ZKSCAN5 transcriptional regulation of APOC1 modulates ferroptosis via PI3K/AKT/SREBP2/SLC1A5 axis

Abstract

Background

Prostate cancer is a great substantial health challenge among the cancer type with a high incidence and serving as the main cause of cancer-related deaths in men. Apolipoprotein C1 encodes a member of the apolipoprotein C family. The APOC1 has been confirmed as an oncogene of prostate cancer. However, the mechanism of how the APOC1 protein influence remains to be elucidated.

Methods

The expression of APOC1 was detected in both prostate cancer tissues and prostate cancer cell lines. The APOC1 knockdown and overexpression cell models were created. The effect of APOC1 on prostate cancer cell proliferation,metastasis, EMT and ferroptosis were explored by colony formation, wound healing,transwell assays, CCK-8 and western blotting in vitro and subcutaneous tumor formation in nude mice. Furthermore, the mechanism of how APOC1 inhibits ferroptosis in prostate cancer through PI3K/AKT/SREBP2/SLC1A5 was detected. Meanwhile, the interaction of APOC1 and ZKSCAN5 (zinc finger with KRAB and SCAN domains 5) was determined using Chromatin Immunoprecipitation (ChIP).

Results

APOC1 expression was significantly upregulated in prostate cancer tissues and cell lines. Genetic silencing of APOC1 by shRNA demostrated potent tumor-suppressive effects, markedly inhibiting cell proliferation, metastasis and EMT, while concurrently enhancing ferroptosis rates. Then, APOC1 was shown to modulate cholesterol homeostasis via the PI3K/AKT/SREBP2/SLC1A5 signaling cascade, thereby influencing ferroptosis susceptibility in prostate cancer cells. Mechanistically, ZKSCAN5 was identified as a transcriptional repressor of APOC1 through direct promoter binding. Notably, the anti-ferroptosis function of APOC1 was mediated through SREBP2-dependent transcriptional regulation, with Cut&Tag (Cleavage Under Targets and Tagmentation) confirming SREBP-2′s direct binding to the SLC1A5 promoter.

Conclusion

In prostate cancer, APOC1 regulates ferroptosis via PI3K/AKT/SREBP2/SLC1A5 axis, meanwhile ZKSCAN5 negatively regulates the expression of APOC1.

Introduction

Prostate cancer is the most common malignant tumor among males and ranks as the second leading cause of cancer-related deaths in the male population globally [1, 2]. Although China’s prostate cancer incidence remains lower than that in European nations and the US, studies have projected that the rate of prostate cancer in China reflects a substantial percentage increase of 517% over the period from 2015 to 2030, meanwhile, expected to elevateits ranking from the 7th to 3rd most prevalent cancer type in the country [3, 4]. While radiation therapy, surgical intervention, and androgen deprivation therapy (ADT) have demonstrated efficacy in enhancing the survival rates and prolonging the survival duration of prostate cancer patients, a significant proportion of these individuals subsequently progress to castration-resistant prostate cancer (CRPC) with metastic spread and an unfavorable prognosis, the incidence of this condition is rising and resulting in poor clinical outcomes [5,6,7]. Therefore, elucidating the mechanisms underlying the initiation and progression of prostate cancer, and subsequently identifying effective novel therapeutic targets, are of paramount importance for enhancing patient survival rates.

Apolipoproteins serve as indispensable structural and functional constituents within lipoproteins. The protein family plays a vital role in the cholesterol metabolism [8]. Apolipoproteins are amphipathic proteins characterized by exposed α-helical or β-sheet domains that mediate lipid binding and transport. Structurally, these domains interact with lipid cores to form lipoprotein particles like low-density lipoprotein (LDL) and high-density lipoprotein (HDL) [9]. Cellular cholesterol efflux operates through two distinct yet complementary pathways: the first involves passive aqueous diffusion, wherein cholesterol spontaneously translocates between the plasma membrane and HDL particles, with cholesterol esterification on HDL maintaining a concentration gradient of unesterified cholesterol to sustain continuous outward flux; the second pathway is actively mediated by lipid-free apolipoproteins (e.g., ApoA-I), which directly interact with cell surface receptors to solubilize phospholipids and cholesterol, thereby generating nascent pre-β-HDL particles—this process requires precise coordination of membrane-bound apolipoprotein binding sites and intracellular cholesterol trafficking machinery to mobilize lipids from cytoplasmic pools to specialized membrane domains dedicated to HDL assembly. As demonstrated, both aqueous diffusion and direct apolipoprotein-mediated pathways critically depend on the apolipoprotein family, underscoring their pivotal role in regulating intracellular cholesterol metabolism [10]. Also, the members can influence the tumorigenesis across various cancer types, evidences show that the apolipoproteins exhibit dual regulatory effects, functioning as both promoters and inhibitors by modulating critical cellular processes such as proliferation, apoptosis, inflammation, metabolic reprogramming, angiogenesis, ferroptosis, immune suppression and the invasive and migratory capabilities [11]. We observed that Apolipoprotein A-I (ApoA-I) is highly expressed in advanced prostate cancer, where it participates in lipid metabolic reprogramming through MYC-mediated regulation, thereby promoting tumor initiation and progression [12]. Conversely, in pancreatic cancer, ApoA-I exhibits tumor-suppressive properties by inhibiting low-density lipoprotein receptor (LDLR) expression, which subsequently suppresses cell migration and invasion in advanced pancreatic cancer [13]. Apolipoprotein C1 (APOC1), a member of the apolipoprotein C family, is known to promote the progression of hepatocellular cancer with a high expression level by inhibiting the transformation of M2 into M1 macrophages via the ferroptosis pathway [14]. Also, the high APOC1 expression can act through the Wnt signaling pathway to influence the EMT of renal cell cancer [15]. There are evidences reveal that the APOC1 protein plays a role in the formation of triglyceride-rich lipoproteins and high-density lipoproteins, and is involved in the metabolic processes of lipoproteins like very low-density lipoprotein (VLDL) and LDL, furthermore regulating the cholesterol metabolism [16]. In addition, APOC1 was found to be highly expressed in prostate cancer, but no more investigation into the mechanism in prostate cancer is currently available [17].

Ferroptosis is defined as an iron-dependent, non-apoptotic form of regulated cell death that is mechanistically distinct from canonical pathways of apoptosis, autophagy and necrosis and it is predominantly propelled by the buildup of phospholipid hydroperoxides within cellular membranes [18, 19]. Ferroptosis is characterized by iron-dependent accumulation of lipid-reactive oxygen species (lipid ROS), this process is driven by excessive lipid peroxidation, which arises from gluthathione (GSH) depletion, impaired glutathione peroxidase 4 (GPX4) activity, and dysfunction of the cystine/glutamate antiporter system Xc⁻. These pathological alterations ultimately inducing ferroptosis [20]. Ferroptosis exhibits a robust association with a multitude of pathophysiological process, encompassing aging, neurodegenerative disorders, ischemia–reperfusion injury, viral infection, and, most prominently, the progression of cancer [21]. Numerous studies have confirmed that ferroptosis is closely associated with the initiation and progression of prostate cancer [22]. The PI3K/AKT pathway serves as an essential transduction network for cellular signaling and a central mediator, orchestrating a multitide of fundamental cellular process, including growth, proliferation, metabolism, and survival [23]. In the process of cancer, research identified the 7-dehydrocholesterol, a metabolic intermediate of the distal cholesterol biosynthesis pathway, plays a important role in protecting cells from ferroptosis [24]. SREBPS play a pivotal role in lipid metabolism by regulating the expression of genes that are integral for metabolic processes of lipid. Among the SREBP family,SREBP2 is primarily responsible for regulating the transcription of cholesterol-metabolizing enzymes. While in the nucleus, mature SREBP2 acts as a main regulator, controlling the transcription of a multitude of factors that participate in cholesterol metabolism [25].

This study identifies APOC1 as a prostate cancer oncogene that promotes ferroptosis resistance through the PI3K/AKT/SREBP2 signaling pathway. Mechanistically, SREBP2 directly binds the SLC1A5 promoter, upregulating expression of this solute carrier. SLC1A5 facilitates glutamine uptake and then the elevated GSH levels suppress lipid peroxidation, thereby reducing ferroptosis susceptibility. These findings establish a concise molecular mechanism by which APOC1 drives metabolic reprogramming to evade ferroptosis in prostate cancer [26].

Materials and methods

Databases used for the analysis of APOC1 in prostate cancer

The UALCAN database (https://ualcan.path.uab.edu/index.html, accessed on 12 October 2023) was used to assess the expression levels of APOC1 in different kinds of cancers. The GEPIA2 (gene expression profiling interactive analysis, http://gepia2.cancer-pku.cn/#index, accessed on 12 October 2023), an integrated interactive web platform leveraging data from the Genotype-Tissue Expression (GTEx) project and The Cancer Genome Atlas (TCGA) database. The SREBP2 protein expressions in different prostate cancer cell lines were retrieved from the Human Protein Atlas (HPA) database (https://www.proteinatlas.org/,accessed on 18 September 2024).

Patients specimens and cell culture

A total of 6 patients diagnosed with prostate cancer and underwent radical prostatectomy were enrolled in this study. The Ethical Committee agreed the study conduction with the approval number of WDRY2023-K107. All the prostate cancer tissues and adjacents cancer tissues were collected from Renmin Hospital of Wuhan University (Wuhan, China) between October 2023 and January 2025 in accordance with ethical principles, and before the operation, all the patients had never accepted radical therapy or chemotherapy. Patient demographics and tumor characteristics are summarized in Supplementary Table 1. Prostate cancer tissues were collected fresh-frozen immediately after surgical resection and stored at − 80 °C until use. DU145 and PC3, the two prostate cancer cell lines and the normal prostate epithelial cells, RWPE-1, were obtained from Cell Bank of Chinese Academy of Sciences (Shanghai, China). DU145 represents an intermediate stage of hormone-refractory prostate cancer and exhibits EMT features. PC3 models aggressive, castration-resistant prostate cancer. Both cell lines effectively simulate advanced-stage clinical prostate cancer and are well-suited for studying tumor proliferation, migration, and invasion. Furthermore, their inherent resistance to multiple chemotherapeutic agents makes them highly valuable for investigating mechanisms of tumor drug resistance. Prostate cancer cells were maintained in RPMI-1640 medium (HyClone, USA, SH30027.01) supplemented with 10% fetal bovine serum (FBS; Gibco, USA, A5669401) and 100X penicillin–streptomycin solution (Servicebio, China, G4003-100ML). The RWPE-1 cell line was cultured in K-SFM medium (Gibco, USA, 17005042) with 10% FBS and 100 × penicillin–streptomycin Solution. All experimental cells were propagated at 37 °C within a humidified incubator maintained at 5% CO₂ concentration.

RNA extraction and qRT-PCR assay

We used TRI Reagent (Absin, China, abs60154) to extract total RNA from DU145 and PC3 cells. The PrimeScript™ RT Reagent Kit (TaKaRa, China, RR037A) was used to perform reverse transcription reactions following standardized protocols for complementary DNA (cDNA) synthesis. Quantitative real-time PCR (qRT-PCR) analyses were executed utilizing TB Green® Premix Ex Taq™ II (TaKaRa, China, RR820A). 1 μg RNA per sample was used for reverse transcription.This quantity aligns with standard protocols. For cDNA, 50 ng of cDNA templates per reaction in a 20 μL volume is enough. The gene expression levels of target genes were quantified relative to GAPDH reference levels using the comparative threshold cycle (2^−ΔΔCT) normalization algorithm. The used primer sequences are fully specified in Supplementary Table 2.

Cell transfection

The cell models including knockout and over-expression types were constructed (Viraltherapy, China) including OE-APOC1, sh-APOC1, sh-SREBP2 and sh-SLC1A5. Transient transfection was implemented using Lipofectamine 2000 (Invitrogen, USA, 11668027). Prior to transfection, cells were seeded in 6-well plates to achieve 60–70% confluency. For transfection, each well received 2 μg of shRNA plasmid and 5 μL of Lipofectamine 2000, diluted in 800 μL of serum-free RPMI-1640 basal medium. The mixture was incubated at 37 °C with 5% CO₂ for 6 h. Subsequently, the transfection medium was aspirated, and cells were supplemented with 1 mL of RPMI-1640 medium containing 10% FBS. Cultures were maintained at 37 °C with 5% CO₂ for an additional 48 h. Transfected cells were then harvested for RNA extraction, followed by RT-PCR and Western Blot analyses.

Western blotting

Cell/tissue were prepared in ice-cold RIPA lysis buffer (Beyotime, China, P0013B) supplemented with 1% phosphatase inhibitor (Servicebio, China, G2007-1ML). Following a 30-min incubation on ice, lysates were centrifuged at 13,000×g for 15 min at 4 °C. Supernatants were collected, and protein concentrations were quantified using a BCA assay (Invitrogen, USA, 23,227). Samples were then mixed with 5 × loading buffer, denatured by boiling at 100 °C for 15 min, and stored at − 80 °C or − 20 °C based on experimental requirements. Equal protein amounts were separated by SDS-PAGE (Epizyme, China, PG112) and followed by membranes (Millipore, USA, IPVH00010) transfer. Membranes were blocked with Rapid Blocking Buffer (Epizyme, China, PS108P) for 15 min at room temperature prior to antibody incubation. Then were incubated with primary antibodies overnight at 4 °C, followed by secondary antibody incubation for 60 min at room temperature. Specific protein bands were visualized using an ECL kit (Beyotime, China, P0018S) and quantified by ImageJ software. Detailed information regarding the primary antibodies used in this study is listed in Supplementary Table 3.

Colony formation assay

The APOC1-knockdown, APOC1-overexpression and untreated controls DU145 and PC3 cells were seeded separately into 6-well plates (Corning, USA, 3516) to conduct colony formation assays at a density of 500 cells/well and cultured for 14 days. To measure the groups, the colonies were fixed with 4% paraformaldehyde (Servicebio, China, G1101-500ML) for 20 min, stained with 1% crystal violet (Servicebio, China, G1014-50ML) for 20 min, and colonies containing ≥ 50 cells were enumerated.

Wound-healing assay

In this experiment, DU145 and PC3 cells were seeded separately in 6-well plates under three conditions: APOC1-knockdown, APOC1-overexpression, and untreated controls. Cells were cultured until the density reached approximately 90% confluency prior to subsequent experimental procedures. Wound healing assays were performed by creating a linear wound in near-confluent cell monolayers using a sterile 200-μL pipette tip. Cells were cultured in medium supplemented with 2% FBS to limit proliferation-mediated artifacts. Wound closure was assessed by acquiring phase-contrast microscopy images at 0 h, 24 h, 48 h post-wounding using an inverted microscope.

Transwell assay

In Transwell migration assays, 3 × 10⁴ DU145 and PC3 cells (APOC1-knockdown, APOC1-overexpression, and untreated controls) were seeded into Matrigel-precoated upper chambers (Corning, USA, 354480) with 200 μL of serum-free medium. The lower chambers were filled with 500 μL of complete medium containing 10% FBS as a chemoattractant. After a 48 h incubation at 37 °C, non-migratory cells were gently removed from the upper membrane surface using cotton swabs. Migrated cells on the lower membrane surface were fixed with 4% paraformaldehyde for 20 min, stained with 1% crystal violet, and quantified under microscope.

Cell counting Kit-8 (CCK-8) assay

Cell proliferation was assessed using a CCK-8 assay. Cells were seeded into 96-well plates (Corning, USA, 3300) at a density of 5,000 cells/well and cultured for 24 h. Subsequently, 10% CCK-8 solution (Biosharp, China, BS350B) was added to each well, followed by 2 h incubation at 37 °C. Absorbance was measured at 450 nm using a microplate reader. Statistical analyses were performed based on optical density (OD) values.

Transmission electron microscopy (TEM)

The prostate cancer cells were fixed via sequential immersion in 2.5% glutaraldehyde (Biosharp, China, BL911A) at 4 °C for 2 h and 1% osmium tetroxide (Seebio, China, 75630) followed by dehydration through an ethanol gradient and embedding in Spurr's resin (Sigama-Aldrich, USA, EM0300). Ultrathin sections (50 nm) were prepared, counterstained with 4% uranyl acetate/lead citrate (Head Biotechnology, China, SPI-02624/HD17810) double staining, and examined using a Hitachi HT7700 transmission electron microscope (Japan) at an accelerating voltage of 120 kV with an exposure time of 2.5 s per frame to visualize mitochondrial ultrastructure.

Immunohistochemistry (IHC)

APOC1 expression in prostate cancer tissues and matched adjacent normal tissues was evaluated by immunohistochemical (IHC) staining. The obtained tissue samples were first subjected to fixation with 4% paraformaldehyde, paraffin-embedded (FFPE) tissue blocks were sectioned into 4-μm-thick slices, followed by deparaffinization, rehydration, and antigen retrieval via microwave treatment in citrate buffer (pH 6.0) (Solarbio, China, C1010). Endogenous peroxidase activity was blocked using 3% hydrogen peroxide (MKBio, China, MM-0750), and sections were incubated overnight at 4 °C with primary antibody (1:200 dilution). Horseradish peroxidase (HRP)-conjugated secondary antibody was applied for 40 min at room temperature, with visualization achieved through 3,3′-diaminobenzidine (DAB) (MKBio, China, MM-0701) substrate and hematoxylin counterstaining (MKBio, China, MS-4008). Scoring was independently performed by two board-certified pathologists blinded to clinical annotations.

Chromatin immunoprecipitation (ChIP) assay

ChIP kit (ABclonal, China, RK20258) was used to verify the binding of protein and DNA promoter in prostate cancer cells. For each chromatin immunoprecipitation (ChIP) experiment, 2 × 10⁷ cells was collected. Prostate cancer cells were incubated with 1% formaldehyde (MKBio, China, MM-1507) solution for 10 min to cross-link DNA and protein, followed by ultrasonication to sheared the DNA into fragments of 200–500 bp. After centrifugation, 15 μg supernatant was collected and immunoprecipitated overnight at 4 °C with magnetic beads coupled with the ZKSCAN5 antibody against the target gene or normal rabbit IgG. Following the reversal of cross-linking, the precipitated DNA was purified and amplified using qRT-PCR.

Measurement of GSH and MDA

The concentration of GSH was quantified by GSH and GSSG Assay Kit (Beyotime Institute of Biotechnology, China, S0053) following the manufacturer’s instructions. Based on experimental requirements, cells were subjected to different treatments. For each treatment, cell pellets from one 10 cm culture dish were collected and resuspended in a protein removal reagent M solution at 3 × the pellet volume. Rapid freeze–thaw cycles were performed twice by alternating between liquid nitrogen and a 37 °C water bath. Samples were then incubated at 4 °C or on ice for 5 min, followed by centrifugation at 10,000 g for 10 min at 4 °C. The supernatant was collected for total glutathione quantification, which was conducted according to the kit instructions. Malondialdehyde (MDA) levels, a biomarker of lipid peroxidation, were quantified using the Lipid Peroxidation MDA Assay Kit (Beyotime Institute of Biotechnology, China, S0131S) following the protocol. Based on experimental requirements, cells were subjected to different treatments. For each treatment, cell pellets from one 10 cm culture dish were collected and lysed using 200 μL of RIPA lysis buffer. After lysis, samples were centrifuged at 10,000 g–12,000 g for 10 min, and the supernatant was collected for subsequent assays. In microcentrifuge tubes, 0.1 mL of PBS was added as a blank control, 0.1 mL of standard solutions at varying concentrations was added for standard curve preparation, and 0.1 mL of sample was added for testing. Subsequently, 0.2 mL of MDA detection working solution was added to each tube. Absorbance was measured at 532 nm using a microplate reader, and MDA content was calculated accordingly.

Measurement of Fe²⁺

Fe²⁺ levels was measured using Ferric and Ferrous Ion Assay Kit (Beyotime Institute of Biotechnology, China, S1066S). Based on experimental requirements, cells were subjected to different treatments. For each treatment, cells were cultured in one 10 cm dish, washed once with PBS, and residual liquid was aspirated. Cells were then digested using EDTA-free trypsin. For lysis, 200 μL of BeyoLysis™ Buffer H for Metabolic Assay was added, followed by gentle pipetting. Homogenization was performed under ice-bath conditions using a grinder, and samples were incubated on ice for 5–10 min to ensure complete cell lysis. Samples were centrifuged at 12,000 × g for 3–5 min at 4 °C. Subsequently, 10 μL of 1 M HCl was added to 200 μL of the supernatant, mixed thoroughly by pipetting, and incubated at 60 °C for 30 min. Another centrifugation step followed at 12,000 × g for 10 min at 4 °C. The final supernatant was used to measure absorbance at 593 nm using a microplate reader. Quantification was performed by comparing values to standard curves.

Tumor xenograft assay

To investigate the role of APOC1 in prostate carcinogenesis, subcutaneous tumor xenograft experiments were conducted using 4-week-old BALB/c nude mice. Animals received subcutaneous injections of 3 × 10⁶ APOC1-knockdown prostate cancer cells or 3 × 10⁶ normal control cells into the right flank. Tumor growth was monitored biweekly by measuring tumor volume (calculated as π/6 × length × width²) and tumor weight. At experimental termination (6 weeks post-injection), mice were euthanized, and tumors were harvested for subsequent analyses. All procedures adhered to the NIH Guide for the Care and Use of Laboratory Animals and recieved approval form the Ethics Committee of Renmin Hospital of Wuhan University (Ethics number: WDRM20240818).

Statistical analysis

The SPSS Statistics 26 software was used for all statistical analyses. All data were expressed as mean ± SD. Student’s t-test was used for the comparison between different groups. The χ2 test was used to assess the correction between the level of protein and clinical characteristics. Spearman's correlation analysis was used to evaluate the relationship between target genes. All statistical tests were considered statistically significant when P values less than 0.05.

Results

APOC1 is overexpressed in prostate cancer tissues and cells

APOC1 has emerged as an oncogene across multiple tumor types. Our analysis of pan-cancer expression patterns, using data from UALCAN (Fig. 1A) and the TCGA database (Fig. 1B), revealed that prostate cancer tissues consistently show higher APOC1 levels than their normal counterparts. Among the 497 prostate cancer cases, the majority were adenocarcinoma, with 204 cases exhibiting a Gleason score ≥ 8, indicating high-grade malignancy. The upregulation was further validated through the GEPIA2 database (Fig. 1C), where we also noted that APOC1 expression correlates with Gleason scores, displaying a malignancy-dependent pattern (Fig. 1D). Further analysis via GEPIA2 highlighted APOC1 as a notable prognostic marker for prostate cancer (Fig. 1E).

Fig. 1

APOC1 is overexpressed in prostate cancer tissues and cells. A The analysis results of the APOC1 expression of different kinds of cancer cells from the UCALAN database. B The expression of APOC1 of prostate cancer was showed in 497 tumor tissues and 52 normal tissues from TCGA. C The expression of APOC1 of prostate cancer was showed in 492 tumor tissues and 152 normal tissues from GEPIA2. D Changes in APOC1 expression levels across different stages of the Gleason Score in prostate cancer. E The disease-free survival curve demonstrates a close association between APOC1 and prostate cancer prognosis. F APOC1 was upregulated in prostate cancer compared to the tumor adjacent parts. G Immunohistochemical staining showed an upregulated expression level of APOC1 in prostate cancer tissues in comparsion with adjacent tumor tissues. H, I APOC1 was upregulated on both mRNA and protein levels in prostate cancer cell lines contrast to RWPE-1. All data is presented as mean ± SD. *P < 0.05, ***P < 0.001

Bioinformatics assessments consistently pointed to significant APOC1 upregulation in prostate cancer tissues relative to adjacent normal tissues, with these expression differences showing statistical significance and clear associations with patient prognostic outcomes. To confirm these findings experimentally, we collected tumor and paired adjacent normal tissues from clinical prostate cancer patients and performed western blot. The results aligned closely with our bioinformatics predictions, confirming that APOC1 protein expression is indeed elevated in prostate cancer tissues compared to adjacent normal ones (Fig. 1F). Consistently, we performed immunohistochemical (IHC) staining on prostate cancer tissues and their matched adjacent non-cancerous tissues. The results demonstrated that APOC1 expression was significantly higher in cancer tissues compared to adjacent non-cancer tissues (Fig. 1G).

Next, we explored APOC1 expression profiles in vitro using the human prostate epithelial cell line RWPE-1 and the prostate cancer cell lines DU145 and PC3. Both protein (Fig. 1H) and mRNA (Fig. 1I) levels of APOC1 were found to be higher in DU145 and PC3 cells than in the immortalized RWPE-1 cells. Taken together, the combination of bioinformatics predictions and experimental validation underscores the aberrant overexpression of APOC1 in prostate cancer, hinting at its possible role in driving tumor progression.

APOC1 promotes the proliferation, invasion and migration of prostate cancer cells

To investigate APOC1 function in prostate cancer, we stably knocked down APOC1 using independent shRNAs (shAPOC1#1/shAPOC1#2), also, the lentiviral mediated overexpression models were built in DU145 and PC3 cells. RT-PCR confirmed the significant APOC1 downregulation and overexpression in the groups compared to the controls (Supplementary Fig. 1).

Then, the colony formation, wound-healing assay, transwell assay and CCK-8 assay were used to explore the function of APOC1 on tumor. Functionally, the suppression of APOC1 significantly compromised the colony formation capacity of prostate cancer cells, as evidenced by a marked reduction in clonogenic survival fractions observed in colony formation assays, while in contrast, the formation capacity of overexpression groups were far more than the vectors (Fig. 2A). Concordantly, cell proliferation rates were substantially decreased with the APOC1 konckdown groups, meanwhile increased following APOC1 overexpressioned groups, quantified through CCK-8 assays which revealed time-dependent growth promotion compared to control groups (Fig. 2C). In vitro functional assays further demonstrated impaired metastatic potential: in APOC1 knockdown groups wound healing assays showed delayed scratch closure kinetics while the overexpression groups showed an accelerated wound closure (Fig. 2D). Then, transwell migration demonstrated markedly attenuated invasive potentials in APOC1-silenced cells, nevertheless, the migration rate was significant increased in the overexpression groups (Fig. 2E). Mechanistic investigations employing western blot analysis uncovered EMT phenotypic markers which revealed that the APOC1 promoted the EMT process of prostate cancer cells, statistical bar charts for quantitative analysis (Fig. 2F).

Fig. 2

APOC1 promotes the proliferation, invasion and migration of prostate cancer cells. A The colony formation of the prostate cancer cells after different interferences. B, C The cell viability mesured by CCK-8 of the APOC1 knockdown and APOC1-OE groups of the two prostate cancer cell lines. D Representative images and statistic graphics of wound healing. E The transwell migration assays reveal the migration potential of the DU145 and PC3 with knockdown or overexpression process. F Western blot analysis shows the APOC1-OE activated the EMT of prostate cancer cells. Datas are presented as mean ± SD (n = 3). Statistical significance was determined by Student’s t test or One/Two way ANOVA, **P < 0.01, ***P < 0.001 vs. Vector

In general, these multidimensional functional and molecular analyses definitively establish APOC1 as a critical oncogenic mediator that not only sustains proliferative vigor but also orchestrates metastatic progression in prostate cancer through EMT regulation.

APOC1 increases ferroptosis resistance in prostate cancer cells

APOC1 is an established oncogene driving prostate cancer progression via enhanced proliferation, invasion, and EMT. However, the underlying mechanism remains unclear. Given APOC1's central role in lipid metabolism, we hypothesize that APOC1 promotes prostate cancer oncogenesis by conferring resistance to ferroptosis.

To investigate the relationship between APOC1 and ferroptosis in prostate cancer, we performed GO enrichment analysis (Gene Ontology Enrichment Analysis), which tell us the strong relationship between APOC1 and oxidative stress in prostate cancer cells (Fig. 3A). Then GSEA bioinformtics analysis which revealed a significant correlation between APOC1 expression and ferroptosis-related pathways (Fig. 3B). Pharmacological validation using the ferroptosis inducer erastin, which inhibits the cystine/glutamate antiporter (system xc −), depleting glutathione and triggering lipid peroxidation-mediated cell death, in APOC1 knockdown DU145/PC3 cells and then measured the cell viability after 24 h, demonstrated a reduced cell activity, an effect partially rescued only by the ferroptosis-specific inhibitor Ferrostatin-1, but not by apoptosis inhibitor Z-VAD-FMK or necroptosis inhibitor Nec-1 (Fig. 3C). Detailed information on these reagents is provided in the Supplementary Table 4. Using APOC1-knockdown DU145 and PC3 cell models treated with the ferroptosis inducer erastin, we assessed cell viability at 0, 24, 48, and 72 h. Notably, compared to the control groups, the knockdown groups exhibited significantly reduced cell viability (Fig. 3D). The above explorations demonstrated that APOC1 may influence the ferroptosis rather than other cell death forms.

Fig. 3

APOC1 increases ferroptosis resistance in prostate cancer cells. A The GO enrichment shows the relationship between APOC1 and oxidative stress. B The correlation of APOC1 and ferroptosis from GSEA analysis. C Erastin, Ferrostatin-1, Z-VAD-FMK, Nec-1,inform us the death form which APOC1 induced is ferroptosis. D The cell viability comparison of Vector and shAPOC1 cells with erastin interference. E The ferroptosis biomarkers analysed by western blot. F, G The Fe and MDA levels in prostate cells after treating with erastin. G Electron microscopy revealed mitochindrial morphological changes characteristic of ferroptosis. Datas are presented as mean ± SD (n = 3). Statistical significance was determined by Student’s t test or One/Two way ANOVA, **P < 0.01, ***P < 0.001 vs. Vector

So we further try to find other the relationship between APOC1 and ferroptosis. GPX4/SLC7A11 are key ferroptosis markers, western blot analysis confirmed significant change of GPX4 following APOC1 modulation, while SLC7A11 not remarkable, statistical bar charts for quantitative analysis (Fig. 3E). Concurrent measurements of intracellular labile iron pools showed elevated iron levels in erastin-treated APOC1 deficient cells (Fig. 3F). During cellular oxidative stress, lipid oxidation occurs, leading to the breakdown of fatty acids into complex compounds, including malondialdehyde (MDA). MDA serves as a natural byproduct of lipid peroxidation in biological systems. Since its levels directly correlate with lipid oxidation intensity, MDA quantification is widely utilized as a robust biomarker for assessing oxidative lipid damage. Using MDA assay kits, we quantified intracellular MDA levels across four experimental groups: Vector control, Erastin + Vector, Erastin + shAPOC1#1, and Erastin + shAPOC1#2. Our analysis revealed significantly elevated MDA accumulation in Erastin-treated groups compared to untreated controls. Morever, within the Erastin-treated cohorts, APOC1-knockdown cells exhibited marked increases in MDA levels relative to non-targeting shRNA controls, indicating enhanced lipid peroxidation under APOC1 suppression (Fig. 3G). Ultrastructural analysis by transmission electron microscopy further revealed mitochindrial morphological changes characteristic of ferroptosis including mitochondrial shrinkage, increased membrane density,and cristae disruption specifically in Erastin/APOC1 co-treated cells (Fig. 3H).

Through the aforementioned investigations, we demonstrate that APOC1 is indeed associated with ferroptosis regulation in prostate cancer. Furthermore, as an oncogene, APOC1 promotes cancer progression by enhancing ferroptosis resistance in prostate cancer cells, thereby facilitating malignant development.

APOC1 enhances ferroptosis resistance in prostate cancer cells by regulating cholesterol metabolism through the PI3K/AKT/SREBP2 signaling pathway

We demonstrated that APOC1 influences ferroptosis, but how APOC1 played the role remains unknown. As we mentioned before, APOC1 is a regulator of cholesterol metabolism. Also, evidences inspire us that within physiological limits, elevated cholesterol levels correlate with enhanced resistance to ferroptosis in mammalian cells. So we first quantified cholesterol levels in APOC1-knockdown and overexpression prostate cancer cells. APOC1 overexpression significantly elevated intracellular cholesterol content (Fig. 4A), consistent with its established role in lipoprotein metabolism. As we know, SREBP2 is a regulator of cholesterol metabolism, so in the prostate cancer cells, we also measured cholesterol levels in wild-type cells and SREBP2-knockdown cells, which corroborates our hypothesis (Fig. 4B).

Fig. 4

APOC1 enhances ferroptosis resistance in prostate cancer cells by regulating cholesterol metabolism through the PI3K/AKT/SREBP2 signaling pathway. A The cholesterol assay kit was used to measure cholesterol levels in the Vector groups, APOC1 knockdown groups, and APOC1 overexpression groups following. B The cholesterol levels were measured in the Vector control group and SREBP2 knockdown group. C The correlation of APOC1 and PI3K/AKT signaling pathway from GSEA analysis. D The SREBP2 levels in individual cells from prostate cancer cell lines in The Human Protein Atlas. E Western blot analysis demonstrated that APOC1 regulated the PI3K/AKT/SREBP2 signaling pathway in DU145 cells. F Western blot analysis revealed that GPX4 levels significantly decreased in SREBP2-knockdown DU145 cells. G Fe levels in SREBP2-knockdown and Vector DU145 cells after treating with erastin. H MDA levels in SREBP2-knockdown and Vector DU145 cells after treating with erastin.Datas are presented as mean ± SD (n = 3). Statistical significance was determined by Student’s t test or One/Two way ANOVA, **P < 0.01, ***P < 0.001 vs. Vector

We found that APOC1 and SREBP2 both have an effect on cholesterol metabolism, but the relationship between the two key proteins is unclear. Relevant studies have demonstrated that in the context of cholesterol metabolism, SREBP2 is regulated by the PI3K/AKT signaling pathway. Subsequent, GSEA analysis identified a significant positive association between APOC1 expression levels and PI3K/AKT pathway activation (Fig. 4C). Next,bioinformatics analysis of the Human Protein Atlas revealed higher SREBP2 expression levels in DU145 cells compared to PC3 cells (Fig. 4D), prompting selection of DU145 for subsequent mechanistic studies. To investigate whether APOC1 mediates SREBP2 regulation through the PI3K/AKT signaling pathway, we performed Western blot analysis. The results confirmed that APOC1 indeed modulates SREBP2 via this pathway, thereby regulating cellular cholesterol metabolism (Fig. 4E). Thereafter, SREBP2 knockdown was performed, followed by western blot analysis of cellular proteins, which demonstrated a significant reduction in intracellular GPX4 levels in the knockdown group compared to the control group (Fig. 4F). Following SREBP2 knockdown, intracellular MDA and Fe²⁺ levels were quantified, demonstrating consistency with the western blot findings (Fig. 4G,H).

Thus, our findings establish that APOC1 modulates both cholesterol metabolism and ferroptosis in prostate cancer cells through the PI3K/AKT/SREBP2 signaling axis.

APOC1 regulates ferroptosis by modulating the transcriptional regulation of SREBP2 of SLC1A5

In our preliminary work, we found that APOC1 regulates ferroptosis resistance in prostate cancer via the PI3K/AKT/SREBP2 signaling pathway. However, the specific target through which it acts in the ferroptosis process remained unclear. To dig into this, we turned to CUT&Tag sequencing. The results showed that SREBP2, acting as a transcriptional regulator, can directly bind to gene promoter regions, likely influencing DNA transcription.

GO enrichment analysis shed light on SREBP2’s functional associations—we saw strong links to lipid metabolism, transcriptional regulation, and oxidative stress response pathways (Fig. 5A). Meanwhile, KEGG pathway analysis highlighted its connection to the PI3K/AKT signaling cascade, which lines up well with our earlier experimental observations and strengthens their credibility (Fig. 5B).

Fig. 5

APOC1 regulates ferroptosis by modulating the transcriptional regulation of SREBP2 of SLC1A5. A GO analysis indicated that SREBP2 is associated with gene transcription, lipid metabolism, and oxidative stress. B KEGG analysis revealed that SREBP2 is associated with prostate cancer, the PI3K/AKT signaling pathway, and transcription processes. C Venn diagram analysis of the intersection between SREBP2 Cut&Tag data and ferroptosis-related genes identified 381 overlapping genes. D Integrative Genomic Viewer (IGV) plot showing SREBP2 Cut&Tag peaks in the SLC1A5 gene promoter region (framed in red). E Western blot analysis demonstrated that SREBP2 regulated the SLC1A5 expression level at the protein level in DU145 cells. F The intracellular GSH levels in the Vector, Vector + Erastin, Erastin + shSLC1A5#1, and Erastin + shSLC1A5#2 groups were measured using a GSH detection kit. G Fe²⁺ levels in SLC1A5-knockdown and Vector DU145 cells after treating with erastin. H MDA levels in SLC1A5-knockdown and Vector DU145 cells after treating with erastin.Datas are presented as mean ± SD (n = 3). Statistical significance was determined by Student’s t test or One/Two way ANOVA, **P < 0.01, ***P < 0.001 vs. Vector

To pinpoint how SREBP2 modulates ferroptosis, we cross-referenced the target genes bound by SREBP2 at their promoters with known ferroptosis-related gene sets. Using a Venn diagram, we identified 381 overlapping genes (Fig. 5C). We then delved into these 381 genes, combining a review of existing literature with insights from our GO and KEGG analyses, and zeroed in on SLC1A5 as a key target of SREBP2 (Fig. 5D).

SLC1A5 is no stranger to ferroptosis research—it’s known to play a critical regulatory role here. As a plasma membrane transporter, it mediates glutamine uptake, a process that’s pivotal to how ferroptosis develops and progresses. Here’s how it works: intracellular glutamine, brought in by SLC1A5, undergoes reductive deamination to form glutamate. This glutamate then swaps with extracellular cystine via the system Xc⁻ antiporter, letting cystine enter the cell. Once inside, cystine gets reduced to cysteine, which is the rate-limiting building block for glutathione (GSH) synthesis. Higher GSH levels boost the cell’s antioxidant capacity, making it more resistant to ferroptosis. This makes SLC1A5 a key player in regulating ferroptosis resistance in prostate cancer cells.

To confirm the relationship, we knocked down SREBP2 and checked via western blot—sure enough, SLC1A5 expression changed in parallel, confirming that SREBP2 regulates SLC1A5 (Fig. 5E). We then knocked down SLC1A5 and treated cells with erastin. This led to a concentration-dependent drop in intracellular GSH levels (Fig. 5F). We also measured Fe²⁺ and MDA levels, which both rose, confirming that ferroptosis was being induced (Fig. 5G,H).

Taken together, these findings show that SLC1A5 is a critical modulator of ferroptosis. In short, SREBP2 exerts precise control over ferroptosis by targeting SLC1A5—an insight that carries important implications for prostate cancer research.

ZKSCAN5 transcriptionally regulates APOC1 expression in prostate cancer cells

We’ve shown that APOC1 functions as an oncogene in prostate cancer: it drives tumor progression and boosts resistance to ferroptosis, making it a key player in how the disease advances. With that in mind, we wanted to find molecular regulators that can dampen APOC1 activity—since dialing down APOC1 might help slow or stop prostate cancer growth. Transcription factors, which are central to controlling gene transcription, seemed like promising candidates here, as they directly influence how genes are expressed.

To track down upstream regulators of APOC1, we started with in silico promoter analysis using the UCSC database. That’s how we zeroed in on ZKSCAN5 as a potential transcription factor involved (Fig. 6A). Next, we turned to the JASPAR database to predict where ZKSCAN5 might bind on the APOC1 promoter. The analysis pointed to a specific base sequence with the highest likelihood of binding (Fig. 6B), and we also mapped out the mutated version of this binding site for comparison (Fig. 6C).

Fig. 6

ZKSCAN5 transcriptionally regulates APOC1 expression in prostate cancer cells. A Transcription factors that may bind to the APOC1 promoter region were screened using the UCSC Genome Browser database. B The binding site base sequences of ZKSCAN5 in the APOC1 promoter region were predicted using the JASPAR database. C The binding site of ZKSCAN5 and APOC1 and the sequence of point mutations. D The expression of ZKSCAN5 of prostate cancer was showed in 497 tumor tissues and 52 normal tissues from TCGA. E Western blot analysis demonstrated that ZKSCAN5 regulated the APOC1 expression level at the protein level in DU145 cells. F The chip experiment revealed that ZKSCAN5 influence the APOC1 at the gene transcription level G The transwell assay showed that ZKSCAN5 overexpression could reduce the the pro-tumorigenic function of APOC1. Datas are presented as mean ± SD (n = 3). Statistical significance was determined by Student’s t test or One/Two way ANOVA, **P < 0.01, ***P < 0.001 vs. Vector

Looking at expression patterns, UALCAN bioinformatics data showed that ZKSCAN5 levels are significantly lower in prostate cancer tissues than in normal prostate tissue (Fig. 6D). When we experimentally overexpressed ZKSCAN5 in prostate cancer cells, an unexpected observation emerged during the experimental phase: APOC1 expression dropped (Fig. 6E). To confirm this was a direct effect, we ran chromatin immunoprecipitation (ChIP) assays, which showed ZKSCAN5 actually binds to the APOC1 promoter. Functional tests backed this up, proving ZKSCAN5 regulates APOC1 transcription (Fig. 6F). This inverse relationship—higher ZKSCAN5 linked to lower APOC1—tells us ZKSCAN5 acts as a transcriptional repressor of APOC1 in prostate cancer.

We then used transwell assays to dig into how this regulation affects cell behavior. By overexpressing APOC1 in DU145 cells, we could tease out ZKSCAN5’s role and clarify how both factors work together to influence cell migration (Fig. 6G). What stood out was that when ZKSCAN5 suppresses APOC1, it also weakens the cancer cells’ resistance to ferroptosis. That suggests ZKSCAN5 might act as a tumor suppressor in prostate cancer, countering the disease’s progression.

These findings add useful insights for research into ways to inhibit prostate cancer development,particularly by targeting the ZKSCAN5-APOC1 axis.

Knockdown of APOC1 synergizes with Docetaxel to enhance antitumor efficacy in prostate cancer

Docetaxel, a microtubule-stabilizing drug from the taxane family, is the backbone of first-line chemotherapy for advanced prostate cancer [27]. It’s the standard go-to for metastatic castration-resistant prostate cancer (mCRPC), and in metastatic hormone-sensitive prostate cancer (mHSPC), pairing it with androgen deprivation therapy (ADT) works better than ADT alone—especially for patients with a heavy tumor burden, where it significantly boosts survival. Even in high-risk localized cases, using ADT as neoadjuvant or adjuvant therapy during the hormone-sensitive phase improves pathological response rates and keeps biochemical recurrence at bay longer [28, 29].However, cautious interpretation is warranted: many patients develop primary or acquired resistance to docetaxel, and its harsh side effects limit how widely it can be used. That’s why we’re looking for new approaches to target these resistance mechanisms—like the APOC1 gene ablation we’re studying here—which might help get past these hurdles and lead to better patient outcomes.

To test this, we first did xenograft experiments with nude mice, implanting them with prostate cancer cells and their APOC1-knockdown counterparts. The results were clear: knocking down APOC1 made tumors smaller, confirming it helps drive tumor growth (Fig. 7A). Next, we wanted to see how well APOC1 knockdown works alongside docetaxel. When we compared the combination group to the DMSO control, both tumor volume and weight dropped significantly—and the combination had the strongest effect (Fig. 7B). We’ve plotted the tumor weights in bar graphs (Fig. 7C,D), and tracking growth over time showed the combination kept tumors in check consistently throughout the experiment (Fig. 7E,F).

Fig. 7

Knockdown of APOC1 synergizes with Docetaxel to enhance antitumor efficacy in prostate cancer. A The tumor formation ability of APOC1-knockdown prostate cancer cells was compared with that of wild-type prostate cancer cells in nude mouse xenograft models. B The tumor formation ability was compared among wild-type prostate cancer cells nude mIse xenograft groups receiving APOC1-knockdown prostate cancer cells,, docetaxel monotherapy, and combination treatment with APOC1-knockdown cells plus docetaxel. C, D The tumor weight of different treatment groups was monitored over time. E, F The tumor volume of different treatment groups was monitored over time. G The effect of knockdown of APOC1 on the expression levels of APOC1 and Ki67 in subcutaneous tumors of nude mice was detected by immunohistochemistry. Datas are presented as mean ± SD (n = 3). Statistical significance was determined by Student’s t test or One/Two way ANOVA, **P < 0.01, ***P < 0.001 vs. Vector

These results point to a real therapeutic potential in targeting the APOC1 axis: it could make prostate cancer cells more sensitive to chemotherapy and help overcome docetaxel resistance. We also looked at the tumors under the microscope with immunohistochemistry. In both the single-treatment (either APOC1 knockdown or docetaxel alone) and combination groups, APOC1 and Ki-67 expression was lower—but the combination group showed the biggest drop (Fig. 7G).

Putting this all together, it seems that silencing APOC1 works with docetaxel to boost antitumor effects, possibly by making cancer cells less resistant to ferroptosis. This approach looks promising for tackling docetaxel resistance and reducing its toxicity. Now we need to dig deeper into how it works to make sure it translates well to the clinic.

Discussion

Prostate cancer is often called a “cold tumor” because it has few tumor-infiltrating T cells, which makes it inherently unresponsive to immunotherapy. On top of that, standard chemotherapy like docetaxel faces big issues: many tumors become resistant to it, and it comes with severe side effects [30, 31]. That’s why researchers are looking for new approaches, and ferroptosis has emerged as a promising one. Ferroptosis is a regulated form of cell death driven by lipid peroxidation and the buildup of redox-active iron; it’s good at wiping out cancer cells, and more and more studies show it can help get around treatment resistance [32]. Inducing ferroptosis to kill tumor cells is clearly a direction worth exploring for cancer treatment. Since ferroptosis is closely tied to lipid metabolism, genes and key molecules involved in how tumor cells handle lipids have become key targets for cancer suppression research [33].

We set our sights on the APOC1 gene, which has strong links to lipid metabolism and cholesterol balance [34]. While past studies have hinted that APOC1 is involved in several types of cancer, there’s not much research directly connecting it to messed-up lipid metabolism or explaining how it actually drives cancer growth [35]. Our work here shows that targeting APOC1-mediated lipid metabolism can trigger ferroptosis in prostate cancer and reverse treatment resistance. We’ve uncovered a new mechanism: APOC1 helps cancer cells resist ferroptosis by coordinating both cholesterol biosynthesis and glutamine metabolism. What’s more, we found that APOC1 plays an unexpected role as an oncogene in transcriptional regulation through the SREBP2-SLC1A5 axis—way beyond its usual job in maintaining lipid balance.

Functioning as a metabolic regulator of ferroptosis resistance, APOC1 upregulation protects prostate cancer cells from erastin-induced cell death. This observation aligns with recent studies implicating lipid metabolic remodeling in ferroptosis control. Our work significantly extends current knowledge by revealing a coordinated dual mechanism: PI3K/AKT-driven SREBP2 activation stimulates cholesterol production, and SREBP2 subsequently enhances SLC1A5 expression. Together, these processes maintain cellular membrane stability through cholesterol enrichment while bolstering antioxidant defenses via glutathione biosynthesis, ultimately creating a comprehensive ferroptosis protection system.While SREBP2 is classically recognized as a master regulator of cholesterol synthesis, our Cut&Tag data reveal its novel role as a direct transcriptional activator of SLC1A5 [36]. This finding aligns with recent studies suggesting non-canonical functions of SREBPs in nutrient sensing beyond lipid metabolism [37]. The Cut&Tag analysis reveals strong evolutionary conservation of the SREBP2 binding site within the SLC1A5 promoter region. Functional studies demonstrate that genetic inhibition of SLC1A5 completely eliminates APOC1-induced glutathione elevation, confirming this regulatory pathway's role in connecting amino acid metabolism with cellular redox balance. Mechanistically, SLC1A5-facilitated glutamate import establishes a concentration gradient that promotes cystine uptake through SLC7A11, subsequently boosting glutathione production. This coordinated “glutamate-cystine exchange” system elucidates the unexpected dual metabolic effects of APOC1 overexpression meanwhile simultaneous stimulation of lipid production (via cholesterol synthesis) and antioxidant defense (through GSH generation). These findings provide a unifying framework for understanding SLC1A5's variable contributions to tumor biology, suggesting its oncogenic potential depends on specific metabolic conditions within the tumor microenvironment.

From a therapeutic perspective, our findings propose several actionable targets: APOC1 neutralization via monoclonal antibodies or antisense oligonucleotides, SREBP2 inhibition using emerging small molecules (e.g. fatostatin derivatives), or SLC1A5 blockade with inhibitors like V-9302 [38, 39]. Combinatorial strategies targeting both cholesterol synthesis (e.g. statins) and glutamate metabolism may synergize to overcome ferroptosis resistance, particularly in APOC1-high tumors.

Although our findings characterize the APOC1-SREBP2-SLC1A5 pathway using cell lines and xenograft systems, future studies should verify these results in patient-derived organoids and clinical specimens. The molecular drivers underlying elevated APOC1 expression in prostate malignancies and particularly potential androgen receptor involvement remains to be fully studied. Furthermore, possible interactions between this axis and alternative metabolic routes, including glutamine metabolism, merit additional exploration.

Conclusion

While traditionally recognized as a lipid metabolism regulator within the apolipoprotein family, APOC1's functional repertoire extends beyond conventional boundaries, as demonstrated by our findings. This study establishes APOC1 as a pivotal metabolic orchestrator coordinating cholesterol production and amino acid uptake to promote ferroptosis evasion in prostate malignancies (Fig. 8). We reveal a novel regulatory paradigm involving SREBP2's bifunctional activity and the metabolic symbiosis between SLC1A5 and SLC7A11 transporters. These mechanistic revelations significantly enhance comprehension of tumor metabolic adaptability while simultaneously proposing targeted intervention strategies against therapy-resistant prostate cancer through metabolic pathway modulation.

Fig. 8

Mechanism model of APOC1-mediated cholesterol metabolism and ferroptosis resistance in prostate cancer