Combination of glutathione synthesis inhibitor and glucose uptake inhibitor, nanoparticle delivery system and application thereof

Abstract

The invention discloses a combination of a glutathione synthesis inhibitor and a glucose uptake inhibitor, a nanoparticle delivery system and application thereof, and belongs to the field of medicines. The invention proves that the SLC7A11 is remarkably overexpressed in lung adenocarcinoma and is related to poor clinical prognosis; experiments find that the combination of the glutathione synthesis inhibitor and the glucose uptake inhibitor shows an effect of enhancing lung adenocarcinoma treatment in medium and high SLC7A11 expression cells, and can also achieve an effect equivalent to glucose deprivation under the condition of SLC7A11 overexpression in low expression cells. In order to optimize a delivery mode and minimize systemic toxicity, the invention also prepares a dual-cell membrane coated dual-drug nanoparticle delivery system, the system shows the ability to enhance tumor targeting and drug controllable release, effectively solves the problem of expression difference (heterogeneity) of SLC7A11 in tumors, and shows a significant anti-tumor effect in a preclinical model, and the system has good application prospects. And a promising treatment method is provided for treating lung adenocarcinoma.

Description

Technical Field

[0001] The present invention relates to the field of medicine, and particularly to combinations of glutathione synthesis inhibitors and glucose uptake inhibitors, nanoparticle delivery systems, and their applications. Background Art

[0002] The global cancer burden is increasing, making cancer a major global health challenge. Among all cancer types, lung cancer remains the leading cause of cancer-related deaths, with lung adenocarcinoma (LUAD) being its main subtype. The invasive characteristics and poor prognosis of LUAD are mainly attributed to its complex molecular mechanisms and unique metabolic adaptations.

[0003] Cancer cells undergo extensive metabolic reprogramming to support their rapid proliferation and survival in the hostile tumor microenvironment. This metabolic plasticity is particularly evident in LUAD, where cells exhibit enhanced glucose uptake (Warburg effect), increased glutamine utilization, and elevated antioxidant defense mechanisms. These metabolic alterations create unique vulnerabilities that may be exploited therapeutically. Among these adaptations, the regulation of redox homeostasis has emerged as a key determinant of cancer cell survival, in which the cystine / glutamate transporter SLC7A11 plays a crucial role.

[0004] Recent studies have revealed that cancer cells with overexpressed SLC7A11 exhibit unique metabolic vulnerabilities. Under glucose deprivation conditions, these cells undergo a special form of regulated cell death called disulfidptosis. Mechanistically, this process is characterized by excessive cystine uptake, which requires substantial NADPH consumption to be reduced to cysteine. Glucose deprivation further restricts the intracellular NADPH supply, leading to the toxic accumulation of cystine and other disulfide-bonded molecules. The resulting disulfide stress induces abnormal crosslinking of actin cytoskeletal proteins, disrupting cell structural integrity and ultimately leading to cell death. The glucose transporter GLUT1 is mainly overexpressed in cancer cells, promoting glucose uptake necessary for maintaining cellular redox homeostasis. BAY-876 is a selective GLUT1 inhibitor that has been shown to induce disulfidptosis in SLC7A11-overexpressing cells through NADPH depletion. However, the therapeutic efficacy of GLUT1 inhibition is limited by tumor SLC7A11 expression heterogeneity and the potential systemic toxicity associated with long-term glucose deprivation. Buthionine sulfoximine (BSO) is an inhibitor of glutamine-cysteine ligase (GCL), which depletes the cellular glutathione (GSH) pool by blocking its synthesis. Considering the crucial roles of NADPH and GSH in maintaining cellular redox balance, the inventors of the present invention have found that the combination of GLUT1 inhibition and BSO presents a method that may synergistically enhance disulfidptosis induction. Therefore, the prognostic significance of SLC7A11 expression in LUAD was explored, and targeted therapeutic strategies were developed to overcome SLC7A11-mediated treatment heterogeneity. The synergistic potential of combining GLUT1 inhibition with BSO was evaluated, and a novel dual-membrane-coated nanoparticle delivery system was developed to enhance the therapeutic effect while minimizing systemic toxicity. Summary of the Invention

[0005] The object of the present invention is to provide a combination of a glutathione synthesis inhibitor and a glucose uptake inhibitor, a nanoparticle delivery system, and their applications, to solve the problems existing in the above-mentioned prior art. The nanoparticle delivery system loaded with the dual drugs is more effective and safer, providing a promising direction for the treatment of lung adenocarcinoma, laying a foundation for future clinical research, and may also improve the prognosis of lung adenocarcinoma patients.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] The present invention provides the application of a combination of a glutathione synthesis inhibitor and a glucose uptake inhibitor in any one of the following:

[0008] (1) Application in the preparation of a drug for treating lung adenocarcinoma;

[0009] (2) Application in the preparation of a drug for improving SLC7A11 expression heterogeneity in lung adenocarcinoma.

[0010] Optionally, the glutathione synthesis inhibitor includes BSO, and the glucose uptake inhibitor includes BAY-876.

[0011] The present invention also provides a nanoparticle delivery system, which is a nanoparticle coated with double cell membranes and the drug loaded thereon. The double cell membranes are lung cancer cell membranes and macrophage cell membranes, and the drug is a glutathione synthesis inhibitor and a glucose uptake inhibitor.

[0012] Optionally, the glutathione synthesis inhibitor includes BSO, and the glucose uptake inhibitor includes BAY-876.

[0013] The present invention also provides a method for preparing the nanoparticle delivery system as described above, including the following steps:

[0014] After dissolving the glutathione synthesis inhibitor and the glucose uptake inhibitor separately, they are ultrasonically emulsified with dichloromethane containing poly(lactic-co-glycolic acid) copolymer under ultrasonic conditions. Then, the formed primary emulsion is dropped into a polyvinyl alcohol solution to form a secondary emulsion, stirred at room temperature, washed and freeze-dried to obtain nanoparticles.

[0015] After mixing the lung cancer cell membrane, macrophage cell membrane and the nanoparticles, they are extruded through a polycarbonate porous membrane to obtain a nanoparticle delivery system.

[0016] Optionally, the mass-volume ratio of the glutathione synthesis inhibitor to the dichloromethane containing poly(lactic-co-glycolic acid) copolymer is 1 mg:(1 - 10) mL;

[0017] The mass-volume ratio of the glucose uptake inhibitor to the dichloromethane containing poly(lactic-co-glycolic acid) copolymer is 1 mg:(1 - 10) mL;

[0018] Wherein, the mass-volume ratio of poly(lactic-co-glycolic acid) copolymer to dichloromethane in the dichloromethane containing poly(lactic-co-glycolic acid) copolymer is 1 mg:(10 - 50) mL.

[0019] Optionally, the volume ratio of the primary emulsion to the polyvinyl alcohol solution is 1:(1 - 3), and the mass-volume fraction of the polyvinyl alcohol solution is 2% - 5%.

[0020] Optionally, the mass ratio of the lung cancer cell membrane, macrophage cell membrane and nanoparticles is 1:1:(1 - 3).

[0021] The present invention also provides the application of the nanoparticle delivery system as described above in any one of the following:

[0022] (1) Application in the preparation of a drug for treating lung adenocarcinoma;

[0023] (2) Use in the preparation of a drug for improving the heterogeneity of SLC7A11 expression in lung adenocarcinoma.

[0024] Optionally, the glutathione synthesis inhibitor and the glucose uptake inhibitor are used in combination to synergistically induce disulfidptosis in lung adenocarcinoma cells with medium to high expression of SLC7A11, improve the heterogeneity of SLC7A11 expression in lung adenocarcinoma and / or achieve an enhanced therapeutic effect on lung adenocarcinoma.

[0025] The present invention discloses the following technical effects:

[0026] The present invention synergistically enhances the induction of disulfidptosis through the combination of BSO (glutathione synthesis inhibitor) and BAY-876 (glucose uptake inhibitor), producing a potent anti-tumor effect. Notably, in cells with medium to high SLC7A11 expression, the cell death induced by the combination of the two drugs is more significant than glucose deprivation alone under the condition of SLC7A11 overexpression. In cells with low SLC7A11 expression, the combination treatment achieved a cell death level comparable to glucose deprivation under the condition of SLC7A11 overexpression. This treatment method effectively solves the heterogeneity of SLC7A11 expression in tumors and provides a more widely applicable treatment strategy without SLC7A11 enhancers.

[0027] The combination treatment of BSO and BAY-876 enhances disulfidptosis by disrupting cellular redox homeostasis. Disulfide stress, as a specific subset of oxidative stress, occurs when the cellular reducing capacity (especially NADPH and GSH) is impaired, leading to the oxidation of cysteine residues and the formation of abnormal protein disulfide bonds. BSO-mediated inhibition of GSH synthesis creates an "oxidative defense gap", making the cells particularly sensitive to stress conditions. This vulnerability caused by GSH depletion may even exceed the metabolic vulnerability usually observed in SLC7A11 overexpressing cells.

[0028] To enhance the potential of combination therapy and mitigate the potential side effects of the combination of the two drugs, the present invention also developed a nanoparticle delivery system (FM@NPs-BAY-876&BSO). This innovative approach significantly improves drug targeting and enables controlled release, increasing the accumulation of drugs in tumor cells, thereby enhancing the anti-tumor effect while minimizing systemic toxicity. In vivo experiments have demonstrated that this nanoparticle-based delivery system exhibits good safety while maintaining a potent anti-tumor effect. The present invention provides a promising approach for the treatment of lung adenocarcinoma by addressing tumor SLC7A11 expression heterogeneity and improving drug delivery. Although disulfidptosis has previously been identified as a cell death mechanism, the present invention provides a unique method through a novel combination therapy of two drugs, and this method may also be applicable to other cancer types with metabolic vulnerability characteristics. Brief Description of the Drawings

[0029] To more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following will briefly introduce the accompanying drawings required for use in the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0030] Figure 1 Expression levels of SLC7A11 in 33 tumor types and their corresponding normal tissues in the TCGA and GTEx databases;

[0031] Figure 2 High expression of SLC7A11 in LUAD and the results of its correlation analysis with poor prognosis; A: Volcano plot showing differentially expressed genes in LUAD, with SLC7A11 significantly upregulated; B - C: Box plots and paired analysis showing that the expression of SLC7A11 in tumor tissues is significantly higher than that in normal tissues (***p < 0.001); D - E: Kaplan - Meier survival analysis shows that the overall survival rate (D) and progression - free survival (E) of patients with high SLC7A11 expression are significantly reduced (p = 0.006 and p = 0.027);

[0032] Figure 3 Results of the correlation analysis between SLC7A11 expression and clinical parameters; A - F: Results of the correlation analysis between SLC7A11 expression and gender, age, tumor stage, T - grade, N - grade, and M - grade, respectively;

[0033] Figure 4 Results of the correlation analysis between SLC7A11 expression and clinical parameters: A: Nomogram for predicting the overall survival rate of SLC7A11 expression and clinicopathological features; B: Validation column Figure 1 Calibration curves for the accuracy of 1 - year, 3 - year, and 5 - year overall survival rates; C - D: Forest plots of univariate and multivariate Cox regression analyses, showing the prognostic significance of SLC7A11 and other clinical factors;

[0034] Figure 5 SLC7A11 - related genes and the results of their immune association analysis in LUAD; A: Circular plot showing the co - expression network of SLC7A11 and its related genes; B: KEGG pathway enrichment analysis of differentially expressed genes, with the glutathione metabolism pathway significantly enriched; C: Gene Ontology (GO) analysis showing the enrichment of biological processes and cellular components related to SLC7A11 expression;

[0035] Figure 6Results of SLC7A11-related genes and their immune associations in LUAD; A: Correlation analysis of glycolytic gene dependency scores in the DepMap database, showing a negative correlation between SLC7A11 and ALDH3A2 and SLC2A1 (GLUT1); B: Gene dependency correlation analysis confirming the relationship between SLC7A11 and SLC2A1 in LUAD; C-F: Correlation analysis of SLC7A11 expression and immune cell infiltration levels, showing a negative correlation with dendritic cells, monocytes, and T cells (C, D, E), and a positive correlation with activated NK cells (F); J: Comparison of immune cell subset infiltration levels between high and low SLC7A11 expression groups;

[0036] Figure 7 Verification of SLC7A11 expression levels and their prognostic impact in LUAD by tissue microarray analysis; A-C: Representative immunohistochemical staining images of high (A), medium (B), and low (C) H scores of SLC7A11 expression in tissue microarrays; D: Kaplan-Meier survival analysis comparing high H score group with low H score group (p<0.001); E: Stratified survival analysis comparing high, medium, and low H score groups (p<0.001); F: Box plot comparing H scores of tumor and normal tissues (***p<0.001);

[0037] Figure 8 Experimental verification that SLC7A11 overexpression exacerbates glucose deficiency-induced disulfidptosis in LUAD cells through redox imbalance; A-B: Western blot analysis of SLC7A11 expression in A549 and H1299 cells using empty vector (EV) or SLC7A11 overexpression (OE) conditions. β-tubulin was used as an internal reference; C: Representative phase contrast microscopy images of cell morphology under specified conditions;

[0038] Figure 9 Experimental verification that SLC7A11 overexpression exacerbates glucose deficiency-induced disulfidptosis in LUAD cells through redox imbalance; A-D: Flow cytometry analysis of PI-positive cell death: Flow cytometry analysis of PI-positive cell death in A549 cells (A, C) and H1299 cells (B, D) under conditions of sufficient glucose (+Glucose), glucose deficiency (-Glucose), or glucose deficiency with SLC7A11 overexpression (**P<0.01);

[0039] Figure 10 Immunofluorescence images showing F-actin (red) and nuclei (DAPI, blue) of A549 (A) and H1299 cells (B) under different conditions, scale bar: 40μm;

[0040] Figure 11 Experimental verification that SLC7A11 overexpression exacerbates glucose deprivation-induced disulfidptosis in LUAD cells through redox imbalance; A-J: Metabolic parameters of A549 cells: cystine concentration (A), cysteine concentration (B), GSH level (C), GSSG concentration (D), NADP+ / NADPH ratio (E); F-J: Metabolic parameters of H1299 cells: cystine concentration (F), cysteine concentration (G), GSH level (H), GSSG concentration (I), NADP+ / NADPH ratio (J); Data are expressed as mean ± standard deviation from three independent experiments; *P<0.05, **P<0.01, ***P<0.001, ns: no significant difference;

[0041] Figure 12 Effect of BSO in combination with glucose deprivation on SLC7A11-mediated treatment heterogeneity; A-B: Changes in cell viability (24 h) of A549 and H1299 cells with increasing BSO concentration (0-1000 μM) under glucose-sufficient conditions; C-D: Changes in cell viability of A549 and H1299 cells with BSO concentration under glucose-deprived conditions; E: Western blot analysis of differential expression of SLC7A11 in 16HBE, H1299, and A549 cells; F: Changes in cell viability of normal bronchial epithelial cells (16HBE) under glucose deprivation and 500 μM BSO treatment; G: Representative phase-contrast microscopic images of cell morphology under specified conditions;

[0042] Figure 13 Flow cytometry analysis of PI-positive cell death in A549 cells (A, C) and H1299 cells (B, D) under glucose deprivation and / or 500 μM BSO treatment;

[0043] Figure 14 Immunofluorescence images showing reorganization of F-actin (red) and nuclei (DAPI, blue) in A549 (A) and H1299 (B) cells under different treatment conditions, scale bar: 40 μm;

[0044] Figure 15Metabolic parameters of A549 and H1299 cells; metabolic parameters of A549 cells, A: cystine concentration, B: cysteine concentration, C: GSH level, D: GSSG concentration, E: NADP+ / NADPH ratio; metabolic parameters of H1299 cells: F: cystine concentration, G: cysteine concentration, H: GSH level, I: GSSG concentration, J: NADP+ / NADPH ratio; data are expressed as mean ± standard deviation, from three independent experiments, *P<0.05, **P<0.01, ***P<0.001, ns: no significant difference;

[0045] Figure 16 In vivo synergistic inhibition of LLC tumor growth by BAY-876 and BSO combination therapy; A: Representative bioluminescence images showing tumor changes in LLC tumor-bearing mice under control, BSO (450 mg / kg), BAY-876 (3 mg / kg) or combination treatment of both; B: Quantification of bioluminescence signals in each treatment group (p / s / cm 2 / sr, n = 3 - 5 mice / group); C: Body weight changes during 14-day treatment, showing no significant systemic toxicity; D: Tumor volume change curves in each treatment group; E - F: Final tumor mass (E) and representative tumor images (F) at the end of treatment; G: H&E staining of major organs (heart, liver, spleen, lung and kidney) in each treatment group, showing no obvious histopathological abnormalities, scale bar: 100 μm; H: Representative immunohistochemical images of TUNEL, Ki-67 and Cleaved Caspase3 staining in tumor sections of each treatment group, scale bar: 50 μm; data are expressed as mean ± standard deviation, *P<0.05, **P<0.01, ***P<0.001, ns: no significant difference;

[0046] Figure 17 Dynamic light scattering (DLS) analysis shows the particle size distribution of different nanoparticle preparations;

[0047] Figure 18Characteristics and targeting verification results of double-membrane encapsulated PLGA nanoparticles; A: Quantitative analysis of the particle sizes of NPs, LLCM, M2M, and FM@NPs formulations; B: Transmission electron microscope (TEM) images showing the morphological characteristics of NPs, LLCM, M2M, and FM@NPs, with enlarged area views below; C: Coomassie brilliant blue staining showing the protein profiles of M2, LLC cells, NPs, M2M, LLCM, and FM@NPs; D: Western blot analysis showing membrane-specific markers (CD68 and CD44) and cytoplasmic marker (GAPDH) in different formulations; E: Fluorescence imaging in mice showing tumor distribution at 0, 12, and 24 h after injection of different nanoparticle formulations; F: Ex vivo imaging of major organs and tumors collected 24 h after injection, showing the biodistribution of different nanoparticle formulations;

[0048] Figure 19 Enhanced therapeutic effects of BAY-876 and BSO delivered by double-membrane encapsulated PLGA nanoparticles; A: Representative bioluminescence images of tumor-bearing mice in different treatment groups (control group, BAY-876 + BSO, FM@NPs-BAY-876&BSO) (n = 3 - 5 mice / group); B: Quantification of bioluminescence signals in each treatment group (p / s / cm 2 / sr); C: Final tumor mass analysis showing significant antitumor effects in the FM@NPs-BAY-876&BSO group; D: Representative images of excised tumors in different treatment groups; E: Tumor volume change curves during 14-day interval treatment; F: Monitoring of body weights of mice in each group showing no significant systemic toxicity; G: H&E staining of major organs in each treatment group showing no obvious histopathological abnormalities, scale bar: 100 μm; H-I: Hemolysis assay results showing the blood compatibility of different formulations, with double-distilled water as the positive control and normal saline as the negative control (n = 3); J: Representative immunohistochemical images of TUNEL, Ki-67, and Cleaved Caspase3 staining in tumor sections of each treatment group, scale bar: 50 μm; Data are presented as mean ± standard deviation; *P < 0.05, **P < 0.01, ***P < 0.001, ns: no significant difference;

[0049] Figure 20 Time-dependent cytotoxicity analysis of BSO on LUAD cells under glucose-deficient conditions; A - B: Cell viability curves of A549 cells (A) and H1299 cells (B) at different time points (4 h, 8 h, 12 h, 16 h, 20 h, and 24 h) after treatment with different concentrations of BSO (0 - 10 4 μM) under glucose-deficient conditions (-Glucose); Calculate the IC 50Values; cell viability was evaluated by CCK-8 assay; data were expressed as mean ± standard deviation from three independent experiments. Detailed implementation manners

[0050] The various exemplary implementation manners of the present invention will now be described in detail. This detailed description should not be considered as a limitation of the present invention, but rather as a more detailed description of certain aspects, features, and implementation schemes of the present invention.

[0051] It should be understood that the terms used in the present invention are only for describing specific implementation manners and are not intended to limit the present invention. Additionally, for the numerical ranges in the present invention, it should be understood that each intermediate value between the upper and lower limits of the range is also specifically disclosed. Any intermediate value within any stated value or stated range, as well as each smaller range between any other stated value or intermediate value within the stated range, is also included in the present invention. The upper and lower limits of these smaller ranges may be independently included or excluded from the range.

[0052] Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the present invention pertains. Although the present invention only describes preferred methods and materials, any methods and materials similar or equivalent to those described herein may also be used in the implementation or testing of the present invention. All documents mentioned in this specification are incorporated by reference to disclose and describe the methods and / or materials related to the said documents. In case of conflict with any incorporated document, the content of this specification shall prevail.

[0053] Without departing from the scope or spirit of the present invention, various improvements and variations can be made to the specific implementation manners of the present invention specification, which are obvious to those skilled in the art. Other implementation manners obtained from the present invention specification are obvious to those skilled in the art. The present invention specification and examples are only exemplary.

[0054] Regarding "comprising", "including", "having", "containing", etc. used herein, they are all open-ended terms, meaning including but not limited to.

[0055] After validating the target through bioinformatics and tissue chip analysis, the present invention demonstrated the enhanced anti-tumor effect of BAY-876 / BSO combination therapy in cell and animal models. Subsequently, a double-membrane-coated PLGA nanoplatform was developed to achieve homologous targeted delivery. Specifically, by integrating M2-type macrophage membranes and LLC tumor cell membranes, precise delivery of the BAY-876 / BSO combination was achieved. This treatment strategy disrupts cellular redox homeostasis by simultaneously inhibiting glucose uptake and glutathione synthesis, thereby inducing disulfidptosis through F-actin cytoskeleton reorganization.

[0056] The above technical solutions and technical effects will be further described below with specific embodiments.

[0057] Example 1

[0058] 1. Experimental methods

[0059] 1.1 Data acquisition and preprocessing

[0060] The normalized gene expression data and corresponding clinical information of all cancer and normal tissues were downloaded from the public databases TCGA (The Cancer Genome Atlas) and GTEx (Genotype-Tissue Expression) through the UCSC Xena platform (https: / / xenabrowser.net / datapages / ). Patients with incomplete survival information were excluded, and the data were integrated for downstream analysis.

[0061] 1.2 Differential expression analysis and generation of volcano plots

[0062] The expression of SLC7A11 between tumor tissues and adjacent normal tissues of various cancer types was analyzed using the R package limma. A specific comparison (logFC < 1) was made for the expression levels of SLC7A11 between lung adenocarcinoma (LUAD) and normal lung tissues. The ggplot2 package was used to generate volcano plots to visualize the log2 fold change (log2FC) and statistical significance (-log10 adjusted p-value) of differentially expressed genes. Genes with an adjusted p-value < 0.05 were considered to be statistically significant.

[0063] 1.3 Survival analysis

[0064] Kaplan-Meier survival analysis was performed to evaluate the overall survival (OS) and progression-free survival (PFS) of patients with high and low expression of SLC7A11. Patients were divided into high-expression and low-expression groups based on the median of the expression values. The survival curves were compared using the log-rank test and were generated using the R packages survival and survminer.

[0065] 1.4 Prognostic analysis and model construction

[0066] A prognostic nomogram incorporating important clinical variables and SLC7A11 expression levels was constructed using the 'rms' R package to predict 1-year, 3-year, and 5-year overall survival. The predictive accuracy of the nomogram was evaluated using calibration curves, which compare predicted survival probabilities with observed survival rates. In addition, univariate and multivariate Cox proportional hazards regression models were constructed to determine whether SLC7A11 expression is an independent prognostic factor in LUAD patients. Covariates included age, gender, pathological stage, and SLC7A11 expression levels. Hazard ratios (HRs) and their 95% confidence intervals (CIs) were calculated to quantify the prognostic impact of SLC7A11. Variables with p < 0.05 in univariate analysis were included in the multivariate model. Forest plots were generated using the forestplot R package.

[0067] 1.5 Co-expression, correlation, dependence, and functional enrichment analysis

[0068] Co-expression analysis was performed to identify genes significantly associated with SLC7A11 expression. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the clusterProfiler R package. The relationship between SLC7A11 expression and glycolysis gene dependency scores obtained from the Cancer Dependency Map (DepMap) database was evaluated using Spearman correlation analysis. Scatter plots were generated to visualize the results, and p < 0.05 was defined as statistically significant.

[0069] 1.6 Immune correlation analysis

[0070] Pearson correlation coefficients were calculated to analyze the relationships between immune cell subtypes. The CIBERSORT algorithm was used to quantify immune cell infiltration levels. The relationship between SLC7A11 expression levels and known immune checkpoints was analyzed to investigate its role in potential immune escape mechanisms in LUAD.

[0071] 1.7 Analysis of clinical samples using tissue microarrays

[0072] A retrospective study was conducted on tumor and paired adjacent normal tissues from 163 LUAD patients who underwent surgical resection at the Affiliated Hospital of Nantong University between January 2010 and June 2017 to construct tissue microarrays (TMAs). TMAs were constructed by taking 2-mm diameter core biopsies from representative tumor regions of formalin-fixed paraffin-embedded (FFPE) tissue blocks. Clinical characteristics, including age, gender, degree of differentiation, and pathological TNM stage, were extracted from medical records.

[0073] The expression of SLC7A11 was evaluated by immunohistochemistry (IHC) staining. Briefly, TMA sections were dewaxed, hydrated, and antigen retrieval was performed using citrate buffer (pH 6.0). After blocking endogenous peroxidase activity with 3% hydrogen peroxide, the sections were incubated overnight at 4 °C with rabbit anti-SLC7A11 primary antibody (1:200, Proteintech, 26864-1-AP), followed by incubation with a universal secondary antibody (1:500, Proteintech, PK10006). Antigen detection was performed using DAB substrate. Digital images were captured using a slide scanner (NDP C9600-01, HAMAMATSU).

[0074] The expression of SLC7A11 was quantified using the H-score system, and the calculation formula is:

[0075] H-score = Σ (percentage of cells × intensity score);

[0076] Among them, the staining intensity was graded as 0 (negative), 1+ (weak), 2+ (moderate), or 3+ (strong). The final score ranged from 0 to 300 and was independently evaluated by two pathologists. The chi-square test was used to analyze the association between the expression level of SLC7A11 and clinical parameters.

[0077] This research protocol was approved by the Ethics Committee of the Affiliated Hospital of Nantong University, and all participants signed informed consent forms.

[0078] 1.8 Cell culture

[0079] All cell lines were confirmed to be free of mycoplasma contamination. Human lung adenocarcinoma cell lines (A549 and H1299, characterized by medium-high and low basal SLC7A11 expression, respectively) and normal bronchial epithelial cell line (16HBE) were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin at 37 °C in a humidified incubator with 5% CO 2 2. Mouse lung cancer cell line LLC and mouse macrophage cell line RAW264.7 were cultured in DMEM containing 10% FBS under the same conditions. For the glucose deprivation experiment, cells were cultured in glucose-free DMEM (Servicebio, G4583) supplemented with dialyzed FBS (ThermoFisher, A3160901). To simulate additional metabolic stress, cells were treated with or without different concentrations of BSO (0 - 1000 μM) (Aladdin, B30577).

[0080] 1.9 Lentivirus-mediated overexpression of SLC7A11

[0081] The full-length coding sequence of SLC7A11 (NM_014331) was cloned into the pcDNA3.1 expression vector (GenePharma, Shanghai, China), and the empty vector was used as a negative control. The pcDNA3.1-SLC7A11 plasmid and the helper plasmids (psPAX2 and pMD2.G) were co-transfected into HEK293T cells using Lipofectamine 3000 transfection reagent (Invitrogen, L3000001) to produce lentiviral particles.

[0082] A549 and H1299 cells were seeded into 6-well plates at a confluence of 30 - 50% and infected with lentiviral particles in the presence of 8 μg / mL polybrene (Sigma-Aldrich, B305771). After 24 h, the medium was replaced with fresh complete medium, and after 48 h, 2 μg / mL puromycin was added for screening. A stable cell line was established during the 7 - 10-day screening period, during which the medium was changed every 2 - 3 days to eliminate uninfected cells. Overexpression of SLC7A11 was confirmed by Western blot analysis, and then stable SLC7A11-overexpressing cells were used to evaluate cell viability and cell death under various experimental conditions (including glucose deprivation).

[0083] 1.10 Cell Death and Viability Assays

[0084] Cell death and viability of cells with different SLC7A11 expression levels were evaluated under glucose deprivation and / or BSO treatment.

[0085] For cell death assays, cells were seeded into 24-well plates one day before treatment. After an appropriate treatment time, cells were digested with trypsin, collected, and washed once with PBS. Then the cells were resuspended in cold PBS containing 1 μg / mL propidium iodide (PI) (Elabscience, E-CK-A211). The proportion of PI-positive cells was analyzed using a flow cytometer (AttuneNxT, Invitrogen), indicating cell death.

[0086] For cell viability assays, cells were seeded into 96-well plates at a density of 5000 cells per well. After treatment with different concentrations of BSO (0 - 1000 μM) and / or glucose deprivation for a specified time, 90 μL of medium and 10 μL of 10× Cell Counting Kit-8 (CCK-8) solution (Vazyme, Nanjing, China) were added to each well. The plate was incubated at 37 °C for 1 h, and the absorbance was measured at 450 nm using a microplate reader (SpectraMaxM5, Sunnyvale, CA, USA).

[0087]

[0088] For immunofluorescence staining, after washing twice with PBS, cells were fixed with 3.7% formaldehyde in PBS at room temperature. The fixed cells were permeabilized by washing with PBS containing 0.1% Triton X-100 for 2 - 4 cycles of 5 minutes each. To visualize the actin cytoskeleton, Actin-Tracker Red (Beyotime, C2207S) was diluted 1:100 in PBS containing 1 - 5% BSA and 0.1% Triton X-100, and the staining solution was added to the wells. Cells were incubated at room temperature in the dark for 30 - 60 min, followed by washing 2 - 4 times with PBS containing 0.1% Triton X-100 for 5 min each. The nuclei were counterstained with a mounting medium containing DAPI (Beyotime, C1005). Fluorescent images were captured using a confocal microscope (Observer7, Zeiss) with appropriate filter settings.

[0089] 1.11 Metabolite and Cystine Uptake Assays

[0090] The following methods were used to measure cellular metabolite levels under glucose deprivation and / or BSO treatment:

[0091] (1) NADP+ / NADPH quantification: Using an NADP+ / NADPH colorimetric assay kit (Elabscience, E-BC-K803-M), NADPH and total NADP+ / NADPH levels were detected by a WST-8-dependent colorimetric reaction, and the absorbance was measured at 450 nm;

[0092] (2) GSH and GSSG quantification: Using a colorimetric assay kit (Elabscience, E-BC-K097-M), total glutathione (T-GSH) and oxidized glutathione (GSSG) were quantified based on the DTNB and glutathione reductase reaction, and the absorbance was measured at 412 nm. The GSH level was calculated as GSH = T-GSH - 2×GSSG;

[0093] (3) Cysteine quantification: Using a colorimetric assay kit (Elabscience, E-BC-K352-M), based on the principle of the reduction of phosphotungstic acid to tungsten blue, the absorbance was measured at 600 nm;

[0094] (4) Cystine uptake assay: Using a fluorescence assay kit (Elabscience, E-BC-F066), the cellular cystine uptake ability was evaluated by detecting the fluorescence intensity of the absorbed cystine analog.

[0095] All assays were performed according to the manufacturer's instructions. The results were normalized to the total protein content and expressed as fold change relative to the control group. Each experiment was repeated three times.

[0096] 1.12 Western blotting analysis

[0097] Protein samples were extracted from cells or cell membranes using RIPA lysis buffer supplemented with protease and phosphatase inhibitors. Protein concentration was determined using a BCA protein assay kit. Equal amounts of protein (20 μg) were separated by SDS-PAGE gel electrophoresis. The proteins were transferred onto PVDF membranes and blocked with 5% non-fat milk in TBST at room temperature for 1 h. The membranes were incubated with specific primary antibodies overnight at 4 °C, including SLC7A11 (1:1000; Proteintech, 26864-1-AP), β-Tubulin (1:1000; Cell Signaling Technology, 2146s), CD44 (1:5000; Proteintech, 60224-1-Ig), CD68 (1:1000; Proteintech, 28058-1-AP), and GAPDH (1:100000; Proteintech, 60004-1-Ig). After incubation with the primary antibodies, the membranes were incubated with HRP-conjugated secondary antibody (mouse anti-IgG, 1:10000; Rockland, Gilbertsville, PA, USA) or IRDye800-conjugated secondary antibody (anti-rabbit / mouse IgG, 1:10000; Rockland, Gilbertsville, PA, USA) at room temperature for 2 h. For visualization and quantification, the membranes were processed using enhanced chemiluminescence (ECL) reagents and a gel imaging system (GelDoc Go, USA) or an Odyssey infrared imaging system (LI-COR, Lincoln, NE, USA).

[0098] 1.13 Xenograft experiment

[0099] The experimental protocol was approved by the Animal Protection and Use Committee of Nantong University.

[0100] Five-week-old ICR healthy mice were purchased from the Animal Center of Nantong University and housed under specific pathogen-free (SPF) conditions with a 12-h light / dark cycle. The environmental temperature and humidity were maintained at 21 - 23 °C and 45%, respectively. Food and water were provided ad libitum. LLC mouse lung adenocarcinoma cells were resuspended in DMEM containing 10% fetal bovine serum (FBS) and subcutaneously injected into the right thigh of each mouse at a dose of 1×10 8 cells per mouse. When the tumor volume reached 50 - 100 mm 3At that time, the mice were randomly grouped, with 3 - 5 mice in each group. In the combination treatment group, the mice were intraperitoneally injected with 3 mg / kg BAY - 876 (MedChemExpress, 1799753 - 84 - 6) and 450 mg / kg BSO (Aladdin, B30577) daily, dissolved in a mixture of 100 μL of 40% DMSO, 20% PEG300 (MedChemExpress, 25322 - 68 - 3), and 40% normal saline. In the single - drug treatment group, the mice were injected with 3 mg / kg BAY - 876 or 450 mg / kg BSO respectively, using the same solvent composition. The control group was intraperitoneally injected with 100 μL of DMSO - normal saline mixture daily. For the FM@NPs - BAY - 876&BSO group, the mice received the same doses of BAY - 876 and BSO as the combination treatment group (calculated according to the encapsulation efficiency), administered by tail vein injection.

[0101] Approved according to the institutional ethics guidelines, the maximum allowable tumor burden length limit was 1.5 cm. At the experimental endpoint, each mouse was intraperitoneally injected with D - luciferin substrate (MedChemExpress, 2591 - 17 - 5), and bioluminescence imaging was performed using a Tanon ABL X5 imaging system (Tanon, Shanghai, China) 10 min later.

[0102] 1.14 Histological and immunohistochemical analysis

[0103] Normal tissue specimens were fixed, paraffin - embedded, and sectioned with a thickness of 4 - 6 μm. The sections were dewaxed with xylene and rehydrated through gradient ethanol (100%, 95%, 70%). Hematoxylin (YEASEN, 60524ES60) staining was performed. The sections were immersed in hematoxylin solution for 3 - 5 min, followed by rinsing with tap water for 1 - 2 min. Differentiation was carried out using 0.3% acidic ethanol, and after washing again, 1% ammonia water treatment was used to restore clear blue nuclear staining. After rinsing, eosin staining was performed for 1 - 3 min, and rinsing was carried out again to remove excess dye. The sections were dehydrated through gradient ethanol, cleared with xylene, and mounted with neutral gum. The stained sections were observed under an optical microscope to evaluate nuclear (blue) and cytoplasmic (pink) staining.

[0104] The methods for fixation, paraffin embedding, and sectioning of tumor tissue specimens were the same as those of normal tissues. The sections were dewaxed and rehydrated through the same gradient ethanol process, and then antigen retrieval was performed using citrate buffer (pH 6.0) in a pressure cooker. Endogenous peroxidase activity was blocked with 3% hydrogen peroxide, and the sections were incubated with 5% bovine serum albumin (BSA) to reduce non-specific binding. For TUNEL (pricella, P-CA-007) staining, the TdT working solution was used according to the manufacturer's instructions, and then incubated with streptavidin-HRP solution and DAB substrate for colorimetric detection. For Ki-67 (1:1000; Cell Signaling Technology, 9449s) and Cleaved Caspase-3 (1:500; Cell Signaling Technology, 9661s) staining, the sections were incubated with specific primary antibodies overnight at 4°C. The secondary antibody incubation was carried out at room temperature for 30 min, and colorimetric detection was performed using DAB substrate. The sections were counterstained with hematoxylin, dehydrated, cleared, and mounted. The stained sections were imaged using a microscope (Olympus BX43).

[0105] 1.15 Nanoparticle preparation

[0106] Nanoparticle preparation method: The nanoparticles encapsulating BAY-876 and BSO were prepared using the double emulsion solvent evaporation method. The specific operations were as follows: BAY-876-loaded nanoparticles: 10 mg of BAY-876 was dissolved in 200 μL of DMSO, then mixed with 1 mL of poly(lactic-co-glycolic acid) (PLGA) dichloromethane solution (100 mg of PLGA dissolved in 1 mL of dichloromethane), added to 3 mL of 7% (w / v) polyvinyl alcohol (PVA) solution for ultrasonic emulsification, and further emulsified again in 50 mL of 1% (w / v) PVA solution to obtain BAY-876-loaded nanoparticles. BSO-loaded nanoparticles: First, 10 mg of BSO was dissolved in 100 μL of deionized water. Then, it was emulsified with 2 mL of PLGA dichloromethane solution (40 mg of PLGA dissolved in 2 mL of dichloromethane) under ultrasonic conditions to form a primary emulsion. The primary emulsion was dropped into 10 mL of 2% (w / v) PVA solution under continuous ultrasonic conditions to form a secondary emulsion, obtaining BSO-loaded nanosphere particles. The above nanoparticle solution was stirred at room temperature to fully volatilize the organic solvent. The nanoparticles were collected by centrifugation at 15,000×g for 10 minutes, washed three times with deionized water to remove unencapsulated drugs, freeze-dried, and stored at -20°C. For the preparation of fluorescently labeled nanoparticles (NPs-DiR) for targeting research, similar to the preparation method of BAY-876-loaded nanoparticles, the DiR solution (Sigma, USA) was added to the PLGA dichloromethane solution in advance to prepare DiR-labeled nanoparticles.

[0107] The encapsulation efficiency of BAY-876 and BSO was determined by using high-performance liquid chromatography (HPLC) to quantify the unencapsulated drug in the supernatant collected during the nanoparticle preparation process. Standard calibration curves were established for each drug to calculate its concentration. The encapsulation efficiency was calculated using the following formula:

[0108]

[0109] The encapsulation efficiencies of PLGA@NPs-BAY-876 and PLGA@NPs-BSO were 79.9% and 75.5%, respectively. Each experiment was repeated three times, and the results were expressed as the mean ± standard deviation.

[0110] 1.16 Preparation of LLC and M2 macrophage membranes (LLCM and M2M)

[0111] M2 macrophage membranes (M2M) were prepared by polarizing M0 macrophages (RAW264.7 cells) to the M2 phenotype using interleukin 4 (IL4) at 20 ng / ml for 24 h. LLC cells and M2 macrophages were suspended in a homogenization buffer containing 20 mM Tris-HCl (pH 7.5), 10 mM KCl, 75 mM sucrose, 2 mM MgCl 2 and a protease / phosphatase inhibitor tablet. The suspension was homogenized using a JY92-II N homogenizer (75 W) and centrifuged at 3000×g for 10 min at 4 °C. The supernatant was collected and centrifuged again at 10,000×g for 30 min at 4 °C to obtain a membrane-rich suspension. Serum exosome extraction reagent (VEX Exosome Isolation Reagent (from serum)) was added to the suspension at a ratio of 3:1, incubated for 24 h, and centrifuged at 10,000×g for 1 h at 4 °C. The collected membranes were quantified for protein using a BCA protein assay kit and stored in water at 4 °C for later use.

[0112] 1.17 Preparation and characterization of FM@NPs

[0113] FM@NPs were prepared by sequentially incorporating LLCM, M2M, and PLGA nanoparticles (NPs) with a weight ratio of film to particles of 1:1:2 (LLCM:M2M:NPs). The mixture was extruded through 400 nm and 200 nm polycarbonate porous membranes 15 times using a mini-extruder (Avanti Polar Lipids). The morphologies of NPs, LLCM, M2M, and FM@NPs were characterized using a scanning electron microscope (SEM, S-3400N, Hitachi, Japan). The particle sizes of NPs, LLCM, M2M, and FM@NPs were measured by dynamic light scattering (DLS) using a Mastersizer 3000 laser particle size analyzer (Malvern Instruments Ltd., Malvern, UK).

[0114] 1.18 In vivo tumor targeting evaluation

[0115] To evaluate the tumor targeting ability of the FM@NPs delivery system, LLC cells (1×10 6 cells / 100 μL PBS) were subcutaneously injected into the right flank of mice. When the tumor volume reached approximately 100 - 200 mm 3 , the mice were randomly divided into the FM@NPs-Dir and NPs-Dir groups (n = 3 per group). Dir was loaded into the nanoparticles at a concentration of 0.2% w / w, and 200 μL of FM@NPs-Dir or NPs-Dir was administered to the mice via tail vein injection. Bioluminescence imaging was performed at 0, 12, and 24 h after injection using a Tanon ABL X5 imaging system (Tanon, Shanghai, China). The imaging parameters were set as follows: exposure time 1 s, binning factor 4, and field of view 12.5 cm. The fluorescence intensity was quantified using the manufacturer's software and expressed as photons per square millimeter per second (PPP ms -1 ). After the final imaging at 24 h, the mice were sacrificed by carbon dioxide inhalation. The major organs (heart, liver, spleen, lung, and kidney) and tumors were harvested for ex vivo imaging to evaluate tissue distribution. Tissue-specific accumulation was quantified by measuring the fluorescence intensity and normalizing it according to tissue weight.

[0116] 1.19 Hemolysis test

[0117] Blood compatibility was evaluated by hemolysis assay. Fresh blood was collected from healthy ICR mice, and red blood cells (RBCs) were separated by centrifugation at 1500 rpm for 10 min. The RBCs were washed with PBS until the supernatant became colorless and then diluted with PBS. The experimental groups (NPs-BAY-876&BSO, FM@NPs-BAY-876&BSO) were incubated with the RBC suspension at 37 °C for 2 h. Normal saline and double-distilled water were used as negative (0% hemolysis) and positive controls (100% hemolysis), respectively. After centrifugation, the supernatant was collected and the absorbance was measured at 540 nm. The hemolysis rate was calculated as follows:

[0118]

[0119] 1.20 Statistical analysis

[0120] All bioinformatics analyses were performed using R software (version 4.3.0), while the experimental data were analyzed using GraphPad Prism 9. The Wilcoxon rank-sum test and Kruskal-Wallis test (as applicable) were used to determine statistical significance. Correlation analysis was performed using the Pearson correlation coefficient. The paired t-test was used to compare SLC7A11 expression between tumors and matched normal tissues. The chi-square test was used to analyze the association between SLC7A11 expression and clinical characteristics. Kaplan-Meier curves were analyzed using the log-rank test, and a p-value < 0.05 was considered statistically significant. All experiments were independently repeated at least three times, and the data were expressed as the mean ± standard deviation (SD).

[0121] 2. Experimental results and analysis

[0122] 2.1 SLC7A11 is highly expressed in LUAD and is associated with poor prognosis

[0123] This invention integrated high-throughput data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases and evaluated the expression of SLC7A11 in 33 tumor types. The analysis showed that SLC7A11 was overexpressed in multiple tumor types, including LUAD (lung adenocarcinoma), LUSC (lung squamous cell carcinoma), and BRCA (breast invasive carcinoma). In contrast, SLC7A11 expression was lower in the corresponding normal tissues ( Figure 1 ). Subsequently, volcano plot analysis verified the overexpression of SLC7A11 in LUAD ( Figure 2 A), and differential analysis and paired differential analysis also consistently confirmed its elevated expression level ( Figure 2 B, C). Kaplan-Meier survival analysis showed that patients with elevated SLC7A11 expression had shorter overall survival (OS) and progression-free survival (PFS).Figure 2 In D and E), it shows that there is a strong correlation between the elevated expression of SLC7A11 and poor prognosis.

[0124] Next, the relationship between SLC7A11 expression and clinical characteristics was investigated. Higher SLC7A11 expression was observed in male patients (p = 0.0004), while there was no significant correlation with age, tumor stage, primary tumor size, lymph node involvement, or distant metastasis ( Figure 3 In A - F). The nomogram prediction model based on clinical data showed that the total nomogram score was negatively correlated with the 1-year, 3-year, and 5-year survival probabilities ( Figure 4 In A). The calibration of the nomogram prediction with the observed OS rate ( Figure 4 In B) showed high prediction accuracy, especially for the 1-year (0.97) and 3-year (0.883) survival rates. In addition, Cox regression analysis further supported the prognostic significance of SLC7A11 ( Figure 4 In C and D), highlighting its potential as a prognostic biomarker.

[0125] In summary, the research results of the present invention show that SLC7A11 is overexpressed in LUAD and is closely related to poor prognosis, highlighting its potential as a therapeutic target for LUAD.

[0126] 2.2 Analysis of SLC7A11-related genes and immune correlation in LUAD

[0127] To understand the interaction between genes, co-expression analysis of the SLC7A11 gene was performed. The analysis found that SLC7A11 was positively correlated with NMRAL2P, AKR1C2, TRIM16L, CYP4F3, TXNRD1, and SRXN1, indicating its role in cell metabolism, redox balance, and stress response ( Figure 5 In A).

[0128] Next, the present invention performed enrichment analysis on the high-expression and low-expression groups of SLC7A11. Specifically, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis showed that the differentially expressed genes were enriched in pathways such as glutathione (GSH) metabolism. In addition, Gene Ontology (GO) analysis revealed enrichment in cell metabolic processes, redox processes, and stress responses, further supporting the connection between SLC7A11 and cell metabolism ( Figure 5 In B and C).

[0129] In addition, since cancer cells adapt to the highly oxidative environment through metabolic reprogramming, including increased glucose uptake and enhanced cystine import (by upregulating SLC7A11 expression), the present invention performed a gene effect score (CERES) correlation analysis of glycolytic genes using DepMap data. The results showed that SLC7A11 was negatively correlated with ALDH3A2 and SLC2A1 (GLUT1) Figure 6 in A). ALDH3A2 is an aldehyde dehydrogenase involved in oxidative stress and metabolic processes, while SLC2A1 is a glucose transporter closely related to glucose uptake. Subsequent gene-dependency correlation analysis further confirmed the close relationship between SLC7A11 and SLC2A1 in LUAD Figure 6 in B).

[0130] The present invention also comprehensively analyzed the relationship between the expression level of SLC7A11 and the tumor immune microenvironment in LUAD. It was found that the expression of SLC7A11 was negatively correlated with the infiltration levels of monocytes, dendritic cells, and regulatory T cells (Tregs) Figure 6 in C, D, E), while it was positively correlated with activated NK cells Figure 6 in F). Although the correlation coefficient (R value) was low, these relationships were statistically significant, possibly indicating a complex interaction between SLC7A11 expression and the infiltration of various immune cells. Similarly, the comparison of immune cell subset infiltration between the high-expression and low-expression groups of SLC7A11 showed a weak but consistent correlation between SLC7A11 expression and immune cell infiltration Figure 6 in G).

[0131] Based on these analyses, the present invention suggests that treatment strategies targeting SLC7A11 should mainly focus on cell metabolism, particularly the glucose metabolic pathway and the glutathione (GSH) metabolic pathway. Considering the weak correlation between SLC7A11 expression and immune cell infiltration, immunotherapy may have a poor effect on treating LUAD with high SLC7A11 expression.

[0132] 2.3 Verification of the expression level of SLC7A11 in LUAD and its prognostic impact by tissue microarray analysis

[0133] To verify the expression level of SLC7A11, the present invention used a tissue microarray (TMA) containing tumor and adjacent normal tissues from 163 LUAD patients in the Affiliated Hospital of Nantong University. Immunohistochemistry (IHC) staining was performed, and the expression was classified into low Figure 7 in A), medium Figure 7 in B), and high Figure 7 in C) H-scores according to the staining intensity and the proportion of positive cells.

[0134] Kaplan-Meier survival analysis showed that the overall survival of patients with high SLC7A11 expression was significantly shorter than that of patients with low expression ( Figure 7 in D, p < 0.001). Stratification analysis further indicated that as the SLC7A11 expression level increased, the survival rate showed a downward trend ( Figure 7 in E). In addition, compared with adjacent normal tissues, the expression of SLC7A11 was significantly elevated in tumor tissues ( Figure 7 in F). These findings suggest that SLC7A11 may serve as an important prognostic marker in LUAD.

[0135] To further explore the association between SLC7A11 expression and clinicopathological features, the present invention performed chi-square tests on various clinical categories. The analysis showed a significant correlation between SLC7A11 expression and both tumor T stage and N stage (Table 1). Specifically, high SLC7A11 expression was mainly observed in the T1-T2 stage (p = 0.0189), and increased expression was detected in patients at the N0 stage (p = 1.86e-08). In addition, high SLC7A11 expression was mainly seen in LUAD patients at stage I-II, while it was less common in stage III-IV diseases (p = 0.000228). These results indicate that SLC7A11 expression is closely associated with early tumor stages (T1-T2 and N0), highlighting its potential role in the early progression of LUAD.

[0136] Table 1 Analysis of the association between SLC7A11 protein expression and clinicopathological parameters of 163 patients with lung adenocarcinoma

[0137]

[0138] 2.4 Overexpression of SLC7A11 exacerbates glucose deprivation-induced disulfidptosis related to redox dysregulation in LUAD cells

[0139] Based on the metabolic vulnerability caused by metabolic reprogramming, cell death induced by high SLC7A11 expression under glucose deprivation conditions was identified as a unique form of cell death called disulfidptosis. The present invention verified this phenomenon using cell lines with different SLC7A11 expression levels. In A549 cells, overexpression of SLC7A11 significantly increased its expression level ( Figure 8 in A-B). When exposed to glucose deprivation conditions, A549 cells overexpressing SLC7A11 showed a significant increase in cell death rate ( Figure 8 in C and Figure 9 in C), accompanied by obvious morphological changes, including cell shrinkage and F-actin contraction ( Figure 10In contrast, H1299 cells, characterized by low basal SLC7A11 expression, exhibited enhanced adaptation to glucose deprivation and maintained redox homeostasis. However, once SLC7A11 was overexpressed, glucose-deprived H1299 cells showed a death pattern similar to that of A549 cells ( Figure 8 in C, Figure 9 in B and D, Figure 10 in B).

[0140] Subsequently, key biochemical markers of the two cell lines after these interventions were analyzed. In A549 cells, glucose deprivation induced the accumulation of cystine and cysteine, and SLC7A11 overexpression further increased the levels of cystine and cysteine ( Figure 11 in A, B). The synchronous depletion of the GSH pool and the increase in the NADP+ / NADPH ratio indicated an increased use of NADPH for cystine reduction ( Figure 11 in C-E). H1299 cells showed minimal perturbation of cystine and cysteine levels under glucose deprivation, which was consistent with their lower baseline concentrations. However, SLC7A11 overexpression led to significant alterations in all measured metabolic parameters, including increased levels of cystine, cysteine, and the NADP+ / NADPH ratio ( Figure 11 in F-J).

[0141] In summary, the present invention confirmed that high SLC7A11 expression induces disulfidptosis under glucose deprivation conditions. The metabolic analysis of the present invention revealed two important observations regarding the cellular redox state: the known NADPH consumption during cystine reduction and, notably, the severe depletion of the GSH pool. While NADPH depletion is a known pathway leading to disulfidptosis, the findings of the present invention suggest that GSH depletion may also contribute to severe redox imbalance in these cells. These observations raise an interesting possibility that disulfidptosis may result from the complex interplay of multiple redox perturbations, with both NADPH and GSH potentially playing a role.

[0142] 2.5 BSO synergizes with glucose deprivation to overcome SLC7A11-mediated treatment heterogeneity

[0143] Although previous TCGA analyses showed widespread overexpression of SLC7A11 in LUAD, both local tissue microarray (TMA) data and cell experiments revealed significant heterogeneity in tumor SLC7A11 expression levels. As shown in Table 1, most LUAD cases exhibited moderate to high SLC7A11 expression, while a few showed low expression. This molecular heterogeneity led to differences in treatment responses, and efficacy differences were also observed even in tumors with elevated SLC7A11 expression. Based on the findings of the present invention that both NADPH consumption and GSH depletion promote disulfidptosis, it was hypothesized that pharmacological targeting of GSH synthesis might enhance the therapeutic effect of glucose deprivation-induced disulfidptosis. This combined strategy might overcome the treatment variability associated with different SLC7A11 expression levels in tumor cells.

[0144] To test this hypothesis, the present invention examined the effect of BSO on the viability of A549 and H1299 cells under various conditions. Under glucose-sufficient conditions (+Glucose), treatment with BSO alone had little effect on cell viability ( Figure 12 in A, B). However, under glucose-deprived (-Glucose) conditions, as the concentration of BSO increased (0 - 1000 μM), cell viability decreased in a dose-dependent manner, which was more significant in A549 cells, while H1299 cells showed initial resistance followed by a sharp decline in cell viability over time ( Figure 12 in C, D). Based on these cell viability curves, the optimal BSO concentration was selected for subsequent experiments ( Figure 20 in A, B). In addition, the combination of BSO and glucose deprivation showed little cytotoxicity to normal bronchial epithelial cells (16HBE) ( Figure 12 in E, F).

[0145] In subsequent experiments, the combination of BSO and glucose deprivation induced a greater degree of cell death in A549 and H1299 cells compared to individual interventions ( Figure 12 in G). Notably, in A549 cells, the cell death induced by this combination was more significant than glucose deprivation alone under SLC7A11 overexpression conditions, while in H1299 cells, the combined treatment achieved a cell death level comparable to glucose deprivation under SLC7A11 overexpression conditions ( Figure 13 in A - D). In addition, under combined treatment, cells showed more obvious shrinkage and F-actin condensation ( Figure 14 in A, B).

[0146] Metabolomic analysis revealed that, compared to glucose deprivation alone, the combined treatment significantly increased the levels of cystine and cysteine in A549 cells ( Figure 15In A and B), which are comparable to the levels observed under glucose deprivation in the context of SLC7A11 overexpression, the GSH, GSSG, and NADP+ / NADPH ratios also changed accordingly ( Figure 15 In C - E). In contrast, H1299 cells showed lower cystine and cysteine accumulation under combination treatment compared to glucose deprivation in the context of SLC7A11 overexpression ( Figure 15 In F and G), but exhibited more significant GSH depletion, while the change in NADP+ / NADPH was less obvious than expected ( Figure 15 In H - J).

[0147] Collectively, these findings indicate that BSO enhances disulfidptosis under glucose deprivation by inhibiting GSH synthesis and exacerbating disulfide stress, thereby improving the therapeutic effect. The differential responses between A549 (medium - high SLC7A11 expression) and H1299 (low SLC7A11 expression) cells highlight the versatility of this combination therapy: it achieves better efficacy in medium - high SLC7A11 - expressing cells while maintaining an effect comparable to SLC7A11 overexpression in low - expressing cells, thus demonstrating good therapeutic potential in tumor subsets with different SLC7A11 expression levels.

[0148] 2.6 BAY - 876 and BSO combination therapy synergistically inhibits LLC tumor growth in vivo

[0149] To evaluate the therapeutic potential of the combination therapy in vivo, the present invention established a pre - clinical LLC xenograft model. After tumor formation, the mice were randomly divided into four groups: control group, BSO alone group, BAY - 876 alone group, and BAY - 876 and BSO combination group. Bioluminescence imaging showed that the tumors in the control group continued to grow, while the combination therapy led to significant growth inhibition ( Figure 16 In A and B). During the 14 - day treatment period, all groups maintained stable body weights, indicating less systemic toxicity caused by the treatment ( Figure 16 In C).

[0150] Quantitative analysis of tumor progression showed that BAY - 876 monotherapy could moderately delay tumor growth, the anti - tumor effect of BSO alone was weak, while the combination of the two drugs significantly inhibited tumor growth ( Figure 16 In D). The tumor mass at endpoint analysis further confirmed this observation, with the combination - therapy group having the lowest tumor weight ( Figure 16 In E and F). Histological examination of major organs (heart, liver, spleen, lung, and kidney) showed no obvious toxicity in all treatment groups, supporting the safety of this combination approach ( Figure 16 In G).

[0151] To elucidate the mechanism of the enhanced antitumor effect, immunohistochemical (IHC) analysis was performed. The results showed an increase in TUNEL-positive cells and a decrease in Ki-67 expression in the combination group, indicating enhanced cell death and reduced proliferation, respectively. Notably, comparable Cleaved Caspase-3 levels among the groups suggested that the observed cell death was mainly mediated by disulfidptosis rather than apoptosis ( Figure 16 in H). These findings together demonstrated that the combination of BAY-876 and BSO exhibited a synergistic antitumor effect in vivo while maintaining good safety.

[0152] 2.7 Characterization and targeting verification of double-membrane-coated PLGA nanoparticles

[0153] Although the combination therapy of BAY-876 and BSO demonstrated a synergistic antitumor effect, several limiting factors were found in its practical application. Glucose transporter inhibitors lack tumor targeting when administered systemically, which can interfere with the normal metabolism of important organs. In addition, its therapeutic window is narrow (i.e., the effective dose is close to the toxic dose), which may pose safety problems especially during long-term use. Moreover, BSO exhibits unfavorable pharmacokinetic properties, including rapid clearance and limited tumor accumulation, requiring long-term exposure to achieve the best therapeutic effect and potentially generating synergistic toxicity when combined with other chemotherapeutic drugs. These therapeutic limitations require the development of targeted delivery strategies to improve drug bioavailability and minimize off-target effects.

[0154] Drug delivery systems based on nanocarriers have emerged as a promising approach to overcome these limitations by improving pharmacokinetics, controlling drug release, and enhancing tumor-specific accumulation. Among various nanocarrier platforms, poly(lactic-co-glycolic acid) (PLGA) has attracted attention due to its biodegradability, biocompatibility, and diverse drug-loading capabilities. However, traditional PLGA nanoparticles (NPs) are mainly limited to local administration due to insufficient targeting ability. To address this limitation, cell membrane coating technology has become an innovative strategy to provide enhanced targeted delivery through biomimetic surface modification. Various cell sources, including red blood cells, tumor cells, and immune cells, have demonstrated the potential of membrane coating applications, especially in targeting the tumor microenvironment (TME) where tumor-associated macrophages (TAMs) play a key role in tumor progression.

[0155] To utilize these biological properties, the present invention designed double-cell-membrane-coated nanoparticles by integrating Lewis lung cancer membrane (LLCM) and M2-polarized RAW264.7 macrophage membrane (M2M) onto polyethyleneimine (PEI)-modified PLGA NPs, forming the FM@NPs nanocomplex. Dynamic light scattering (DLS) analysis showed different particle size distributions among LLCM, M2M, NPs, and FM@NPs (Figure 17 , Figure 18 In A). Transmission electron microscopy (TEM) showed that the vesicle structure was maintained in both LLCM and M2M, while the NPs exhibited a uniform spherical morphology ( Figure 18 In B).

[0156] Protein characterization studies were performed to verify the retention of membrane proteins in the FM@NPs complex. Coomassie Brilliant Blue staining showed a unique protein distribution between the cell and membrane fractions, and a consistent distribution pattern was observed in LLCM, M2M, and the FM@NPs complex ( Figure 18 In C). Western blot analysis confirmed the retention of membrane-specific markers (CD68 and CD44) in the complex, while the cytoplasmic marker (GAPDH) remained undetectable, verifying the membrane extraction process and biological function ( Figure 18 In D).

[0157] The in vivo targeting efficiency and biodistribution of the FM@NPs complex were evaluated using Dir-labeled nanoparticles in subcutaneous tumor-bearing mice. After tail vein injection, the FM@NPs-Dir complex showed significantly enhanced tumor accumulation at 0, 12, and 24 hours post-injection compared to the unmodified NPs-Dir control ( Figure 18 In E). Bioluminescence imaging analysis showed that the FM@NPs-Dir complex preferentially localized to the tumor, followed by liver distribution, which is consistent with the metabolic pattern of PLGA ( Figure 18 In F). Quantitative analysis of tissue-specific fluorescence intensity (PPP ms -1 ) confirmed that double membrane coating significantly improved tumor targeting efficiency while reducing non-specific organ distribution compared to unmodified PLGA NPs.

[0158] 2.8 Enhanced therapeutic effects of BAY-876 and BSO delivery by double membrane-coated PLGA nanoparticles

[0159] On the basis of the successful development and characterization of double membrane-coated PLGA nanoparticles, their potential to address the limitations of the combined therapy of BAY-876 and BSO was next evaluated. BAY-876 and BSO were encapsulated in double membrane-coated PLGA nanoparticles (FM@NPs-BAY-876&BSO), and their in vivo antitumor effects were evaluated. Compared with the free drug combination therapy (BAY-876&BSO), the nanoparticle encapsulation formulation achieved superior tumor growth inhibition ( Figure 19 In A, B), resulting in a significant reduction in tumor size and mass ( Figure 19 In C, D). Long-term monitoring of tumor volume further confirmed the enhanced therapeutic effect ( Figure 19 In E), which is consistent with the improved tumor targeting and retention of FM@NPs previously observed in this invention.

[0160] Importantly, the nanoparticle delivery system maintained excellent safety, as confirmed by stable body weight ( Figure 19 in F) and normal histological findings in major organs including the heart, liver, and lungs ( Figure 19 in G). The biocompatibility of the delivery system was further verified by a hemolysis assay, in which the NPs-BAY-876&BSO and FM@NPs-BAY-876&BSO groups showed negligible hemolytic activity compared to the positive control ( Figure 19 in H, I). Mechanistic studies using TUNEL staining and the proliferation marker Ki-67 and the apoptosis marker Cleaved Caspase-3 showed that the enhanced antitumor response was achieved through a cell death pathway similar to that of the free drug combination, but with higher efficiency due to improved drug delivery ( Figure 19 in J).

[0161] These findings confirm that the double-membrane-coated PLGA nanoparticle platform of the present invention is an effective method to overcome the limitations of the combination therapy of BAY-876 and BSO in the treatment of LUAD, achieving enhanced antitumor effects and reduced off-target effects simultaneously through targeted delivery.

[0162] The embodiments described above are only for describing the preferred embodiments of the present invention and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. Use of a combination of a glutathione synthesis inhibitor and a glucose uptake inhibitor in any of the following: (1) Application in the preparation of drugs for treating lung adenocarcinoma; (2) Application in the preparation of drugs to improve the heterogeneity of SLC7A11 expression in lung adenocarcinoma.

2. The use according to claim 1, characterized in that The glutathione synthesis inhibitor includes BSO, and the glucose uptake inhibitor includes BAY-876.

3. A nanoparticle delivery system, characterized in that: The nanoparticle delivery system comprises nanoparticles coated with double cell membranes and drugs loaded thereon, wherein the double cell membranes are lung cancer membranes and macrophage membranes, and the drugs are glutathione synthesis inhibitors and glucose uptake inhibitors.

4. The nanoparticle delivery system according to claim 3, characterized in that The glutathione synthesis inhibitor includes BSO, and the glucose uptake inhibitor includes BAY-876.

5. A method for preparing the nanoparticle delivery system according to claim 3 or 4, characterized in that: The following steps are involved: After dissolving the glutathione synthesis inhibitor and the glucose uptake inhibitor respectively, the mixture was ultrasonically emulsified with dichloromethane containing polylactic acid-co-glycolic acid copolymer under ultrasonic conditions, and then the formed colostrum was added dropwise to the polyvinyl alcohol solution to form a secondary emulsion, which was stirred at room temperature, washed and freeze-dried to obtain nanoparticles; The lung cancer membrane, the macrophage membrane and the nanoparticles are mixed and then extruded through a polycarbonate porous membrane to obtain a nanoparticle delivery system.

6. The preparation method according to claim 5, characterized in that: The mass volume ratio of the glutathione synthesis inhibitor and the dichloromethane containing the polylactic acid-glycolic acid copolymer is 1 mg: (1-10) mL; The mass volume ratio of the glucose uptake inhibitor to the dichloromethane containing the polylactic acid-glycolic acid copolymer is 1 mg: (1-10) mL; Wherein, the mass volume ratio of the polylactic acid-glycolic acid copolymer to dichloromethane in the dichloromethane containing the polylactic acid-glycolic acid copolymer is 1 mg:(10-50) mL.

7. The preparation method according to claim 5, characterized in that: The volume ratio of the colostrum to the polyvinyl alcohol solution is 1:(1-3), and the mass volume fraction of the polyvinyl alcohol solution is 2%-7%.

8. The preparation method according to claim 5, characterized in that: The mass ratio of the lung cancer membrane, macrophage membrane and nanoparticles is 1:1:(1-3).

9. Use of the nanoparticle delivery system according to claim 3 or 4 in any of the following: (1) Application in the preparation of drugs for treating lung adenocarcinoma; (2) Application in the preparation of drugs to improve the heterogeneity of SLC7A11 expression in lung adenocarcinoma.

10. The use according to claim 9, characterized in that The glutathione synthesis inhibitor and the glucose uptake inhibitor are used in combination to synergistically induce disulfide death in lung adenocarcinoma cells that express medium or high levels of SLC7A11, thereby improving the heterogeneity of SLC7A11 expression in lung adenocarcinoma and / or achieving improved treatment effects for lung adenocarcinoma.

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