Inflammasome Activation by Neutrophil Extracellular Traps (NETs) in the MDA-MB-231 Human Breast Cancer Cell Line

TL;DR

This study explores how NETs from neutrophils activate the NLRP3 inflammasome in breast cancer cells, promoting inflammation and tumor progression.

Contribution

The study reveals a novel interplay between NETs and the NLRP3 inflammasome in breast cancer progression.

Findings

NETs increased NLRP3, CASP1, and IL1B expression in MDA-MB-231 cells.

Inhibitors of IL-1R and P2X7 reduced IL1B and NLRP3 expression.

NETs accelerated tumor migration, inhibited by inflammasome inhibitors.

Abstract

Inflammation is a key feature in breast cancer progression, with neutrophil extracellular traps (NETs) playing an important role. NETs are DNA-based structures released by neutrophils that can promote tumor adhesion, invasion, and immune evasion. Another crucial mechanism is the inflammasome, a multiprotein complex that drives inflammation through cytokine release. Both mechanisms are present in tumors and may act synergistically. In this study, we evaluated how isolated NETs modulate the NLRP3 inflammasome in a human breast cancer model. Exposure of MDA-MB-231 cells to NETs increased the expression of NLRP3, CASP1, and IL1B. Blocking IL-1R with Anakinra reduced IL1B expression, while inhibition of the P2X7 receptor with A740003 decreased NLRP3 and IL1B. ELISA confirmed that NETs stimulate IL-1β release, which was reduced by MCC950, Anakinra, and A740003. Functionally, NETs accelerated tumor cell migration, and this effect was inhibited by MCC950 and Anakinra. Bioinformatics analysis of TCGA breast cancer samples showed differential inflammasome gene expression among subtypes and a positive correlation between inflammasome components and NET-related genes. These findings highlight the interplay between inflammatory and immune mechanisms in breast cancer progression and may support the development of new therapeutic strategies.

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1. Introduction

Breast cancer has the highest global incidence, representing 11.7% of total cancer cases. Among women, it accounts for 24.5% of all cancer types, being the leading cause of cancer-related deaths. In 2020, 2.3 million women were diagnosed, resulting in 685,000 deaths. Breast cancer affects women worldwide, particularly after puberty, with increasing rates later in life. Genetic factors contribute to 5–10% of cases, whereas environmental and lifestyle factors account for the majority of cases [1,2].

Breast cancer can be classified into subtypes that vary by specific characteristics. Luminal A and Luminal B rely on the expression of hormone receptors, such as the estrogen receptor and the progesterone receptor. Another subtype involves the overexpression of the human epidermal growth factor receptor 2 (HER2). The last group is referred to as Triple-Negative, characterized by the absence of hormone receptors and HER2 expression [3].

In 1863, Rudolf Virchow hypothesized that chronic inflammation could lead to malignant neoplasms, promoting cell proliferation and tumor development [4,5]. Inflammatory cells in tumors create a favorable environment for tumor growth, genomic instability, and the formation of new blood vessels. However, inflammation can also inhibit tumor growth. Key immune mechanisms include neutrophil extracellular traps (NETs) and the inflammasome. NETs are web-like structures composed of decondensed chromatin and proteins such as neutrophil elastase and myeloperoxidase, released by neutrophils in response to infection or sterile inflammation. In the tumor microenvironment, NETs contribute to immune evasion, metastasis, and therapeutic resistance [6,7].

The inflammasome, particularly NLRP3, is involved in the release of pro-inflammatory cytokines and is associated with a form of programmed cell death called pyroptosis. Its activation may involve priming by TLRs and cytokine receptors, followed by a second signal that promotes inflammasome assembly, leading to cytokine release [8,9].

Activation of the inflammasome by neutrophil extracellular traps (NETs) has been described in some studies and is observed in several conditions such as autoimmune diseases and cancer. Recent research has shown the relationship between NETs and the inflammasome in tumor progression. Wang and colleagues (2022) observed that NETs promote migration and invasion of non-small cell lung cancer cells through the epithelial–mesenchymal transition (EMT) process. They found that the expression of the long noncoding RNA (lncRNA) MIR503HG inhibited the metastatic potential associated with inflammation triggered by NETs in lung cancer cells by inhibiting the NF-κB/NLRP3 pathway activation [10].

More recently, Mousset and colleagues (2023) identified that chemotherapeutic agents used in the treatment of lung metastases derived from breast cancer activate the inflammasome. Released cytokines induce neutrophils to release NETs, leading to TGF-β activation and conferring resistance to chemotherapy [11].

Our research group also observed a possible relationship between NETs and the inflammasome. We observed increased IL-1β expression in MCF-7 and MDA-MB-231 cell lines upon stimulation with NETs, suggesting a direct effect of NETs on the inflammasome pathway in tumor cells [12].

2. Results

2.1. NETs Induce NLRP3 Inflammasome Activation in MDA-MB-231 Cells

Recent studies have demonstrated that NETs and the NLRP3 inflammasome pathway cooperate to promote cancer progression [10,11]. Here, we analyzed the gene expression of NLRP3, CASP1 (caspase-1), and IL1B (IL-1β) in MDA-MB-231 cells treated with NETs. NLRP3 and IL-1β expression peaked at 12 h, while caspase-1 expression increased after 24 h (Figure 1A). ELISAs showed a significant increase in IL-1β release after 12 h, indicating NETs activate the inflammasome pathway, leading to cytokine release (Figure 1B). To expand our observations, we have also challenged MDA-MB-453 cells with NETs. As seen in Figure S1 in Supplementary Materials, treatment with NETs upregulated both NLRP3 and IL1B gene expression in the MDA-MB-453 cell line.

2.2. Activation of NLRP3 Inflammasome Promotes Tumor Cell Migration

To evaluate the involvement of NLRP3 in NET-induced IL1B gene expression, we employed the inflammasome inhibitor, MCC950 to assess NLRP3’s role in inflammasome assembly and cytokine release. qRT-PCR showed a significant decrease in NLRP3 expression upon treatment with MCC950, but no change in CASP1 and IL1B gene expression was observed (Figure 1C). ELISAs revealed reduced IL-1β release upon treatment with MCC950, confirming a role for NLRP3 in the NET effect towards MDA-MB-231 cells (Figure 1D). We further evaluated the impact of NLRP3 inhibition on NET-induced tumor cell migration. Figure 1E,F shows that NETs increased MDA-MB-231 migration. Remarkably, the NET effect was strongly attenuated upon pre-treatment with MCC950, highlighting NLRP3’s role in tumor cell migration promoted by NETs.

2.3. The IL-1β Receptor, IL-1R1, Cooperates with NETs to Promote NLRP3 Inflammasome Activation

It is well-known that IL-1b may enhance its own expression upon an autocrine loop [13]. Therefore, we next evaluated the impact of IL-1R blockade on NET-induced effects. qRT-PCR revealed that IL-1R inhibition by the receptor antagonist, anakinra, significantly reduced IL-1B gene expression, but not CASP1 or NLRP3 (Figure 2A). ELISAs showed decreased IL-1β release upon IL-1R inhibition (Figure 2B). In addition, IL-1R blockade attenuated NET-induced tumor cell migration, consistent with a role for IL-1b in this effect.

Blockade of IL-1R also decreased the gene expression of CSF3, which encodes granulocyte colony-stimulating factor (G-CSF) (Figure 2E) as well as CXCL8 (Figure 2F), a potent chemotactic for neutrophils within the tumor microenvironment as well as NET inducer [14].

2.4. NETs Induce the Second Signal of NLRP3 Inflammasome Activation Through P2X7R in MDA-MB-231 Cells

It has been demonstrated that the antimicrobial peptide LL-37 present on NETs can directly activate the P2X7 receptor in an ATP-independent manner, thereby leading to NLRP3 activation in macrophages [15]. Therefore, we employed the P2X7 receptor antagonist, A740003, to assess its role in NET-induced inflammasome activation in MDA-MB-231 cells. qRT-PCR showed decreased NLRP3 and IL1B gene expression upon P2X7 receptor inhibition, but no change in CASP1 (Figure 3A). ELISAs confirmed reduced IL-1β release upon treatment with A740003, indicating a role for the P2X7 receptor as a second signal in NET-induced NLRP3 activation in breast cancer cells (Figure 3B).

2.5. In Silico Analysis of Gene Markers for Inflammasome, Neutrophils, and NETs

To correlate our in vitro findings with patient data, we further analyzed the expression of inflammasome-related genes across different breast cancer subtypes. As shown in Figure 4A, genes in the inflammasome pathway were expressed across all subtypes, with notable differences. In the aggressive Triple Negative subtype, P2X7R, CASP1, and IL1B were highly expressed, while PYCARD and IL1R1 were more expressed in the less aggressive Luminal A subtype. NLRP3 expression did not differ significantly across subtypes.

We then interrogated a possible relationship between the inflammasome pathway genes and neutrophil or NET gene signatures in the tumor microenvironment. A positive correlation was found between inflammasome genes and neutrophil signatures, with CASP1 and PYCARD showing moderate correlation (Figure 4B). On the other hand, all inflammasome pathway genes, except PYCARD, showed high correlation with an NET gene signature (Figure 4C).

These results align with our in vitro findings, confirming high inflammasome expression in breast cancer and a clear link between the inflammasome pathway and NETs.

3. Discussion

Inflammation plays a crucial role in cancer, being one of its distinct hallmarks [16]. In the early stages, inflammatory cells can promote tumor growth, create a conducive environment, increase genomic instability, and stimulate new blood vessel formation [5]. Among the inflammatory mechanisms operating within the tumor microenvironment, neutrophil extracellular traps (NETs) have emerged as important factors in initiating and sustaining inflammation, frequently exerting pro-tumoral effects that facilitate tumor progression and metastasis. Likewise, the inflammasome acts as a key mediator of inflammatory signaling, contributing to a favorable microenvironment for tumor growth, invasion, and dissemination.

IL-1β, a key product of the inflammasome activation, initiates inflammatory processes and induces neutrophils to release NETs. This has been observed in breast cancer [11]. Our group found that blocking the IL-1R receptor reduced systemic NET levels [17]. Mousset et al. (showed that chemotherapy activates the inflammasome in breast cancer, with IL-1β triggering NETosis and conferring chemoresistance via TGF-β activation [11,17]. The NLRP3 inflammasome is extensively studied in various diseases, including cancer. Inhibition with MCC950 has been shown to reduce inflammasome activity in various pathologies [10,18,19]. In lung cancer cells, Wang and colleagues noted a significant decrease in inflammasome-related gene expression (NLRP3, CASP1, IL1B, CXCL8) [10]. Yaw et al. [20] observed reduced IL-1β in pancreatic adenocarcinoma cell lines treated with MCC950, leading to decreased inflammation [20]. These findings highlight the importance of the NLRP3 inflammasome in cancer.

IL-1β also regulates the inflammasome, acting as a priming signal. It binds to the IL-1R receptor, activating the NF-κB pathway directly or through IRAK-1, initiating priming [21]. Guo et al. [22] showed that C57BL/6J mice with orthotopic xenografts had decreased IL-1β release, reduced tumor size, and increased survival when IL-1R was blocked with IL-1Ra [22]. This underscores IL-1R’s role in reactivating the NLRP3 inflammasome in breast cancer. In addition, we previously demonstrated that in vivo IL-1R blockade reduces G-CSF gene expression in 4T1 breast cancer tumors [17]. IL-8’s importance was demonstrated through a feedback loop in which NETs increase IL-8 expression and release, driving further NET release [12]. This indicates that NLRP3 inflammasome activation via IL-1R may recruit neutrophils to the tumor microenvironment. Although direct detection of caspase-1 and IL-1β cleavage would further substantiate inflammasome activation, technical limitations prevented consistent detection under our experimental conditions.

NETs have been linked to inflammasome activation. Kahlenberg et al. [15] proposed that NETs act as a second activation signal for the inflammasome via the LL-37 peptide, binding to the P2X7 receptor, leading to K+ efflux and NLRP3 activation [15]. Huang et al. [23] showed that recombinant CRAMP, the mouse equivalent of LL-37, also activates the inflammasome through P2X7 receptor [23]. In breast cancer, Tafani et al. [24] showed hypoxia increases P2X7 receptor expression, and Park et al. [25] demonstrated that high P2X7 receptor expression enhances metastatic migration and invasion [24,25]. Our results confirm that NETs influence inflammasome activation in MDA-MB-231 cells by binding to P2X7 receptor, promoting NLRP3 inflammasome assembly and IL-1β release.

Metastasis is the primary cause of cancer-related deaths. For metastatic breast cancer, survival is around 5% [26]. Inflammasome activation and NETs have been linked to metastatic processes. Wang et al. [10] showed that NLRP3 inflammasome activation increases metastasis in breast cancer by promoting epithelial–mesenchymal transition (EMT) [10]. Also, our group [12] demonstrated that NETs induce EMT in Luminal A profile cells (MCF7), transforming them into metastatic cells [12]. Wang and colleagues [10] observed the NETs/inflammasome pathway’s role in metastasis in non-small cell lung cancer and squamous cell carcinoma. Pre-treatment with MCC950 reduced cell migration, supporting the involvement of the NLRP3 inflammasome in mechanisms associated with migration and possibly metastatic progression.

This study has some limitations that should be acknowledged. Functional analyses were performed using the MDA-MB-231 cell line, as no significant effects were observed in the Luminal A MCF-7 cells under inflammasome-activating conditions. Therefore, extrapolation of these findings to other breast cancer subtypes should be made with caution. In addition, the absence of in vivo experiments is a limitation, as it precludes evaluation of the tumor microenvironment in its full complexity. Nevertheless, the in vitro human cell model employed here enabled controlled mechanistic investigation of NETs–inflammasome interactions.

Our analysis shows a strong correlation between the NLRP3 inflammasome and NETs in breast cancer. TCGA data from Wang [10] indicates consistent NLRP3 expression across breast cancer subtypes, suggesting additional factors beyond NLRP3 may be necessary for tumor progression [10]. Our study connects NETs, P2X7 receptor binding, inflammasome activation, and IL-1β release, contributing to a more aggressive breast cancer profile.

4. Materials and Methods

4.1. Cell Culture

The breast cancer cell lines MDA-MB-231 and MDA-MB-453 were obtained from the Rio de Janeiro Cell Bank (Rio de Janeiro, RJ, Brazil). Cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM; Thermo Fisher Scientific, Waltham, MA, USA), supplemented with 10% fetal bovine serum (FBS; Cultilab, Campinas, Brazil) and 1% penicillin–streptomycin (Thermo Fisher Scientific), and maintained at 37 °C in a humidified incubator with 5% CO_2_.

4.2. Neutrophil Isolation

Venous blood samples were collected from healthy donors into tubes or syringes containing 100 mM sodium citrate at a 1:10 dilution. The whole blood was carefully layered onto conical tubes containing Histopaque-1077 (Merck, Darmstadt, Germany) at a 2:1 ratio to create a density gradient. The tubes were centrifuged at 400× g for 30 min at room temperature. Peripheral blood mononuclear cells and blood plasma were discarded. The collected neutrophils were lysed in ACK solution (155 mM NH_4_Cl, 10 mM KHCO_3_, 0.1 mM EDTA, pH 7.4) for at least 5 min with gentle mixing to remove erythrocytes. The conical tubes containing the neutrophils were centrifuged at 400× g for 10 min at 4 °C, and the cells were kept on ice thereafter. The lysis process was repeated, and the tube was centrifuged again. Subsequently, the cells were washed with sterile phosphate-buffered saline (PBS), centrifuged, and carefully resuspended in RPMI 1640 medium without fetal serum. Neutrophils were counted using a Neubauer chamber (Sigma-Aldrich, St. Louis, MO, USA), and the suspension was adjusted to 1 × 10^7^ neutrophils/mL. The purity and viability of the obtained neutrophils were assessed through staining with methylene blue and Trypan blue, respectively. The entire procedure was conducted in a sterile environment to prevent external contamination. All procedures were conducted in accordance with ethical guidelines and approved by the institutional ethics committee of the Clementino Fraga Filho University Hospital (Federal University of Rio de Janeiro), under protocol number 50336921.2.0000.5257.

4.3. NET Generation

Neutrophil extracellular traps (NETs) were collected according to a previously established protocol [27]. Neutrophils (1 × 10^7^ cells/mL) were transferred to a sterile Petri dish and incubated with 500 nM Phorbol 12-myristate 13-acetate (PMA; Merck, Darmstadt, Germany) for 3 h at 37 °C and 5% CO_2_. After incubation, the medium was carefully removed, and the bottom layer was recovered by adding chilled sterile PBS, then transferred to 1.5 mL tubes. The tubes were centrifuged at 1000× g for 10 min at 4 °C to remove cellular debris, then the supernatant was transferred to other 1.5 mL tubes. The isolated NETs were quantified by measuring DNA using a NanoDrop Lite spectrophotometer (Thermo Fisher Scientific). Subsequently, the fresh or stored NETs were incubated at 4 °C for up to 24 h and used in subsequent experiments.

4.4. Sample Collection for Experiments

Breast carcinoma cells (5 × 10^5^ cells) were seeded into 6-well culture plates and incubated for 24 h at 37 °C and 5% CO_2_ in 1 mL of culture medium containing 10% FBS. After incubation, cells were washed twice with sterile PBS and maintained in 1 mL of serum-free DMEM medium at 37 °C for 16 h. Following the starvation period, the medium was changed, and 500 ng/mL of NETs were added. After treatment with NETs for 12 h at 37 °C and 5% CO_2_, the cell supernatant was collected for ELISA. The cells were then carefully washed twice with PBS, and 500 μL of TRIzol (Thermo Fisher Scientific) was added. Homogenization was performed multiple times to ensure efficient RNA extraction. In some cases, after the starvation period, cells were treated with commercial inhibitors 1 h before the addition of NETs: MCC950 (100 μM, NLRP3 inhibitor), Anakinra (500 ng/mL, IL-1β receptor inhibitor), and A740003 (50 nM, P2X7 receptor antagonist).

4.5. Quantitative RT-PCR

A total of 5 × 10^5^ cells were washed twice with phosphate-buffered saline (PBS) and incubated in serum-free medium for 10 h to induce starvation, followed by stimulation with NETs at a concentration of 500 ng/mL and inhibitors. After 16 h, cells were washed twice with PBS to remove residual NETs, and total RNA was extracted using TRIzol Reagent (Thermo Fisher Scientific, Waltham, MA, USA). For each sample, 1 µg of RNA was treated with DNase I and subjected to reverse transcription to synthesize cDNA. Quantitative real-time PCR was then performed using SYBR Green Real-Time PCR Master Mix (Thermo Fisher Scientific) on the StepOnePlus Real-Time PCR System (Thermo Fisher Scientific). All reagents and primers obtained from Thermo Fisher Scientific exhibited reaction efficiencies of 90–110%. Primer sequences are listed in Table 1. Gene expression was normalized to GAPDH, and relative fold changes were calculated using the 2^–ΔΔCT^ method.

4.6. ELISA

Supernatants obtained from cells cultured in the absence or presence of NETs, and treated or untreated with MCC950, Anakinra, or A740003 for 12 h, were collected after debris was removed by centrifugation at 1000× g for 10 min. Subsequently, the samples were quantified for IL-1β using an enzyme-linked immunosorbent assay (ELISA) with a commercial kit (PeproTech, Inc., Cranbury, NJ, USA) according to the manufacturer’s protocol. The plate with the samples was read on a SpectraMax ABS Plus spectrophotometer (Molecular Devices, LLC, San Jose, CA, USA) at 405 nm.

4.7. Migration Assay

MDA-MB-231 cells (1 × 10^6^) were maintained in serum-free medium for 24 h. Subsequently, the cells were washed twice with PBS, trypsinized, centrifuged, resuspended, and counted using a Neubauer chamber. Later, certain groups received treatment with the inhibitors Anakinra (500 ng/mL) or MCC950 (100 μM) for 1 h, followed by challenge with NETs (500 ng/mL). For the migration assay, a 48-well Boyden chamber with polycarbonate membranes (Neuro Probe, Gaithersburg, MD, USA) containing 8 µm pores was used. In the lower well of the chamber, DMEM medium containing 2% fetal bovine serum (FBS) was added as the chemoattractant. The challenged or non-challenged cells with NETs and treated or untreated with the inhibitors were resuspended in serum-free medium (1 × 10^6^ cells/mL), and 50 µL of this suspension was added to each upper well of the Boyden chamber. Each condition was replicated in triplicate. The assay was conducted for 5 h at 37 °C in 5% CO_2_. After the incubation period, the membrane was carefully removed, and the upper surface was scraped to eliminate non-migrated cells. Subsequently, the membrane was fixed and stained with the Panoptic Rapid Staining kit (Laborclin, Pinhais, Brazil), then mounted on a glass slide. Photographs were captured at a 200× magnification using a bright-field microscope. A total of 10 fields per condition were counted, and the average number of migrated cells per field was calculated.

4.8. Analysis of Gene Expression in Breast Cancer Patients

For the analysis of gene expression related to the inflammasome, RNA-seq data from 1215 breast cancer patients in the Cancer Genome Atlas (TCGA) repository were used. The transcript values for each neutrophil-related gene (RPKM, Reads Per Kilobase Million) were stratified by breast cancer subtypes: Luminal A (lumA), Luminal B (lumB), HER2+ (HER2), and Triple Negative (TN). The correlation between neutrophil signature genes and inflammasome genes was analyzed using the cBioPortal platform, which provides graphs, Spearman coefficients, and corresponding statistical values [28,29].

For analysis of gene co-expression, the GEPIA 2 [30] tool was utilized to generate correlation analyses between target genes and subsets of neutrophil signature genes (DEFA4, DEFA1B, MMP8, CEACAM6, CEACAM8, LTF, MPO, and ARG1) as well as NETs signature genes (ACTN1, CAT, CTSG, DEFA3, ELANE, LTF, MPO, MYH9, PADI4, S100A12, S100A9, ACTB, ACTG1, ACTN4, AZU1, ENO1, KRT10, LCP1, LYZ, MNDA, PRTN3, S100A8, and TKT). Based on this data, genetic correlation tables were generated as presented in the results.

4.9. Statistical Analysis

Statistical analysis was performed using GraphPad Prism 5 (GraphPad Software, San Diego, CA, USA). Graphs represent the mean of at least three independent experiments ± standard deviation. In the qRT-PCR, ELISA, and migration assays, non-paired analysis of variance (ANOVA) was applied to determine statistical differences. To analyze gene expression of inflammasome components across different breast cancer subtypes, the Mann–Whitney U-test was used. Correlations of RNA-seq values (RPKM) obtained from TCGA were statistically analyzed using the non-parametric Spearman’s test. Results were considered statistically significant when the p-value was ≤0.05.

5. Conclusions

We conclude that in the triple-negative breast cancer cell line MDA-MB-231, the NLRP3 inflammasome can be activated through a feedback mechanism. In this mechanism, the cytokine IL-1β, released by the inflammasome itself, functions as a priming and first-activation signal by binding to the IL-1R receptor on the surface of tumor cells. Moreover, NETs can act as a second activation signal by binding to the P2X7 receptor, initiating NLRP3 inflammasome activity and the release of pro-inflammatory cytokines, thereby restarting the cycle.