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. 2026 Jul 20;11(30):45176–45185. doi: 10.1021/acsomega.6c03709

Lathyrol Targets G6PD to Disrupt Redox Homeostasis in Non-Small Cell Lung Cancer

Zhaoxuan Li †,‡, Linlin Zhang ‡, Xueyan Zhen †,§, Xinglu Liu †,‡, Yan Ren §,*, Wei Jia ‡,*
PMCID: PMC13449201  PMID: 42569152

Abstract

Lathyrol, a bioactive natural compound derived from plants of the Euphorbiaceae family, exhibits antitumor activity, and its molecular targets and underlying mechanisms remain incompletely understood. In this study, thermal proteome profiling (TPP) was applied to systematically identify lathyrol-binding proteins in non-small cell lung cancer (NSCLC) cells. TPP analysis identified glucose-6-phosphate dehydrogenase (G6PD) as a candidate target of lathyrol. A cellular thermal shift assay (CETSA) confirmed increased thermal stability of G6PD upon treatment. Molecular docking indicated a potential interaction between lathyrol and G6PD. The peptide-centric local stability assay (PELSA) revealed localized conformational changes in the C-terminal region of G6PD consistent with the predicted interaction interface. Enzymatic assays showed reduced G6PD activity accompanied by decreased intracellular NADPH levels. Quantitative proteomics indicated alterations in the pathways associated with glucose metabolism and redox regulation. These findings identify G6PD as a functional target of lathyrol in NSCLC cells and link its inhibition to disruption of cellular redox balance and metabolic homeostasis.

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1. Introduction

1.1. Background on NSCLC

Lung cancer represents a major global malignancy and continues to be the leading cause of cancer-related death worldwide. Among its histological subtypes, non-small cell lung cancer (NSCLC) constitutes approximately 80–85% of all diagnosed cases. Although surgical resection remains the most effective therapeutic approach for patients with early- or intermediate-stage disease, most individuals with NSCLC are diagnosed at an advanced stage, in which case systemic therapy becomes the primary treatment option. Conventional chemotherapy remains widely used in clinical practice; nevertheless, its clinical benefit is frequently limited by pronounced systemic toxicity and the emergence of drug resistance. Despite the encouraging clinical outcomes achieved with targeted therapies, their broader application remains limited by restricted accessibility, high cost, and incompletely characterized adverse effects. Taken together, these limitations highlight a pressing need for the development of novel therapeutic strategies for NSCLC that offer improved efficacy while minimizing toxicity.

1.2. Introduction to Lathyrol

Traditional Chinese medicine (TCM), with a history spanning several millennia, has long played an important role in the prevention and treatment of cancer. Extensive clinical experience has demonstrated that TCM can enhance the efficacy of chemotherapy and suppress tumor recurrence, thereby improving patient survival and quality of life. , The mature dried seeds of Euphorbia lathyris L, known as Semen Euphorbiae (SE), are commonly used as medicinal materials in anticancer TCM prescriptions. Lathyrol, a lathyrane-type diterpenoid, is a natural product isolated from SE and is one of its major constituents. Previous studies have shown that, in lung cancer cell models, lathyrol can act on sarco/endoplasmic reticulum Ca2+-ATPase 2 (SERCA2), thereby inducing endoplasmic reticulum stress, triggering apoptosis, and inhibiting cancer cell proliferation.

However, despite its strong potential as an antitumor natural compound, the direct molecular targets of lathyrol in NSCLC remain undefined. This gap not only limits a deeper understanding of its mechanism of action but also constrains its further clinical application.

1.3. TPP Identifies G6PD as a Candidate Target of Lathyrol

Elucidating the interactions between drug molecules and disease-related targets is essential for understanding their therapeutic mechanisms. Many natural products and bioactive small molecules act by coordinately regulating multiple molecular targets and associated signaling pathways, underscoring the importance of efficient and accurate target identification strategies. Thermal proteome profiling (TPP), which integrates ligand-induced protein thermal stability changes with liquid chromatography–tandem mass spectrometry (LC–MS/MS), enables unbiased, label-free identification of potential drug targets across the proteome.

TPP offers notable advantages, including high accuracy, high throughput, and a relatively short experimental workflow. It requires neither chemical modification of small molecules nor pre-enrichment of target proteins, and it allows high-throughput target screening in either cell lysates or intact cells under near-physiological conditions. Although challenges related to reproducibility and quantitative accuracy persist when applying TPP to complex biological samples, the technique provides precise information on compound–protein interactions, making it particularly valuable for natural products with incompletely characterized mechanisms of action.

Building on the previously established normalization approach using indexed retention time (iRT) peptides as internal standards, we applied TPP to identify the protein targets of lathyrol in NSCLC and identified G6PD (glucose-6-phosphate dehydrogenase) as a candidate target associated with lathyrol treatment.

1.4. Pentose Phosphate Pathway (PPP) and G6PD

The pentose phosphate pathway (PPP) is a major branch of glucose metabolism responsible for generating ribose-5-phosphate (R-5-P) and reduced nicotinamide adenine dinucleotide phosphate (NADPH). R-5-P serves as an essential precursor for nucleotide biosynthesis, whereas NADPH provides the reducing power required for biosynthetic reactions and for maintaining cellular redox homeostasis. In malignant cells, PPP flux is often elevated to support the substantial biosynthetic demands associated with rapid proliferation and to counteract oxidative stress.

Glucose-6-phosphate dehydrogenase (G6PD), the initial rate-limiting enzyme of the PPP, catalyzes the conversion of glucose-6-phosphate to 6-phosphoglucono-δ-lactone, concomitantly generating NADPH from NADP+. Numerous studies have shown that G6PD is abnormally upregulated or hyperactivated in a variety of cancersincluding breast, liver, and gastric cancersas well as in NSCLC, compared with normal tissues. , Elevated G6PD expression has also been closely associated with poor prognosis and chemotherapy resistance. By regulating intracellular NADPH and R-5-P levels, G6PD profoundly influences malignant phenotypes, including uncontrolled proliferation, resistance to apoptosis, enhanced metastatic potential, and angiogenesis.

In this study, we employed TPP-based chemoproteomics to identify G6PD as a potential functional target of lathyrol in NSCLC cells. Subsequent cellular thermal shift assay (CETSA), molecular docking, peptide-centric local stability assay (PELSA), enzymatic activity analysis, and proteomic profiling further supported the interaction between lathyrol and G6PD. Our results demonstrate that lathyrol inhibits G6PD enzymatic activity, thereby suppressing PPP flux and exerting antitumor effects.

2. Materials and Methods

2.1. Reagents and Antibodies

Purified lathyrol (purity >98%) was purchased from Shanghai Yuanye Biological Co., Ltd. (Shanghai, China). For cell culture, Dulbecco’s modified Eagle’s medium (DMEM), 0.25% trypsin-EDTA, penicillin–streptomycin mixture, and cell freezing medium were all obtained from Meilun Biotechnology (Dalian, China); fetal bovine serum (FBS) was purchased from BIOEXPLORER (California, USA).

The Cell Counting Kit-8 (cat. no. AC11L054) was purchased from Shanghai Liji Biotechnology (Shanghai, China). The G6PD enzyme activity assay kit (cat. no. S0189) and the NADP+/NADPH assay kit (cat. no. S0179) were purchased from Beyotime Biotechnology (Shanghai, China). The protease and phosphatase inhibitor cocktail for protein lysis and the BCA protein assay kit (cat. no. P0012S) for protein concentration determination were also obtained from Beyotime Biotechnology. DL-Dithiothreitol (DTT) for reduction, iodoacetamide (IAA) for alkylation, and the dimethyl sulfoxide (DMSO) were obtained from Sigma-Aldrich (Missouri, USA). Sequencing-grade trypsin was purchased from Promega (Wisconsin, USA).

The rabbit monoclonal antibody against G6PD and the rabbit antibody against β-Actin were both obtained from ABclonal (Wuhan, China). The horseradish peroxidase (HRP)-conjugated goat anti-rabbit secondary antibody was purchased from Wuhan SanYing Biotechnology (Wuhan, China).

2.2. Cell Lines and Cell Culture

The human non-small cell lung cancer cell line A549 was provided by the National Cell Resource Center (Beijing, China). Cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 10% fetal bovine serum (FBS), 100 U/mL penicillin, and 100 μg/mL streptomycin, and maintained in a humidified incubator at 37 °C with 5% CO2.

2.3. Cell Viability Assay

A549 cells were plated in 96-well plates (5 × 103 cells per well) and treated with increasing concentrations of Lathyrol for 24 h. Cell viability was subsequently evaluated using the Cell Counting Kit-8 (CCK-8) assay, with absorbance measured at 450 nm on a microplate reader (Tecan, Switzerland). The IC50 value of Lathyrol was determined to be 354.5 μM by nonlinear regression analysis using GraphPad Prism (version 10.1.2), and an approximate concentration of 360 μM was selected for subsequent thermal proteome profiling experiments.

2.4. Thermal Proteome Profiling (TPP)

A549 cells were treated with Lathyrol (360 μM) or vehicle control (DMSO) for 1 h. Cells were then washed with ice-cold PBS, collected, and lysed in PBS containing protease inhibitors by sonication. After centrifugation at 20,000g for 10 min, the supernatants were collected for subsequent thermal profiling analysis. Samples were grouped according to protein quantification results, and each group was divided into eight aliquots, with each aliquot containing 100 μg of total protein. To normalize TPP data using indexed retention time (iRT) standard peptides, iRT standards were spiked in at 10 ng per sample with a standard-to-protein ratio of 1:5000 (w/w). The samples were heated at 37, 42, 47, 52, 57, 62, 67, and 72 °C for 3 min and then incubated at room temperature for 3 min. After heating, the lysates were centrifuged at 20,000g for 20 min at 4 °C to separate soluble proteins from precipitates. The supernatants were collected while avoiding contact with the pellet and the tube walls, and were reserved for subsequent experiments.

Sample volumes were normalized based on BCA quantification results, using the lowest-temperature point within each corresponding group as the reference; equal volumes of the soluble protein supernatants were then taken for subsequent procedures. An 8 M denaturant was added to each sample, followed by reduction with DTT (5 mM) at 37 °C for 1 h and subsequent alkylation with iodoacetamide (10 mM) in the dark for 45 min. Samples were diluted with ammonium bicarbonate to 50 mM and digested overnight with trypsin at an enzyme-to-protein ratio of 1:50 (m/m) at 37 °C. Digestion was quenched by acidification (pH < 2) using trifluoroacetic acid. Peptides were then desalted with MonoSpin C18 columns, vacuum-dried, and stored at −80 °C prior to LC–MS/MS analysis. Dried peptides were reconstituted in 0.1% formic acid and analyzed using an Orbitrap Eclipse high-resolution mass spectrometer (Thermo Fisher Scientific, USA) coupled to an Easy-nLC 1200 nano-HPLC system. Peptides were separated on a C18 column and eluted with a gradient before entering the mass spectrometer via a nanoESI source. MS scan range was m/z 160–1500, with collision energies of 20–59 eV. Data were acquired in DDA mode, and experiments were performed in triplicate.

MS data were searched for protein identification using MaxQuant (version 2.0.3.1). Search parameters included mass accuracies of 4.5 ppm for precursor ions and 20 ppm for fragment ions. Trypsin/P was selected as the digestion enzyme, allowing a maximum of two missed cleavages. Carbamidomethylation on cysteine residues was defined as a fixed modification, whereas methionine oxidation and N-terminal protein acetylation were treated as variable modifications. “Match between runs” was enabled for protein identification, and identification thresholds were set to achieve false positives <1% at both the protein and peptide-spectrum-match levels. Downstream data processing was performed using R (version 4.2.2). Proteins exhibiting more than 50% missing values were excluded from further analysis, and the remaining missing data were imputed using the k-nearest neighbor (KNN) algorithm. Protein melting-curve fitting and melting-temperature (Tm) calculation were performed using the R package TPP (version 3.28.0).

2.5. Cellular Thermal Shift Assay (CETSA)

The cellular thermal shift assay (CETSA) was conducted to assess target engagement in cells. A549 cells, prepared under the same treatment conditions as described for TPP, were exposed to 360 μM Lathyrol or vehicle (DMSO) for 1 h prior to analysis. After treatment, cells were collected, washed with PBS, and distributed into PCR tubes. The samples were heated in a thermal cycler at gradient temperatures ranging from 42 to 67 °C (in 5 °C increments) for 3 min, followed by cooling to room temperature. The cells were then lysed by repeated freeze–thaw cycles, and the lysates were centrifuged at 20,000g for 20 min at 4 °C to separate soluble proteins. The supernatants were subjected to Western blot analysis using a specific anti-G6PD antibody to assess the binding between Lathyrol and G6PD.

2.6. Molecular Docking

Molecular docking was performed to predict the binding mode between lathyrol and G6PD. The human G6PD crystal structure (PDB ID: 6JYU) was obtained from the Protein Data Bank, and the three-dimensional structure of lathyrol was retrieved from the PubChem database in SDF format and converted to PDBQT format for docking. AutoDock Vina (version 1.5.7) was used to perform the docking simulations. The binding affinity scores were used to evaluate the interaction strength between the ligand and the protein, and the hydrogen bonds, as well as hydrophobic interactions, were analyzed. The docking results were visualized by using PyMOL (version 2.6.0).

2.7. Peptide-Centric Local Stability Assay (PELSA)

The assay was conducted according to the established protocol of Li et al., with the following adjustments. After discarding the culture medium, A549 cells were washed twice with ice-cold PBS and scraped in PBS containing 1% (v/v) protease inhibitor cocktail. Cell lysates were subjected to three freeze–thaw cycles alternating between liquid nitrogen and a 37 °C water bath. Lysates were centrifuged at 20,000g for 10 min at 4 °C. The supernatant was collected, and protein concentration was determined via the BCA assay. Samples were adjusted to 1 mg/mL using lysis buffer. A 50 μL aliquot of supernatant was incubated with PD or DMSO at 25 °C for 30 min. Trypsin was added at a 1:2 (w/w) enzyme-to-protein ratio (2.5 μg/μL stock), followed by 10-s vortex mixing, digestion at 37 °C with 1000 rpm shaking for 50 s, and termination by boiling at 100 °C for 8 min. Then, 165 μL of 8 M guanidine hydrochloride (GdmCl) (3 × sample volume) was added to the boiled digest. Reduction and carbamidomethylation were performed as described in the TPP experiment. The samples were transferred to pre-equilibrated 10-kDa centrifugal filters (Vivacon 500; Sartorius Stedim Biotech) and centrifuged at 14,000g for 30 min. Filters were washed with 200 μL HEPES buffer (60 mM, pH 8.2) and recentrifuged (14,000g, 30 min). Combined filtrates were acidified with 1% TFA. Acidified peptides were loaded onto Pierce C18 Tips, desalted, eluted with 80% acetonitrile/0.1% TFA, and the eluates were completely dried.

Peptides were injected onto a nanoElute UPLC system (Bruker Daltonics). Peptides were separated using a reverse-phase column (25 cm × 75 μm, C18, 1.8 μm, made in-house) with a gradient of 2–22% mobile phase B (0.1% formic acid in acetonitrile) over 45 min, followed by a 15 min gradient of 22–80% B at a flow rate of 300 nL/min. Eluting peptides were directly ionized via electrospray ionization (CaptiveSpray) using a capillary voltage of 1.7 kV and detected using a timsTOF Pro Q-TOF (Bruker Daltonics) operating in DIA-PASEF mode 26 with an ion mobility range (1/k0) of 0.60–1.60 Vs/cm2. For tandem MS, the following parameters were used: number of PASEF MS/MS scans (10); total cycle time (1.16 s); target intensity (20,000); intensity threshold (2500); charge range (0–5); isolation width (2 m/z for m/z < 700 and 3 m/z for m/z > 700); and collisional energy (20–59 eV).

The MS raw data were searched against the SwissProt Homo sapiens reference database using Spectronaut (version 17). The search parameters are set as follows: mass tolerance for precursor ions was 10 ppm, and for product ions was 0.02 Da. Carbamidomethylation was specified as a fixed modification. Oxidation of methionine and acetylation of the N-terminus were set as variable modifications. A maximum of 2 miscleavage sites was allowed. The identified proteins contained at least 1 unique peptide with a false discovery rate of less than 1%. Significant peptides were filtered with q-fold-change >2 and p-value (t-test) < 0.05. The candidate domain of drug-targeted proteins was visualized with PELSA-Decipher.

2.8. Enzyme Activity Assay & NADPH Measurement

The G6PD activity assay kit and the NADPH content assay kit were purchased from Beyotime Biotechnology (Shanghai, China). All procedures were performed strictly according to the manufacturer’s instructions. The absorbance was measured using a microplate reader. The protein concentration of each sample was determined by the BCA method, and the G6PD activity and NADPH levels were normalized to the corresponding protein content as described in the kit protocols.

2.9. Proteomic Analysis and Bioinformatics

To systematically evaluate the effects of lathyrol on cellular metabolic pathways, quantitative proteomic analysis was performed.

After treatment with Lathyrol or DMSO, A549 cells were washed twice with precooled PBS and lysed in a buffer containing 8 M urea and protease inhibitors. The samples were sonicated on ice for 30 min and centrifuged at 14,000 rpm for 20 min. The supernatant was collected, and protein concentrations were determined using the BCA assay. Excess samples were stored at −80 °C for subsequent analysis.

Proteins were extracted, digested, and enriched prior to LC-MS/MS detection. The resulting peptides were separated and analyzed using a high-performance liquid chromatography–tandem high-resolution mass spectrometry (LC-MS/MS) system. Protein identification was performed using Spectronaut software (Biognosys, Switzerland), with a false discovery rate (FDR) threshold of <0.01 at both the peptide spectrum match (PSM) and protein levels. Differentially expressed proteins between paired phenotypic groups were identified by univariate analysis, using fold change >1.5 and p < 0.05 (t-test) as screening criteria.

Significantly differentially expressed proteins were further subjected to gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Bioinformatic analyses were conducted by using standard online databases and R software (version 4.2.2).

2.10. Statistical Analysis

All experiments were independently performed at least three times. Data are presented as mean ± standard deviation (SD). Statistical comparisons between two groups were performed using a two-tailed t-test, and multiple-group comparisons were analyzed using one-way analysis of variance (ANOVA). A p-value <0.05 was considered statistically significant. GraphPad Prism 10.1.2 (GraphPad Software, USA) and R software (version 4.2.2) were used for statistical analysis and graph generation.

3. Results

3.1. Lathyrol Inhibits A549 Cell Viability in a Concentration-Dependent Manner

To measure the inhibition effect of Lathyrol on the viability of human A549 cells, the CCK-8 assay was performed on the cells treated with different concentrations of Lathyrol for 24 h. The results clearly showed that A549 cell viability decreased in a concentration-dependent manner under Lathyrol treatment (Figure A). The IC50 value of Lathyrol was calculated to be 354.5 μM (Figure B), and therefore, a concentration of 360 μM was selected for subsequent experiments.

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Lathyrol reduces A549 cell viability in a dose-dependent manner. (A) CCK-8 assay showing cell viability after treatment with different concentrations of Lathyrol for 24 h. (B) Dose–response curve and IC50 value of Lathyrol at 24 h. IC50 = 354.5 μM. Data are shown as the means ± SD (n = 3). * p < 0.05, **p < 0.01, and ***p < 0.001 versus untreated control cells.

3.2. TPP Reveals G6PD as a Potential Target of Lathyrol in A549 Cells

In the TPP assay, the same amount of proteins was treated under an eight-temperature gradient, and the nondenatured proteins that remained in the supernatant were identified and quantified by LC-MS/MS from control and Lathyrol treatment groups, respectively. The thermal melting curves of proteins were generated from the protein intensity at the eight-temperature treatment, in which the T m values of proteins were defined as the temperature point of 50% intensity remaining in the proteins by MS quantification. The ΔT m values between control and Lathyrol treatment groups indicated the impacts and affinity of Lathyrol binding to targets, and the coefficient of determination R 2 of the thermal melting curves showed the change trends of protein quantification under gradient heat treatment. A total of 3161 proteins were identified and quantified from the supernatants, and the thermal melting curve of each protein was generated using an in-house program. After applying the selection criteria (ΔT m > 4 °C, coefficient of determination R 2 > 0.8, and plateau <0.3 in the fitted melting curves), 83 candidate proteins were obtained. Among these, glucose-6-phosphate dehydrogenase (G6PD), the first rate-limiting enzyme of the pentose phosphate pathway (PPP), exhibited a pronounced thermal shift (ΔT m = 52.62 °C, R 2 = 1; Figure B). G6PD has been reported to play a critical role in supporting lung cancer cell proliferation and resistance to oxidative stress. Considering its prominent ΔT m, high-quality melting-curve fitting, and well-established relevance to cancer-related metabolic pathways, G6PD was prioritized for subsequent validation.

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Thermal proteome profiling identifies G6PD as a target of Lathyrol. (A) Schematic of the TPP experiment. (B) The melting curve of Lathyrol shifted significantly upon drug treatment using the TPP package. L: Lathyrol, melting point: 52.62 °C; slope: −0.1; plateau: 0.06; R2:1. C: DMSO, melting point: 48.46 °C; slope: −0.061; plateau: 0; R2:0.94.

3.3. CETSA Confirms the Binding of Lathyrol to G6PD

To validate the TPP screening results, the CETSA with higher sensitivity was further performed to determine whether G6PD can bind to lathyrol. The WB image results clearly showed that the abundance of G6PD had a slower decrease in the Lathyrol group compared with that of G6PD in the control group under the same gradient heat treatment, which supported that the thermal stability of G6PD was markedly enhanced in A549 cells with Lathyrol treatment (Figure A). The quantification results on the G6PD bands of WB double confirmed the results mentioned above (Figure B). This effect was consistently observed across multiple independent CETSA experiments, indicating that lathyrol can interact with G6PD and alter its thermal stability.

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Validation of G6PD as a potential target of Lathyrol. (A) CETSA immunoblot showing the thermal stability of G6PD in A549 cells with or without Lathyrol treatment at the indicated temperatures. (B) Quantification of G6PD band intensity from panel (A). (C) Schematic representation of the molecular docking model illustrating the interaction between Lathyrol and G6PD. (D) Peptide-centric local stability assay (PELSA) showing changes in protease susceptibility of G6PD upon Lathyrol treatment. The band intensities were measured by densitometry, normalized, and presented as mean ± SD (n = 3).

Taken together, the results of TPP and CETSA provide converging evidence that G6PD may serve as a potential target of lathyrol in A549 cells and support a possible interaction between lathyrol and G6PD, suggesting its role as a functionally relevant molecular target.

3.4. Molecular Docking Supports Interaction between Lathyrol and G6PD

To further investigate the interaction between Lathyrol and G6PD, molecular docking analysis was performed. The results showed that Lathyrol could stably bind within the active pocket of G6PD, with a predicted binding free energy of −7.0 kcal/mol, suggesting a strong binding affinity between the two molecules.

Binding mode analysis revealed that the diterpenoid skeleton of Lathyrol forms notable Pi–alkyl and alkyl interactions with Tyr503 and Tyr507, both of which are key residues involved in the binding of the natural substrate glucose-6-phosphate (G6P). In addition, the polar groups of Lathyrol establish a hydrogen-bonding network with Arg50, Arg56, and Arg57, residues located at the dimer interface of G6PD (Figure C). This indicates that Lathyrol binding may potentially influence the oligomeric state of G6PD.

Collectively, the molecular docking results provide structural evidence supporting a potential competitive inhibitory binding mode of lathyrol toward G6PD.

3.5. PELSA Reveals Localized Conformational Changes in G6PD upon Lathyrol Treatment

To further elucidate the structural basis underlying the interaction between lathyrol and G6PD, we employed the peptide-centric local stability assay (PELSA) to analyze changes in protease susceptibility across different regions of G6PD following lathyrol treatment, thereby assessing local conformational stability at the peptide level.

Compared with the control group, multiple G6PD-derived peptides exhibited markedly altered protease sensitivity upon Lathyrol treatment. Notably, the most pronounced changes were predominantly distributed within the C-terminal region of G6PD, particularly spanning residues 300–330 and 390–510. These regions displayed substantial changes in peptide abundance after drug treatment, suggesting that Lathyrol binding may induce localized conformational alterations in G6PD, thereby modulating the accessibility of these regions to proteolytic digestion and indicating region-specific structural perturbations (Figure D).

Further comparison of the PELSA results with molecular docking analysis revealed a high degree of consistency between the predicted Lathyrol-binding region and the peptides showing significant responses in the PELSA assay. This agreement was particularly evident within the 390–510 region, where both approaches indicated potential involvement in the interaction between Lathyrol and G6PD.

3.6. Proteomic Analysis Reveals Lathyrol-Induced Redox and Metabolic Reprogramming

To evaluate the global impact of Lathyrol on the proteome of A549 cells and to characterize the associated cellular responses at the systematic level, we performed quantitative LC-MS/MS-based proteomic profiling. Using a cutoff of fold change >1.5 (or <0.67) and p < 0.05, a total of 314 proteins were identified with significantly differential expression, including 161 upregulated and 153 downregulated proteins (Figure A).

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Proteomic profiling of A549 cells following Lathyrol treatment. (A) Volcano plot highlighting differentially expressed proteins. (B) Mean intensity scatter showing the overall distribution of protein abundance between groups. (C) Gene Ontology (GO) enrichment analysis of significantly altered proteins. (D) KEGG pathway enrichment analysis revealing metabolic and redox-related pathways potentially affected by Lathyrol.

At the global expression level, the altered proteins exhibited a clear pattern of metabolic reprogramming. Multiple proteins involved in oxidative stress regulation, cell cycle progression, ribosomal function, and organelle biogenesis showed systematic changes. In parallel, several key proteins associated with energy metabolism, lipid biosynthesis, and mitochondrial function were markedly affected. Collectively, these results indicate that lathyrol treatment is accompanied by broad alterations in cellular metabolic and redox-related processes.

GO enrichment analysis revealed that the differentially expressed proteins were mainly localized to the cytoplasm, membrane-bound organelles, and extracellular vesicles. Functionally, they were enriched in protein binding, RNA binding, and structural molecule activity and were associated with biological processes including organelle organization, macromolecular assembly, protein localization, and nitrogen-containing compound metabolism (Figure B). KEGG pathway analysis further demonstrated enrichment in the pentose phosphate pathway, NADPH-generating processes, redox regulation, lipid biosynthesis, oxidative phosphorylation, purine metabolism, and glycolysis/gluconeogenesis, along with pathways related to ribosome function, spliceosome activity, and ubiquitin-mediated proteolysis (Figure C).

Overall, quantitative proteomic analysis revealed that lathyrol treatment induced widespread alterations in proteins involved in redox homeostasis and glucose metabolism, indicating a global metabolic response at the proteome level.

3.7. Lathyrol Inhibits G6PD Enzymatic Activity and Reduces NADPH Generation

Given that G6PD serves as a key regulatory enzyme in the PPP and is essential for cellular NADPH production, we next investigated whether lathyrol treatment influenced G6PD enzymatic activity and intracellular NADPH levels to further substantiate G6PD as a molecular target of lathyrol.

To evaluate whether lathyrol affects G6PD enzymatic function, enzyme activity and intracellular NADPH levels were measured in A549 cells using commercial assay kits. The results showed that lathyrol treatment significantly reduced both G6PD activity (Figure A) and NADPH (Figure B) content compared with the control group.

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Inhibition of G6PD enzymatic function by Lathyrol. (A) G6PD enzymatic activity measured in A549 cells following Lathyrol treatment. (B) Intracellular NADPH levels assessed under the same treatment conditions. Data are shown as the means ± SD (n = 3). * p < 0.05, **p < 0.01, and ***p < 0.001 versus untreated control cells.

These results demonstrate that lathyrol directly inhibits G6PD enzymatic activity and is associated with a marked reduction in intracellular NADPH levels.

4. Discussion

As a key regulatory component of the pentose phosphate pathway, G6PD is essential for sustaining NADPH production, preserving cellular redox homeostasis, and meeting the biosynthetic demands associated with rapid cell proliferation.

G6PD is frequently overexpressed in multiple cancers, including lung, renal, and liver malignancies, and is closely linked to oxidative stress responses, metabolic dysregulation, and malignant phenotypes. Consequently, targeting G6PD has increasingly emerged as a promising direction in tumor metabolic therapy. Against this background, our study identifies G6PD as a previously unrecognized potential molecular target of lathyrol, thereby providing mechanistic insight into its antitumor activity through metabolic regulation and offering new evidence for natural-product-based G6PD-targeting strategies.

It is noteworthy that natural products, due to their structural complexity, diverse bioactive components, and limited modifiable sites, often pose substantial challenges for identifying direct molecular targets using traditional approaches, thereby constraining mechanistic studies over the long-term. Lathyrol, one of the major active constituents of Semen Euphorbiae (SE), has been used in traditional Chinese medicine for many years and has shown certain antitumor potential. Although previous studies have suggested that Lathyrol can inhibit lung cancer cell proliferation by inducing endoplasmic reticulum stress, its molecular target has remained undefined. By identifying G6PD as a potential binding protein of Lathyrol, our findings extend previous observations and suggest that metabolic regulation may represent an additional, previously underappreciated dimension of Lathyrol’s antitumor activity.

In this study, we employed TPP, a target-discovery strategy that does not require chemical modification of small molecules and enables global assessment of protein thermal stability under near-physiological conditions, allowing the identification of proteins potentially interacting with Lathyrol within a complex cellular context. Compared with conventional target-identification methods, TPP is better suited for natural products with complex structures and limited amenable functional groups for chemical derivatization, thus providing a technically feasible and broadly applicable approach for elucidating the mechanisms of natural products. Notably, the application of TPP in this study enabled unbiased identification of G6PD without prior assumptions regarding Lathyrol’s molecular targets, thereby reducing target-selection bias and strengthening the robustness of the target discovery process, and nominating G6PD as a candidate target for further investigation.

Beyond the identification of candidate targets, our quantitative proteomic analysis revealed widespread alterations in proteins involved in redox regulation, NADPH-associated metabolism, and glucose metabolic pathways following Lathyrol treatment. The enrichment of PPP- and redox-related pathways is consistent with the central role of G6PD in maintaining NADPH homeostasis and suggests that modulation of G6PD activity may contribute to coordinated metabolic remodeling rather than isolated enzymatic suppression. These proteome-wide changes further support the potential functional relevance of the Lathyrol–G6PD association and indicate that perturbation of G6PD activity may propagate to broader metabolic networks that are critical for tumor cell survival. Notably, the peptide-level structural perturbations revealed by PELSA, together with the spatial consistency between responsive peptides and the docking-predicted interface, provide additional evidence supporting a localized interaction between Lathyrol and G6PD, which may underlie the observed proteomic alterations.

In summary, this study primarily employs TPP to identify G6PD as a candidate target of lathyrol in non-small cell lung cancer. Subsequent CETSA, molecular docking, and PELSA collectively support the interaction between lathyrol and G6PD and suggest that this interaction is accompanied by localized conformational perturbations within the protein structure. Enzymatic activity assays demonstrated inhibition of G6PD activity, while quantitative proteomic analysis revealed alterations in redox- and metabolism-related pathways, indicating that perturbation of G6PD may propagate to broader metabolic networks beyond its enzymatic function.

Together, these multilevel data suggest a mechanistic link between lathyrol exposure and modulation of G6PD-centered redox regulation, providing a coherent explanation for the observed metabolic alterations.

These results provide new insights into the metabolic mechanisms underlying the activity of lathyrol and highlight the utility of TPP as a powerful approach for target discovery in natural product research.

5. Conclusion

The signal transduction induced by drug target proteins is a key to unlocking their molecular mechanism. In order to more precisely figure out the antitumor effects of Lathyrol, several approaches from different angles were applied to identify and evaluate the potential target proteins of Lathyrol. In this study, G6PD was identified as a candidate target protein of Lathyrol in the TPP assay, an in situ approach with high sensitivity for target protein identification. The G6PD antibody was adopted to evaluate the thermal stability change of G6PD upon Lathyrol treatment by CETSA, which clearly showed that more G6PD remained in supernatants under the same temperature treatment due to binding with Lathyrol and getting higher thermal stability. The molecular docking analysis further suggested a potential interaction between lathyrol and G6PD at the molecular structure level, while PELSA revealed localized conformational changes in the C-terminal region of G6PD upon lathyrol treatment, showing partial consistency with the docking-predicted interaction interface. Moreover, quantitative proteomic analysis revealed changes in the expression of proteins associated with PPP and glutathione metabolism, indicating a disturbance in metabolic homeostasis. Consistent with this, functional assays revealed that lathyrol modulated G6PD enzymatic activity and reduced intracellular NADPH levels. Collectively, these results support the idea that G6PD may serve as a potential functional target of lathyrol in A549 cells, contributing to its antitumor effects through redox regulation.

Nevertheless, several limitations must be noted. The current findings are primarily based on a single-cell model and require further validation in additional experimental systems. In addition, direct evidence of the interaction between lathyrol and G6PD remains limited, and the detailed mechanistic links between G6PD modulation and downstream metabolic alterations need to be further clarified. Future studies incorporating complementary approaches will help strengthen target validation and provide a more comprehensive understanding of the underlying mechanisms.

Acknowledgments

This work was supported by the Clinical Key Specialty Support Program of the Shanghai Hongkou District Health Commission (Grant No. HKZK2020A04); the “Strengthening Traditional Chinese Medicine Excellence” Initiative (Phase II) of the Shanghai Hongkou District Health Commission (Grant No. HKGYQYXM-2022-11); the Development and Validation of a Prediction Model for Benign versus Malignant Subsolid Pulmonary Nodules (Grant No. Hongwei 2301-01); The Study on the Impact of KEAP1Mutation on Drug Resistance in Lung Cancer and the Synergistic Effect of ML385 in Chemotherapy (Key Project, 2024-2027, Supported by Shanghai Traditional Chinese Medicine-Integrated Hospital Young Scientist Program 2024KJCY001), and The Significance of KEAP1 Gene Mutation in Non-Small Cell Lung Cancer (Youth Project, 2024-2025, Supported by Shanghai Hongkou District Health Commission Project 2403-3).

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (https://proteomecentral.proteomexchange.org) via the iProX partner repository , with the data set identifier PXD080468.

Z.L. (First Author): Conceptualization, investigation, methodology, and writing–original draft. L.Z., X.Z., X.L.: Investigation, validation, and writing–review and editing. Y.R. (Co-corresponding author): Conceptualization, supervision, and writing–review and editing. W.J. (Co-corresponding author): Conceptualization, supervision, funding acquisition, and writing–review and editing.

The authors declare no competing financial interest.

References

  1. Chen P., Liu Y., Wen Y., Zhou C.. Non-Small Cell Lung Cancer in China. Cancer Commun. 2022;42(10):937–970. doi: 10.1002/cac2.12359. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Yan H.-J., Zheng X., Zeng Y., Wan J., Chen J., Deng Z., Mao Y., Hu W., Zhang J., Zhong A., Zhao C., Mao W., Tian D.. Salvage Surgery and Conversion Surgery for Patients with Nonsmall Cell Lung Cancer: A Narrative Review. Int. J. Surg. 2025;111(1):1032–1041. doi: 10.1097/JS9.0000000000001921. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Tiansheng G., Junming H., Xiaoyun W., Peixi C., Shaoshan D., Qianping C.. Lncrna Metastasis-Associated Lung Adenocarcinoma Transcript 1 Promotes Proliferation and Invasion of Non-Small Cell Lung Cancer Cells Via Down-Regulating Mir-202 Expression. Cell J. 2020;22(3):375–385. doi: 10.22074/cellj.2020.6837. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Puri S., Saltos A., Perez B., Le X., Gray J. E.. Locally Advanced, Unresectable Non-Small Cell Lung Cancer. Curr. Oncol. Rep. 2020;22(4):31. doi: 10.1007/s11912-020-0882-3. [DOI] [PubMed] [Google Scholar]
  5. The L.. Lung Cancer Treatment: 20 Years of Progress. Lancet. 2024;403(10445):2663. doi: 10.1016/S0140-6736(24)01299-6. [DOI] [PubMed] [Google Scholar]
  6. Wang K., Chen Q., Shao Y., Yin S., Liu C., Liu Y., Wang R., Wang T., Qiu Y., Yu H.. Anticancer Activities of Tcm and their Active Components Against Tumor Metastasis. Biomed. Pharmacother. 2021;133:111044. doi: 10.1016/j.biopha.2020.111044. [DOI] [PubMed] [Google Scholar]
  7. Cai J., Wang L., Xu M., Zhu S., Chen Y., Zhong J., Li J., Zhang P., Zhang T., Ye Q., Ao H.. Multi-Target Therapeutics of Geraniin From Geranium Wilfordii Maxim. And Related Species: Mechanisms and Applications. J. Ethnopharmacol. 2026;356:120765. doi: 10.1016/j.jep.2025.120765. [DOI] [PubMed] [Google Scholar]
  8. Bailly C.. Yuexiandajisu Diterpenoids From Euphorbia Ebracteolata Hayata (Langdu Roots): An Overview. Phytochemistry. 2023;213:113784. doi: 10.1016/j.phytochem.2023.113784. [DOI] [PubMed] [Google Scholar]
  9. Zhu A., Zhang T., Wang Q.. The Phytochemistry, Pharmacokinetics, Pharmacology and Toxicity of Euphorbia Semen. J. Ethnopharmacol. 2018;227:41–55. doi: 10.1016/j.jep.2018.08.024. [DOI] [PubMed] [Google Scholar]
  10. Chen P., Li Y., Zhou Z., Pan C., Zeng L.. Lathyrol Promotes Er Stress-Induced Apoptosis and Proliferation Inhibition in Lung Cancer Cells by Targeting Serca2. Biomed. Pharmacother. 2023;158:114123. doi: 10.1016/j.biopha.2022.114123. [DOI] [PubMed] [Google Scholar]
  11. Atanasov A. G., Zotchev S. B., Dirsch V. M., International N. P. S. T., Supuran C. T.. et al. Natural Products in Drug Discovery: Advances and Opportunities. Nat. Rev. Drug Discovery. 2021;20(3):200–216. doi: 10.1038/s41573-020-00114-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Chen X., Liu J., Lu P., Zhou J., Jiang L., Zhai Y., Guo M., Lei H., Wang H., Zhang X., Wang T., Pan H., Wu J.. Unraveling Traditional Chinese Medicine with Single-Cell Rna Sequencing: Current Applications and Future Frontiers. Phytomedicine. 2025;149:157556. doi: 10.1016/j.phymed.2025.157556. [DOI] [PubMed] [Google Scholar]
  13. Mateus A., Kurzawa N., Perrin J., Bergamini G., Savitski M. M.. Drug Target Identification in Tissues by Thermal Proteome Profiling. Annu. Rev. Pharmacol. Toxicol. 2022;62:465–482. doi: 10.1146/annurev-pharmtox-052120-013205. [DOI] [PubMed] [Google Scholar]
  14. Le Sueur C., Hammarén H. M., Sridharan S., Savitski M. M.. Thermal Proteome Profiling: Insights Into Protein Modifications, Associations, and Functions. Curr. Opin. Chem. Biol. 2022;71:102225. doi: 10.1016/j.cbpa.2022.102225. [DOI] [PubMed] [Google Scholar]
  15. Mateus A., Kurzawa N., Becher I., Sridharan S., Helm D., Stein F., Typas A., Savitski M. M.. Thermal Proteome Profiling for Interrogating Protein Interactions. Mol. Syst. Biol. 2020;16(3):e9232. doi: 10.15252/msb.20199232. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Tu Y., Tan L., Tao H., Li Y., Liu H.. Cetsa and Thermal Proteome Profiling Strategies for Target Identification and Drug Discovery of Natural Products. Phytomedicine. 2023;116:154862. doi: 10.1016/j.phymed.2023.154862. [DOI] [PubMed] [Google Scholar]
  17. Zhen X.. et al. A Data Normalization Method of Thermal Proteome Profiling. Chem. J. Chin. Univ. 2024;45(12):48–54. doi: 10.7503/cjcu20240286. [DOI] [Google Scholar]
  18. TeSlaa T., Ralser M., Fan J., Rabinowitz J. D.. The Pentose Phosphate Pathway in Health and Disease. Nat. Metab. 2023;5(8):1275–1289. doi: 10.1038/s42255-023-00863-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Ju H.-Q., Lin J., Tian T., Xie D., Xu R.. Nadph Homeostasis in Cancer: Functions, Mechanisms and Therapeutic Implications. Signal Transduction Targeted Ther. 2020;5(1):231. doi: 10.1038/s41392-020-00326-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Deng H., Chen Y., Wang L., Zhang Y., Hang Q., Li P., Zhang P., Ji J., Song H., Chen M., Jin Y.. Pi3K/Mtor Inhibitors Promote G6Pd Autophagic Degradation and Exacerbate Oxidative Stress Damage to Radiosensitize Small Cell Lung Cancer. Cell Death Dis. 2023;14(10):652. doi: 10.1038/s41419-023-06171-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Ma H., Zhang F., Zhou L., Cao T., Sun D., Wen S., Zhu J., Xiong Z., Tsau M., Cheng M., Hung L., Zhou Y., Li Q.. C-Src Facilitates Tumorigenesis by Phosphorylating and Activating G6Pd. Oncogene. 2021;40(14):2567–2580. doi: 10.1038/s41388-021-01673-0. [DOI] [PubMed] [Google Scholar]
  22. Yang H.-C., Wu Y., Yen W., Liu H., Hwang T., Stern A., Chiu D. T.. The Redox Role of G6Pd in Cell Growth, Cell Death, and Cancer. Cells. 2019;8(9):1055. doi: 10.3390/cells8091055. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Zhen X., Zhang M., Hao S., Sun J.. Glucose-6-Phosphate Dehydrogenase and Transketolase: Key Factors in Breast Cancer Progression and Therapy. Biomed. Pharmacother. 2024;176:116935. doi: 10.1016/j.biopha.2024.116935. [DOI] [PubMed] [Google Scholar]
  24. Song J., Sun H., Zhang S., Shan C.. The Multiple Roles of Glucose-6-Phosphate Dehydrogenase in Tumorigenesis and Cancer Chemoresistance. Life. 2022;12(2):271. doi: 10.3390/life12020271. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Ahamed A., Hosea R., Wu S., Kasim V.. The Emerging Roles of the Metabolic Regulator G6Pd in Human Cancers. Int. J. Mol. Sci. 2023;24(24):17238. doi: 10.3390/ijms242417238. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Zeng T., Li B., Shu X., Pang J., Wang H., Cai X., Liao Y., Xiao X., Chong Y., Gong J., Li X.. Pan-Cancer Analysis Reveals that G6Pd is a Prognostic Biomarker and Therapeutic Target for a Variety of Cancers. Front. Oncol. 2023;13:1183474. doi: 10.3389/fonc.2023.1183474. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Li K., Chen S., Wang K., Wang Y., Xue L., Ye Y., Fang Z., Lyu J., Zhu H., Li Y., Yu T., Yang F., Zhang X., Guo S., Ruan C., Zhou J., Wang Q., Dong M., Luo C., Ye M.. A Peptide-Centric Local Stability Assay Enables Proteome-Scale Identification of the Protein Targets and Binding Regions of Diverse Ligands. Nat. Methods. 2025;22(2):278–282. doi: 10.1038/s41592-024-02553-7. [DOI] [PubMed] [Google Scholar]
  28. Thakor P., Siddiqui M. Q., Patel T. R.. Analysis of the Interlink Between Glucose-6-Phosphate Dehydrogenase (G6Pd) and Lung Cancer through Multi-Omics Databases. Heliyon. 2024;10(15):e35158. doi: 10.1016/j.heliyon.2024.e35158. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Wang H., Bi T., Yang W.. Developing New Strategies to Construct Pseudo-Natural Macrocycles for Undruggable Targets. Acc. Chem. Res. 2025;58(19):3096–3110. doi: 10.1021/acs.accounts.5c00524. [DOI] [PubMed] [Google Scholar]
  30. Yang T., Wang S., Li H., Zhao Q., Yan S., Dong M., Liu D., Chen X., Li R.. Lathyrane Diterpenes From Euphorbia Lathyris and the Potential Mechanism to Reverse the Multi-Drug Resistance in Hepg2/Adr Cells. Biomed. Pharmacother. 2020;121:109663. doi: 10.1016/j.biopha.2019.109663. [DOI] [PubMed] [Google Scholar]
  31. Aldehoff A. S., Karkossa I., Broghammer H., Krupka S., Weiner J., Goerdeler C., Nuwayhid R., Langer S., Wabitsch M., Rolle-Kampczyk U., Klöting N., Blüher M., Heiker J. T., von Bergen M., Schubert K.. Advanced Proteomics Approaches Hold Potential for the Risk Assessment of Metabolism-Disrupting Chemicals as Omics-Based Nam: A Case Study Using the Phthalate Substitute Dinch. Environ. Sci. Technol. 2025;59(31):16193–16216. doi: 10.1021/acs.est.5c01206. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Song J.. Applications of the Cellular Thermal Shift Assay to Drug Discovery in Natural Products: A Review. Int. J. Mol. Sci. 2025;26(9):3940. doi: 10.3390/ijms26093940. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Ma J., Chen T., Wu S., Yang C., Bai M., Shu K., Li K., Zhang G., Jin Z., He F., Hermjakob H., Zhu Y.. Iprox: An Integrated Proteome Resource. Nucleic. Acids. Res. 2019;47(D1):D1211–D1217. doi: 10.1093/nar/gky869. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Chen T., Ma J., Liu Y., Chen Z., Xiao N., Lu Y., Fu Y., Yang C., Li M., Wu S., Wang X., Li D., He F., Hermjakob H., Zhu Y.. Iprox in 2021: Connecting Proteomics Data Sharing with Big Data. Nucleic. Acids. Res. 2022;50(D1):D1522–D1527. doi: 10.1093/nar/gkab1081. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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

Data Availability Statement

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (https://proteomecentral.proteomexchange.org) via the iProX partner repository , with the data set identifier PXD080468.

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