synergistically induces apoptosis. (A,B) Flow cytometric analysis of apoptosis in FGFR1 depleted DU145 cells treated with olaparib (10 μM, 60 h). (C,D) Flow cytometric analysis of DU145 cells co-treated with olaparib (10 μM, 72 h) and PD173074 (1 μM, 72 h). (E) Western blot analysis of apoptosis-related proteins in FGFR1 depleted DU145 cells treated with olaparib. (F) Western blot analysis of apoptosis-related proteins in DU145 cells co-treated with olaparib and PD173074. (G) Immunohistochemical staining for the apoptosis marker Cleaved Caspase-3 in tumor sections obtained from each treatment group. ***, P<0.001.

FGFR1 upregulates BRCA2 expression via MAPK/ERK pathway activation in mCRPC cells

To explore potential downstream mediators, we performed GSEA analyses across three independent mCRPC transcriptomic cohorts (SU2C/PCF-PolyA, SU2C/PCF-Capture, and GSE118435), comparing BRCA2-high versus BRCA2-low groups. Notably, among canonical FGFR1 signaling cascades (MAPK, PI3K-AKT, and PLCγ), the MAPK pathway emerged as the most consistently enriched in BRCA2-high tumors across all datasets (Figure 5A,5B).

Figure 5 FGFR1 upregulates BRCA2 expression via MAPK/ERK pathway activation in mCRPC cells. (A,B) Results of GSEA analysis of BRCA2 high and BRCA2 low groups across PolyA, Capture, and GSE118435. (C,D) qPCR and western blot showed the results of transient FGFR1 overexpression in PC3 and of MAPK inhibitor SL327 (10 μM, 22 h) treatment after overexpression. **, P<0.01; ***, P<0.001. GSEA, gene set enrichment analysis; mCRPC, metastatic castration-resistant prostate cancer; NES, normalized enrichment score; qPCR, quantitative real-time polymerase chain reaction.

To functionally validate this association, we transiently overexpressed FGFR1 in PC3 cells. FGFR1 overexpression led to marked upregulation of BRCA2 expression. Importantly, pharmacologic inhibition of MAPK/ERK signaling in this context attenuated ERK phosphorylation and significantly suppressed BRCA2 induction at both mRNA and protein levels (Figure 5C,5D).

Discussion

Recent studies have highlighted the pivotal role of FGFR1 signaling in the progression and therapeutic resistance of mCRPC (23,27). Aberrant activation of FGFR1, through amplification or overexpression, has been implicated in promoting castration resistance, metastatic dissemination, and poor clinical outcomes in advanced prostate cancer (22,23). While FGFR1 inhibition has shown promising antitumor effects in preclinical models, its contribution to treatment resistance mechanisms—particularly DNA damage response modulation—remained largely unexplored (27).

Our study presented the first evidence that FGFR1 positively regulates BRCA2 expression in mCRPC, thereby contributing to resistance against PARP inhibitor therapy. Our data supported a model in which FGFR1 signaling preserves BRCA2-dependent HRR, thereby limiting PARP-inhibitor activity via the MAPK pathway (Figure 6). Across three independent clinical transcriptomic cohorts, FGFR1 expression strongly correlated with BRCA2. To probe intermediates, we performed GSEA by stratifying samples into BRCA2-high vs. BRCA2-low groups in each cohort and intersected enriched pathways with canonical FGFR1 modules (MAPK/ERK, PI3K/AKT, PLCγ); these analyses converged on MAPK/ERK. Functionally, genetic or pharmacologic FGFR1 inhibition reduced BRCA2 expression and sensitized cells to the PARP inhibitor olaparib: in DU145, FGFR1 knockdown significantly enhanced olaparib-induced apoptosis, and in vivo co-treatment reduced xenograft growth and increased apoptotic markers. Xenograft studies enabled us to quantify the on-treatment therapeutic effect size on tumor growth and apoptosis under systemic dosing. Accordingly, in-vivo validation was required to strengthen causal inference and to demonstrate that the observed molecular regulation translates into a clinically meaningful antitumor effect.

Figure 6 Proposed model system of FGFR1-mediated olaparib sensitivity regulation. FGFR1 maintained BRCA2 expression via the MAPK pathways, thereby limiting the efficacy of olaparib. Genetic FGFR1 knockdown or pharmacologic inhibition with PD173074 reduced BRCA2 capacity, creating a DNA-repair defect that sensitized cells to PARP inhibition and promoted proliferation inhibition and apoptosis. Olaparib induced synthetic lethality in cells with loss of function of HRR, which led to cell growth inhibited and apoptosis increased. HRR, homologous recombination repair; mCRPC, metastatic castration-resistant prostate cancer.

Complementarily, transient FGFR1 overexpression in PC3 raised p-ERK and BRCA2, whereas MAPK inhibition blunted p-ERK and attenuated BRCA2 induction, supporting FGFR1-MAPK-BRCA2 as the operative axis. Placed within the broader mCRPC landscape, this pathway sits alongside other reported routes of PARP-inhibitor resistance-HRR restoration/reversion events, PI3K/AKT activation, replication-fork stabilization, and drug efflux, and suggests rational combinations in settings where MAPK suppression and BRCA2/HRR reduction are pharmacodynamically verified.

Across resistance pathways, a common convergence point is elevated BRCA2, which restores HRR capacity and attenuates PARP-inhibitor sensitivity. Prior studies established that non-mutational regulation of BRCA2 can meaningfully modulate HRR/PARPi response, the lncRNA PCAT-1 repressed BRCA2 and controlled HRR (30), and CHEK2 loss increased BRCA2 expression, enhanced HRR, and conferred PARPi resistance (21). Within this framework, our data indicated that FGFR1-MAPK/ERK signaling maintained high BRCA2, providing a mechanistic basis for reduced olaparib efficacy. Consistently, FGFR1 knockdown or PD173074 lowered BRCA2 and sensitized DU145 cells to olaparib, whereas transient FGFR1 overexpression in PC3 increased p-ERK and BRCA2, and MAPK inhibition blunted these effects. Together, these findings position BRCA2 upregulation as a functional hub of resistance and support biomarker-guided co-targeting in which on-treatment p-ERK suppression and BRCA2 down-modulation with durable benefit.

Importantly, our findings support the rationale for combining FGFR1 inhibition with PARP inhibitors as a synergistic strategy to enhance therapeutic efficacy in mCRPC. Given that BRCA2 expression is a key determinant of olaparib sensitivity, and FGFR1 appears to maintain BRCA2 levels, targeting FGFR1 may disrupt this compensatory mechanism, re-sensitizing tumors to DNA damage-induced cell death. This has immediate translational implications: mCRPC patients with intact but overexpressed BRCA2 and high FGFR1 may derive suboptimal benefit from olaparib alone.

Furthermore, FGFR1 expression itself may serve as a predictive biomarker for PARP inhibitor responsiveness. Stratifying patients based on FGFR1 levels could help identify those who are most likely to benefit from olaparib monotherapy versus those requiring combinatorial strategies. Prospective clinical validation is warranted to determine the utility of FGFR1 expression as a companion diagnostic. To better inform clinical translation, future studies will evaluate an in vitro spheroid model as a potentially equally useful, complementary platform for deeper mechanistic, potential toxicities and pharmacodynamic investigation.

Conclusions

In conclusion, our work identifies FGFR1 as a novel upstream regulator of BRCA2 and a modulator of olaparib sensitivity in mCRPC. This study supports the therapeutic potential of FGFR1 and PARP inhibitor co-targeting and lays the foundation for biomarker-guided precision treatment strategies in advanced prostate cancer.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the ARRIVE reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-490/rc

Data Sharing Statement: Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-490/dss

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-490/prf

Funding: This work was supported by grants from the National Natural Science Foundation of China (Nos. 82072813, 82373166 and 82573325), the Science and Technology Development Fund (FDCT) of Macao SAR (Nos. 0090/2022/A and 0116/2023/RIA2), Emergency Key Program of Guangzhou Laboratory (No. EKPG21-04), Guangzhou Municipal Science and Technology Project (No. 202201020346), Guangdong Province Key Areas R&D Plan Project (No. 2023B1111030006), and the Postdoctoral Fellowship Program (No. GZC20251388).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-490/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. All experiments involving animals were conducted according to the ethical policies and procedures approved by the South China University of Technology (No. S-2023-078-01).

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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