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. 2026 Feb 7;163:40. doi: 10.1186/s41065-026-00649-y

miR-4652-3p suppresses glutamine metabolism induced by the inflammatory microenvironment in non-small cell lung cancer by regulating MYC/SLC1A5

Yihua Que 1,#, Yan Song 2,#, Deng Huang 3, Xianzhen Wu 4,✉, Yang Pan 5,6,✉
PMCID: PMC12977689  PMID: 41654992

Abstract

Background

MicroRNAs (miRNAs) play a crucial role in tumorigenesis and malignant transformation. Studies indicate that miR-4652-3p is aberrantly expressed in various cancer types. However, its impact and underlying mechanisms in non-small cell lung cancer (NSCLC) have not been investigated.

Methods

A549 cells were stimulated with IL-1β, TNF-α, and IL-6 (each at 10 ng/ml) to mimic an inflammatory microenvironment. Metabolic status was evaluated by measuring glutamine uptake, α-ketoglutarate (α-KG), and ATP levels. Functional studies employed the glutaminase inhibitor (CB-839), the MYC inhibitor (10058-F4), SLC1A5 small interfering RNA (siSLC1A5-2), a miR-4652-3p mimic, and overexpression plasmids. Molecular interactions were validated using chromatin immunoprecipitation (ChIP), dual-luciferase reporter assays, and RNA pull-down experiment. CCK-8 and Transwell assays were used for the assessment of cell malignant phenotypes. The functional significance of miR-4652-3p was further verified in a xenograft mouse model.

Results

miR-4652-3p was downregulated in NSCLC, while MYC and SLC1A5 were upregulated. Inflammatory stimulation enhanced A549 cell proliferation, glutamine uptake, and α-KG/ATP production; these effects were attenuated by CB-839. ChIP and dual-luciferase assays demonstrated that MYC binds the SLC1A5 promoter and activates its transcription. Inhibiting MYC or knocking down SLC1A5 significantly reduced glutamine uptake. Mechanistic analysis revealed that miR-4652-3p directly targets both MYC and SLC1A5 mRNA. miR-4652-3p suppressed glutamine metabolism in NSCLC cells by negatively regulating the MYC/SLC1A5 axis, consequently inhibiting cell growth and tumor progression in a xenograft mouse model, an effect reversed by MYC or SLC1A5 overexpression.

Conclusions

miR-4652-3p blocked the inflammatory microenvironment-induced glutamine metabolic reprogramming by directly suppressing the MYC/SLC1A5 axis, thereby inhibiting NSCLC progression. The miR-4652-3p/MYC/SLC1A5 pathway represents a key regulatory mechanism for metabolic adaptation in NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-026-00649-y.

Keywords: miR-4652-3p, Non-small cell lung cancer, Inflammatory microenvironment, miR-4652-3p/MYC/SLC1A5 pathway, Metabolic reprogramming

Background

Lung cancer is the second most common cancer globally, accounting for 18% of cancer-related deaths [1]. Non-small cell lung cancer (NSCLC) constitutes over 80% of lung cancer cases, with its incidence showing an increasing trend [2]. Treatment for NSCLC encompasses conventional surgery, chemotherapy, radiotherapy, and emerging immunotherapies for advanced disease. However, due to inadequate screening programs and the late onset of clinical symptoms, the majority of patients are diagnosed at an advanced stage, resulting in a dismal prognosis [3]. Consequently, there is an urgent need to develop novel, sensitive biomarkers for early diagnosis and to identify new therapeutic targets for advanced tumors.

MicroRNAs (miRNAs) are small endogenous RNAs that post-transcriptionally regulate gene expression, primarily by negatively influencing mRNA stability [4]. Most miRNAs function as tumor suppressors or oncogenes in a tissue-specific manner, and dysregulation of miRNA expression is closely linked to the initiation and progression of human cancers [5]. Their high stability in bodily fluids and ease of detection [6]make miRNAs promising candidates for tumor biomarker research [7, 8]. In NSCLC, numerous miRNAs (miR-196b-5p, miR-486, miR-21) have been shown to be aberrantly expressed and to function as oncogenes or tumor suppressors by regulating processes such as cell proliferation, apoptosis, invasion, and metastasis [9, 10]. miR-4652-3p was found to target HIPK2 in oral cancer [11]and to regulate ZEB1 via a competing endogenous RNA (ceRNA) mechanism in meningiomas [12], indicating its significant potential in tumor regulation. However, miRNA expression is subject to tissue-specific regulation and varies across different cancer types. The expression and functional role of miR-4652-3p in NSCLC remain unknown.

The pathogenesis of NSCLC results from the interplay of multiple factors, including smoking and inflammation [13]. The chronic inflammatory microenvironment is recognized as a key driver of cancer development, significantly increasing lung cancer risk [14, 15]. The underlying mechanism involving transcription factor-driven inflammatory pathways that recruit various leukocytes and promote the release of cytokines such as TNF-α, TGF-β, IL-1β, and IL-6. These inflammatory mediators act through autocrine and paracrine mechanisms to support tumor cell survival, activate NF-κB and STAT3 signaling pathways, and induce epithelial–mesenchymal transition (EMT), thereby promoting tumor metastasis [16, 17]. In non-small cell lung cancer (NSCLC), a study by Yun Peng et al. compared the plasma levels of 12 inflammatory cytokines between NSCLC patients and healthy controls. The results showed significantly elevated levels of IL-6, IL-1β, and TNF-α in the NSCLC group, whereas no statistically significant differences were observed in IL-5, IFN-α, IL-2, IL-10, IL-8, IL-17, or IL-4 [18]. Among these, IL-1β is one of the most abundant and influential cytokines in the tumor microenvironment. Its aberrant expression is closely linked to lung cancer progression and poor prognosis [19]. TNF-α has also been demonstrated to promote NSCLC growth within specific concentration ranges [20]. Furthermore, elevated IL-6 levels are associated with cancer cachexia and cancer-related fatigue. Plasma IL-6 is regarded as a key indicator of malignancy-associated inflammation and is significantly correlated with malnutrition and reduced overall survival in NSCLC patients [21, 22].

Concurrently, tumor metabolic reprogramming, particularly the aberrant dependence on glucose and glutamine, is a hallmark of cancer essential for maintaining malignant phenotypes [23–25]. Glutamine, a multifunctional nutrient, is critical for tumor cell energy supply, biosynthesis, and redox homeostasis [26]. The MYC/SLC1A5 pathway plays a central role in inducing glutamine metabolic reprogramming and addiction, representing a novel mechanism driving NSCLC progression and metastasis [27]. It is currently unclear whether and how miR-4652-3p might suppress inflammation-induced glutamine metabolism in lung cancer by regulating MYC/SLC1A5. This study systematically investigates the expression level of miR-4652-3p in NSCLC, validates its function in regulating tumor cell growth and metastasis, and specifically elucidates the molecular mechanism by which it counteracts the cancer-promoting effects of inflammation through targeting and negatively regulating MYC/SLC1A5, thereby inhibiting glutamine metabolism.

Methods

Cell culture and treatment

The human non-small cell lung cancer (NSCLC) cell line A549 and the normal lung epithelial cell line BEAS-2B were purchased from Procell Life Science & Technology Co., Ltd. (Wuhan, China). Cells were maintained in RPMI-1640 medium (Gibco, USA) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin solution. Cultures were incubated under standard conditions (37 °C, 5% CO₂, humidified atmosphere).

To simulate the inflammatory microenvironment, A549 cells were serum-starved in serum-free medium for 6 h, followed by incubation with human recombinant IL-1β (10 ng/ml) [28], TNF-α (10 ng/ml) [29], and IL-6 (10 ng/ml) [30] for 6 h.

Cell transfection

A549 cells were seeded in 6-well plates (2.1 × 10⁴ cells/well) and incubated overnight. Upon reaching 80% confluence, cells were transfected with either an exogenous DNA or RNA using Lipofectamine 3000 transfection reagent (Invitrogen, USA), strictly according to the manufacturer’s protocol. After 6 h of incubation with the transfection complex, the medium was replaced with complete growth medium containing 10% FBS. Cells were further cultured for 48 h prior to subsequent analyses.

Quantitative real-time PCR

Total RNA was isolated using TRIzol™ Reagent (Invitrogen, USA). cDNA was synthesized using a reverse transcription kit. Quantitative PCR amplification was performed using a real-time PCR system (Bioneer, Korea). U6 small nuclear RNA served as the endogenous reference for miR-4652-3p quantification, while GAPDH mRNA was used for MYC and SLC1A5 quantification. miR-4652-3p and U6 were detected using the BeyoFast SYBR Green One-Step qRT-PCR Kit (Beyotime, China). The expressions of MYC, SLC1A5 and GAPDH were quantified using the corresponding TaqMan assay kits from Thermo Fisher Scientific (USA). The detailed information of primers and kits can be found in Supplementary file 1. Relative gene expression levels were calculated using the 2−ΔΔCT method.

Cell counting Kit-8 (CCK-8)

Transfected A549 cells in the logarithmic growth phase were seeded into 96-well plates at a density of 5 × 10³ cells per well. After 24 h of treatment, 10 µL of CCK-8 reagent was added to each well. Following a 2-hour incubation at 37 °C, absorbance was measured at 450 nm using a microplate reader.Inline graphic.

Transwell

Transwell® chambers (Corning, USA) were coated with Matrigel® matrix (BD Biosciences, USA) diluted in serum-free RPMI-1640 medium. After uniform coating onto the polycarbonate membrane, chambers were polymerized at 37 °C for 4 h. Serum-starved A549 cells (2 × 10⁴ cells) were seeded into the upper chamber. The lower chamber was filled with medium containing 10% FBS as a chemoattractant. After 24 h of incubation at 37 °C, cells on the lower surface were fixed with 4% paraformaldehyde, stained with crystal violet, and the number of invaded cells in five randomly selected fields was counted under a microscope.

Animal experiments

BALB/c nude mice (male, 4–6 weeks old) were obtained from the Animal Experiment Center of Huazhong University of Science and Technology in Wuhan, China. A549 cells transfected with miR-4652-3p mimics, MYC-overexpressing plasmid (pcMYC), or SLC1A5-overexpressing plasmid (pcSLC1A5), along with corresponding control cells, were harvested and resuspended in PBS at a density of 1 × 10⁶ cells in 200 µL. The cell suspensions were subcutaneously injected into the flanks of the mice (n = 5 per group). At the end of the experiment, the mice were euthanized, and tumors were excised and weighed. Tumor volume (V) was calculated using the formula: Inline graphic.

Chromatin immunoprecipitation (ChIP)

A549 cells were transfected with different plasmids (pcDNA empty vector, pcMYC overexpression vector, wild-type or mutant SLC1A5 promoter constructs (Supplementary file 2) for 48 h. Protein-DNA complexes were cross-linked using 1% formaldehyde. Cells were lysed, and chromatin was fragmented to 200–500 bp fragments via sonication. Chromatin fragments were incubated overnight at 4 °C with anti-MYC antibody or control IgG. Immune complexes were captured using Protein A/G magnetic beads and washed stringently with buffers. Complexes were eluted, cross-links were reversed at 65 °C, and DNA was purified. Enrichment of the SLC1A5 promoter region was quantified by qPCR relative to Input DNA (normalization control) and IgG (negative control). Results were expressed as fold enrichment.

Western blotting

Proteins were extracted using RIPA lysis buffer (Beyotime, Shanghai, China) supplemented with a protease and phosphatase inhibitor cocktail. Protein concentration was determined using a BCA protein assay kit (Thermo Fisher, MA, USA). Proteins were denatured in SDS-PAGE loading buffer (Beyotime, Shanghai, China) at 100 °C for 5 min and separated on 7.5–15% SDS-polyacrylamide gels. Conditioned medium (CM) was collected after incubating cells in serum-free medium for 24 h at 37 °C, followed by centrifugation at 2000×g for 10 min at 4 °C. For Western blotting, separated proteins were transferred to PVDF membranes. After blocking, membranes were incubated overnight at 4 °C with the following primary antibodies: MYC (WB, Abcam #ab9132, 1:5,000), GAPDH (WB, Cell Signaling Technology #5174, 1:5000), and SLC1A5 (WB, Abcam #ab237704, 1:1,000). Following washes, membranes were incubated with a goat anti-Rabbit IgG secondary antibody conjugated to Alexa Fluor 594 (ThermoFisher, #A11012). The chemiluminescence system (Bio-Rad, USA) imaging system was performed to measure all bands.

Bioinformatic analysis

The JASPAR database (https://jaspar.elixir.no/) was used to predict the E-box components of MYC on the SLC1A5 promoter. The miRDB database (https://mirdb.org/custom.html) was utilized to predict the miRNAs targeting MYC and SLC1A5. Candidate miRNAs were prioritized based on their predicted binding scores.

Dual-luciferase reporter assay

The dual-luciferase reporter vectors containing the wild-type (wt) or mutant (mut) MYC (with introduced Xhol, Smal, and Sacl sites) and SLC1A5 (with introduced Bglll and Smal sites) 3’ untranslated regions (3’UTRs) (Supplementary file 2) were constructed by GENE CREATE Biotechnology Company (China) (Figure S1). A549 cells seeded in 24-well plates were co-transfected with luciferase reporter vector and either the miR-4652-3p mimic or negative control (miR-NC) using Lipofectamine 3000. After 24 h, cells were lysed. Firefly and Renilla luciferase activities were measured using the Dual-Luciferase® Reporter Assay System (Promega, USA). Firefly luciferase activity was normalized to Renilla luciferase activity.

Metabolite quantification

Residual glutamine concentration in the culture medium was measured using a Glutamine Assay Kit (BioVision, USA). Glutamine consumption was calculated relative to control groups (normalized to 1). Intracellular α-KG levels were quantified colorimetrically (450 nm) from cell lysates using an α-KG Assay Kit (Abcam, UK). Cellular ATP levels were determined using a luminescence-based ATP Assay Kit (Promega, USA).

Statistical analysis

All statistical analyses were performed using SPSS 24.0 (IBM, USA) and GraphPad Prism 9.0 (GraphPad Software, USA). Continuous variables are presented as mean ± standard deviation (SD). Student’s t-test and one-way ANOVA were used for the data analysis in this study. A p value < 0.05 was considered statistically significant for all analyses.

Results

Enhanced glutamine metabolism in the inflammatory microenvironment promotes NSCLC cell growth

Results demonstrated that IL-1β + TNF-α + IL-6 stimulation significantly promoted A549 cell proliferation (Fig. 1A). Mechanistic studies revealed that this effect was accompanied by a broad activation of glutamine metabolism. The cytokine combination enhanced glutamine uptake in A549 cells (Fig. 1B), increased production of the key metabolic intermediate α-ketoglutarate (α-KG) (Fig. 1C), and consequently elevated ATP synthesis (Fig. 1D). To confirm the functional significance of this metabolic reprogramming, cells were treated with CB-839, a specific glutaminase inhibitor, which suppressed glutaminase activity (Fig. 1E). CB-839 application reduced α-KG and ATP production in A549 cells (Fig. 1C-D), indicating its inhibition of glutamine metabolism. Furthermore, CB-839 treatment partly reversed the IL-1β + TNF-α + IL-6-induced A549 cell proliferation (Fig. 1F). These data demonstrate that inhibiting glutamine metabolism mitigates the accelerated growth of A549 cells driven by the inflammatory microenvironment.

Fig. 1.

Fig. 1

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Enhanced glutamine metabolism in the inflammatory microenvironment promoted NSCLC cell growth. A IL-1β + TNF-α + IL-6 stimulation promotedA549 cell proliferation. B IL-1β + TNF-α + IL-6 stimulation enhanced glutamine uptake in A549 cells. C IL-1β + TNF-α + IL-6 stimulation increased α-ketoglutarate (α-KG) production in A549 cells. D IL-1β + TNF-α + IL-6 stimulation elevated ATP synthesis in A549 cells. E Glutaminase inhibitor CB-839 suppressed enzyme activity, reducing α-KG and ATP production in A549 cells. F CB-839 inhibited the enhanced proliferative capacity of A549 cells induced by IL-1β + TNF-α + IL-6 stimulation. All the experiments were independently repeated three times. *p < 0.05, **p < 0.01, ***p < 0.001

MYC increases glutamine uptake in NSCLC by upregulating SLC1A5 transcription

Under IL-1β + TNF-α + IL-6 stimulation, SLC1A5 mRNA expression was upregulated in A549 cells (Fig. 2A). siRNA screening identified si-SLC1A5-2 as effectively reducing SLC1A5 expression (Fig. 2B). Knockdown of SLC1A5 decreased glutamine uptake in cytokine-treated cells (Fig. 2C). JASPAR database analysis predicted a MYC-binding E-box element in the SLC1A5 promoter. ChIP assay confirmed MYC binding to this promoter region, with enrichment enhanced by MYC overexpression and absent using a mutated promoter plasmid (Fig. 2D). In a dual-luciferase reporter assay, MYC overexpression increased activity of the wild-type, but not mutated, SLC1A5 promoter (Fig. 2E). The MYC inhibitor 10,058-F4 suppressed both SLC1A5 transcription and glutamine uptake (Fig. 2F-G). Furthermore, MYC overexpression increased SLC1A5 mRNA levels and glutamine uptake, effects blocked by siSLC1A5-2 co-transfection (Fig. 2H-I). These data indicate that MYC transcriptionally regulates SLC1A5 to modulate glutamine metabolism under inflammatory conditions.

Fig. 2.

Fig. 2

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MYC increased glutamine uptake in NSCLC by transcriptionally upregulating SLC1A5. A SLC1A5 expression was upregulated in IL-1β + TNF-α + IL-6-stimulated A549 cells. B Screening identified siRNA-2 (siSLC1A5-2) as the most efficient for SLC1A5 knockdown. C SLC1A5 knockdown reduced glutamine uptake in cytokine-treated A549 cells. D Chromatin immunoprecipitation assay confirmed MYC binding to the SLC1A5 promoter. E Dual-luciferase reporter assay demonstrated MYC targeting of SLC1A5. F MYC inhibitor 10,058-F4 suppressed SLC1A5 transcription in cytokine-treated A549 cells. G 10,058-F4-mediated SLC1A5 downregulation decreased glutamine uptake in cytokine-treated A549 cells. H MYC overexpression upregulated SLC1A5 mRNA levels. I MYC overexpression-mediated SLC1A5 upregulation enhanced glutamine uptake in A549 cells. All the experiments were independently repeated three times. ns, no significant difference. *p < 0.05, **p < 0.01, ***p < 0.001

miR-4652-3p negatively regulates MYC and SLC1A5

To further investigate the regulatory mechanism, the miRDB database was used to predict miRNAs (binding score ≥ 80) targeting both MYC and SLC1A5. miR-4652-3p was identified as potentially targeting the 3’UTR regions of both MYC and SLC1A5 (Fig. 3A). RNA Pull-Down assay confirmed significant enrichment of MYC and SLC1A5 mRNA in the isolated miR-4652-3p fraction (Fig. 3B). Transfection with miR-4652-3p mimics elevated intracellular miRNA levels (Fig. 3C). Dual-luciferase reporter vectors were constructed containing wild-type or mutated binding sequences for miR-4652-3p within the MYC and SLC1A5 3’UTRs, as predicted by miRDB (Fig. 3D). Reporter assay revealed that miR-4652-3p mimic decreased the activity of wild-type MYC and SLC1A5 reporters, while mutation of the binding sites completely abolished this inhibitory effect (Fig. 3E-F). Western blotting experiment showed that compared with mimic-negative control (mimic NC), overexpression of miR (via miR mimics) significantly downregulated the expression of MYC and SLC1A5 (Fig. 3G). These results confirm that miR-4652-3p negatively regulated MYC/SLC1A5 expression by binding to their mRNAs.

Fig. 3.

Fig. 3

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miR-4652-3p negatively regulated MYC and SLC1A5. A Prediction of miRNAs targeting MYC and SLC1A5 (binding score ≥ 80) using miRDB database. B RNA pull-down assay confirmed miR-4652-3p targeting of MYC and SLC1A5 mRNA. C Transfection efficiency of miR-4652-3p mimics. D Construction of dual-luciferase reporter vectors containing wild-type or mutated miR-4652-3p binding sites within the MYC/SLC1A5 3’UTR (predicted by miRDB). E Dual-luciferase reporter assay validated miR-4652-3p targeting of MYC. F Dual-luciferase reporter assay validated miR-4652-3p targeting of SLC1A5. G MYC and SLC1A5 protein expression levels under various treatment conditions. All the experiments were independently repeated three times. **p < 0.01, ***p < 0.001

Impact of the miR-4652-3p-MYC/SLC1A5 pathway on NSCLC malignant phenotypes

Compared to BEAS-2B, NSCLC cells (A549) exhibited increased proliferation and migration abilities (Fig. 4A and B). miR-4652-3p expression was lower in NSCLC cells, while the expression of MYC and SLC1A5 was significantly higher (Fig. 4C). Western blot analysis showed higher protein levels of MYC and SLC1A5 in A549 cells than in normal BEAS-2B cells (Fig. 4D). Cell proliferation (CCK-8 assay) and migration were reduced in A549 cells treated with miR-4652-3p mimic, the MYC inhibitor 10,058-F4, or siSLC1A5, compared to their respective controls (Fig. 4E and F). The inhibitory effects of miR-4652-3p on proliferation and migration were reversed by overexpressing either MYC or SLC1A5 (Fig. 4G and H). In a xenograft model established in BALB/c nude mice, A549 cells transfected with the miR-4652-3p mimic exhibited significantly reduced tumor formation capacity. This was reflected in a decreased tumor growth rate (Fig. 4I) and a lower final tumor weight (Fig. 4J). The suppressive effect of miR-4652-3p on tumor growth was reversed by co-expression of either MYC or SLC1A5.

Fig. 4.

Fig. 4

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Impact of the miR-4652-3p-MYC/SLC1A5 regulatory axis on NSCLC malignant phenotypes. A A549 cells exhibited enhanced proliferative capacity compared to BEAS-2B cells. B A549 cells displayed increased migratory capacity compared to BEAS-2B cells. C Compared to BEAS-2B cells, A549 cells exhibited a decrease in the level of miR-4652-3p. D Western blot analysis revealed elevated protein levels of both MYC and SLC1A5 in A549 cells compared to BEAS-2B cells. E Effects of miR-4652-3p, MYC, and SLC1A5 on NSCLC cell proliferation. F Effects of miR-4652-3p, MYC, and SLC1A5 on NSCLC cell migration. G Overexpression of MYC or SLC1A5 reversed the proliferation inhibition induced by miR-4652-3p upregulation in NSCLC cells. H Overexpression of MYC or SLC1A5 reversed the migration inhibition induced by miR-4652-3p upregulation in NSCLC cells. Effects of administering minic NC, miR mimics, miR mimics + pcMYC, or miR mimics + pcSLC1A5 on tumor volume (I) and weight (J). All the experiments were independently repeated three times. *p < 0.05, **p < 0.01, ***p < 0.001

Activation of the MYC/SLC1A5 pathway reverses miR-4652-3p-mediated suppression of glutamine metabolism

Inflammatory stimulation (IL-1β + TNF-α + IL-6) enhanced A549 cell proliferation. This enhancement was attenuated by miR-4652-3p overexpression, and the suppressive effect of miR-4652-3p was reduced upon co‑overexpression of MYC and SLC1A5 (Fig. 5A). miR‑4652‑3p upregulation decreased cytokine‑stimulated glutamine uptake, and MYC/SLC1A5 overexpression reversed this decrease (Fig. 5B). miR-4652-3p mimic reduced the levels of α-KG and ATP in stimulated cells, similar to the effect of the glutaminase inhibitor CB‑839 (Fig. 5C and D). MYC/SLC1A5 overexpression also counteracted the suppression of α‑KG and ATP by miR-4652-3p (Fig. 5C and D). These results indicate that miR‑4652‑3p can restrain glutamine metabolism and cell growth in NSCLC cells, potentially through regulating the MYC/SLC1A5 axis.

Fig. 5.

Fig. 5

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Activation of the MYC/SLC1A5 pathway reversed miR-4652-3p-mediated suppression of glutamine metabolism. A Effect of the miR-4652-3p-MYC/SLC1A5 regulatory axis on proliferation of IL-1β + TNF-α + IL-6-stimulated A549 cells. B Upregulation of miR-4652-3p suppressed glutamine uptake in cytokine-stimulated A549 cells, reversed by MYC/SLC1A5 overexpression. C Upregulation of miR-4652-3p inhibited α-KG production in cytokine-stimulated A549 cells, reversed by MYC/SLC1A5 overexpression. D Upregulation of miR-4652-3p reduced ATP production in cytokine-stimulated A549 cells, reversed by MYC/SLC1A5 overexpression. All the experiments were independently repeated three times. *p < 0.05, **p < 0.01, ***p < 0.001

Discussion

The high mortality rate of NSCLC is closely linked to the lack of early diagnostic markers and effective therapeutic targets, making the exploration of prognostic biomarkers for NSCLC a major research focus [31]. Numerous clinical studies indicate that expression signatures of specific miRNAs are critically associated with patient diagnosis, treatment, and prognosis [32, 33]. For instance, low expression of miR-122a correlates with poor prognosis in lung cancer patients, although its precise roles in diagnosis and therapy remain undefined [34].

Metabolic reprogramming represents a core characteristic enabling cancer cells to sustain proliferation and overcome metabolic challenges [35]. Although the utilization of glucose for aerobic glycolysis (the Warburg effect) in cancer cells has been extensively studied, recent research reveals that cancer cells also exhibit a high dependency on alternative nutrient sources, such as glutamine, for survival [36]. Some cancer cells even demonstrate a glutamine addiction exceeding that of glucose [37]. Notably, the inflammatory microenvironment has been established as a key driver of tumor metabolic reprogramming, including the Warburg effect [38].

Our study establishes miR-4652-3p as a critical tumor suppressor within the inflammatory microenvironment of NSCLC. Bioinformatics screening and dual-luciferase reporter assays confirmed miR-4652-3p as a coordinating regulator with dual-targeting capability, directly binding both MYC and SLC1A5. We further demonstrated that miR-4652-3p negatively regulates IL-1β/TNF-α/IL-6-induced glutamine metabolic reprogramming, thereby suppressing tumor cell proliferation and migration. Addressing the role of MYC in metabolic regulation, previous research has firmly established MYC as a master regulator of tumor metabolism, particularly through regulating glycolysis-related genes [39]. However, the specific mechanisms underlying its regulation of glutamine transporters remained unclear, and the involvement of miRNAs in inflammation-induced metabolic reprogramming was poorly understood. Our study provides evidence that MYC functions as a transcriptional regulator hub that directly binds the SLC1A5 promoter and activates its transcription. This discovery offers a new perspective for understanding how MYC precisely coordinates distinct metabolic pathways.

Xenograft experiments in mice verified that miR-4652-3p overexpression significantly curbs in vivo tumor growth, reflected by reduced tumor growth rates and final tumor weights—effects reversed upon co-expression of MYC or SLC1A5. These findings define miR-4652-3p as an inhibitor of glutamine metabolism in NSCLC cells. This work aligns with the view emphasized by Wang and Zhang that amino acid metabolic reprogramming constitutes a core mechanism in chronic airway diseases and lung cancer [40]. Our data experimentally validate the previously reviewed concept that glutamine metabolism fuels the tricarboxylic acid (TCA) cycle via α-ketoglutarate (α-KG) to meet bioenergetic and biosynthetic demands of cancer cells 1 [40]. We confirmed that inflammatory stimuli enhance glutamine uptake and the production of its metabolites α-KG and ATP, and demonstrated that disruption of the miR-4652-3p/MYC/SLC1A5 axis effectively reverses this process.

Notably, the increase in α-KG accompanying activated glutamine metabolism in the inflammatory context suggests a potential mechanistic link. Deficiency in miR-4652-3p, leading to MYC/SLC1A5 upregulation and subsequent α-KG accumulation, may not sustain tumor growth but represent a key event promoting epigenetic alterations and malignant transformation. This insight provides a new experimental basis for understanding the metabolic mechanisms underlying the “quantitative-to-qualitative” transition from chronic inflammation to malignancy [41].

This study has several limitations. First, there is currently a lack of validation in large-scale clinical cohorts. Existing literature indicates that miR-637 shows low expression in NSCLC, and its expression level is significantly associated with poor patient prognosis, serving as an independent prognostic marker and potentially influencing disease progression by inhibiting phenotypes such as cell proliferation, migration, and invasion [42]. The present investigation has not yet systematically analyzed the expression patterns of miR-4652-3p, MYC, and SLC1A5 in sufficiently large clinical samples, nor further evaluated their correlation with patient outcomes due to limitations in sample availability. Future work will involve collecting substantial clinical specimens to integrate these findings with clinical practice, thereby further clarifying the clinical relevance of miR-4652-3p, MYC, and SLC1A5. Second, the in vitro functional experiments were conducted mainly using a single KRAS-mutant lung adenocarcinoma cell line, A549. Although this cell line is frequently employed to model the interplay between metabolism and inflammation in NSCLC, heterogeneity may exist across NSCLC cases with different genetic backgrounds or histological subtypes, such as lung squamous cell carcinoma. Subsequent studies will extend the experiments to include additional NSCLC cell lines, such as H1299 and H1975, to systematically verify the regulatory effects of miR-4652-3p on the MYC/SLC1A5 axis, glutamine metabolism, and cell proliferation. Finally, in the animal experiments, the study was limited to assessing tumor growth, without exploring the underlying molecular mechanisms in vivo. Animal studies simulate the interaction between tumors and the microenvironment, providing essential preclinical evidence for the development of anti-NSCLC therapeutics [43]. In follow-up research, a series of functional and mechanistic investigations will be performed on tumor tissues to validate alterations in the miR-4652-3p/MYC/SLC1A5 signaling axis within the in vivo setting.

Conclusions

This study reveals that miR-4652-3p links inflammatory signals to glutamine metabolism in NSCLC. Inflammatory cytokines activate glutamine metabolism to promote growth, a process suppressed by miR-4652-3p through targeting the MYC/SLC1A5 axis. The cytokine-induced upregulation of MYC/SLC1A5 aligns with clinical observations of enhanced glutamine metabolism in inflammatory tumor microenvironments [44]. These findings indicate that miR-4652-3p attenuates inflammation-driven growth by inhibiting the MYC/SLC1A5 pathway.

Supplementary Information

Supplementary Material 1. (18.2KB, docx)
Supplementary Material 2. (18.7KB, docx)
Supplementary Material 3. (42.4KB, jpg)

Acknowledgements

No.

Abbreviations

miRNAs

MicroRNAs

NSCLC

Non-small cell lung cancer

ceRNA

Competing endogenous RNA

CCK-8

Cell Counting Kit-8

ChIP

Chromatin Immunoprecipitation

WT

Wild-type

SD

Standard deviation

Authors’ contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Yihua Que, Yan Song, Yang Pan, Deng Huang and Xianzhen Wu. The first draft of the manuscript was written by Xianzhen Wu and all authors commented on previous versions of the manuscript. Yihua Que, Yan Song and Yang Pan performed manuscript revision. All authors read and approved the final manuscript.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

All procedures and experiments involving animals were approved by the Institutional Animal Care Use Committee at The Affiliated Hospital of Youjiang Medical University for Nationalities. This study was carried out in compliance with the ARRIVE (Animal Research Reporting In Vivo Experiment) guidelines.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Yihua Que and Yan Song should be considered joint first author.

Contributor Information

Xianzhen Wu, Email: wxz_20240510@163.com.

Yang Pan, Email: Panyang202509@163.com.

References

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Associated Data

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

Supplementary Materials

Supplementary Material 1. (18.2KB, docx)
Supplementary Material 2. (18.7KB, docx)
Supplementary Material 3. (42.4KB, jpg)

Data Availability Statement

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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