CXCR2-mediated metabolic interaction between prostate cancer cells and the immunosuppressive tumor microenvironment

Yi Sun; Jun Jing; Shangqing Ren; Xu Luo; Wei Wen; Xin Jin; Guohua Zeng; Xuewen Jiang; Mo Zhang; Ju Guo

doi:10.1136/jitc-2025-014725

. 2026 Jul 29;14(7):e014725. doi: 10.1136/jitc-2025-014725

CXCR2-mediated metabolic interaction between prostate cancer cells and the immunosuppressive tumor microenvironment

Yi Sun ¹, Jun Jing ^2,³, Shangqing Ren ⁴, Xu Luo ⁵, Wei Wen ⁶, Xin Jin ^7,⁸, Guohua Zeng ⁹, Xuewen Jiang ^10,^11,^*, Mo Zhang ^12,^13,^*, Ju Guo ^14,^15,^✉

¹Urology, Guangzhou Medical University, Guangzhou, Guangdong, China

²Department of Rheumatology and Clinical Immunology, Shenshan Medical Center, Sun Yat-Sen Memorial Hospital, Shanwei, Guangdong, China

³Guangdong Provincial Key Laboratory of Cancer Pathogenesis and Precision Diagnosis and Treatment, Shenshan Medical Center, Sun Yat-Sen Memorial Hospital, Shanwei, Guangdong, China

⁴Robotic Minimally Invasive Surgery Center, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China

⁵Department of Urology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China

⁶Department of Urology, West China Tianfu Hospital, Sichuan University, Chengdu, Sichuan, China

⁷Department of Urology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China

⁸Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, The Second Xiangya Hospital of Central South University National Clinical Research Center for Metabolic Diseases, Changsha, Hunan, China

⁹Guangzhou Medical University, Guangzhou, Guangdong, China

¹⁰Department of Urology, Qilu Hospital of Shandong University, Jinan, Shandong, China

¹¹Key Laboratory of Urinary Precision Diagnosis and Treatment in Universities of Shandong, Shandong Provincial Engineering Research Center for Precision Diagnosis and Treatment of Urological and Male Reproductive Diseases, Jinan, Shandong, China

¹²Department of Urology, The First Hospital of China Medical University, Shenyang, Liaoning, China

¹³Institute of Urology, China Medical University, Shenyang, Liaoning, China

¹⁴Department of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China

¹⁵Jiangxi Provincial Key Laboratory of Urinary System Diseases, Nanchang, Jiangxi, China

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Supplement: Additional supplemental material is published online only. To view, please visit the journal online (https://doi.org/10.1136/jitc-2025-014725).

None declared.

^✉

Dr Ju Guo; ndyfy02371@ncu.edu.cn

Dr Mo Zhang; peterzhang623@gmail.com

Dr Xuewen Jiang; xwjiang@sdu.edu.cn

PMCID: PMC13422945 PMID: 42527031

Abstract

Background

Neuroendocrine prostate cancer (NEPC) is characterized by strong immune evasion and profound metabolic reprogramming. A high regulatory T cell (Treg)/CD8⁺ T cell ratio and an increased proportion of M2/M1 tumor-associated macrophages (TAMs) in the NEPC tumor microenvironment (TME) are associated with poorer progression-free survival, a phenomenon linked to lipid accumulation within the TME. Understanding the regulatory mechanisms governing both the metabolic and immune landscapes of NEPC is critical.

Methods

To investigate these mechanisms, prostate cancer cell lines and patient samples were analyzed using immunohistochemistry, flow cytometry, PCR, western blotting, and mass spectrometry. The interleukin (IL)-8/CXCR2 signaling pathway was targeted for intervention in two tumor-bearing mouse models.

Results

Data revealed that IL-8/CXCR2 signaling drives the accumulation of free fatty acids and very-long-chain polyunsaturated fatty acids, leading to ferroptosis in tumor-infiltrating CD8⁺ T cells. This, in turn, promotes Treg cell infiltration and an M2 macrophage-dominant immune landscape. Mechanistically, IL-8/CXCR2 signaling upregulates the AKT-mTOR-FAS pathway while activating the mTOR-MYC-ELOVL5 axis via Rictor acetylation. In preclinical studies using NSG and B57BL/6 mouse models, CXCR2 inhibition restored CD8⁺ T cell antitumor activity and enhanced TAM phagocytosis, significantly reducing tumor growth.

Conclusions

These findings highlight CXCR2 as a promising immunotherapeutic target for NEPC and underscore its relevance in translational medicine.

Keywords: T cell, T regulatory cell - Treg, Tumor infiltrating lymphocyte - TIL, Prostate Cancer

WHAT IS ALREADY KNOWN ON THIS TOPIC

Neuroendocrine prostate cancer (NEPC) is characterized by aggressive progression, profound metabolic reprogramming, and an immunosuppressive tumor microenvironment (TME). Lipid accumulation within the TME has been associated with impaired antitumor immunity, but the mechanisms linking metabolic alterations to immune evasion in NEPC remain incompletely understood.

WHAT THIS STUDY ADDS

This study demonstrates that interleukin (IL)-8/CXCR2 signaling promotes the accumulation of free fatty acids and very-long-chain polyunsaturated fatty acids in NEPC, leading to ferroptosis of tumor-infiltrating CD8+ T cells and the establishment of an immunosuppressive TME characterized by increased regulatory T cell infiltration and M2 macrophage polarization. Mechanistically, CXCR2 signaling activates the AKT-mTOR-FAS and mTORC2-MYC-ELOVL5 pathways through Rictor acetylation. Pharmacologic inhibition of CXCR2 restored antitumor immune activity and suppressed tumor growth in preclinical models.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

These findings identify CXCR2 as a potential therapeutic target linking metabolic reprogramming and immune suppression in NEPC. Targeting the IL-8/CXCR2 axis may provide a novel immunometabolic strategy for improving treatment outcomes in patients with NEPC and support further translational and clinical investigation of CXCR2-directed therapies.

For the graphical abstract of this paper see (figure 1)

Introduction

Neuroendocrine prostate cancer (NEPC) represents an aggressive and therapy-resistant subtype of prostate cancer that most commonly emerges as a lineage-plasticity-driven adaptation to androgen receptor (AR)-targeted therapies.¹ NEPC exhibits high CXCR2 expression—the interleukin (IL)-8 receptor—which plays a key role in neuroendocrine differentiation and contributes to drug resistance.² The prostate cancer tumor microenvironment (TME) produces IL-8 through multiple mechanisms, including exosome secretion³ and direct production by prostate epithelial tumorous cells.⁴ Neuroendocrine cells secrete IL-8 and overexpress CXCR2, while luminal tumor cells lack CXCR2 expression.⁵ CXCR2, a G protein-coupled receptor, interacts with angiogenic CXC chemokines and mediates leukocyte chemotaxis and inflammatory responses.⁶ The CXCL8-CXCR1/2 axis is implicated in tumor progression, metastasis, and the regulation of cancer stem cell proliferation and self-renewal.⁷ Despite its established role in tumor, the impact of IL-8/CXCR2 signaling on the immune and metabolic landscapes of the prostate cancer TME remains poorly understood. IL-8 promotes intratumoral infiltration of polymorphonuclear myeloid-derived suppressor cells and reshapes immune cell metabolism within the TME.^3
4 Elevated IL-8 expression has been linked to aggressive prostate cancer phenotypes and AR loss in metastatic disease.⁸

Our previous studies demonstrated that IL-8 regulates lipid metabolism in prostate cancer, facilitating immune evasion.⁹ Notably, NEPC cells produce free fatty acids (FFAs), contributing to CD8⁺ T cell dysfunction.⁹ Emerging immunometabolism research suggests that the TME serves as a metabolic barrier to T cell function.^10
11 Furthermore, we identified IL-8/CXCR2 signaling as a key regulator of immune cell function and metabolic output within the prostate cancer microenvironment,⁹ providing novel insights into how tumor-intrinsic metabolic programs promote the establishment of an immunosuppressive niche.

Given the intricate interplay between tumor lipid metabolism, neuroendocrine differentiation, and immune evasion,^12–14 further investigation is warranted to elucidate how IL-8 binding to CXCR2 and its downstream signaling pathways influence lipid metabolism and immune tolerance in prostate cancer.

Results

The IL-8/CXCR2 pathway reshapes the immune microenvironment in prostate cancer

To investigate the role of IL-8 and CXCR2 in the invasion and lipid metabolism of high-grade prostate cancer, we performed transcriptome sequencing on samples from patients with prostate cancer, comparing those with NEPC and adenocarcinoma. The results showed significantly higher CXCR2 and IL-8 expression in the NEPC group (figure 2A). Meanwhile, survival analyses showed that high CXCR2 expression was associated with poorer overall survival in NEPC samples from the Stand Up To Cancer/Prostate Cancer Foundation (SU2C/PCF) 2019 cohort and in the castration-resistant prostate cancer (CRPC) cohort from GSE35988 (online supplemental figure 1A,B). In addition, in hormone-sensitive prostate adenocarcinoma, elevated CXCR2 expression was associated with tumor metastasis and biochemical recurrence, and exhibited a trend toward worse overall survival (online supplemental figure 1C–E). Similarly, high IL-8 expression was associated with unfavorable prognosis across multiple CRPC cohorts, including West Coast Dream Team (WCDT), GSE35988, and SU2C/PCF 2019, as well as in NEPC samples from the SU2C/PCF 2019 cohort (online supplemental figure 1F–I). Furthermore, in hormone-sensitive prostate adenocarcinoma, elevated IL-8 expression was associated with tumor metastasis and biochemical recurrence (online supplemental figure 1J,K), and was also linked to poorer overall survival (online supplemental figure 1L,M). To assess the impact of the IL-8/CXCR2 pathway on tumor metabolism and immune evasion, we conducted immunohistochemistry (IHC) staining on patients’ tissues. Scattered or clustered NEPC cells expressing IL-8 and CXCR2 were identified, with higher CXCR2 expression observed in NEPC tissues compared with CRPC and adenocarcinoma (figure 2B). Consistently, IL-8 expression was markedly elevated in NEPC samples (figure 2B). We also conducted a correlation analysis between CXCR2 IHC scores and CD8⁺ T-cell infiltration (IHC scores) and the results demonstrate a significant association between CXCR2 expression and CD8⁺ T-cell infiltration, supporting the link between CXCR2 signaling and the immune microenvironment in human tumors (figure 2B). To validate these findings in vitro, we selected BPH-1 served as a benign prostate cell line, while LNCaP—though metastatic in origin—was used as a model for androgen-sensitive prostate cancer; and C4-2B represented the CRPC phenotype; whereas enzalutamide-resistant cells LNCaP/MDVR and C4-2B/MDVR exhibited CXCR2 and IL-8 overexpression (OE). PC3, LASCPC-01, and NCI-H660 were chosen as small cell NEPC cell lines. CXCR2 and IL-8 expression were exclusive to CRPC and NEPC cell lines (figure 2C–D). Furthermore, we analyzed tumor-infiltrating lymphocytes (TILs) in the TME via IHC on patient tissues and flow cytometry (FCM) in xenograft models (human tumor-bearing NSG mice with a humanized immune microenvironment, figure 2E). The results revealed a decrease in CD8+ T cells and an increase in regulatory T cells (Tregs) (figure 2F), suggesting that IL-8/CXCR2 activation may modulate immune cell infiltration in both human and mouse TMEs (figure 1B and F). Notably, while IL-8, CXCR2, and CXCR1 were all upregulated in high-grade prostate cancer (figure 2D), only the coexpression of IL-8 and CXCR2 induced the observed immune modulation (figure 2F). This indicates that CXCR2 exerts a distinct regulatory function within the tumor immune microenvironment when coexpressed with IL-8, whereas CXCR2 upregulation alone is insufficient.

Notably, flow cytometric analysis of orthotopic tumors established using RM-1 or RM-1/CXCR2 cells revealed a significant reduction in the infiltration of B cells, dendritic cells, and neutrophils in RM-1/CXCR2 tumors compared with RM-1 controls (online supplemental figure 1N–P). A similar phenomenon was also observed in our previous study.¹⁵ Additionally, we observed increased expression of Treg-recruiting factors and decreased CD8+ T cell-recruiting factors in the TME (online supplemental figure 2A–E), which may explain the altered TIL distribution. However, further research is needed to fully elucidate these mechanisms.

The IL-8/CXCR2 pathway regulates the metabolic microenvironment of prostate cancer

Several studies have demonstrated that the tumor metabolic microenvironment can reshape the immune microenvironment.^11
14
16 Our previous research also provided preliminary evidence of this phenomenon in the prostate cancer TME.⁹ To further validate these findings, we injected the peripheral blood mononuclear cells (PBMCs) via the tail vein and implanted tumor cells at both inguinal sites of mice. After 3 weeks, the tumors were harvested for analysis. Metabolomic mass spectrometry (MS) revealed significantly enhanced lipid metabolism in tumor-bearing mice with IL-8/CXCR2-activated tumor cells (online supplemental figure 2F). We also compared CXCR2-inactive cell lines (LNCaP and C4-2B) with IL-8/CXCR2-activated cell lines (C4-2B/MDVR and PC3). The results showed that C4-2B/MDVR and PC3 cells efficiently used lipids from the medium, while lipid depletion impaired their growth (online supplemental figure 2G,H). Scanning electron microscopy indicated that in PC3 cells, stimulation with FFA enhanced metabolic activity and mitochondrial function, whereas no significant changes were observed in C4-2B cells (online supplemental figure 2I). Additionally, the LC-MS analysis uncovered that activation of the IL-8/CXCR2 pathway led to an increase of TME lipid infiltration (figure 1G,H), and the Oil Red O staining confirmed increased FA production on IL-8/CXCR2 activation (online supplemental figure 2J). Importantly, blocking CXCR2 inhibited tumor cell proliferation, even in the presence of FFA accumulation in the medium (online supplemental figure 2K); this indicates that lipid metabolism depends on the IL-8/CXCR2 pathway.

Suppression of CD8+ T cells induced by FFA accumulation in the TME

When IL-8 binding to CXCR2, it also upregulates the secretion of Treg-recruiting factors CCL1, CCL17, and CCL22 while simultaneously suppressing CD8+ T cell-recruiting factors CXCL10 and CXCL11 (online supplemental figure 2A–E). Blocking either IL-8 or CXCR2 disrupts this ligand–receptor interaction, thereby preventing downstream immunosuppressive effects (figure 3A–D, online supplemental figure 2A–E). Transwell assay was conducted to evaluate the relative contributions of FFA accumulation and the imbalance of recruiting factors. Clonogenicity analysis revealed that FFA accumulation impaired lymphocyte migration, while CXCL10/11 recruitment was suppressed; in contrast, treatment with a FASN inhibitor significantly restored CD8+ T cell migration (figure 3E). Additionally, the enhanced invasiveness of Treg cells was observed on palmitate supplementation, whereas FASN inhibition effectively suppressed their migration (figure 3E). Notably, the effects of Treg-recruiting factors on Treg migration were comparatively limited (figure 3E). Further mechanistic studies revealed that IL-8/CXCR2 activation regulates FAS expression and recruiting factor production through the AKT-mTOR (Raptor and Rictor) pathway, as confirmed by Western blot analysis (figure 3F–G). This pathway has been implicated in the regulation of FAS expression and Treg-recruiting factors.¹¹ ELISA and Western blot results further demonstrated that the IL-8/CXCR2-AKT pathway upregulates CCL1, CCL17, and CCL22 to enhance Treg recruitment, while concurrently inhibiting CXCL10 and CXCL11 secretion, thereby limiting CD8+ T cell migration (figure 2B–E). However, the immunosuppressive effects of FAS expression and FFA accumulation appear to be more dominant than the effects mediated by recruiting factors, aligning with findings reported by Ma et al.¹¹ Consistently, stronger staining for both Raptor and Rictor was observed in IL-8/CXCR2-activated cell lines (figure 3F–G). Gene expression sequencing of samples from patients with NEPC also revealed enhanced activation of the PI3K/AKT pathway (online supplemental figure 2L,M). Based on these findings, we plan to further investigate the mechanisms by which FFA accumulation influences CD8+ T cell infiltration and the distinct roles of mTORC1 and mTORC2 in regulating FAS expression and FFA accumulation.

IL-8/CXCR2 mediates free fatty acid accumulation and triggers ferroptosis in CD8+ T cells

To test if FA uptake could induce ferroptosis in CD8+ T cells, we first examined the effects of an FFA mixture on CD8+ T cell ferroptosis and cytokine production. on FFA treatment, levels of free iron ions, reactive oxygen species (ROS), and 4-hydroxynonenal (4-HNE) increased, while the glutathione (GSH)/glutathione disulfide (GSSG) ratio declined (figure 4A–C), indicating ferroptosis and significantly impaired CD8+ T cell proliferation. A similar phenomenon was observed in TIL CD8+ T cells from a mouse model with FASN-overexpressing C4-2B cells, IL-8/CXCR2 pathway-activated C4-2B cells, and PC3/FASN KD cells (online supplemental figure 2N and figure 4D). To further confirm whether CD8+ T cell ferroptosis and Treg cell proliferation occur in the TME enriched with FFAs due to IL-8/CXCR2 activation, we cultured C4-2B/CXCR2 cells with/without exogenous IL-8 in the FFA-deprived medium. This led to increased apoptosis of Treg cells and rescued CD8+ T cell viability (figure 4E). Moreover, transferrin receptor 1 (TfR1) expression in CD8+ T cells increased in the TME when the IL-8/CXCR2 pathway was activated or when FFAs accumulated (figure 4F). However, free iron ion levels, ROS, 4-HNE, and TfR1 expression in CD8+ T cells decreased, while the GSH/GSSG ratio improved on GSH treatment or CXCL15 mute therapy in C57BL/6 mice model (online supplemental figure 3A–G). FFAs also significantly suppressed the production of cytotoxic cytokines interferon-gamma (IFN-γ) and tumor necrosis factor-alpha (TNF-α) in CD8+T cells (figure 4G). Notably, inhibiting FASN or blocking the IL-8/CXCR2 pathway rescued FA-induced ferroptosis (figure 4D) and restored IFN-γ and TNF-α production in human CD8+ T cells (figure 3H,I). Since CXCR2 binds to multiple cytokines beyond IL-8 (CXCL15), such as CXCL1 and CXCL2, we used CXCL15 mutant C57BL/6 mice to specifically block the IL-15/CXCR2 axis and assess its impact on tumor progression. Our results confirmed ferroptosis in CD8+ T cells declined within the TME in CXCL15 mutant C57BL/6 mice (online supplemental figure 3H–J) and revealed attenuated tumor growth (online supplemental figure 2K–M). To further evaluate the immunosuppressive effects of IL-8/CXCR2 signaling, we examined FASN’s role in tumor growth and found that FASN inhibition significantly suppressed tumor progression (figure 4J).

IL-8/CXCR2-regulated production of very long-chain polyunsaturated fatty acids

Several studies have demonstrated that long-chain FAs with more unsaturated bonds are more readily taken up by CD36, leading to stronger ferroptosis activation and reduced cytotoxic cytokine production in lymphocytes.^11
17
18 Higher FA uptake by CD36-expressing CD8+ T cells, combined with evidence that TILs with high CD36 expression are more prone to oxidative stress,¹¹ suggests a potential mechanism linking FA metabolism and immune suppression. In this study, metabolic MS analysis revealed elevated levels of very long-chain polyunsaturated FAs (VLC-PUFAs), including docosahexaenoic acid (derived from α-linolenic acid (α-LA)) and clupanodonic acid (derived from linoleic acid (LA)), following IL-8/CXCR2 pathway activation (online supplemental figure 2F, figure 4A,B). This trend was reversed on CXCR2 blockade (figure 5C). Additionally, CD36 expression was higher in tumor-infiltrating CD8+ T cells and Treg cells compared with their counterparts in the spleen, with a similar pattern observed in macrophages (online supplemental figure 4A). Moreover, IL-8/CXCR2 signaling upregulated CD36 expression in tumor cells (online supplemental figure 4B). Further lipidomic analysis of purified CD8⁺ T cells demonstrated that exposure to the NEPC TME led to a marked increase in the uptake of both FFA and VLC-PUFA (online supplemental figure 4C). Metabolomic analysis further indicated that tumor cells secrete long-chain-PUFAs (including VLC-PUFAs) into the TME, where they are subsequently taken up by immune cells (figure 5D, online supplemental figure 4C,D). Indeed, RNA-seq analysis of patient tissues and PCR validation across multiple cell lines confirmed ELOVL5 upregulation in NEPC (figure 5E). Additionally, biological process (BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of NEPC and adenocarcinoma tissues revealed activation of FA elongation pathways in the NEPC group (online supplemental figure 4E). BP and KEGG analyses of multiple cell lines also suggested that the IL-8/CXCR2 pathway regulates VLC-PUFA production (online supplemental figure 4F,G). Given the link between NEPC and IL-8/CXCR2 activation, and the role of ELOVL5 in neuroendocrine differentiation as we found in previous research,¹⁹ we hypothesized that IL-8/CXCR2 plays a crucial role in ELOVL5-mediated VLC-PUFA production. Gene set enrichment analysis (GSEA) of differentially expressed genes between high and low CXCR2 expression groups highlighted MYC pathway activation (online supplemental figure 4H), consistent with reports identifying MYC as an upstream regulator of ELOVL5 expression.²⁰ These findings support the hypothesis of the IL-8/CXCR2–MYC–ELOVL5 regulatory axis in VLC-PUFA metabolism. Treatment with either navarixin (a CXCR2-blocking antibody) or the ELOVL5 inhibitor significantly reduced tumor size in tumor-bearing NSG mouse models (figure 5F–H). Blocking both FASN and ELOVL5 more effectively inhibited Treg cell migration than blocking either enzyme alone in transwell migration assays (figure 5). Additionally, CD8+ T cell migration was restored when both FASN and ELOVL5 were inhibited, demonstrating greater therapeutic efficacy than targeting either factor individually (figure 5). Immunofluorescence and cell staining also confirmed the coexpression of FASN and ELOVL5 with CXCR2 (figure 5J). Further, immunofluorescence and PCR analyses revealed that IL-8/CXCR2 pathway activation significantly increased FASN and ELOVL5 expression in tumor cells (online supplemental figure 5A,B). Collectively, our findings suggest that the IL-8/CXCR2 pathway fosters an immunosuppressive TME by upregulating FASN/ELOVL5 expression, enhancing FFA and VLC-PUFA infiltration, and promoting tumor growth.

Ferroptosis induced by VLC-PUFA

It is important to note that the human body, as well as mice, relies on exogenously sourced α-LA and LA for the synthesis of VLC-PUFAs (online supplemental figure 5C). Consequently, in the mouse model, α-LA and LA were included in the diet at 15% of the mice’s body weight. In vitro, CD8+ T cells cultured with VLC-PUFAs and FFAs exhibited higher levels of ferroptosis (figure 6A) and produced lower amounts of IFN-γ and TNF-α (figure 6B) compared with those cultured with palmitate or VLC-PUFA alone. We then investigated lymphocyte ferroptosis in the TME with and without VLC-PUFAs using a NSG mouse model. Removal of α-LA and LA from the diet significantly reduced CD8+ T cell ferroptotic damage, even when CXCR2 was still activated by IL-8 (figure 5C,D). The CXCR2-blocking antibody Navarixin showed treatment efficacy similar to that of a combination of ELOVL5 and FASN inhibitors (figure 6E). Expression of the TfR1 was upregulated in response to FFA/VLC-PUFA accumulation in the TME or tumor cells expressing IL-8/CXCR2 (figure 6F–H), while GSH/GSSG levels decreased and 4-HNE levels increased under these conditions (figure 5I,J). These findings outline the mechanism that the IL-8/CXCR2 pathway regulates tumor cells to produce VLC-PUFA and FFA; and induce lymphocyte damage within the TME.

IL-8/CXCR2-activated tumor cells also alter the distribution pattern of macrophages in the TME

It has been reported that CD36-mediated lipid uptake by macrophages induces M2 polarization.²¹ In our research, the expression of CD36 was significantly higher in TIL CD8+ T cells and tumor-associated macrophages (TAMs) compared with spleen-infiltrating CD8+ T cells and macrophages (online supplemental figure 4A). TAM levels declined in NEPC tumor tissues, and the M2/M1 macrophage ratio increased as the tumor progressed (online supplemental figure 5D). A similar phenomenon was observed in xenograft models, where TAM infiltration was reduced in animal models constructed with IL-8/CXCR2 pathway-activated tumor cells (online supplemental figure 5E,F). Additionally, our research uncovered that tumor cells in the TME highly express IL-8/CXCR2, they upregulate the infiltration of M2-type macrophages, which also highly express CD36 (online supplemental figure 5G). M2-type TAMs express high levels of CD36 and are regulated by IL-8/CXCR2 (online supplemental figure 5G). Blocking the CD36 pathway prevents macrophages from differentiating into the M2 phenotype, even when tumor cells in the TME express IL-8/CXCR2 (online supplemental figure 5H). We also exposed spleen macrophages to IL-8 medium for 48 hours, resulting in a significant increase in intracellular FA (online supplemental figure 5I). At the same time, the phagocytic ability of macrophages to engulf tumor cells declined when co-cultured with IL-8/CXCR2-activated tumor cells (online supplemental figure 6A). Additionally, macrophage migration was reduced when cultured with the supernatant collected from IL-8/CXCR2-activated tumor cells (online supplemental figure 6B). These data indicate that such a TME promotes M2-type macrophage differentiation and generates an immunosuppressive TME. A study demonstrated that Foxp3+ Tregs can produce IL-10, IL-13, and IL-4, cytokines that contribute to the differentiation of M2 macrophages.²² In our study, the secretion of IL-10, IL-13, and IL-4 was also elevated in the TME with IL-8/CXCR2 pathway-activated tumor cells (online supplemental figure 6C), offering an additional explanation for M2 macrophage infiltration. But why have not M2-type TAMs been damaged by activation-induced stress? Further investigation revealed that the expression of glutathione peroxidase 4 (GPX4) in macrophages, whether collected from spleen samples or TAMs, was higher than in CD8+ T cells from both the spleen and TILs (online supplemental figure 6D). While both GPX1 and GPX4 help protect cells from oxidative damage by detoxifying hydrogen peroxide and FA hydroperoxides,²² unlike GPX4, GPX1 does not reduce hydroperoxides in membrane lipids.²² Our further research also demonstrated that GPX4-overexpressing CD8⁺ T cells exhibited reduced lipid peroxidation and ferroptosis-associated markers compared with control T cells (online supplemental figure 6E–J), indicating effective protection against FFA/VLC-PUFA-induced ferroptotic stress within the TME. Importantly, GPX4-overexpressing CD8⁺ T cells showed significantly enhanced antitumor activity in vivo (online supplemental figure 6K,L). These findings suggest that restoring GPX4 expression can functionally rescue CD8⁺ T cells from ferroptosis and partially restore their cytotoxic capacity in NEPC models with activated IL-8/CXCR2 signaling; and also further highlight that GPX4 can maintain cellular redox balance and prevent oxidative stress.²³

In deeper studies, we isolated CD8+ T cells, Treg cells, and macrophages from both the TME and spleen of tumor-bearing mice and co-cultured them with C4-2B/CXCR2 cells in medium with or without IL-8 (figure 7A). We observed an increase in free iron ions and ROS levels when TME-derived CD8+T cells were co-cultured with C4-2B/CXCR2 in the presence of IL-8 (figure 7B). However, spleen-derived CD8+ T cells did not exhibit this trend (figure 7B), and no such phenomenon was observed in macrophages or Tregs (figure 6C,D). Furthermore, in TME-derived CD8+T cells co-cultured with C4-2B/CXCR2 in the presence of IL-8, we noted increased expression of TfR1, a decline in GSH/GSSG levels, and elevated 4-HNE levels (figure 7E–G). Meanwhile, free iron ion levels, ROS, 4-HNE, and TfR1 expression in CD8+ T cells gradually increased after co-cultured with C4-2B/CXCR2 for 12, 24 and 48 hours (online supplemental figure 7A–G); while Phen Green, Ki 67 and GSH/GSSG gradually decreased (online supplemental figure 7A–F). Above all, we primarily demonstrate that the increased ferroptotic vulnerability of CD8⁺ T cells is associated with lower GPX4 expression compared with Tregs and macrophages.

Mechanism of IL-8/CXCR2 regulation of ELOVL5 expression

Previously results provide a potential explanation for these observations: the IL-8/CXCR2-AKT-mTORC1 pathway regulates FAS expression and increases FFA production (figure 3F–G).¹¹ Furthermore, these results indicate that the MYC pathway plays a significant role in prostate cancer (online supplemental figure 8A–C, and figure 8A), consistent with previous studies showing that MYC upregulates ELOVL5 by regulating SREBP1.²⁰ These findings prompt further investigation into how CXCR2 regulates ELOVL5 expression. Reports suggest that the MYC pathway is modulated by mTOR,^24–27 and in our previous study, we confirmed that the IL-8/CXCR2 pathway regulates mTOR to control lipid production.⁹ Based on this, we hypothesize that the IL-8/CXCR2-mTOR-MYC pathway plays a key role in the regulation of ELOVL5 expression.

To test this hypothesis, we used JQ-1 (a MYC inhibitor) to investigate how mTOR regulates MYC expression. Our findings revealed an interesting observation: the Rictor (mTORC2) inhibitor significantly suppressed MYC expression, whereas rapamycin (a Raptor inhibitor) had a more modest effect on MYC levels (figure 7B,C). These results suggest that mTORC2 may regulate MYC expression, impacting the production of VLC-PUFA. Wiki Pathways and KEGG analysis revealed that the FoxO family may play a crucial role in the CXCR2-mTORC2 regulation of MYC expression (online supplemental figure 8D–F). We further confirmed that genetic depletion of mTORC2 via Rictor short hairpin RNA (shRNA) knockdown (KD) decreased MYC levels (figure 7D,E). In these experiments, the CXCR2 pathway was constitutively activated by adding IL-8 to the medium.

Previous reports suggest that inhibiting the phosphorylation of class IIa HDACs (HDAC4, HDAC5, and HDAC7) significantly attenuates mTORC2 signaling.²⁴ Our findings align with this observation: Reactome pathway analysis revealed that CXCR2 depletion enhanced FoxO pathway activity (online supplemental figure 9A–D). To investigate whether mTORC2-dependent FoxO acetylation, regulated via class IIa HDAC inactivation, was involved, we genetically depleted mTORC2 using Rictor shRNA. This suppression reduced class IIa HDAC phosphorylation, which correlated with inhibited FoxO acetylation and a loss of MYC expression (figure 7D,E). Additionally, FoxO1 was no longer phosphorylated in response to IL-8/CXCR2 pathway activation after Rictor was blocked, although total protein levels remained unchanged (figure 7D,E). These results confirm that MYC expression, through FoxO acetylation influenced by the IL-8/CXCR2 pathway (figure 7D,E). HDACs, particularly class IIa HDACs (such as HDAC4, HDAC5, and HDAC7), enter the nucleus in their dephosphorylated state, deacetylating histones and suppressing gene transcription.^26
27 When these HDACs are phosphorylated, they bind to 14–3-3 proteins and are exported from the nucleus, losing their histone deacetylation activity.^26
27 This nuclear export increases histone acetylation, promoting gene expression.^26
27 Our results confirm that Rictor regulates the phosphorylation of HDACs, impacting their deacetylation efficiency. To explore this further, we inhibited Rictor and restored HDACs’ deacetylation activity, comparing it to the inhibition of both Rictor and HDACs. The results showed that restoring HDACs’ deacetylation activity blocked MYC expression (figure 7D,E), as expected due to FoxO deacetylation (figure 7D,E). Immunofluorescence of tumor tissues confirmed the co-expression of Rictor, MYC, and ELOVL5 (figure 8F). Conversely, reducing HDAC expression rescued MYC expression (figure 7G,H). To investigate epigenetic and transcriptional regulation, we performed Chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR) assays in C4-2B and NCI-H660 cells. In C4-2B cells, H3K27ac enrichment at the Rictor promoter was minimal under control conditions but was significantly increased following acetyl-CoA (AC-CoA) treatment (figure 8), indicating enhanced promoter-associated histone acetylation. In parallel, anti-MYC ChIP revealed significant enrichment of the ELOVL5 promoter in NEPC cells, whereas no enrichment was observed in C4-2B cells, and no signal was detected in IgG controls (figure 8J). And then, to determine whether AC-CoA production is required for IL-8/CXCR2-mediated epigenetic activation of Rictor, we performed ChIP-qPCR assays to assess H3K27ac enrichment at the Rictor promoter. H3K27ac enrichment was minimal under basal conditions and comparable to IgG controls. IL-8 treatment significantly increased H3K27ac enrichment at the Rictor promoter, whereas pharmacological inhibition of AC-CoA synthesis with SB-204990 completely abolished this effect, restoring H3K27ac levels to baseline (figure 8K). Our data support the existence of an mTORC2–HDAC/FoxO phosphorylation–MYC signaling axis.

Furthermore, VLC-PUFA production decreased after blocking MYC or Rictor, while rapamycin had a limited effect (figure 8L). To assess the rescue efficiency of AKT/Rictor blockade, we conducted in vivo studies using PC3/shAKT or PC3/shRictor tumor cells (online supplemental figure 10A). We observed a reduction in Free Iron Ions and ROS levels in CD8+ T cells when the AKT or Rictor pathway was blocked in tumor cells (online supplemental figure 10B), along with a notable decrease in TfR1 expression (online supplemental figure 10C). Additionally, the infiltration of M1/M2 macrophages and the CD8+ T cell/Treg cell ratio was reversed in animal models with PC3/shAKT or PC3/shRictor tumor cells (online supplemental figure 10D). This could be due to the reduction in lipid production by tumor cells after blocking AKT and Rictor (online supplemental figure 10E).

Acetylation of Rictor regulated by acetyl-CoA through the IL-8/CXCR2 pathway

According to LC-MS analysis, activation of the IL-8/CXCR2 pathway led to an increase in AC-CoA production (figure 1G,H and online supplemental figure 2F). Notably, AC-CoA is known to influence histone acetylation, which is associated with an upregulation of Rictor gene expression.²⁸ To investigate how Rictor is regulated by the IL-8/CXCR2 pathway, we performed ELISA to measure AC-CoA levels. The results confirmed an increase in AC-CoA following IL-8/CXCR2 pathway activation (online supplemental figure 11A). We also observed that carnitine palmitoyltransferase 1 (CPT1) expression was significantly upregulated on IL-8/CXCR2 activation (online supplemental figure 11B). As the rate-limiting enzyme of mitochondrial FA import, CPT1 drives β-oxidation (FAO), a primary metabolic pathway that replenishes the intracellular AC-CoA pool.^29
30 Consistently, genetic or pharmacological blockade of CPT1 completely inhibited AC-CoA production in NEPC cells (online supplemental figure 11C). Conversely, Rictor expression was robustly induced by elevated AC-CoA concentrations in the medium (online supplemental figure 11D). Furthermore, luciferase assays demonstrated that Rictor reporter activity was markedly enhanced by FAO enhancers (such as palmitate, L-carnitine, and citrate) as well as direct AC-CoA treatment (online supplemental figure 11E–G). Consequently, the sharp decline in AC-CoA availability caused by CPT1 inhibition subsequently blunts downstream Rictor activation. Collectively, this multilayered loss- and gain-of-function evidence robustly demonstrates a metabolic-flux-driven causal chain where CPT1-dependent FA catabolism dictates Rictor activation via modulating the intracellular AC-CoA pool.

Therapeutic efficacy validated in the CXCL15 mutant C57BL/6 mouse model

We replicated the therapeutic effects observed in the NSG mouse model in C57BL/6 mice and used the detection of CXCL15, the murine homolog of IL-8,⁴ and its receptor CXCR2 to investigate the role of the IL-8/CXCR2 pathway in tumor metabolic reprogramming and its impact on immune cell distribution and survival within the TME. At the cellular level, we first upregulated CXCR2 expression in murine prostate cancer cells (RM-1) and examined the regulation of two key lipid metabolism enzymes, FAS and ELOVL5, through the CXCL15/CXCR2 pathway. Our results demonstrated that CXCL15/CXCR2 activation upregulated the AKT-Raptor-FAS and AKT-Rictor-ELOVL5 pathways (figure 8A,B). Metabolomic analysis revealed that the CXCL15/CXCR2 pathway activation increased the production of palmitic acid and VLC-PUFA (figure 9C). Since exogenous CXCL15 was used in our in vitro experiments, we first measured CXCL15 expression levels in C57BL/6 mice prior to conducting in vivo studies. The results showed that in mouse tumor models using RM-1 and RM-1/CXCR2 tumor cells, CXCL15 secretion levels were significantly upregulated in response to tumor stimulation, peaking at day 10, while no significant changes were observed at the cellular level (figure 8D,E). However, in the CXCL15 mutant model, the tumor failed to induce CXCL15 secretion in mice (figure 9E). Our previous data suggested that murine immune cells take up lipids secreted by tumor cells via the scavenger receptor CD36 on immune cell surfaces. We therefore examined CD36 expression levels on immune cells in C57BL/6 mice. The results demonstrated that, similar to findings in humanized mouse immune TME, CD36 expression was significantly upregulated in macrophages and CD8+ T cells within the murine TME compared with immune cells in the spleen (figure 9F). Furthermore, the in vivo levels of palmitic acid and VLC-PUFA were also elevated via the CXCL15/CXCR2 pathway (figure 9G). Cellular staining revealed that both macrophages and CD8+ T cells within the murine TME had engulfed substantial amounts of lipids (figure 9H). After culturing RM-1/CXCR2 tumor-bearing mice for 40 days, we isolated splenic macrophages and cultured them with different metabolites (figure 10A). The results showed that under conditions with palmitic acid or VLC-PUFA, macrophages were more likely to differentiate into the M2 phenotype and exhibited higher CD36 expression (figure 10B). Further investigation revealed that using a CD36 inhibitor or blocking the CXCL15/CXCR2 pathway reduced lipid uptake in mouse macrophages (figure 9C,D). Our study in NSG Mcie model also indicates that lipid-induced macrophage polarization may be associated with upregulation of the PPAR-γ pathway (figure 10E). Additionally, analysis revealed that rescuing TME-derived CD8⁺ T cells in the CXCL15 Mutant model reduced free iron and ROS levels while enhancing cell activation (figure 10F); and reduced TfR1 expression in CD8+ T cells (figure 10G). This suggests that CXCL15 mutant effectively reduced ferroptosis in CD8+ T cells in mice. Meanwhile, CXCL15 mutant induced a higher M1/M2 ratio in TAMs and decreased CD36 expression (figure 9H,I). Our data also showed that CXCL15 mutant significantly inhibited tumor growth (figure 9J,K).

Potential toxicity of navarixin therapy

Lastly, we evaluated the potential toxicity of Navarixin in NSG mice by assessing liver and kidney function markers, as well as myocardial infarction indicators, at 1, 3, 7, and 14 days postadministration. The results showed no significant side effects at the therapeutic dose used (online supplemental table 1).

Discussion

The TME is a highly dynamic and complex ecosystem that plays a pivotal role in tumor progression and immune regulation.³¹ Within this evolving landscape, tumor cells employ diverse strategies to evade immune surveillance, posing a significant challenge for cancer therapy, particularly in NEPC.⁹ They exploit intrinsic regulatory mechanisms to establish an immunosuppressive TME³² and manipulate immune cell metabolism to further suppress antitumor responses.³³ Notably, lipid metabolites in the TME have emerged as key regulators of immune responses.^34
35 However, the precise mechanisms by which tumors leverage lipid metabolism to evade immune attack remain largely undefined.

Recent studies have provided key insights into these mechanisms. Kumagai et al proposed that RHOA mutations confer a metabolic advantage that promotes the accumulation of Treg cells in tumors, fostering an immunosuppressive TME and impairing TIL function.¹⁰ Similarly, Ma et al demonstrated that CD36-mediated FA uptake by tumor-infiltrating CD8+ T cells induces lipid peroxidation and ferroptosis, ultimately reducing cytotoxic cytokine production and weakening antitumor immunity.¹¹ Furthermore, lipid metabolic enzymes such as the long-chain fatty acyl-CoA synthetases ACSL4 and ACSL3 regulate ferroptosis sensitivity by modulating the balance between PUFA-containing and monounsaturated FA-containing phospholipids.³⁶ However, whether these mechanisms directly drive T cell death within the TME remains unclear. Building on our previous research, we observed that high-grade prostate cancers produce significant levels of FFAs and VLC-PUFAs. And then, our findings also indicate that AC-CoA regulates Rictor expression primarily through epigenetic mechanisms, as evidenced by increased H3K27ac enrichment at the Rictor promoter following AC-CoA supplementation. Importantly, this effect is dependent on AC-CoA production, as inhibition of AC-CoA synthesis abolishes IL-8–induced promoter acetylation, supporting a causal role for AC-CoA in this process. In parallel, we demonstrate that MYC directly binds to the ELOVL5 promoter in a NEPC-specific manner, linking upstream metabolic reprogramming to downstream transcriptional control. Collectively, these findings define a coordinated regulatory axis in which IL-8/CXCR2-driven AC-CoA production promotes epigenetic activation of Rictor, thereby facilitating MYC-dependent transcriptional regulation of lipid metabolism genes such as ELOVL5. According to these data, we established an mTORC2–HDAC/FoxO phosphorylation–MYC regulatory axis. Notably, VLC-PUFA production was significantly reduced on MYC inhibition, leading us to define the IL-8/CXCR2–MYC–ELOVL5 pathway as the core regulatory axis driving lipid metabolic reprogramming. Given the established role of lipid metabolism in immune regulation, we hypothesized that these metabolic byproducts influence the tumor immune microenvironment by interacting with lymphocytes, particularly through CD36-mediated lipid uptake, ultimately leading to ferroptosis. To investigate this hypothesis, we conducted a study examining the underlying mechanisms of lipid-mediated immune suppression in the TME. Our findings reveal novel insights into the metabolic interactions between tumor cells and immune cells, particularly CD8+ T cells, and highlight the therapeutic potential of targeting lipid metabolism. Specifically, we demonstrate that FFAs and VLC-PUFAs produced by NEPC, regulated by the IL-8/CXCR2 pathway, play a critical role in immune evasion. Tumor cells exploit lipid metabolic pathways to create a hostile environment for T cells, impairing their ability to mount an effective antitumor response. FFAs induce oxidative stress and lipid peroxidation in CD8+ T cells, ultimately triggering ferroptosis—an iron-dependent form of cell death. This metabolic suppression not only reduces T cell cytotoxicity but also enhances the tumor’s ability to evade immune surveillance and resist destruction. Moreover, our study highlights the critical role of immune cell ferroptosis—a regulated form of cell death driven by lipid peroxide accumulation and iron-dependent oxidative stress—in tumor immune evasion. Ferroptosis has emerged as a novel mechanism with significant implications for cancer therapy.³⁷ While it has been investigated as a potential strategy for selectively eliminating tumor cells, our findings suggest that it also plays a key role in immune suppression.^38
39 In addition, we further elucidated how tumor cell lipid metabolism drives lipid accumulation in the TME, promoting M2 macrophage polarization, a process also linked to the high expression of CD36 in TAMs. Along with CD8+ T cell ferroptosis, this mechanism is collectively regulated by the IL-8/CXCR2 pathway in NEPC. These findings reveal a previously unrecognized role of the IL-8/CXCR2 signaling pathway in modulating lipid accumulation within CD8+ T cells in the TME. While this pathway is well-documented for its involvement in tumor progression and metastasis, its impact on immune regulation has only recently gained attention.^2
40
41 Additionally, we uncovered how IL-8/CXCR2 regulates ELOVL5 expression, with enrichment analyses identifying several pathways that merit further investigation. Building on our previous research, we proposed that the mTOR-MYC pathway plays a pivotal role in prostate cancer lipid metabolism.⁹ To further explore this, we investigated the molecular mechanisms by which this pathway regulates both lipid metabolism and immune cell function. Our findings reveal that AC-CoA enhances the Rictor-MYC-ELOVL5 pathway through Rictor acetylation, leading to increased VLC-PUFA production.

Our findings align with previous research showing that metabolic byproducts such as lactate, cholesterol, and other lipid metabolites can impair T cell function.^10
11 And our study advances this understanding by directly demonstrating that prostate cancer cells exploit lipid metabolic pathways to produce FFAs and VLC-PUFAs, which drive CD8+ T cell ferroptosis and promote M2 macrophage polarization. This process is primarily governed by the IL-8/CXCR2 signaling pathway. Targeting these metabolic pathways offers a promising strategy to restore both T cell and macrophage function, potentially enhancing the efficacy of immunotherapies (Graphic Abstract).

A notable limitation of the current study is that our findings mainly focus on the primary NEPC microenvironment, while direct validation of the IL-8/CXCR2-driven lipid accumulation and CD8⁺ T cell ferroptosis in metastatic lesions remains limited. This is largely due to clinical and technical constraints; patients with metastatic NEPC primarily receive systemic non-surgical therapies, making fresh, high-quality metastatic biopsies with sufficient cellular material exceptionally scarce for delicate lipidomic profiling and viable T cell isolation. Nevertheless, prior evidence suggests that core immunosuppressive and metabolic mechanisms identified in aggressive primary tumors are frequently conserved in metastatic sites.^42
43 While the complex macroenvironment of established distant niches warrants further validation through future multi-center tissue consortia, our current primary-tumor and ex vivo discoveries provide critical and independent translational insight for early therapeutic intervention. Furthermore, while we established a link between CXCR2-mediated FFA accumulation and CD8⁺ T cell ferroptosis, potential contributions from other microenvironmental metabolites (eg, glucose and amino acids) and parallel ferroptosis-regulatory pathways—such as FSP1-mediated lipid peroxide detoxification, iron metabolism, and redox regulation^44
45—warrant comprehensive characterization. Additionally, given emerging evidence that CXCR2 blockade can synergize with immune checkpoint inhibitors to overcome resistance in immunosuppressive tumors, investigating the crosstalk between IL-8/CXCR2 signaling and immune checkpoints represents a critical next step. Future studies are needed to dissect these multipathway interactions and evaluate combination strategies integrating metabolic targeting with immunotherapy.

Conclusion

In conclusion, IL-8/CXCR2 pathway activation reshapes the tumor immune microenvironment by promoting FFA and VLC-PUFA accumulation, inducing CD8+ T cell ferroptosis, driving M2 macrophage polarization, and facilitating immune evasion. In contrast, CXCR2 inhibition restores T cell function, promotes M1 macrophage polarization, and suppresses tumor growth.

Experimental model and methods details

Patients and samples

Human tissue samples, from human benign prostatic hyperplasia (BPH) and prostate cancer at various stages, were obtained from 20 patients with prostate cancer who underwent surgical resection at The First Affiliated Hospital of Guangzhou Medical University between 2022 and 2024. The adenocarcinoma samples were collected from patients with prostate cancer undergoing robot-assisted radical prostatectomy. CRPC samples were obtained from patients with primary adenocarcinoma of the prostate who were treated with hormonal therapy instead of surgery. Eventually, the tumor recurred (classified as CRPC), leading to urinary obstruction, and transurethral resection of the prostate was performed. NEPC samples represent primary prostate NEPC within the in situ prostate tissue. Each group consisted of nine samples, with average patient ages of 71±3.2 years, 72±1.2 years, 74±3.1 years, and 70±2.2 years, respectively. AR expression was notably present in the BPH, hormone-sensitive adenocarcinoma, and CRPC groups, while in the NEPC group, only one patient exhibited low levels of AR expression.

Cell lines and reagents

The benign prostate cell line BPH-1 (RRID:CVCL_1091) and prostate cancer cell lines LNCaP (RRID:CVCL_0395), C4-2 (RRID:CVCL_4784), PC3 (RRID:CVCL_C8XA), LASCPC-01 (RRID:CVCL_UE17), and NCI-H660 (RRID:CVCL_1576) were obtained from the American Type Culture Collection and confirmed mycoplasma-free. To investigate the molecular mechanisms driving NEPC processes, we used the PC3 cell line as an advanced, AR-negative prostate cancer model. Although PC3 was originally derived from a prostatic adenocarcinoma bone metastasis, it is widely acknowledged and used in the field as a robust in vitro model exhibiting distinct neuroendocrine-like features, characterized by the absence of AR/Prostate-specific antigen (PSA) signaling and the intrinsic expression of neuroendocrine markers naturally express high baseline levels of various neuroendocrine traits and show a strong propensity toward neuroendocrine differentiation under therapeutic or metabolic stress.^5
46–48 Crucially, our group’s prior research has firmly established that CXCR2 serves as a prominent biomarker for NEPC and plays a driving role in promoting neuroendocrine differentiation. Given that PC3 cells naturally exhibit a high baseline expression of CXCR2.² Therefore, PC3 serves as a highly justifiable and biologically relevant model to study the IL-8/CXCR2 axis and metabolic reprogramming in the context of aggressive, AR-negative NEPC lineages. NCI-H660 and LASCPC-01 cells were cultured in HITES medium, while LNCaP, C4-2, and PC3 cells were cultured in RPMI medium supplemented with 10% fetal bovine serum (FBS) and 1% penicillin. BPH-1 cells were cultured in RPMI medium supplemented with 20% FBS and 1% penicillin. The C4-2B/CXCR2 OE, C4-2B/IL-8 OE, C4-2B/CXCR2/IL-8 OE, C4-2B/FASN OE, PC3/CXCR2 KD, PC3/FASN KD, and PC3 ELOVL5 KD cell lines were constructed by Hanbio Tech (Shanghai, China). shRNA targeting FASN or CXCR2 was subcloned into the GFP-positive lentiviral vector FG12 (Addgene) to generate FG12-shFASN/CXCR2, and scrambled shRNA was used to generate the control vector. These cell lines were cultured in RPMI medium supplemented with 10% FBS and 1% penicillin. The LNCaP/MDVR and C4-2B/MDVR cell line were constructed from LNCaP and C4-2B cells and cultured in 10 µM enzalutamide. To test the effects of human IL-8 (hIL-8), FASN inhibitors, AKT blockers, and ELOVL5 KD on these cells, we treated them with 100 ng/mL hIL-8 (Hanbio Tech), 50 µM C75 (FASN inhibitor; Hanbio Tech), 5 µM GSK690693 (AKT inhibitor; Hanbio Tech), or 1.5 µg/mL shELOVL5 (Hanbio Tech). To examine the impact of lipids on the cells, RPMI medium without FBS, supplemented with 1 mM palmitate, was used. Alternatively, cells were cultured in RPMI medium containing lipid-depleted FBS. In some experiments, 50 µM lipids (palmitate and α-LA/LA; diluted in dimethyl sulfoxide [DMSO]) was added to the medium. Cells were also treated with either high (4.5 g/L (25 mM))-glucose or low (1 g/L (5.5 mM))-glucose medium. For CD36 block, we chose sulfosuccinimidyl oleate (10 µM). All cell lines were maintained at 37°C in an atmosphere containing 5% CO2. Cell counts were performed using a hemocytometer, and Trypan Blue staining was used to distinguish between live and dead cells.

It is well established that humans cannot synthesize PUFAs with multiple double bonds de novo; ω−6 and ω−3 PUFAs (mainly α-LA and LA) must be obtained from dietary sources and elongated to form VLC-PUFAs with more than 20 carbon atoms and multiple double bonds.⁴⁹ Since standard culture media contain limited amounts of these essential FAs, we supplemented α-LA and LA in our cell culture experiments and analyzed their metabolic profiles and gene expression.

The RM-1 murine prostate cancer cell line is cultured under standard conditions to ensure optimal growth and viability. The cells are maintained in high-glucose Dulbecco’s Modified Eagle’s Medium supplemented with 10% heat-inactivated FBS, 1% penicillin-streptomycin (100 U/mL), and optionally 2 mM L-glutamine or GlutaMAX to support metabolic activity. Incubation is carried out at 37°C with 5% CO₂ and 95% humidity to prevent medium evaporation. Murine CXCL15 is added at a final concentration of 50 ng/mL as required. The FA6-152 antibody at a final concentration of 10 µg/mL was selected for in vitro experiments to investigate the role of CD36 in regulating immune cell lipid uptake.

Validation of OE and KD cell lines can be found at online supplemental file 1.

Peripheral blood mononuclear cells culture models

PBMCs were collected from donor whole blood samples and isolated by density gradient centrifugation. Palmitate (Nacalai Tesque, Kyoto, Japan) or oleate (Fujifilm Wako) was dissolved in 100% ethanol at 200 mM and conjugated to FA-free bovine serum albumin (BSA) at a 5:1 molar ratio, resulting in a final concentration of 8 mM palmitate-BSA or oleate-BSA. This mixture was prepared by vortexing at 37°C for 3–4 hours with sonication. A total of 1×10⁵ whole PBMCs, or 1×10⁴ sorted T-cell subsets in the presence of 1×10⁵ irradiated Antigen-presenting cells (APCs), were stimulated with anti-CD3 monoclonal antibody (clone: OKT3) and anti-CD28 monoclonal antibody (clone: CD28.2). The cells were cultured in glucose-free RPMI medium (Thermo Fisher Scientific), supplemented with 10% lipid solution without FBS (Biowest, Nuaillé, France), 10 IU/mL IL-2, 20 ng/mL IL-7, 1 mM glucose, and the indicated concentrations of palmitate-BSA or oleate-BSA. Even though the data presented in this manuscript seem to correspond to individual donors, during the implementation of each individual experiment, it is ensured that PBMCs from the same donor are used, so the statistical comparison across groups is unneeded, and all of the donors are healthy people.

Xenograft animal models

Animal care and experiments were conducted in accordance with the guidelines of the Animal Committee of the National Cancer Center and approved by the Ethics Review Committee for Animal Experimentation of the National Cancer Center. Immunocompromised NSG (NOD.Cg-Prkdc Il2rg/SzJ) and nude (nu/nu) mice were obtained from SPF (Beijing) Biotechnology (Beijing, China). We use GraphPad to estimate the required sample size. Before randomization, label the animals using unique identifiers by ear tags, and then use Excel to assign animals to groups. This method helps us eliminate human bias in group assignment. A researcher is responsible for implementing the experimental protocol, while another researcher is responsible for analyzing the data. Neither of them knows the group assignments of the experimental subjects. Finally, the principal investigator combines the analyzed data with the group assignments to summarize the results. This strategy can ensure blinding of investigators during the conduct and analysis of the study. Initially, 3×10⁴ PBMCs were injected via the tail vein into 3–6 weeks old male NSG mice. During each animal experiment, ensure that PBMCs for all mice in both the experimental and control groups are extracted from the same donor’s blood. After 3–5 days, a total of 2×10⁶ cells from various cell lines were suspended in 0.1 mL of 1× RPMI 1640 medium supplemented with 10% FBS and 50% Matrigel (Corning) and then subcutaneously inoculated into the bilateral flanks of the mice. Mice were sacrificed either when tumor xenografts reached 1 cm³ (tumor volume calculated as volume (mm³) = length × height² / 2) or 40 days after the experiment began. In some experimental groups, 80 ng of hIL-8 in 200 µL of Iscove’s Modified Dulbecco’s Medium (Life Technologies, Grand Island, New York, USA) was administered once daily for 2 consecutive days. Mice in the control group received phosphate-buffered saline (PBS). To evaluate metabolic changes after blocking the AKT pathway, GSK690693 (AKT inhibitor) and C75 (FASN inhibitor) were administered intraperitoneally at 20 mg/kg weekly and daily, respectively. Additionally, α-LA and LA were provided as 15% of the mice’s body weight to promote the generation of VLC-PUFAs. Navarixin is typically administered orally to mice at a dose of 1–30 mg/kg daily using a suitable vehicle such as 0.5% carboxymethylcellulose or 5% DMSO+40% PEG300+55% water. For ELOVL5 block in mice we treated the tumor cells with sh-ELOVL5 (20 nmol/L) for 2 weeks before implanting. Tumor samples and serum were collected 3 weeks after tumor cell injection for TIL analysis and ELISA tests. Tumors were also harvested for metabolomics MS, while spleen samples were collected as controls.

Progression-free survival and overall survival in patients

RNA-seq count data from The Cancer Genome Atlas prostate adenocarcinoma cohort were obtained from the cBio Cancer Genomics Portal (https://www.cbioportal.org/), and the corresponding clinical and survival data were retrieved from the UCSC Xena database (https://xena.ucsc.edu/). Count data were log-transformed prior to downstream analyses. Transcriptomic data from the Memorial Sloan Kettering Cancer Center cohort and the SU2C/PCF 2019 dataset were also obtained from cBioPortal. Data from the WCDT cohort were downloaded from https://quigleylab.ucsf.edu/data, and additional transcriptomic datasets (GSE116918 and GSE35988) were retrieved from the Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov). Survival analyses were performed using R software. Kaplan-Meier curves were generated based on CXCR2 and CXCL8 expression levels and corresponding clinical outcomes using the survminer package. For the GSE35988 cohort, samples lacking IL8 expression data were excluded from IL8-related analyses. Optimal cut-off values were determined using the surv_cutpoint function. Differences between survival curves were assessed using the log-rank test, with p<0.05 considered statistically significant.

Animal experiment: C57BL/6 mice and RM-1 cell inoculation

To construct the RM-1/CXCR2 cell line, RM-1 cells were transduced with a CXCR2-overexpressing lentivirus, selected with puromycin, and stable clones were verified by qPCR, Western blot, and FCM for CXCR2 expression. C57BL/6 male mice (6–8 weeks old) were housed under specific pathogen-free conditions with a 12-hour light/dark cycle, controlled temperature (22–25°C), and free access to food and water. Before tumor cell implantation, mice were acclimated for 1 week to minimize stress-related variability.

CXCL15 mutant mice were generated by electroporating C57BL/6J zygotes with a mixture containing 50 ng/µL Cas9 protein (Millipore Sigma), 0.6 pmol/µL each crRNA (spacer sequence GCTGAGCCTTCTACCTGGGA; NCBI GRCm38.4 Chr5:90213456-90213475(+)) and tracrRNA (Millipore Sigma), along with 50 ng/µL ssODN donor (50GCTGAGCCTTCTACCTGGGAAGTGAAGGCTGCCATTGCTCCAGTGGATGCTGGAAGCCTTCTTGCAGTGCTGAGGGTGGAACCTCCCGGAAGGTGCAAGTGAAGCCTGGAAGcgtACCCAGGTAGAAGGCTCAGC, lower case indicates sequence modification; Integrated DNA Technologies, Ultramer). Electroporated zygotes were transferred the same day into pseudopregnant mice, which were allowed to give birth to potential founders. Sanger sequencing identified three founder mice carrying the intended CXCL15 mutation. PCR primers used for genotyping were: CXCL15-F: 5’-TGGCATCTGAGGAAGACACC-3’; CXCL15-R: 5’-CAGGGAAGTCTGCTGCTGTA-3’.

Luciferase-expressing RM-1-Luc cells and RM-1/CXCR2-Luc were cultured under standard conditions (described below), harvested at 80% confluence, and resuspended in PBS or serum-free medium at a concentration of 5×10⁶ cells/mL. Each mouse was anesthetized using isoflurane or intraperitoneal ketamine/xylazine, and 100 µL of the RM-1-Luc cells and RM-1/CXCR2-Luc cell suspension (5×10⁵ cells per mouse) was injected orthotopically into the dorsal prostate region. Tumor progression was monitored in vivo using bioluminescence imaging with an IVIS imaging system. Mice were injected intraperitoneally with D-luciferin (150 mg/kg, 10 min before imaging), and fluorescence signals were captured at different time points to assess tumor growth. Mice were also observed daily for body weight changes and overall health status. At the experimental endpoint, mice were euthanized, and tumors were harvested for histological analysis, FCM, and molecular assays.

Immunohistochemistry and immunofluorescence of tissue samples

IHC analyses were performed in slides from the same sample and captured in representative views. For IHC preparation, all sections (including target sample slides and positive and negative control slides) were deparaffinized, rehydrated, and boiled in citrate buffer (pH 6.0) for 40 min in a water bath prior to antibody staining. The slides were then incubated with primary antibodies (with optimized dilutions previously determined) for 1 hour at room temperature. Horseradish peroxidase-conjugated secondary antibodies (Dako EnVision+Kit) were applied for 30 min, followed by visualization with diaminobenzidine after a 30 min incubation at room temperature. For immunofluorescence, after washing with PBS, the sections were incubated with secondary antibodies—Donkey anti-Rabbit (H+L) Alexa Fluor 532 (Invitrogen), Donkey anti-Goat Mouse (H+L) Alexa Fluor 594, and Donkey anti-Goat (H+L) Alexa Fluor 488 (Invitrogen)—for 90 min at room temperature, and counterstained with 4′,6-diamidino-2-phenylindole (DAPI) (Sigma-Aldrich). A complete list of antibodies used is provided in online supplemental file 1.

Principles of IHC scores

The immunohistochemical staining results were assigned as the mean score considering both the intensity of staining and the proportion of tumor cells with an unequivocal positive reaction. Each section was independently assessed by two pathologists without prior knowledge of the patient data. A proportional rate of positive reactions was observed, and positivity was defined as the presence of brown signals in the cell cytoplasm. This measure is also known as the frequency, defined as follows: 1 for less than 25%, 2 for 26%–50%; 3 for 51%–75%, 4 for greater than 75%. The definition of intensity allocated as below: 3 for strong intensity, 2 for moderate intensity and 1 for weak. When the staining was heterogeneous, each component was scored independently and summed for the results. For example, a specimen containing 75% tumor cells with moderate intensity (3×2=6) and another with 25% tumor cells with weak intensity (1×1=1) received a final score of 6+1=7.

Immunofluorescence of cells and cell lipid uptake fluorescence assay

Cells were seeded the day before fixation (8×10³ cells per well). The cells were washed twice with PBS (14 190–094; Gibco) and fixed with 4% paraformaldehyde (PFA) for 15 min. After fixation, cells were washed three times with PBS, permeabilized for 20 min with 0.1% Triton X-100 in PBS, and blocked with 3% BSA in PBS for 30 min. The cells were then incubated with primary antibodies, diluted in 1% BSA in PBS, for 1.5 hours at 37°C. Following primary antibody incubation, the cells were washed three times with PBS, and secondary antibodies (anti-mouse Alexa 488, Invitrogen) diluted in PBS, along with Hoechst stain (1:500), were added for 30 min at 37°C in the dark. After incubation, cells were washed three times with PBS and stored in PBS at 4°C until imaging. A complete list of antibodies is provided in online supplemental file 1.

For cell lipid uptake fluorescence assay, seed the cells of interest in culture plates and allow them to grow to the desired confluence. Incubate the cells with a lipid-specific fluorescent dye, Boron-dipyrromethene (BODIPY). After incubation, wash the cells with PBS to remove any excess dye or unincorporated lipids. If necessary, fix the cells with paraformaldehyde to preserve the cellular structure. Use a fluorescence microscope or flow cytometer to detect the fluorescence intensity, which indicates lipid uptake by the cells. Quantify the fluorescence signal to assess the level of lipid uptake by the cells.

Western blot, ELISA and GSH/GSSG analyses

After culturing, the cells were lysed, and proteins were extracted using RIPA buffer following the manufacturer’s instructions. The extracted proteins were then separated by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Protein bands were detected using the chemiluminescence method (ECL Plus Western Blot Detection System; Amersham Biosciences, Foster City, California, USA). The concentrations of human cytokines were measured using specific sandwich ELISAs, also in accordance with the manufacturer’s instructions (Elascience, Wuhan, China). GSH and GSSG levels were measured by GSH test Kit (JCBIO, A061-1) and GSSG test Kit (JCBIO, A061-2). A full list of kits and antibodies is provided in online supplemental file 1.

Real-time PCR

Total RNA was extracted using TRIzol reagent, and complementary DNA (cDNA) was synthesized with the iScript cDNA Synthesis Kit (Bio-Rad, Richmond, California, USA). GAPDH was used as the housekeeping gene and served as an internal control. PCR amplification was conducted using SYBR Premix Ex Taq II (TAKARA, Dalian, Liaoning, China) following the manufacturer’s protocol. Reactions were performed on a Bio‐Rad iQ5 thermal cycler (Hercules, California, USA), and the quality of the PCR products was assessed through post-PCR melting curve analysis.

ChIP-qPCR assay

ChIP assays were performed in C4-2B cells treated with or without AC-CoA (500 nM), C4-2B/CXCR2 cells treated with IL-8 (± SB-204990, 30 µM), and in NEPC (NCI-H660) and prostate adenocarcinoma (C4-2B) cells. Cells were cross-linked with 1% formaldehyde, lysed, and sonicated to generate chromatin fragments of 200–500 bp. Immunoprecipitation was carried out using anti-H3K27ac or anti-MYC antibodies, with normal IgG as a negative control, and input chromatin was used as an internal reference. Following reversal of crosslinking, DNA was purified and analyzed by qPCR using primers targeting the Rictor or ELOVL5 promoter regions, as appropriate. Enrichment was calculated relative to input chromatin.

Liquid chromatography-mass spectrometry assay for free fatty acid species

An liquid chromatography-MS (LC-MS) assay was used to determine the concentrations of FFA species in the culture medium. LC was performed using an LC-20ADXR ternary pump system equipped with a DGU-20A5R degassing unit, SIL-20AC autosampler, and CTO-20AC column oven (Shimadzu., Kyoto, Japan). The LC system was coupled with an LTQ Orbitrap XL hybrid linear ion trap-Fourier transform mass spectrometer (Thermo Fisher Scientific). FFAs were detected by extracting the ion chromatograms of deprotonated ions ([M-H]⁻) with a mass tolerance of 10 ppm. Instrument control, data acquisition, and processing were carried out using Xcalibur V.2.1.0 software (Thermo Fisher Scientific).

Flow cytometry analysis

FCM staining and analysis were conducted as previously described in our paper.⁹ The antibodies used in the FCM analyses are listed in the online supplemental file 1. Cells were washed with a wash solution and stained with surface antibodies and a fixable viability dye (Thermo Fisher Scientific). Intracellular staining was then performed using intracellular antibodies and various Staining Buffer Sets (Thermo Fisher Scientific), following the manufacturer’s instructions. After washing, the cells were analyzed using an LSR Fortessa or Symphony instrument (BD Biosciences) and FlowJo software (BD Biosciences). We used FCM to isolate target cell types, and the gating process involved: Initial gating: Forward scatter and side scatter were used to exclude debris and select live, single cells. Dead cells were excluded using viability dyes. Lineage markers: For immune cell isolation, lineage-specific markers such as CD45 for leukocytes were used; Specific cell types: CD8+ T cells: Gated as CD45+CD3+CD8+; Treg cells: Gated as CD45+CD3+CD4+CD25+FOXP3+; macrophages: Gated as CD45+F4/80+CD11b+.

Apoptosis and proliferation analysis

Apoptosis was assessed by FCM using FITC-annexin V, 7-AAD, Phen Green SK, CM-H2DCFDA, Propidium Iodide (Thermo Fisher Scientific), and active caspase-3 staining. The staining reagents were diluted according to the manufacturer’s instructions. Proliferation was evaluated by FCM through the dilution of KI67 (Thermo Fisher Scientific)-labeled cells. All staining reagents were prepared according to the manufacturer’s instructions.

Transwell invasion assay

Matrigel (BD Biosciences) was diluted in a coating buffer (0.01 M Tris, pH 8.0, 0.7% NaCl) to a final concentration of 200–300 µg/mL (1:40–1:45 dilution from stock). Then, 100 µl of the diluted Matrigel was added to the upper chamber of a 24-well transwell (Corning, New York, USA) and incubated at 37°C for 2 hours to allow gelling. After the coating buffer was removed from the permeable support membrane, the test cells were resuspended in medium containing 1% FBS at a density of 2.5×10⁴ cells/300 µl and added to the upper chamber. The lower chamber was filled with 800 µl of fresh culture medium containing 5 µg/mL fibronectin (Santa Cruz, USA). Cells were incubated for 48 hours, and the cell-penetrating capacity was assessed by staining the membrane with the Diff-Quick Stain Kit (K7128, IMEB).

Principles of transwell score

The transwell staining results were assigned as the mean score considering the proportion of stain. This measure is also known as the frequency, defined as follows: 0 for less than 5%, 1 for less than 25%, 2 for 26%–50%; 3 for 51%–75%, 4 for greater than 75%.

Gene expression data analysis

Hierarchical cluster analysis of genes related to FA metabolism in our RNA-seq dataset was performed as described in a previously published study.¹⁹ Differential gene expression analysis was conducted on patient tissues and tumor tissues from mouse models, organized into several groups. Following this, GSEA was carried out on the differentially expressed genes. The KEGG and BP categories from the Gene Ontology database were referenced. Pathway analysis hallmarks were also derived from the previously published study.¹⁹

Quantification and statistical analysis

Statistical analysis was performed using GraphPad Prism V.7 (GraphPad Software, San Diego, California, USA, RRID: SCR_002798) or R V.3.1.1 (R Foundation for Statistical Computing, Vienna, Austria, RRID: SCR_001905). Normality was assessed using the Shapiro-Wilk test. Equality of variances was evaluated using Levene’s test. For comparisons between two groups, paired or unpaired two-tailed Student’s t-tests were applied as appropriate. When normality assumptions were not met, non-parametric tests (Mann-Whitney U test or Wilcoxon signed-rank test) were used. For comparisons among multiple groups, one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test was performed. Statistical reports include t-statistics, df, exact p values, and sample sizes (n) for each group. Effect sizes (Cohen’s d for pairwise comparisons and η² for ANOVA) are provided where applicable (online supplemental table 2).

Sample sizes for animal experiments were determined based on prior experience and pilot data. Post hoc power analysis was conducted using G*Power (V.3.1), assuming α=0.05 and power=0.8, confirming that the sample size was sufficient to detect biologically meaningful differences.

For transcriptomic analyses, differential expression was performed using DESeq2 with Benjamini-Hochberg false discovery rate (FDR) correction. Genes with |log2 fold change|>1 and adjusted p value (FDR) <0.05 were considered significant. Metabolomics data were log-transformed and normalized prior to statistical testing, and multiple testing correction was likewise performed using the Benjamini-Hochberg method to control the FDR. Adjusted p values <0.05 were considered statistically significant for all high-dimensional datasets. Effect sizes (Cohen’s d for pairwise comparisons and η² for ANOVA) are provided in the figure legends where applicable.

Samples were randomly selected and independent. For non-parametric comparisons, data were at least ordinal and distributions were assumed to have similar shapes. Statistical results included U-statistics (or z-statistics for large samples), exact p values, sample sizes, effect sizes, and descriptive statistics. Tumor growth curves were analyzed using two-way ANOVA with treatment and time as between-subject factors, including interaction effects. Normality and homogeneity of variance were assumed. F-statistics, df, exact p values, and post hoc comparisons were reported where applicable. A p value <0.05 was considered statistically significant.

Resource availability lead contact

Source identifier

Please direct any requests for further information or reagents to the lead contact, Yi Sun (yisun666@gzhmu.edu.cn).

Materials availability

Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Yi Sun (yisun666@gzhmu.edu.cn) or check online supplemental table 3.

Supplementary material

online supplemental figure 1

jitc-14-7-s001.pdf^{(25MB, pdf)}

DOI: 10.1136/jitc-2025-014725

online supplemental file 1

jitc-14-7-s002.pdf^{(144.3KB, pdf)}

DOI: 10.1136/jitc-2025-014725

online supplemental table 1

jitc-14-7-s003.pdf^{(404.4KB, pdf)}

DOI: 10.1136/jitc-2025-014725

Footnotes

Funding: This project funded by National Natural Science Foundation of China (Received by YS; Grant no. 81860454); China Postdoctoral Science Foundation (Received by YS; Grant no. 2021M700949); Guangdong Basic and Applied Basic Research Foundation (Received by JJ; Grant no. 2024A1515013090); Grants of Guangdong Science and Technology Department (Received by JJ; Grant no. 2024B1212030002); National Natural Science Foundation of China (Received by JG; Grant no. 82260500); Key Research and Development Program Project of Liaoning Province (Received by MZ; Grant no. 2025JH2/101800396); Natural Science Foundation of Shandong Province (Received by XuJ; Grant no. ZR2023QH010); Liaoning Provincial Science and Technology Plan Joint Program Key R&D Project, (Received by MZ; Grant no. 1210725033).

Provenance and peer review: Not commissioned; externally peer reviewed.

Patient consent for publication: Not applicable.

Ethics approval: This study was approved by the Ethics Committee of First Affiliated Hospital of Guangzhou Medical University (Ethics Office; kyglkgyfyy@163.com; ID number: ES-2024-K033-01). Participants gave informed consent to participate in the study before taking part.

Data availability free text: Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, YS (yisun666@gzhmu.edu.cn).

Data availability statement

Data are available upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

online supplemental figure 1

jitc-14-7-s001.pdf^{(25MB, pdf)}

DOI: 10.1136/jitc-2025-014725

online supplemental file 1

jitc-14-7-s002.pdf^{(144.3KB, pdf)}

DOI: 10.1136/jitc-2025-014725

online supplemental table 1

jitc-14-7-s003.pdf^{(404.4KB, pdf)}

DOI: 10.1136/jitc-2025-014725

Data Availability Statement

Data are available upon reasonable request.

[R1] 1.Wang Y, Wang Y, Ci X, et al. Molecular events in neuroendocrine prostate cancer development. Nat Rev Urol. 2021;18:581–96. doi: 10.1038/s41585-021-00490-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R2] 2.Li Y, He Y, Butler W, et al. Targeting cellular heterogeneity with CXCR2 blockade for the treatment of therapy-resistant prostate cancer. Sci Transl Med. 2019;11:eaax0428. doi: 10.1126/scitranslmed.aax0428. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R3] 3.Xu F, Wang X, Huang Y, et al. Prostate cancer cell-derived exosomal IL-8 fosters immune evasion by disturbing glucolipid metabolism of CD8+ T cell. Cell Rep. 2023;42:113424. doi: 10.1016/j.celrep.2023.113424. [DOI] [PubMed] [Google Scholar]

[R4] 4.Lopez-Bujanda ZA, Haffner MC, Chaimowitz MG, et al. Castration-mediated IL-8 promotes myeloid infiltration and prostate cancer progression. Nat Cancer. 2021;2:803–18. doi: 10.1038/s43018-021-00227-3. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R5] 5.Huang J, Yao JL, Zhang L, et al. Differential expression of interleukin-8 and its receptors in the neuroendocrine and non-neuroendocrine compartments of prostate cancer. Am J Pathol. 2005;166:1807–15. doi: 10.1016/S0002-9440(10)62490-X. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R6] 6.Chapman RW, Phillips JE, Hipkin RW, et al. CXCR2 antagonists for the treatment of pulmonary disease. Pharmacol Ther. 2009;121:55–68. doi: 10.1016/j.pharmthera.2008.10.005. [DOI] [PubMed] [Google Scholar]

[R7] 7.Ha H, Debnath B, Neamati N. Role of the CXCL8-CXCR1/2 Axis in Cancer and Inflammatory Diseases. Theranostics. 2017;7:1543–88. doi: 10.7150/thno.15625. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R8] 8.Maynard JP, Ertunc O, Kulac I, et al. IL8 Expression Is Associated with Prostate Cancer Aggressiveness and Androgen Receptor Loss in Primary and Metastatic Prostate Cancer. Mol Cancer Res. 2020;18:153–65. doi: 10.1158/1541-7786.MCR-19-0595. [DOI] [PubMed] [Google Scholar]

[R9] 9.Sun Y, Jing J, Xu H, et al. N-cadherin inhibitor creates a microenvironment that protect TILs from immune checkpoints and Treg cells. J Immunother Cancer. 2021;9:e002138. doi: 10.1136/jitc-2020-002138. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R10] 10.Kumagai S, Togashi Y, Sakai C, et al. An Oncogenic Alteration Creates a Microenvironment that Promotes Tumor Progression by Conferring a Metabolic Advantage to Regulatory T Cells. Immunity. 2020;53:187–203. doi: 10.1016/j.immuni.2020.06.016. [DOI] [PubMed] [Google Scholar]

[R11] 11.Ma X, Xiao L, Liu L, et al. CD36-mediated ferroptosis dampens intratumoral CD8+ T cell effector function and impairs their antitumor ability. Cell Metab. 2021;33:1001–12. doi: 10.1016/j.cmet.2021.02.015. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R12] 12.Mutlu AS, Gao SM, Zhang H, et al. Olfactory specificity regulates lipid metabolism through neuroendocrine signaling in Caenorhabditis elegans. Nat Commun. 2020;11:1450. doi: 10.1038/s41467-020-15296-8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R13] 13.Zhu M, Huang Y, Bender ME, et al. Evasion of Innate Immunity Contributes to Small Cell Lung Cancer Progression and Metastasis. Cancer Res. 2021;81:1813–26. doi: 10.1158/0008-5472.CAN-20-2808. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R14] 14.Wang J, Yang Y, Shao F, et al. Acetate reprogrammes tumour metabolism and promotes PD-L1 expression and immune evasion by upregulating c-Myc. Nat Metab. 2024;6:914–32. doi: 10.1038/s42255-024-01037-4. [DOI] [PubMed] [Google Scholar]

[R15] 15.Sun Y, Ren S, Wen W, et al. Targeting CXCR2 in prostate cancer cells can block CD47-SIRPα interaction and reverse M2 macrophage polarization in the TME. Mol Cancer. 2025;24:273. doi: 10.1186/s12943-025-02436-1. [DOI] [PMC free article] [PubMed] [Google Scholar]

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PERMALINK

CXCR2-mediated metabolic interaction between prostate cancer cells and the immunosuppressive tumor microenvironment

Yi Sun

Jun Jing

Shangqing Ren

Xu Luo

Wei Wen

Xin Jin

Guohua Zeng

Xuewen Jiang

Mo Zhang

Ju Guo

Abstract

Background

Methods

Results

Conclusions

WHAT IS ALREADY KNOWN ON THIS TOPIC

WHAT THIS STUDY ADDS

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Figure 1. Graphical abstract.

Introduction

Results

The IL-8/CXCR2 pathway reshapes the immune microenvironment in prostate cancer

The IL-8/CXCR2 pathway regulates the metabolic microenvironment of prostate cancer

Suppression of CD8+ T cells induced by FFA accumulation in the TME

IL-8/CXCR2 mediates free fatty acid accumulation and triggers ferroptosis in CD8+ T cells

IL-8/CXCR2-regulated production of very long-chain polyunsaturated fatty acids

Ferroptosis induced by VLC-PUFA

IL-8/CXCR2-activated tumor cells also alter the distribution pattern of macrophages in the TME

Mechanism of IL-8/CXCR2 regulation of ELOVL5 expression

Acetylation of Rictor regulated by acetyl-CoA through the IL-8/CXCR2 pathway

Therapeutic efficacy validated in the CXCL15 mutant C57BL/6 mouse model

Potential toxicity of navarixin therapy

Discussion

Conclusion

Experimental model and methods details

Patients and samples

Cell lines and reagents

Peripheral blood mononuclear cells culture models

Xenograft animal models

Progression-free survival and overall survival in patients

Animal experiment: C57BL/6 mice and RM-1 cell inoculation

Immunohistochemistry and immunofluorescence of tissue samples

Principles of IHC scores

Immunofluorescence of cells and cell lipid uptake fluorescence assay

Western blot, ELISA and GSH/GSSG analyses

Real-time PCR

ChIP-qPCR assay

Liquid chromatography-mass spectrometry assay for free fatty acid species

Flow cytometry analysis

Apoptosis and proliferation analysis

Transwell invasion assay

Principles of transwell score

Gene expression data analysis

Quantification and statistical analysis

Resource availability lead contact

Source identifier

Materials availability

Supplementary material

Footnotes

Data availability statement

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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