The A549 human lung adenocarcinoma (LUAD) cell line, as well as the BEAS-2B bronchial epithelial cell line, the PC9 LUAD cell line, the H520 lung squamous cell carcinoma cell line and the NCI-H1299 NSCLC cell line were obtained from ZFdows Biotech Co., Ltd. All cell lines were authenticated through short tandem repeat profiling, which determined the absence of Mycoplasma contamination. Detailed specifications of all cell lines are provided in Table I, with data derived from the Catalogue of Somatic Mutations in Cancer (Sanger Institute; http://cancer.sanger.ac.uk/cosmic) and the Cancer Cell Line Encyclopedia (American Type Culture Collection; http://www.atcc.org/) databases. All cells were cultured in DMEM/F12 (1:1 ratio; cat. no. BL1917A; Biosharp Life Sciences) enriched with 10% FBS (cat. no. BL305A; Biosharp Life Sciences) under standard conditions (37°C; 5% CO₂) for optimal cell proliferation.

METTL5- and PGAM1-overexpression plasmids were purchased from Heyuan Liji (Shanghai) Biotechnology Co., Ltd. The open reading frames of METTL5 and PGAM1 were cloned into the pcDNA3.1(+) vector. Specific small interfering RNAs (siRNAs), along with a non-targeting negative control siRNA, were obtained from Guangzhou RiboBio Co., Ltd. For transient transfection, cells were seeded in 6-well plates at a density of 3×10⁵ cells per well 24 h prior to transfection. Plasmid DNA (2 µg) or siRNA (50 nM) were transfected into cells using Lipo8000™ reagent (cat. no. C0533; Beyotime Biotechnology) according to the manufacturer's protocol. The transfection mixture was incubated with cells for 6 h at 37°C before replacing with fresh complete medium. After 48 h transfection, cell samples were collected for protein quantification.

For stable gene knockdown, short hairpin RNA (shRNA/sh)-YTHDF1 and sh-PGAM1 lentiviral particles were obtained from Guangzhou RiboBio Co., Ltd. These lentiviral particles were constructed in the pLKO.1-puro vector system, which drives shRNA expression under the human U6 promoter and contains a puromycin resistance gene for selection of transduced cells. A549 and PC9 cells were infected with lentiviral particles encoding either sh-YTHDF1 or sh-PGAM1, or corresponding control shRNA, in the presence of polybrene (8 µg/ml) to enhance infection efficiency. At 48 h post-infection, cells were selected with puromycin (2 µg/ml) for 7–10 days to establish stable cell lines. The knockdown efficiency was validated by western blot analysis 72 h post-infection and prior to use in downstream assays.

Detailed information on the plasmid constructs, siRNA sequences and shRNA sequences is provided in Tables II and III. Validation of transfection efficiency for YTHDF1 and PGAM1 modulations in A549 and PC9 cells is shown in Fig. S1.

Total RNA was extracted from cells using the SteadyPure Mag Tissue & Cell RNA Extraction Kit (cat. no. AG21207; Hunan Accurate Bio-Medical Technology Co., Ltd.). cDNA was synthesized using the Evo M-MLV Reverse Transcription Premix Kit (cat. no. AG11728; Hunan Accurate Bio-Medical Technology Co., Ltd.) according to the manufacturer's instructions. qPCR was performed using the ChamQ Universal SYBR qPCR Master Mix (cat. no. Q711; Vazyme Biotech Co., Ltd.), a ROX reference dye-containing SYBR Green I-based fluorescent dye system. The reactions were performed using an Applied Biosystems™ PCR thermocycler (Thermo Fisher Scientific, Inc.) with three technical replicates (41). The thermal cycling conditions were as follows: Initial denaturation at 95°C for 30 sec, followed by 40 cycles of denaturation at 95°C for 5 sec, and annealing/extension at 60°C for 30 sec. GAPDH was used as the internal reference gene and the relative expression levels of target genes were calculated using the 2^−ΔΔCq method. The specific oligonucleotide sequences used for PCR are shown in Table IV.

Total proteins were extracted from cells using RIPA lysis buffer (cat. no. 89901; ThermoFisher Scientific, Inc.). Protein concentration was determined using the BCA Protein Assay Kit (cat. no. 23227; Thermo Fisher Scientific, Inc.) according to the manufacturer's instructions. Equal amounts of protein (30 µg per lane) were separated by 10% SDS-PAGE and subsequently transferred onto PVDF membranes (MilliporeSigma). The membranes were blocked with 5% non-fat dry milk (cat. no. P0216; Beyotime Biotechnology) in TBST containing 0.1% Tween-20 (cat. no. ST671; Beyotime Biotechnology) for 1 h at room temperature. The membranes were incubated with specific primary antibodies at 4°C overnight. Subsequently, the membranes were incubated with HRP-conjugated goat anti-rabbit IgG (H+L) secondary antibody (1:5,000; cat. no. SA00001-2; Proteintech Group, Inc.) at room temperature for 1 h. Protein bands were visualized using sensitive ECL detection kit (cat. no. PK10002; Proteintech Group, Inc.) and the band intensity was semi-quantified using ImageJ software (version 1.54; National Institutes of Health). The experiment was performed using three independent biological replicates (n=3), with β-actin serving as the loading control. The following primary antibodies were used for western blotting: Anti-METTL5 (1:1,000; cat. no. CL488-16791; Proteintech Group, Inc.), anti-PGAM1 (1:1,000; cat. no. 16126-1-AP; Proteintech Group, Inc.), anti-YTHDF1 (1:1,000; cat. no. 17479-1-AP; Proteintech Group, Inc.), anti-GLUT1 (1:1,000; cat. no. 21829-1-AP; Proteintech Group, Inc.) and anti-β-actin (1:1,000; cat. no. 60008-1-Ig; Proteintech Group, Inc.).

Cells were seeded in 6-well plates at a density of 200 cells/well and maintained under standard conditions (37°C; 5% CO₂; humidified atmosphere). After 14 days culture, during which no additional treatments were applied, cell colonies were fixed with 95% ethanol at room temperature for 15 min and stained with 0.1% crystal violet at room temperature for 20 min. The colonies were visualized using low-magnification microscopy (CKX53; Olympus Corporation) and quantified using ImageJ software (version 1.54; National Institutes of Health). Briefly, digital images were captured and analyzed using the ‘Cell Counter’ (https://imagej.nih.gov/ij/plugins/cell-counter.html) plugin to mark and count clusters containing ≥50 cells, which were defined as viable colonies. Quantification was performed in a blinded manner by two independent observers. Three independent replicates (n=3) were prepared for each sample to ensure reproducibility.

For the migration assay, a total of 5×10⁴ cells were cultured in serum-free DMEM/F12 (1:1) liquid medium(cat. no. BL1917A; Biosharp Life Sciences) in the upper Transwell chamber, whereas 600 µl of DMEM/F12 (1:1) medium supplemented with 10% FBS was added to the lower chamber. After 12–24 h of incubation at 37°C in a humidified atmosphere containing 5% CO₂, the migrated cells were fixed with methanol at room temperature for 15 min, stained with 0.1% crystal violet for 20 min at room temperature and observed under a phase-contrast light microscope (CKX53; Olympus Corporation) at a magnification of ×400. The cells were manually counted in in five randomly selected visual fields per membrane. All experimental groups and biological replicates were seeded with an identical initial density of 5×10⁴ cells per well. Three independent replicates were prepared for each sample to ensure reproducibility.

The cellular metabolic parameters ECAR and OCR were measured on a Seahorse XFe96 metabolic analyzer (Agilent Technologies, Inc.). The glycolytic rate and mitochondrial function were assessed using the Agilent Seahorse XF Glycolytic Rate Assay Kit (cat. no. 103344-100) and the Seahorse XF Cell Mito Stress Test Kit (cat. no. 103015-100), respectively. The assay solution was prepared according to the manufacturer's instructions. Briefly, glucose, pyruvate, glutamine, oligomycin, rotenone/antimycin A and carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone (FCCP) were used at final concentrations of 10 mmol/l, 1 mmol/l, 2 mmol/l, 1.5 µmol/l, 0.5 µmol/l and 1 µmol/l, respectively. Injections were automatically performed by the instrument at the following timepoints: For the OCR assay, oligomycin was injected at 14 min, FCCP was injected at 35 min and Rotenone/Antimycin A was injected at 55 min. For the ECAR assay, glucose was injected at 14 min, oligomycin was injected at 35 min and 2-DG was injected at 55 min. Measurements were recorded after achieving thermal equilibrium and stable pH conditions.

RNA stability was assessed by exposing cells to 5 µg/ml actinomycin D at 37°C in a humidified incubator with 5% CO₂ and extracting total RNA at specified intervals (0, 4 and 8 h). Temporal mRNA expression was quantified using RT-qPCR.

For functional validation, METTL5-overexpressing cell lines were established and treated with the methylation inhibitor 3-deazaadenosine (DAA; cat. no. HY-W013332; MedChemExpress). Cells were seeded at a density of 1×10⁵ cells per well in 6-well plates and allowed to adhere overnight under standard culture conditions (37°C; 5% CO₂). The following day, cells were treated with 50 µM DAA, a concentration previously established to effectively inhibit methyltransferase activity without inducing significant cytotoxicity (42). DAA was dissolved in dimethyl sulfoxide (DMSO; final concentration ≤0.1%; cat. no. HY-Y0320C; MedChemExpress) and added directly to the culture medium. Control cells were treated with an equivalent volume of DMSO vehicle. Cells were incubated at 37°C in a humidified atmosphere with 5% CO₂ for 48 h prior to harvest for downstream assays.

Data (TCGA-LUSC, TCGA-LUAD) used for bioinformatics analysis were obtained from The Cancer Genome Atlas (TCGA) repository (https://portal.gdc.cancer.gov/). The mRNA expression patterns and prognostic importance of METTL5 and PGAM1 in NSCLC were examined using R software (https://www.r-project.org/; version 4.3.2). Differentially expressed genes (DEGs) were identified using the ‘limma’ package with a significance threshold of adjusted P-value <0.05 and log₂ fold change (log₂FC) >1. Gene expression correlation analysis was performed using the Gene Expression Profiling Interactive Analysis (GEPIA) platform (43). Potential targets of METTL5 were identified using the M6A2Target database (44).

All statistical analyses were performed using GraphPad Prism (version 9.5; Dotmatics) and R (https://www.r-project.org/; version 4.3). Data are presented as the mean ± standard deviation (SD). Comparisons between two groups were performed using unpaired Student's t-tests (for independent samples) or paired t-tests (for matched samples, as indicated in figure legends), whereas multi-group comparisons were performed using one-way ANOVA followed by the Bonferroni post hoc test. Survival probabilities were calculated using Kaplan-Meier analysis and differences in survival curves were assessed using the log-rank test. Gene expression correlations were quantified using Spearman's rank coefficients. All experiments were performed in triplicate. P<0.05 was considered to indicate a statistically significant difference.

Analysis of transcriptomic data obtained from TCGA revealed significantly elevated METTL5 mRNA expression levels in NSCLC (Fig. 1A). Furthermore, METTL5 mRNA expression was significantly upregulated in colon adenocarcinoma, stomach and esophageal carcinoma, pan-kidney cohort, stomach adenocarcinoma, uterine corpus endometrial carcinoma, head and neck squamous cell carcinoma, kidney renal clear cell carcinoma, LIHC, kidney chromophobe and cholangiocarcinoma (Fig. 1B). RT-qPCR and western blotting revealed consistent upregulation patterns, with lung cancer cell lines (A549, PC9 and H520) exhibiting significantly higher METTL5 mRNA and protein expression levels compared with normal pulmonary epithelial cells (Fig. 1D). Prognostic evaluation through Kaplan-Meier analysis indicated that elevated METTL5 expression was associated with reduced survival rates in patients with NSCLC (Fig. 1C).

To investigate the role of METTL5 in NSCLC pathogenesis, cell proliferation and migration were evaluated after METTL5 knockdown or overexpression. Western blotting demonstrated the successful knockdown or overexpression of METTL5 in experimental models constructed through transfection (Fig. 1E and F). The colony formation assay showed that silencing of METTL5 significantly suppressed the proliferation of A549 and PC9 lung cancer cells, whereas ectopic overexpression significantly enhanced cell proliferation (Fig. 2A and B). The Transwell migration assay showed that silencing of METTL5 significantly inhibited the migration of lung cancer cells, whereas its overexpression significantly stimulated cell migration (Fig. 2C and D). These findings collectively indicated that METTL5 serves an oncogenic role in NSCLC, positioning it as a promising diagnostic biomarker and therapeutic target.

To investigate the molecular mechanisms via which METTL5 contributes to NSCLC progression, the M6A2Target database was used to predict the targets of METTL5. PGAM1 mRNA was identified as a key potential target (45). Subsequent analysis using the GEPIA database showed a significant positive correlation between the mRNA expression levels of METTL5 and PGAM1 (R=0.45; P=5.4×10⁻⁵⁶; Fig. 3A). Analysis of transcriptomic data obtained from TCGA showed that the mRNA expression levels of PGAM1 were higher in NSCLC tissues compared with corresponding healthy tissues (Fig. 3B). For functional validation, METTL5-overexpressing cell lines were established and treated with the methylation inhibitor 3-deazaadenosine (DAA). Western blot analysis revealed that overexpression of METTL5 significantly increased PGAM1 protein levels compared with the negative control, while treatment with the methylation inhibitor DAA reversed this effect (Fig. 3C), indicating that PGAM1 expression is dependent on METTL5-mediated methylation. These findings collectively suggested that PGAM1 mRNA was methylated by METTL5 under physiological conditions.

Studies have shown that m⁶A readers serve an important role in methylation (46,47). Based on the predictions of the M6A2Target database and Shi et al (48) (GSE ID: GSE136433), YTHDF1 was identified as an m⁶A reader that recognizes and binds to methylated PGAM1 mRNA. Western blotting further confirmed these findings, indicating that PGAM1 protein expression was significantly lower in YTHDF1-silenced cells compared with control cells (Fig. 3D). These findings align with those of RNA immunoprecipitation (RIP) sequencing in previous studies (48,49), determining direct molecular interactions between YTHDF1 and PGAM1 mRNA. Furthermore, RNA stability analysis revealed that the silencing of YTHDF1 accelerated PGAM1 mRNA decay rates in NSCLC cells, indicating enhanced mRNA degradation (Fig. 3E and F) These findings collectively indicated that YTHDF1 directly recognized m⁶A-modified PGAM1 mRNA to regulate its stability and expression.

As an important enzyme in glycolysis, PGAM1 mediates the interconversion between 3-phosphoglycerate (3-PGA) and 2-phosphoglycerate (2-PGA), thereby enhancing cellular energy metabolism. Through its regulatory role in maintaining equilibrium between these metabolites, PGAM1 affects ancillary metabolic processes. This enzymatic activity influences a number of biosynthetic processes, not only channeling carbon flux towards biosynthetic pathways for macromolecule production but also maintaining cellular redox homeostasis. Furthermore, emerging evidence indicates that PGAM1 regulates mitochondrial function and shapes the tumor immune microenvironment, collectively driving malignant proliferation and metastatic spread in neoplastic tissues (50–52). In the present study, the functional importance of the METTL5/PGAM1 axis in NSCLC pathogenesis and energy metabolism was examined. Metabolic flux analysis showed that PGAM1-knockdown cells exhibited a decreased ECAR but an increased OCR (Fig. 4F and G).

Studies have shown that overexpression of GLUT1 and GLUT3 can promote glucose uptake in tumor cells and lead to chemoresistance by activating oncogenic signaling pathways, such as the PI3K/AKT pathway (53,54). Hexokinase 2 (HK2) is a key enzyme in glycolysis initiation, and its activation can drive tumor metabolism toward glycolysis (55,56). Phosphofructokinase, platelet (PFKP) and 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatases (PFKFB)-3 serve important roles in tumor glycolysis, inducing high glycolytic activity, which may lead to drug resistance (57). To determine the molecular mechanism of METTL5/PGAM1-mediated glycolysis, correlation analysis was performed between PGAM1 expression and GLUT1, GLUT3, HK2, PFKP or PFKFB3 expression (Fig. 4A-E). The correlation between PGAM1 and GLUT1 expression exhibited the highest significance (P=4.12ⅹ10⁻¹⁸³; R=0.6). This finding was validated by detecting protein expression. Knockdown of PGAM1 significantly decreased GLUT1 protein expression in NSCLC cells, whereas its overexpression had the opposite effect (Fig. 5A).

Furthermore, the effects of METTL5 on GLUT1 expression were investigated. Overexpression of METTL5 significantly upregulated GLUT1 expression in NSCLC cells, whereas its knockdown significantly downregulated GLUT1 expression (Fig. 5B). In rescue experiments, compared with the METTL5-knockdown group, GLUT1 protein expression was elevated in cells with METTL5 knockdown combined with PGAM1 overexpression, implying that PGAM1 overexpression partially reversed the downregulation of GLUT1 caused by METTL5 deficiency. This supported the present hypothesis that PGAM1 acts downstream of METTL5 in regulating GLUT1 expression (Fig. 5C).