FABP4 interacts with PPARγ to promote malignant progression in pancreatic cancer

Summary

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with an exceptionally poor prognosis. Fatty acid-binding protein 4 (FABP4) has been implicated in tumorigenesis and peroxisome proliferator-activated receptor γ (PPARγ) signaling, but its precise functional role and underlying molecular mechanisms in PDAC remain poorly defined. Here, we showed that FABP4 is markedly upregulated in pancreatic cancer cells. Co-immunoprecipitation assays revealed an interaction between FABP4 and PPARγ, and FABP4 overexpression significantly enhanced pancreatic cancer cell viability, proliferation, and migratory capacity in vitro. Moreover, FABP4 overexpression was associated with increased lipid metabolic activity and reduced sensitivity to ferroptosis, and it substantially promoted the tumorigenic potential of PANC-1 cells in vivo. Notably, pharmacological inhibition of PPARγ effectively attenuated the malignant phenotypes elicited by FABP4 overexpression in pancreatic cancer cells, underscoring that PPARγ is critically involved in the FABP4-associated tumor progression phenotype.

Graphical abstract

Highlights

• •FABP4 significantly promotes the malignant progression of pancreatic cancer
• •FABP4 interacts with PPARγ at the protein level
• •Inhibition of PPARγ effectively reverses the oncogenic effects of FABP4

Pharmacological procedures; Endocrine regulation; Cancer

Introduction

Disrupted lipid metabolism is a hallmark of metabolic disorders and a major risk factor for obesity, type 2 diabetes, cardiovascular disease, and cancer, often leading to multi-organ damage including the liver, pancreas, and cardiovascular system.¹ These conditions impose substantial clinical and economic burdens worldwide. A key pathophysiological feature is dyslipidemia coupled with impaired lipid homeostasis, which drives excessive lipogenesis and lipid accumulation underlying many metabolism-related diseases.² Fatty acid-binding protein 4 (FABP4) expression is induced by lipid overload and functions as a critical regulator in lipid metabolism-associated pathologies.³

FABP4, also known as adipocyte protein 2 (aP2), is a highly expressed member of the FABP family, classically described in differentiated adipocytes and macrophages. As a small, water-soluble intracellular chaperone, FABP4 facilitates fatty acid (FA) uptake, intracellular trafficking, storage, and catabolism, thereby coordinating lipid flux and modulating glucolipid metabolism.^4,5 It interacts with peroxisome proliferator-activated receptor γ (PPARγ) and hormone-sensitive lipase (HSL) to regulate adipocyte homeostasis and energy balance.⁶ FAs not only serve as substrates for FABP4-mediated transport but also act as signaling ligands that modulate FABP4 expression.⁷ Transcriptional control by FAs, PPARγ agonists, insulin, and other cues governs FABP4 levels during cellular differentiation.^8,9,10 Although predominantly cytosolic, FABP4 can be secreted into circulation, where elevated concentrations correlate with obesity, atherosclerosis, and cardiovascular disease.^6,7,11,12,13 Beyond metabolic contexts, FABP4 has emerged as a pro-tumorigenic factor. Intracellular FABP4 promotes carcinogenesis and tumor progression within the tumor microenvironment (TME) by influencing lipid metabolism and signaling networks.¹⁴ Our prior work further links FABP4 to the pathogenesis of type 2 diabetes and diabetic nephropathy.^6,11 Together with classic adipokines that foster tumorigenesis via lipid metabolic reprogramming, FABP4 represents a critical intracellular lipid chaperone driving cancer-promoting processes.

PPARγ, a member of the nuclear hormone receptor superfamily, regulates lipid metabolism, insulin sensitivity, and glucose homeostasis¹⁵ and is highly expressed in adipocytes and macrophages. Accumulating evidence demonstrates that PPARγ promotes tumorigenesis in multiple cancers, including breast, liver, and pancreatic carcinoma.^16,17,18 Given its pro-tumorigenic actions and established interaction with FABP4, we hypothesized that FABP4 may cooperate with PPARγ to influence tumor lipid metabolism.

Epidemiological studies have linked body mass index (BMI), a surrogate marker of obesity, with increased risk of pancreatic ductal adenocarcinoma (PDAC) and poorer survival.¹⁹ Proposed mechanisms include dysregulated FA handling and altered lipid metabolism.²⁰ Emerging evidence indicates that FABP4 promotes tumor proliferation and progression by shuttling FAs into cancer cells to fuel energy demands.²¹ FABP4 has been shown to drive development and progression in multiple malignancies, including breast, ovarian, and colorectal cancers,^21,22,23 and is highly expressed in pancreatic cancer.²³ Nevertheless, its precise functional role and regulatory mechanisms in PDAC remain undefined.

In this study, we investigated FABP4 function and its potential regulatory pathways, focusing on the interaction between FABP4 and PPARγ and on how FABP4 may modulate the malignant phenotype of pancreatic cancer through binding and regulating PPARγ. By delineating the role of the FABP4-PPARγ axis in pancreatic cancer biology, we aim to uncover insights with diagnostic and therapeutic implications for PDAC.

Results

FABP4 is highly expressed in pancreatic cancer cells

FABP4 expression was assessed in human pancreatic cancer cell lines (PANC-1 and AsPC-1) and a normal human pancreatic ductal epithelial cell line (HPDE6-C7) by quantitative real-time PCR (real-time qPCR) and western blot. Compared with HPDE6-C7 cells, FABP4 expression was significantly elevated in both PANC-1 and AsPC-1 cell lines at the mRNA and protein levels (p < 0.05 vs. HPDE6-C7, n = 3 biological replicates of each cell line) (Figures 1A and 1B). To elucidate the functional role of FABP4 and its potential regulatory mechanisms in pancreatic cancer, we generated FABP4-overexpressing (OE-FABP4) and FABP4-knockdown (FABP4-targeting small interfering RNAs [si-FABP4]) PANC-1 and AsPC-1 cell models via plasmid transfection and small interfering RNA (siRNA)-mediated interference, respectively, with matched control groups (OE-NC and si-NC) established for comparative analyses. Successful establishment of these models was confirmed by real-time qPCR (p < 0.05 vs. OE-NC/si-NC) (Figures 1C and 1D) and western blot (p < 0.05 vs. OE-NC/si-NC) (Figures 1E and 1F). Overexpression of FABP4 was achieved in both cell lines, whereas FABP4 knockdown was efficiently induced in both cell lines.

Figure 1.

FABP4 is highly expressed in pancreatic cancer cells

(A) Real-time qPCR analysis showing FABP4 mRNA expression levels in human pancreatic cancer cell lines (PANC-1 and AsPC-1) and normal human pancreatic ductal epithelial cells (HPDE6-C7). As a result, FABP4 mRNA levels were significantly elevated in both PANC-1 and AsPC-1 cells compared with HPDE6-C7 cells (mean ± SD, n = 3 biological replicates per cell line; ∗p < 0.05 vs. HPDE6-C7, unpaired two-tailed t test).

(B) Western blot analysis was performed to assess FABP4 protein expression levels across pancreatic cancer cell lines and non-malignant pancreatic cells. The results showed that FABP4 protein expression was markedly upregulated in PANC-1 and AsPC-1 pancreatic cancer cells compared with the human pancreatic ductal epithelial cell line HPDE6-C7, with all differences reaching statistical significance (mean ± SD, n = 3 biological replicates per cell line; ∗p < 0.05 vs. HPDE6-C7, unpaired two-tailed t test).

(C) Real-time qPCR was performed to validate the transfection efficiency of the FABP4-overexpressing constructs in PANC-1 and AsPC-1 pancreatic cancer cells. The results demonstrated that FABP4 mRNA levels were markedly upregulated in cells transfected with the FABP4 plasmid (OE-FABP4 group) compared with those transfected with the empty vector control (OE-NC group), with a statistical significance (mean ± SD, n = 3 biological replicates per cell line; ∗p < 0.05 vs. OE-NC, unpaired two-tailed t test).

(D) Real-time qPCR validation of the knockdown efficiency of three FABP4-targeting small interfering RNAs (si-FABP4s) in PANC-1 and AsPC-1 pancreatic cancer cells. The results demonstrated that FABP4 mRNA levels were markedly downregulated in si-FABP4-transfected cells compared with those transfected with negative control siRNA (si-NC), with all differences reaching statistical significance (mean ± SD, n = 3 biological replicates per cell line; ∗p < 0.05 vs. si-NC, unpaired two-tailed t test).

(E) Western blot analysis confirming FABP4 protein overexpression in PANC-1 and AsPC-1 pancreatic cancer cells transfected with the FABP4-overexpressing plasmid (OE-FABP4) relative to empty vector controls (OE-NC). Densitometric quantification of FABP4 band intensities normalized to the internal control (GAPDH) revealed a significant upregulation in OE-FABP4 groups, with all differences reaching statistical significance compared to corresponding OE-NC controls (mean ± SD, n = 3 biological replicates per cell line; ∗p < 0.05, unpaired two-tailed t test).

(F) Western blot confirming decreased FABP4 protein expression in si-FABP4 cells compared with si-NC controls in both cell lines (mean ± SD, n = 3 biological replicates, ∗p < 0.05 vs. si-NC, unpaired two-tailed t test). All data are presented as mean ± standard deviation (SD). Comparisons between two groups were performed using unpaired two-tailed Student’s t test. Significance levels are indicated as ∗p < 0.05 vs. corresponding control group; ns indicates no statistical significance (p ≥ 0.05). All experiments were repeated independently at least three times with consistent results.

FABP4 promotes malignant phenotypes in pancreatic cancer cells

The effects of FABP4 overexpression and knockdown on cell viability, proliferation, and migration were evaluated in PANC-1 and AsPC-1 cells using Cell Counting Kit-8 (CCK-8), colony formation, and wound healing assays, respectively. Overexpression of FABP4 significantly enhanced cell viability, proliferation, and migratory capacity in both PANC-1 and AsPC-1 cells (p < 0.05 vs. OE-NC; n = 3 biological replicates per cell line) (Figures 2A–2C and 2E). In contrast, FABP4 knockdown markedly suppressed these malignant phenotypes, reducing viability, proliferation, and migration (p < 0.05 vs. si-NC; n = 3 biological replicates per cell line) (Figures 2B–2D and 2F).

Figure 2.

FABP4 promotes pancreatic cancer cell proliferation, colony formation, and migration in vitro

(A and B) CCK-8 cell viability assays. PANC-1 and AsPC-1 cells were transfected with either FABP4-overexpressing plasmid (OE-FABP4) or FABP4-targeting siRNA (si-FABP4), with corresponding empty vector (OE-NC) and negative control siRNA (si-NC) groups as controls. Cell viability was measured at 48, 72, and 96 h post-transfection. FABP4 overexpression (OE-FABP4) significantly increased cell viability at all tested time points compared with OE-NC controls (A), whereas FABP4 knockdown (si-FABP4) significantly reduced cell viability relative to si-NC controls (B) (mean ± SD, n = 3 biological replicates per cell line; ∗p < 0.05 vs. corresponding controls, unpaired two-tailed t test).

(C and D) Colony formation assays. The visible colonies formed in PANC-1 and AsPC-1 cells with FABP4 overexpression (OE-FABP4) or transient FABP4 knockdown (si-FABP4) were fixed with 4% paraformaldehyde, stained with crystal violet, and counted (colonies with >50 cells were considered positive). FABP4 overexpression significantly increased colony numbers compared with OE-NC controls (C), while FABP4 knockdown led to a significant reduction in colony numbers relative to si-NC controls (D) (mean ± SD, n = 3 biological replicates per cell line; ∗p < 0.05 vs. corresponding controls, unpaired two-tailed t test).

(E and F) Wound healing (scratch) assays. Confluent monolayers of PANC-1 and AsPC-1 cells with FABP4 overexpression (OE-FABP4) or knockdown (si-FABP4) were scratched using a 200 μL pipette tip to create a standardized wound gap. Wound closure was imaged at 0, 24, and 48 h, and the migration distance was quantified. FABP4 overexpression accelerated wound closure at 24 and 48 h compared with OE-NC controls (E), whereas FABP4 knockdown impaired wound closure relative to si-NC controls (F) (mean ± SD, n = 3 biological replicates per cell line; ∗p < 0.05 vs. corresponding controls, unpaired two-tailed t test). ns indicates no statistical significance. All data are presented as mean ± standard deviation (SD). Comparisons between two groups were performed using unpaired two-tailed Student’s t test. Significance levels are indicated as ∗p < 0.05 vs. corresponding control group; ns indicates no statistical significance (p ≥ 0.05). All experiments were repeated independently at least three times with consistent results.

FABP4 regulates lipid metabolic activity in pancreatic cancer cells

To investigate the impact of FABP4 on lipid metabolism in pancreatic cancer cells, we measured changes in lipid metabolism-related indicators. The results showed that in both PANC-1 and AsPC-1 cells, overexpression of FABP4 significantly increased the levels of free FAs (FFAs) and malondialdehyde (MDA) (p < 0.05 vs. OE-NC; n = 3 biological replicates per cell line) (Figures 3A and 3C), whereas knockdown of FABP4 significantly decreased their FFA and MDA content (p < 0.05 vs. si-NC; n = 3 biological replicates per cell line) (Figures 3B and 3D). To directly address whether FABP4 regulates de novo lipogenesis, we examined the mRNA expression of key lipogenic enzymes including FA synthase (FASN), ATP-citrate lyase (ACLY), and stearoyl-CoA desaturase-1 (SCD1) in PANC-1 cells under FABP4 overexpression and knockdown conditions. Our results demonstrated that FABP4 overexpression significantly upregulated the mRNA expression of FASN, ACLY, and SCD1 (p < 0.05 vs. OE-NC; n = 3 biological replicates), while FABP4 knockdown markedly downregulated their expression (p < 0.05 vs. si-NC; n = 3 biological replicates) (Figures 3E–3J). Together, these data indicate that FABP4 overexpression not only increases intracellular FFA levels but also actively promotes de novo lipogenesis by upregulating the transcription of key lipogenic genes. Oil red O staining was used to detect changes in lipid droplet content in PANC-1 cells following FABP4 overexpression. The results demonstrated that FABP4 overexpression significantly increased the lipid droplet content in PANC-1 cells (p < 0.05 vs. OE-NC; n = 3 biological replicates) (Figure 3K).

Figure 3.

FABP4 regulates lipid metabolic activity and lipogenic gene expression in pancreatic cancer cells

(A and B) Quantification of intracellular free fatty acid (FFA) levels. PANC-1 and AsPC-1 cells were transfected with either FABP4-overexpressing plasmid (OE-FABP4) or FABP4-targeting siRNA (si-FABP4), with corresponding empty vector (OE-NC) and negative control siRNA (si-NC) groups as controls. FABP4 overexpression (OE-FABP4) significantly increased intracellular FFA levels in both cell lines compared with OE-NC controls (A), whereas FABP4 knockdown (si-FABP4) significantly reduced FFA levels relative to si-NC controls (B) (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. corresponding controls).

(C and D) Malondialdehyde (MDA) measurement as an indicator of lipid peroxidation. Consistent with the FFA level trends, FABP4 overexpression (OE-FABP4) significantly increased MDA levels in PANC-1 and AsPC-1 cells compared with OE-NC controls (C), while FABP4 knockdown (si-FABP4) led to a significant reduction in MDA levels relative to si-NC controls (D) (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. corresponding controls).

(E–J) Real-time qPCR analysis of lipogenic gene expression. PANC-1 cells with FABP4 overexpression (OE-FABP4) or transient FABP4 knockdown (si-FABP4) were harvested for total RNA extraction, followed by cDNA synthesis and real-time qPCR using gene-specific primers. FABP4 overexpression significantly upregulated the mRNA expression of stearoyl-CoA desaturase 1 (SCD1, E), ATP-citrate lyase (ACLY, G), and fatty acid synthase (FASN, I) in PANC-1 cells, while FABP4 knockdown resulted in a significant downregulation of these lipogenic genes (F, H, and J, respectively) (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. corresponding controls).

(K) Oil red O staining of intracellular lipid droplets. PANC-1 cells with FABP4 overexpression (OE-FABP4) or control transfection (OE-NC) were fixed with 4% paraformaldehyde, stained with oil red O working solution, and counterstained with hematoxylin. Representative pictures show that FABP4 overexpression significantly increased lipid droplet content in PANC-1 cells, as quantified by integrated optical density (IOD) using ImageJ software (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. OE-NC). Scale bars: 100 μm. All data are presented as mean ± standard deviation (SD). Comparisons between two groups were performed using unpaired two-tailed Student’s t test. Significance levels are indicated as ∗p < 0.05 vs. corresponding control group. All experiments were repeated independently at least three times with consistent results.

Subsequently, to further explore the effect of FABP4 alteration on intracellular lipid levels in pancreatic cancer cells, high-resolution untargeted lipidomic relative quantification analysis was performed on PANC-1 cells from the OE-FABP4 group (n = 3) and the OE-NC control group (n = 3). A total of 30 lipid subclasses and 746 lipid molecules were identified (Figure S1A). Changes in the expression of various lipid subclasses in PANC-1 cells were compared using chromatography-mass spectrometric analysis. The results indicated that upon FABP4 overexpression, the levels of different lipid subclasses in PANC-1 cells were altered compared to the control group. Specifically, levels of monoacylglycerols (MGs), diacylglycerols (DGs), phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), phosphatidic acids (PAs), phosphatidylinositols (PIs), and sphingosine phosphates (SPHPs) were elevated, whereas the levels of ceramides (Cer), cholesterol esters (ChEs), and sphingomyelins (SMs) were lower than those in the control group (Figures S1B and S2).

FABP4 expression is associated with altered levels of ferroptosis-related markers in pancreatic cancer cells

FABP4 has been reported to regulate ferroptosis across multiple malignancies.² To explore whether FABP4 participates in ferroptosis modulation in pancreatic cancer, we performed a series of functional experiments. First, given that excess intracellular ferrous iron catalyzes hydroxyl radical generation to drive ferroptosis onset,²⁴ we quantified intracellular iron ion levels in human pancreatic cancer cell lines. The results demonstrated that FABP4 overexpression (n = 3) significantly reduced intracellular iron ion content, while FABP4 knockdown (n = 3) led to a marked elevation of intracellular iron levels, with both changes reaching statistical significance compared to their respective negative controls (OE-NC/si-NC, p < 0.05) (Figures 4A and 4B). Second, as the accumulation of iron metabolism-associated reactive oxygen species (ROS) can damage cellular membranes and ultimately trigger ferroptotic cell death,²⁵ we further assessed ferroptosis-related ROS levels in pancreatic cancer cells. Consistent with the iron level trends, FABP4 overexpression decreased ferroptosis-associated ROS levels, whereas FABP4 knockdown increased ROS accumulation, with all differences statistically significant versus corresponding negative controls (OE-NC/si-NC, p < 0.05; n = 3 biological replicates per cell line) (Figures 4C and 4D).

Figure 4.

FABP4 regulates ferroptosis-related marker expression and redox homeostasis in pancreatic cancer cells

(A and B) Quantification of intracellular ferrous iron (Fe²⁺) levels. PANC-1 and AsPC-1 cells were transfected with either FABP4-overexpressing plasmid (OE-FABP4) or FABP4-targeting siRNA (si-FABP4), with corresponding empty vector (OE-NC) and negative control siRNA (si-NC) groups as controls. FABP4 overexpression (OE-FABP4) significantly decreased intracellular iron ion levels in both cell lines compared with OE-NC controls, whereas FABP4 knockdown (si-FABP4) led to a significant elevation of intracellular iron levels relative to si-NC controls (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. corresponding controls).

(C and D) Measurement of ferroptosis-associated reactive oxygen species (ROS) levels. Consistent with the iron level trends, FABP4 overexpression significantly reduced ROS levels in PANC-1 and AsPC-1 cells, while FABP4 knockdown resulted in a significant increase in ROS accumulation (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. corresponding controls).

(E and F) Real-time qPCR analysis of glutathione peroxidase 4 (GPX4) mRNA expression. PANC-1 and AsPC-1 cells with stable FABP4 overexpression (OE-FABP4) or transient FABP4 knockdown (si-FABP4) were harvested for total RNA extraction, followed by cDNA synthesis and real-time qPCR using gene-specific primers. FABP4 overexpression significantly increased GPX4 mRNA levels in both cell lines, whereas FABP4 knockdown markedly reduced GPX4 mRNA expression (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. corresponding controls).

(G and H) Real-time qPCR analysis of solute carrier family 7 member 11 (SLC7A11) mRNA expression. FABP4 overexpression significantly upregulated SLC7A11 mRNA levels in PANC-1 and AsPC-1 cells, while FABP4 knockdown led to a significant downregulation of SLC7A11 mRNA expression (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. corresponding controls). All data are presented as mean ± standard deviation (SD). Comparisons between two groups were performed using unpaired two-tailed Student’s t test. Significance levels are indicated as ∗p < 0.05 vs. corresponding control group; ns indicates no statistical significance (p ≥ 0.05). All experiments were repeated independently at least three times with consistent results.

Glutathione peroxidase 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11) are well-established core regulators of ferroptosis. GPX4 functions as a critical antioxidant enzyme that counteracts lipid peroxidation by reducing lipid peroxide accumulation, thereby suppressing ferroptotic cell death.²⁶ SLC7A11, by mediating cystine/glutamate antiporter activity and regulating glutathione (GSH) synthesis, negatively regulates ferroptosis.²⁷ To further characterize the regulatory role of FABP4 in pancreatic cancer ferroptosis, we assessed the mRNA expression levels of these two canonical ferroptosis markers via real-time qPCR. The results demonstrated that FABP4 overexpression led to a significant upregulation of GPX4 mRNA levels in both PANC-1 and AsPC-1 pancreatic cancer cell lines. In contrast, FABP4 knockdown (n = 3) markedly reduced GPX4 mRNA expression, with all changes reaching statistical significance compared to their respective negative controls (OE-NC/si-NC, p < 0.05; n = 3 biological replicates per cell line) (Figures 4E and 4F). Consistent with the GPX4 expression trends, FABP4 overexpression significantly increased SLC7A11 mRNA levels in both PANC-1 and AsPC-1 cells, whereas FABP4 knockdown resulted in a significant downregulation of SLC7A11 mRNA expression (OE-NC/si-NC, p < 0.05; n = 3 biological replicates per cell line) (Figures 4G and 4H).

FABP4 promotes tumor growth and malignant progression of PANC-1 cells in vivo

To evaluate the functional role of FABP4 in promoting tumorigenicity in vivo, we established a subcutaneous xenograft model by implanting PANC-1 cells into nude mice. The results demonstrated that FABP4 overexpression (OE-FABP4 group, n = 6) led to a significant acceleration of tumor growth kinetics compared with the negative control group (OE-NC, n = 5) (p < 0.05) (Figure 5A). This finding is consistent with previous reports indicating that FABP4 enhances pancreatic cancer cell proliferation and tumor progression. Immunohistochemical (IHC) analysis of the excised xenograft tumors further confirmed the molecular changes associated with FABP4 overexpression. Compared to OE-NC controls, tumors in the OE-FABP4 group exhibited markedly elevated expression levels of both FABP4 and PPARγ (p < 0.05 vs. OE-NC) (Figures 5B and 5C). Consistent with the enhanced growth rate, the proliferative activity within the tumors was significantly increased, as evidenced by a higher percentage of Ki67-positive cells in the OE-FABP4 group (p < 0.05 vs. OE-NC) (Figure 5D). Both OE-FABP4 and OE-NC tumors exhibited robust CD31-positive microvessels, and quantitative analysis revealed no statistically significant difference between the two groups (Figure 5E).

Figure 5.

FABP4 promotes the tumor growth and malignancy of PANC-1 cells

(A) Longitudinal monitoring of subcutaneous xenograft tumor growth. PANC-1 cells stably overexpressing FABP4 (OE-FABP4, n = 6) or empty vector controls (OE-NC, n = 5) were subcutaneously implanted into nude mice. Tumor volume was measured every 7 days over a 28-day period. FABP4 overexpression led to a significant acceleration of tumor growth kinetics compared with OE-NC controls (mean ± SD, ∗p < 0.05 vs. OE-NC).

(B–E) Immunohistochemical (IHC) analysis of xenograft tumor tissues. (B) OE-FABP4 tumors showed markedly elevated FABP4 protein levels compared with OE-NC controls (n = 6 vs. n = 5, mean ± SD, ∗p < 0.05 vs. OE-NC), confirming efficient in vivo transgene expression. Scale bars: 100 μm. (C) OE-FABP4 tumors exhibited significantly increased PPARγ expression levels relative to OE-NC controls (mean ± SD, ∗p < 0.05 vs. OE-NC). Scale bars: 100 μm. (D) The proliferative activity of tumor cells, as measured by the percentage of Ki67-positive nuclei, was significantly higher in OE-FABP4 tumors than in OE-NC controls (mean ± SD, ∗p < 0.05 vs. OE-NC). Scale bars: 100 μm. (E) IHC staining for platelet endothelial cell adhesion molecule-1 (CD31) was performed to evaluate microvessel density within tumors. No statistically significant difference in CD31-positive microvessel counts was observed between OE-FABP4 and OE-NC groups (mean ± SD, ns, p ≥ 0.05). Scale bars: 50 μm. All data are presented as mean ± standard deviation (SD). Comparisons between two groups were performed using unpaired two-tailed Student’s t test. Significance levels are indicated as ∗p < 0.05 vs. corresponding control group; ns indicates no statistical significance (p ≥ 0.05). All experiments were repeated independently at least three times with consistent results.

FABP4 interacts with PPARγ at the protein level

Bioinformatic analysis has identified a peroxisome proliferator response element (PPRE) within the human FABP4 promoter region, suggesting that PPARγ can transcriptionally regulate FABP4 expression by binding to this specific motif.²⁸ To further investigate whether FABP4 drives pancreatic cancer progression through the PPARγ signaling axis, we established a PPARγ-overexpressing PANC-1 cell model via plasmid transfection, alongside a corresponding negative control (OE-NC) group. Overexpression efficiency was verified by real-time qPCR and western blot, showing increases in PPARγ mRNA and protein levels to 1,307.6-fold and 3.1664-fold, respectively, relative to OE-NC (p < 0.05; n = 3 biological replicates per cell line) (Figures 6A and 6B). Real-time qPCR analysis demonstrated that the overexpression of FABP4 elevated the mRNA levels of PPARγ by a factor of 1.4208. Conversely, the overexpression of PPARγ augmented the mRNA levels of FABP4 by a factor of 5.482 (p < 0.05 compared to the OE-NC; n = 3 biological replicates for each cell line) (Figures 6C and 6D), indicating mutual transcriptional regulation. Immunofluorescence colocalization in PANC-1 cells revealed predominant cytoplasmic localization of both FABP4 and PPARγ, with lower nuclear expression (Figure 6E). To validate the physical interaction between these two proteins, we performed Co-immunoprecipitation (Co-IP) assays. Initial experiments in human embryonic kidney 293T (HEK293T) cells, utilizing plasmid co-transfection to express exogenous FABP4 and PPARγ, confirmed a direct interaction between the exogenous proteins at the protein level (Figure 6F). Furthermore, endogenous Co-IP assays conducted in PANC-1 cells demonstrated that endogenous FABP4 and PPARγ also form a complex in a native cellular context (Figure 6G).

Figure 6.

FABP4 interacts with PPARγ at the protein level and reciprocally regulates transcriptional expression in pancreatic cancer cells

(A and B) Establishment and validation of PPARγ-overexpressing PANC-1 cell models. PANC-1 cells were transfected with a PPARγ-overexpressing plasmid (OE-PPARγ), with empty vector-transfected cells (OE-NC) as controls. Real-time qPCR analysis revealed that PPARγ mRNA levels were upregulated by 1,307.6-fold in OE-PPARγ cells compared with OE-NC controls. Western blot analysis further confirmed that PPARγ protein levels were increased by 3.1664-fold relative to OE-NC controls (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. OE-NC).

(C and D) Reciprocal transcriptional regulation between FABP4 and PPARγ. Real-time qPCR analysis demonstrated that FABP4 overexpression (OE-FABP4) in PANC-1 cells increased PPARγ mRNA levels to 1.4208-fold compared with OE-NC controls (C), while PPARγ overexpression (OE-PPARγ) elevated FABP4 mRNA levels to 5.482-fold relative to OE-NC controls (D) (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. OE-NC).

(E) Subcellular localization of FABP4 and PPARγ via immunofluorescence staining. PANC-1 cells were fixed, permeabilized, and stained with specific antibodies against FABP4 and PPARγ, followed by fluorescently labeled secondary antibodies. Representative micrographs show that both FABP4 and PPARγ are predominantly localized in the cytoplasm of PANC-1 cells, with relatively lower expression levels in the nucleus. Scale bars: 25 μm.

(F and G) Co-immunoprecipitation (Co-IP) confirms direct FABP4-PPARγ protein interaction. (F) HEK293T cells were co-transfected with FABP4 and PPARγ expression plasmids, followed by cell lysis and immunoprecipitation using anti-FABP4 or anti-PPARγ antibodies. Western blot analysis of the immunoprecipitated complexes confirmed a direct protein-protein interaction between exogenous FABP4 and PPARγ. (G) Endogenous Co-IP assays were performed in PANC-1 cells using anti-FABP4 or anti-PPARγ antibodies. The results demonstrated that endogenous FABP4 and PPARγ also form a stable complex in a native cellular context, validating the physiological relevance of their interaction in pancreatic cancer cells. All data are presented as mean ± standard deviation (SD). Comparisons between two groups were performed using unpaired two-tailed Student’s t test. Significance levels are indicated as ∗p < 0.05 vs. corresponding control group. All experiments were repeated independently at least three times with consistent results.

Inhibition of PPARγ significantly reverses the FABP4 overexpression phenotypes

The PPARγ-targeted inhibitor GW9662 was administered to FABP4-overexpressing PANC-1 cells. Conversely, FABP4-knockdown PANC-1 cells were subjected to either PPARγ overexpression or treatment with the PPARγ-targeted agonist GW1929 (n = 3 biological replicates per cell line). Changes in viability, proliferation, and migration of PANC-1 cells under these treatments were assessed. The results showed that inhibiting PPARγ significantly suppressed the enhanced viability, proliferation, and migration capabilities induced by FABP4 overexpression (p < 0.05 vs. DMSO control group) (Figures 7A–7C). In contrast, neither PPARγ overexpression (Figures S3A–S3C) nor GW1929-mediated PPARγ activation (Figures S3D–S3F) in FABP4-knockdown PANC-1 cells resulted in significant changes in viability, proliferation, or migration. Inhibition of PPARγ using GW9662 in FABP4-overexpressing PANC-1 cells significantly decreased the levels of FFA and MDA in PANC-1 cells to only 62.2% and 80.75% of the control group, respectively (p < 0.05 vs. DMSO) (Figures 7D and 7E) and significantly increased intracellular iron ion and ROS content to 1.067-fold and 1.197-fold of the control group, respectively (p < 0.05 vs. DMSO) (Figures 7F and 7G). Concurrently, this treatment significantly reduced GPX4 levels and SLC7A11 levels in PANC-1 cells to only 10.9% and 16.1% of the control group (p < 0.05 vs. DMSO) (Figures 7H and 7I).

Figure 7.

Pharmacological inhibition of PPARγ reverses FABP4-driven malignant phenotypes and ferroptosis resistance in pancreatic cancer cells

(A–C) Reversal of FABP4-mediated proliferative and migratory capabilities by GW9662. PANC-1 cells with FABP4 overexpression (OE-FABP4) were treated with the irreversible PPARγ antagonist GW9662 (2-chloro-5-nitrobenzanilide) or DMSO vehicle control. (A) CCK-8 cell viability assays demonstrated that GW9662 treatment significantly reversed the augmented viability induced by FABP4 overexpression at 48, 72, and 96 h post-treatment in comparison with DMSO controls (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. DMSO-treated OE-FABP4 group). (B) Colony formation assays revealed that the treatment with GW9662 significantly reduced the enhanced colony formation capacity of OE-FABP4 cells when compared with the DMSO controls (mean ± SD, n = 3 biological replicates for each cell line, ∗p < 0.05 vs. DMSO-treated group). (C) Wound healing assays indicated that GW9662 treatment significantly inhibited the enhanced migratory capacity of OE-FABP4 cells at 24 and 48 h as compared with DMSO controls (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. DMSO-treated group).

(D and E) GW9662 restores lipid metabolic homeostasis and alleviates oxidative stress in OE-FABP4 cells. (D) Treatment with GW9662 significantly decreased intracellular free fatty acid (FFA) levels to 62.2% of the values in the DMSO control group in OE-FABP4 cells (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. DMSO-treated group). (E) GW9662 treatment significantly reduced MDA levels to 80.75% of DMSO control values in OE-FABP4 cells (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. DMSO-treated group).

(F and G) GW9662 restores ferroptosis sensitivity in OE-FABP4 cells by modulating redox homeostasis. (F) GW9662 treatment significantly increased intracellular ferrous iron (Fe²⁺) levels to 1.067-fold of DMSO control values in OE-FABP4 cells (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. DMSO-treated group). (G) GW9662 treatment significantly increased ferroptosis-associated ROS levels to 1.197-fold of DMSO control values in OE-FABP4 cells (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. DMSO-treated group).

(H and I) GW9662 downregulates ferroptosis defense markers by inhibiting PPARγ transcriptional activity. (H) GW9662 treatment significantly decreased glutathione peroxidase 4 (GPX4) mRNA levels to 10.9% of DMSO control values in OE-FABP4 cells (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. DMSO-treated group). (I) GW9662 treatment significantly decreased solute carrier family 7 member 11 (SLC7A11) mRNA levels to 16.1% of DMSO control values in OE-FABP4 cells (mean ± SD, n = 3 biological replicates per cell line, ∗p < 0.05 vs. DMSO-treated group). All data are presented as mean ± standard deviation (SD). Comparisons between two groups were performed using unpaired two-tailed Student’s t test. Significance levels are indicated as ∗p < 0.05 vs. corresponding control group; ns indicates no statistical significance (p ≥ 0.05). All experiments were repeated independently at least three times with consistent results.

Conversely, overexpression of PPARγ in FABP4-knockdown PANC-1 cells resulted in no significant difference in FFA levels but a significant decrease in MDA (Figures S4A and S4B). Furthermore, treatment of FABP4-knockdown PANC-1 cells with the agonist GW1929 significantly increased FFA levels without altering MDA (Figures S4C and S4D). Overexpression of PPARγ in FABP4-knockdown PANC-1 cells resulted in no significant difference in iron content but a significant increase in ROS levels (Figures S4E and S4F). Furthermore, treatment of FABP4-knockdown PANC-1 cells with the agonist GW1929 significantly increased both iron content and ROS levels (Figures S4G and S4H).

Discussion

FABP4, an intracellular FA chaperone, participates in energy metabolism and is considered a potential metabolic marker.²⁹ Recent studies have reported elevated FABP4 expression in several malignancies, including breast and colorectal cancers,^22,23 whereas its role in hepatocellular carcinoma appears opposite.³⁰ Here, we confirm that FABP4 is significantly upregulated in PDAC cells compared with normal pancreatic ductal epithelial cells. Our functional assays demonstrate that FABP4 overexpression promotes proliferation and migration of pancreatic cancer cells, while FABP4 knockdown suppresses these malignant phenotypes, suggesting FABP4 as a potential therapeutic target in PDAC.

FFAs released by cancer-associated adipocytes fuel tumor growth.³¹ FABP4 facilitates FA transport and mediates metabolic crosstalk.^32,33 Our results show that FABP4 overexpression increases FFA levels in pancreatic cancer cells, whereas knockdown reduces them. Moreover, FABP4 overexpression elevates MDA levels, a lipid peroxidation end product, and this effect is reversed by PPARγ inhibition, indicating that FABP4 promotes lipid peroxidation via PPARγ.

To gain deeper insight, we performed untargeted lipidomics study in FABP4-overexpressing PANC-1 cells. We observed increased levels of PCs, PEs, and PIs, as well as elevated SPHPs (a sphingosine-1-phosphate derivative linked to metastasis),³⁴ and decreased ceramides, which are associated with apoptosis.³⁵ These findings indicate that FABP4 reprograms the lipid landscape to support a pro-survival and pro-metastatic environment.

PPARγ is a master regulator of adipogenesis and has been implicated in cancer progression.³⁶ We found that FABP4 overexpression increases PPARγ expression, while FABP4 knockdown decreases it. Co-IP confirmed a direct protein interaction between FABP4 and PPARγ, and immunofluorescence showed predominant cytoplasmic colocalization. Importantly, inhibition of PPARγ with GW9662 effectively reversed FABP4-induced malignant phenotypes, demonstrating that FABP4 acts at least in part through PPARγ.

Ferroptosis is an iron-dependent cell death process.³⁷ In breast cancer and lung cancer models, FABP4 has been shown to protect against ROS-induced ferroptosis and promote tumor recurrence.² Our results show that FABP4 overexpression reduces intracellular iron and ROS levels and upregulates GPX4 and SLC7A11 (key negative regulators of ferroptosis), whereas FABP4 knockdown exerts opposite effects. Inhibiting PPARγ in FABP4-overexpressing cells significantly increased iron and ROS and reduced GPX4 levels, suggesting that FABP4 may contribute to ferroptosis resistance, at least in part, through its interaction with PPARγ. However, direct functional evidence (e.g., rescue experiments with ferroptosis-specific inhibitors) is still required to establish causality. GPX4 is a crucial anti-lipid peroxidation enzyme; its downregulation promotes ferroptosis and enhances chemosensitivity.^24,38 Collectively, our findings indicate that FABP4 participates in ferroptosis regulation in pancreatic cancer; the ferroptosis-related changes observed upon PPARγ inhibition are consistent with the hypothesis that FABP4 may exert this effect, at least partially, through PPARγ.

An apparent paradox emerged: FABP4 overexpression increased MDA levels—a lipid peroxidation end product—while upregulating GPX4 and suppressing ROS and iron, collectively indicating ferroptosis resistance. This discordance is reconciled by recognizing that MDA elevation reflects enhanced lipid turnover rather than ongoing ferroptosis. FABP4 facilitates FA uptake and storage in lipid droplets, sequestering oxidizable polyunsaturated fatty acids (PUFAs) away from membranes.² Concurrently, FABP4 promotes SCD1-mediated desaturation, reducing the PUFA pool vulnerable to peroxidation,^2,39 and upregulates GPX4 to reinforce antioxidant capacity. Thus, FABP4 appears to create a state of high lipid flux accompanied by enhanced ferroptosis defense, a configuration where MDA serves as a marker of metabolic activity rather than cell death.⁴⁰

In conclusion, FABP4 is markedly upregulated in pancreatic cancer cells and acts as a key oncogenic driver, as its overexpression significantly enhances pancreatic cancer cell viability, proliferation, migratory capacity, lipid metabolic activity, and in vivo tumorigenic potential in PANC-1 xenograft models. Mechanistically, FABP4 interacts with PPARγ at the protein level, thereby promoting the malignant phenotypes of pancreatic cells and modulating key ferroptosis-related markers. Inhibiting PPARγ effectively reverses the pro-tumorigenic effects of FABP4. The elucidation of this mechanism provides insights for the early diagnosis and therapeutic targeting of PDAC.

Limitations of the study

Unresolved mechanism of PPARγ regulation by FABP4: while our Co-IP data confirm protein-protein interaction, the functional consequence of this association is unknown. It remains unclear whether FABP4 binding enhances PPARγ transcriptional activity, stabilizes PPARγ protein, or promotes its nuclear translocation. Future studies using PPRE luciferase reporter assays, cycloheximide chase assays for protein stability, and subcellular fractionation are needed to define the precise mechanism.

Incomplete phenotypic rescue and potential compensation: PPARγ overexpression or GW1929 treatment did not reverse the effects of FABP4 knockdown (Figures S3 and S4), suggesting that FABP4’s pro-tumorigenic functions are not solely dependent on PPARγ. Compensatory upregulation of the closely related FABP5 (observed in our preliminary data) may partially explain this observation. Combinatorial targeting of FABP4/PPARγ and FABP5 is warranted.

Lack of direct functional evidence for ferroptosis: our study demonstrates that FABP4 modulates ferroptosis-related markers (iron, ROS, GPX4, and SLC7A11). However, we did not directly assess whether these changes affect sensitivity to ferroptotic cell death. For example, rescue experiments using specific ferroptosis inhibitors (ferrostatin-1 or liproxstatin-1) in combination with inducers (erastin or RSL3) are required to confirm that the observed alterations truly confer ferroptosis resistance. Additionally, the apparent paradox of increased MDA alongside suppressed ROS/GPX4 warrants further investigation, including direct measurement of oxidized PUFAs by targeted lipidomics.

In vivo model limitations: our subcutaneous xenograft model does not fully recapitulate the complex tumor microenvironment, particularly the role of cancer-associated adipocytes, which are a major source of FABP4 in obese patients. Orthotopic or genetically engineered mouse models (GEMMs) would provide more physiologically relevant insights.

Only male mice were used in the xenograft experiments, as the primary aim of this study was to establish the mechanistic role of FABP4 under controlled conditions to minimize variability. Consequently, these findings may not fully capture sex-specific differences, and future studies incorporating both sexes are warranted to validate and extend our conclusions.

Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Prof. Rui Xiao (xiaorui@immu.edu.cn).

Materials availability

This study did not generate new unique reagents. All materials and methods used for data.

Data and code availability

This study did not report any standardized datasets, original computer code, algorithms or computational models, or new biomolecular structures. The original western blot images are included in the supplemental information. The microscopy data reported in this paper will be shared by the lead contact upon request. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Acknowledgments

This work was supported by Natural Science Foundation of Inner Mongolia Autonomous Region, China (2022MS08049 and 2025MS08111), Science and Technology Project of Inner Mongolia Autonomous Region, China (2025KYPT0037), Key Project of Inner Mongolia Medical University, China (YKD2022ZD018), Youth Project of Inner Mongolia Medical University, China (YKD2024QN034), Talent Training Project-Sailing Series of the Affiliated Hospital of Inner Mongolia Medical University, China (QH202401), and Public Hospital Joint Project of Inner Mongolia Medical Sciences Academy, China (2025GLLH0100).

Author contributions

C.-x.Y. and C.-x.L., data curation, formal analysis, investigation, methodology, validation, visualization, writing – original draft, and writing – review and editing; Q.Z. and J.Y., formal analysis, investigation, and methodology; H.W. and J.H., funding acquisition and project administration; J.-j.R. and R.X., conceptualization, funding acquisition, project administration, and writing – review and editing.

Declaration of interests

The authors declare that they have no conflict of interest.

STAR★Methods

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies
Primary antibody: anti-FABP4 (rabbit polyclonal, for WB)	Proteintech (Wuhan, China)	Cat# 12802-1-AP; RRID: AB_2102442
Primary antibody: anti-PPARγ (rabbit polyclonal, for WB)	Proteintech (Wuhan, China)	Cat# 16643-1-AP; RRID: AB_10596794
Primary antibody: anti-GAPDH (rabbit polyclonal)	Proteintech (Wuhan, China)	Cat# 10494-1-AP;RRID: AB_2263076
IRDye® 800CW goat anti-rabbit IgG secondary antibody	LICOR Biosciences (Lincoln, NE, USA)	Cat# 926-32211; RRID: AB_621843
Primary antibody: anti-FABP4 (for IHC)	Proteintech (Wuhan, China)	Cat# 12802-1-AP; RRID: AB_2102442
HRP-conjugated goat anti-rabbit secondary antibody	BOSTER Bio (Wuhan, China)	Cat# BA1032; RRID: AB_2716305
CoraLite®488 IgG (H+L) secondary antibody for FABP4 (goat anti-rabbit)	Proteintech (Wuhan, China)	Cat# SA00013-2; RRID: AB_2797132
CoraLite®594 IgG (H+L) secondary antibody for PPARγ (goat anti-mouse)	Proteintech (Wuhan, China)	Cat# SA00013-3; RRID: AB_2797133
Primary antibody: anti-PPARγ (mouse monoclonal, for IF)	Proteintech (Wuhan, China)	Cat# 66936-1-Ig; RRID: AB_2882260
Chemicals and reagents
DMEM medium	MeilunBio (Dalian, China)	MA0212
RPMI 1640 medium	MeilunBio (Dalian, China)	MA0215
Fetal bovine serum (FBS)	BD BIO (Shanghai, China)	F814-500
Penicillin-streptomycin	BD BIO (Shanghai, China)	A307-500
0.25% trypsin-EDTA	BD BIO (Shanghai, China)	A200-100
RNA-easy Isolation Reagent	Vazyme Biotech (Nanjing, China)	R701-01
RIPA lysis buffer	Beyotime Biotechnology (Shanghai, China)	P0013B
Triton X-100	Beyotime Biotechnology (Shanghai, China)	P0096
Immunostaining blocking buffer	Beyotime Biotechnology (Shanghai, China)	P0260
Critical commercial assays
PrimeScript™ II cDNA Synthesis Kit	TaKaRa Bio (Shiga, Japan)	RR047A
TB Green® Premix Ex Taq™ II (Tli RNaseH Plus)	TaKaRa Bio (Shiga, Japan)	RR820A
Lipid Peroxidation MDA Assay Kit	Solarbio (Beijing, China)	BC0025
Free Fatty Acid Assay Kit	Grace Biotechnology (Suzhou, China)	G0901W
Reactive Oxygen Species Assay Kit (DCFH-DA)	Nanjing Jiancheng Bioengineering Institute (Nanjing, China)	E004-1-1
Serum Iron Assay Kit	Nanjing Jiancheng Bioengineering Institute (Nanjing, China)	A039-1-1
Oil Red O Staining Kit	Kulaibo Technology (Beijing, China)	SL75101-50 mL
High-resolution untargeted lipidomics service	Shanghai Applied Protein Technology (Shanghai, China)	YAS202401230000-1
Streptavidin-biotin complex (SABC)	BOSTER Bio (Wuhan, China)	SA1094
DAB substrate kit	BOSTER Bio (Wuhan, China)	SA2025
Co-immunoprecipitation (Co-IP) kit	Epizyme (Shanghai, China)	YJ201
Software and algorithms
ImageJ v1.54 g	National Institutes of Health(USA)	https://imagej.net/imagej-wiki-static/Welcome
GraphPad Prism 8.0	Dotmatics(Boston,USA)	https://www.graphpad.com/
LipidSearch software	Mitsui Knowledge Industry(Tokyo, Japan)	https://www.mitsui-kid.co.jp/en/
Experimental models: Cell lines
PANC-1	Beina Chuanglian Biotechnology(Bei jing, China)	BNCC339759
AsPC-1	Procell Life science &Technology(Wuhan, China)	CL-0027
HPDE6-C7	Beina Chuanglian Biotechnology (Bei jing, China)	BNCC338285
Experimental models: Organisms/strains
BALB/c nude mice (Foxn1−/− nu, male, 4–6 weeks)	SPF (Beijing) Biotechnology	N/A

Experimental model and study participant details

Cell lines

The human pancreatic cancer cell lines PANC-1 (originating from a 56-year-old male patient) and AsPC-1 (originating from a 62-year-old female patient), as well as the normal human pancreatic ductal epithelial cell line HPDE6-C7 (originating from an adult male donor), were purchased from Beijing Beina Chuanglian Biotechnology Research Institute (Beijing, China). All cell lines were authenticated by short tandem repeat (STR) profiling and tested negative for mycoplasma contamination prior to use.

Animals

BALB/c nude mice (Foxn1^−/− nu, male, 4–6 weeks) were obtained from SPF Biotechnology Co., Ltd. (Beijing, China) and housed under SPF conditions with autoclaved commercial chow and sterile water. All animal procedures were approved by the Ethics Committee of Inner Mongolia Medical University (YKD202401103) and conformed to the principles outlined in the Declaration of Helsinki. Because pancreatic cancer progression is influenced by sex hormones, only male mice were used; this limitation is discussed in the “Limitations of the study” section.

Human subjects

This study did not involve human participants or primary human tissues.

Method details

Cell culture and transfection

PANC-1 and HPDE6-C7 cells were cultured in DMEM medium (Cat# MA0212, MeilunBio, Dalian, China), while AsPC-1 cells were maintained in RPMI 1640 medium (Cat# MA0215, MeilunBio, Dalian, China). Both media were supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin. Cells were cultured at 37°C in a humidified incubator containing 5% CO₂, and the culture medium was refreshed every 2–3 days. Upon reaching 80–90% confluence, cells were passaged using 0.25% trypsin-EDTA.

For gene silencing and overexpression experiments, PANC-1 and AsPC-1 cells were seeded into 6-well plates at an appropriate density and cultured overnight to achieve 60–70% confluence at the time of transfection. Cells were then transfected with FABP4-specific siRNA (synthesized by Sangon Biotech, Shanghai, China) or an FABP4 overexpression plasmid (ORIGENE, Rockville, MD, USA) using Lipofectamine³⁰⁰⁰ transfection reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. The empty vector was used as a negative control for overexpression experiments. After 6 h of transfection, the culture medium was replaced with fresh complete medium. Cells were cultured for an additional 48 h, and the efficiency of gene silencing or overexpression was validated by quantitative real-time PCR (qRT-PCR) and Western blot analysis before subsequent experiments were performed.

RNA extraction and qRT-PCR

Total RNA was extracted from cultured cells using RNA-easy Isolation Reagent (Cat# R701-01, Vazyme Biotech, Nanjing, China) according to the manufacturer’s protocol. Briefly, cells were lysed directly in the culture plate by adding the reagent, and the lysate was collected into RNase-free tubes. After adding chloroform, the mixture was vigorously shaken and centrifuged at 12,000 × g for 15 min at 4°C. The upper aqueous phase was carefully transferred to a new tube, and an equal volume of isopropanol was added to precipitate the RNA. Following centrifugation and washing with 75% ethanol, the RNA pellet was air-dried and dissolved in RNase-free water. RNA concentration and purity were determined using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). For cDNA synthesis, 1 μg of total RNA was reverse transcribed using the PrimeScript™ II cDNA Synthesis Kit (Cat# RR047A, TaKaRa Bio, Shiga, Japan) in a 20 μL reaction volume according to the manufacturer’s instructions. Quantitative real-time PCR was performed using TB Green® Premix Ex Taq™ II (Tli RNaseH Plus, Cat# RR820A, TaKaRa, Japan) on a 7500 Fast Real-Time PCR System (Applied Biosystems, Foster City, CA, USA). The thermal cycling conditions were as follows: initial denaturation at 95°C for 30 s, followed by 40 cycles of denaturation at 95°C for 5 s and annealing/extension at 60°C for 34 s. A dissociation curve analysis was performed at the end of each run to verify amplification specificity. The GAPDH gene was used as an internal control. All reactions were performed in triplicate, and relative expression levels were calculated using the 2^−ΔΔCT method. The primers used in this step are listed in Primer and siRNA sequences table.

Primer and siRNA sequences table

Primer Name	Primer Sequence (5’-3’)
GAPDH-F	TCGGAGTCAACGGATTTGGTC
GAPDH-R	ATGGAATTTGCCATGGGTGGA
FABP4-F	TATGAAAGAAGTAGGAGTGGGC
FABP4-R	TACCAGGACACCCCCATCTAA
GPX4-F	CCAAGTTTGGACACCGTCTCT
GPX4-R	TCCTTCTCTATCACCAGGGGC
SLC7A11-F	CTACTATGGTCAGAAAGCCTGT
SLC7A11-R	CAGCATAAGACAAAGCTCCAAA
PPARγ-F	CGACCAGCTGAATCCAGAGT
PPARγ-R	ATCTCCTGCACAGCCTCCAC
FABP5-F	GGTGCATTGGTTCAGCATCAGG
FABP5-R	TCATAGATCCGAGTACAGGTGAC
SCD1-F	CCCCACCTACAAGGATAAGGA
SCD1-R	CACGAGCCCATTCATAGACAT
ACLY-F	CAGCAGGACAGCATCTTTTTC
ACLY-R	TGGACTTGGGACTGAATCTTG
FASN-F	ACTCCATGTTTGGTGTTTGTC
FASN-R	TGGAGATCACATGCGGTTTA
FABP4 siRNA-292 Sense(5′-3′)	(FAM)GCAGAUGACAGGAAAGUCATT(5′-3′)
FABP4 siRNA-292 Antisense(3′-5′)	UGACUUUCCUGUCAUCUGCTT
FABP4 siRNA-170 Sense(5′-3′)	(FAM)GCAUGGCCAAACCUAACAUTT
FABP4 siRNA-170 Antisense(3′-5′)	AUGUUAGGUUUGGCCAUGCTT
FABP4 siRNA-411 Sense(5′-3′)	(FAM)GGUGGAAUGCGUCAUGAAATT
FABP4 siRNA-411 Antisense(3′-5′)	UUUCAUGACGCAUUCCACCTT
FABP4 siRNA-NC Sense(5′-3′)	(FAM)UUCUCCGAACGUGUCACGUTT
FABP4 siRNA-NC Antisense(3′-5′)	ACGUGACACGUUCGGAGAATT

Western Blot analysis

Total protein was extracted from cultured cells using RIPA lysis buffer (Cat# P0013B, Beyotime Biotechnology, Shanghai, China) supplemented with protease inhibitors. Cells were washed with ice-cold PBS and lysed on ice for 30 min with intermittent vortexing. The lysate was centrifuged at 12,000 × g for 15 min at 4°C, and the supernatant containing the protein was collected. Protein concentration was determined using a BCA Protein Assay Kit (Beyotime, China). Protein samples were mixed with 5× SDS-PAGE protein loading buffer at a 4:1 ratio and denatured by heating at 95°C for 7 min. Equal amounts of protein (30 μg per lane) were separated by SDS-PAGE gels (Beyotime, China) for approximately 2 h and then transferred onto a nitrocellulose (NC) membrane at a constant current of 200 mA for 1 h using a wet transfer system. The membrane was blocked with 5% skim milk in TBST (Tris-buffered saline containing 0.1% Tween 20) for 1 h at room temperature and then incubated overnight at 4°C with primary antibodies diluted in primary antibody dilution buffer. The following primary antibodies were used: FABP4 (1:5000 dilution, Cat# 12802-1-AP, Proteintech, China), PPARγ (1:1000 dilution, Cat# 16643-1-AP, Proteintech, China), and GAPDH (1:10000 dilution, Cat# 60004-1-Ig, Proteintech, China). After washing three times with TBST (10 min each), the membrane was incubated with an infrared fluorescent dye-labeled goat anti-rabbit IgG secondary antibody (1:1000 dilution, Cat# RK-611-130-002, LICOR Biosciences, Lincoln, NE, USA) for 1 h at room temperature in the dark. Following three additional washes with TBST, the membrane was scanned using an Odyssey CLx Infrared Imaging System (LICOR, USA). Band intensities were quantified using ImageJ software (v1.54 g, NIH, USA), and relative protein expression levels were normalized to the GAPDH internal control.

Cell proliferation assay (CCK-8)

Cell proliferation was assessed using the Cell Counting Kit-8 (CCK-8) assay. Transfected cells in the logarithmic growth phase were trypsinized, counted, and seeded into 96-well plates at a density of 4 × 10³ cells per well in 100 μL of complete culture medium. Each experimental group was set up with five replicate wells. At 24, 48, 72, and 96 h after seeding, 10 μL of CCK-8 reagent (Meilunbio, Dalian, China) was added to each well, and the plates were incubated for an additional 2 h at 37°C. The absorbance at 450 nm was measured using an ELX800 microplate reader (BioTek Instruments, Winooski, VT, USA). A blank control containing only medium without cells was included for background subtraction. The experiment was repeated three times independently, and a proliferation curve was plotted with time on the x axis and absorbance on the y axis.

Colony formation assay

For the colony formation assay, transfected cells were trypsinized, counted, and seeded into 6-well plates at a low density of 400 cells per well in 2 mL of complete culture medium. The cells were cultured at 37°C in a 5% CO₂ incubator for 2–3 weeks, with the culture medium replaced every 3 days. Colony formation was monitored periodically under a microscope. When visible colonies appeared and the largest colonies contained more than 50 cells, the assay was terminated. The medium was gently aspirated, and the cells were washed once with PBS. Colonies were fixed with 4% paraformaldehyde for 20 min at room temperature, washed again with PBS, and then stained with 10% crystal violet solution for 5 min. Excess stain was gently washed off with tap water, and the plates were air-dried. Images of the entire wells were captured using a digital camera. Colonies containing at least 50 cells were counted manually or using ImageJ software. Each experiment was performed in triplicate and repeated three times independently.

Wound healing assay

Cell migration ability was evaluated using the wound healing assay. Cells were seeded into 6-well plates at a density of 4 × 10⁵ cells per well and cultured overnight to form a confluent monolayer. After successful transfection and upon reaching >90% confluence, a straight scratch was created in the cell monolayer using a sterile 200 μL pipette tip. The detached cells were removed by gently washing the wells twice with PBS, and fresh serum-free medium was added to minimize cell proliferation during the assay. The scratch wounds were observed under an inverted microscope (Olympus IX73), and images were captured at 0, 24, and 48 h at predetermined positions along the scratch. The wound area was measured using ImageJ software, and the wound closure percentage was calculated as [(Area at 0 h - Area at time t) /Area at 0 h] × 100%. Each experiment was performed in triplicate and repeated three times independently.

Measurement of MDA, FFA, ROS, and iron levels

For the measurement of malondialdehyde (MDA), free fatty acids (FFA), reactive oxygen species (ROS), and iron levels, cells were harvested, washed with ice-cold PBS, and lysed by sonication in an ice bath. The lysate was centrifuged to remove debris, and the supernatant was collected for subsequent assays. Protein concentration of the supernatant was determined using the BCA method to normalize the results.

MDA levels were measured using a Lipid Peroxidation MDA Assay Kit (Cat# BC0025, Solarbio, Beijing, China) based on the thiobarbituric acid (TBA) method. The absorbance at 532 nm and 600 nm was measured using a microplate reader, and the MDA content was calculated according to the manufacturer’s formula and expressed as nmol/mg protein.

FFA levels were quantified using a Free Fatty Acid Assay Kit (Cat# G0901W, Grace Biotechnology, Suzhou, China) based on a copper ion colorimetric method. The absorbance at 550 nm was measured, and the FFA concentration was calculated from a standard curve and expressed as μmol/g protein.

Intracellular ROS levels were determined using a Reactive Oxygen Species Assay Kit (Cat# E004-1-1, Nanjing Jiancheng Bioengineering Institute, Nanjing, China) employing the fluorescent probe DCFH-DA. Cells were incubated with 10 μM DCFH-DA in serum-free medium for 30 min at 37°C in the dark. After washing to remove excess probe, fluorescence intensity was measured using a fluorescence microplate reader with excitation at 485 nm and emission at 525 nm. Results were expressed as relative fluorescence units (RFU) per mg protein.

Total cellular iron content was measured using a Serum Iron Assay Kit (Cat# A039-1-1, Nanjing Jiancheng, China) based on the chromogenic reaction of ferrous iron. Following sonication of samples, the absorbance at 520 nm was measured, and the iron concentration was calculated from a standard curve and expressed as μmol/g protein.

Oil Red O staining

To assess intracellular lipid accumulation, Oil Red O staining was performed using a commercial kit (Cat# SL75101-50 mL, Kulaibo Technology, Beijing, China) according to the manufacturer’s instructions. Cells cultured in 6-well plates were washed gently with PBS, fixed with the provided fixative solution for 20 min, and then rinsed with distilled water. The cells were incubated with Oil Red O working solution for 20 min at room temperature, followed by destaining with 60% isopropanol. After washing with distilled water, the stained cells were observed and photographed under an inverted microscope. The staining results were analyzed and quantified using ImageJ software by measuring the integrated density of the red signal.

High-resolution untargeted lipidomic relative quantification analysis

Cell culture supernatants were collected from PANC-1 cells in the FABP4 overexpression group (OE-FABP4, n = 3) and the empty vector control group (OE-NC, n = 3). The samples were sent to Shanghai Applied Protein Technology (Shanghai, China) for high-resolution untargeted lipidomic relative quantification analysis (Project No.: YAS202401230000-1). Lipid separation was performed using a UHPLC Nexera LC-30 A system (Shimadzu, Kyoto, Japan). Lipids were detected using electrospray ionization (ESI) in both positive and negative ion modes. Data acquisition, lipid identification, and peak extraction were processed using LipidSearch software (Mitsui Knowledge Industry, Tokyo, Japan). The relative expression changes of various lipid subclasses and individual lipid species between the OE-FABP4 and OE-NC groups were compared using chromatographic-mass spectrometric analysis.

Xenograft tumor model in nude mice

For xenograft studies, PANC-1 cells overexpressing FABP4 (OE-FABP4, n = 6) or empty vector control (OE-NC, n = 5) were harvested, washed with PBS, and resuspended in serum-free DMEM at 1×10⁷ cells/mL. Each mouse (prepared as described in the Experimental Model and Study Participant Details section) received a subcutaneous injection of 1×10⁶ cells (100 μL) into the right flank. Tumor length and width were measured every seven days with a digital caliper, and tumor area was calculated as length × width. All mice were euthanized 28 days after injection. Tumors were excised, weighed, and processed for immunohistochemistry and molecular analyses.

Immunohistochemistry (IHC) staining

Paraffin-embedded tissue blocks were sectioned at a thickness of 4 μm using a microtome. The sections were mounted onto poly-L-lysine-coated slides and baked at 60°C for 90 min to ensure firm adhesion. Deparaffinization was performed by immersing the sections in xylene three times (10 min each), followed by rehydration through a graded ethanol series (100%, 95%, 85%, and 75% for 5 min each) and a final rinse in distilled water. For antigen retrieval, sections were immersed in sodium citrate buffer (10 mM, pH 6.0) and heated at 98°C for 20 min in a microwave oven, then allowed to cool naturally to room temperature. Endogenous peroxidase activity was blocked by incubation in 3% H₂O₂ for 15 min at room temperature in the dark. After washing with phosphate-buffered saline (PBS, 0.01 M, pH 7.4) three times for 5 min each, sections were blocked with 5% bovine serum albumin (BSA) at 37°C for 30 min to prevent non-specific binding. The sections were then incubated overnight at 4°C with a primary antibody against FABP4 (rabbit polyclonal, 1:500 dilution, Cat# 12802-1-AP, Proteintech, Wuhan, China). Following three washes with PBS, the sections were incubated with a horseradish peroxidase (HRP)-conjugated goat anti-rabbit secondary antibody (1:200 dilution, Cat# BA1032, BOSTER Bio, Wuhan, China) at 37°C for 30 min. After additional washes, sections were incubated with streptavidin-biotin complex (SABC, Cat# SA1094, BOSTER Bio, China) at 37°C for 30 min. Color development was performed using a DAB substrate kit (Cat# SA2025, BOSTER Bio, China) under microscopic observation, and the reaction was terminated by rinsing with tap water when specific brown staining appeared. Nuclei were counterstained with hematoxylin for 1 min, followed by bluing in running tap water for 5 min. Finally, sections were dehydrated through a graded ethanol series, cleared in xylene, and mounted with neutral resin. Images were captured using an OLYMPUS IX73 fluorescence inverted microscope (Olympus Corporation, Tokyo, Japan). For each section, five random fields were selected, and the staining intensity was analyzed using ImageJ software (NIH, Bethesda, MD, USA).

Immunofluorescence (IF)

Cells were seeded on sterile glass coverslips placed in 6-well plates and cultured overnight to allow attachment. After removing the culture medium, cells were washed once with PBS, fixed with 4% paraformaldehyde for 20 min at room temperature, and permeabilized with 1% Triton X-100 (Cat# P0096, Beyotime, China) for 20 min. Following three washes with PBS, cells were blocked with immunostaining blocking buffer (Cat# P0260, Beyotime, China) for 30 min at room temperature. Cells were then incubated with the FABP4 primary antibody (1:500 dilution, Cat# 12802-1-AP, Proteintech, China) for 2 h at room temperature, followed by incubation with the corresponding fluorescent secondary antibody (1:500 dilution, Cat# SA00013-2, Proteintech, China) for 1 h in the dark. After three washes with PBS, cells were incubated with the PPARγ primary antibody (1:500 dilution, Cat# 66936-1-Ig, Proteintech, China) for 2 h, followed by its corresponding fluorescent secondary antibody (1:500 dilution, Cat# SA00013-3, Proteintech, China) for 1 h in the dark. After final washes with PBS, the coverslips were mounted onto glass slides using an anti-fade mounting medium. Images were captured using a fluorescence microscope (Olympus IX73), and colocalization analysis was performed using ImageJ software.

Co-immunoprecipitation (Co-IP)

Total protein was extracted from cell samples using a commercial Co-IP kit (Cat# YJ201, Epizyme, Shanghai, China) according to the manufacturer’s instructions. The cell lysates were pre-cleared by incubation with Protein A/G magnetic beads for 1 h at 4°C. The pre-cleared lysates were then incubated overnight at 4°C with either FABP4 antibody (1:500 dilution, Cat# 12802-1-AP, Proteintech, China) or PPARγ antibody (1:500 dilution, Cat# 16643-1-AP, Proteintech, China). Normal rabbit IgG was used as a negative control. Following the overnight incubation, Protein A/G magnetic beads were added to each sample, and incubation was continued for an additional 8 h at 4°C with gentle rotation. The beads were collected using a magnetic stand and washed thoroughly with washing buffer according to the kit’s instructions. The bound proteins were eluted by boiling the beads in 5× SDS-PAGE loading buffer at 95°C for 7 min. The eluted samples were then subjected to Western blot analysis to detect protein interactions, using the reciprocal antibodies for detection.

Quantification and statistical analysis

Statistical analysis and graphical representation were performed using GraphPad Prism 8.0 software (Dotmatics, Boston, USA). Lipid identification and peak extraction from untargeted lipidomics data were processed using LipidSearch software (Mitsui Knowledge Industry, Tokyo, Japan). All data are presented as the mean ± standard deviation (SD). Comparisons between two groups were performed using the unpaired two-tailed Student’s t test. A p-value of less than 0.05 was considered statistically significant and denoted as ‘∗‘; otherwise, it was marked as ‘ns’ (not significant). All statistical details, including exact p-values, n values, and test types, can be found in the figure legends and the results section.

Published: June 27, 2026