| BackgroundLung cancer remains the most lethal cancer worldwide,with lung adenocarcinoma being the most common pathological type of lung cancer.In recent years,immunotherapy has shown remarkable efficacy in the treatment of lung adenocarcinoma,but is still limited by drug resistance and recurrence due to tumor immune heterogeneity.Therefore,it is particularly critical to explore the mechanisms of immune heterogeneity in lung adenocarcinoma and develop novel tools to predict patient prognosis and immunotherapy efficacy.Oncogenic transformation induces metabolic reprogramming of the tumor,which in turn affects the tumor microenvironment(TME).Therefore,therapeutic strategies that target tumor metabolism are highly promising.As an energy source that both tumor cells and immune cells depend on,glutamine(Gln)is heavily depleted in tumor cells.However,some inflammatory anti-tumor immune cells do not depend on or even reject Gln metabolism,thus targeting Gln metabolism to suppress tumors and enhance anti-tumor immunity of immune cells holds great promise.However,the metabolic characteristics of Gln in lung adenocarcinoma is still not fully elucidated,making targeting Gln metabolism for lung adenocarcinoma lacking sufficient theoretical basis.PurposeThe aim of this study was to investigate the metabolic characteristics of Gln in lung adenocarcinoma,to construct a prognostic risk model related to Gln metabolism,and to screen key Gln metabolism regulators as potential targets for lung adenocarcinoma treatment.MethodsBased on 73 regulatory factors of Gln metabolism and the Single Sample Gene Set Enrichment Analysis(ssGSEA)algorithm,this study calculated and analyzed the differences in the distribution of Gln metabolism levels in lung adenocarcinoma patients from The Cancer Genome Atlas(TCGA)database.Based on single cell sequencing samples of lung adenocarcinoma extracted from the Gene Expression Omnibus(GEO)database,differences in Gln metabolism levels in tumors and various types of immune cells were calculated and analyzed.Based on 504 lung adenocarcinoma patients from TCGA,we screened prognosis-related Gln metabolism genes by univariate COX regression analysis,clustered the 504 lung adenocarcinoma patients by consistent clustering algorithm and identified differentially expressed genes among different clusters.Further,multivariate COX regression and Lasso regression analysis was used to construct a prognostic risk model,and classified patients into high and low risk groups based on risk scores.Meanwhile,719 lung adenocarcinoma samples from GEO and 33 lung adenocarcinoma samples collected from our hospital were used as validation cohorts to validate the model,respectively.Heterogeneity of the immune microenvironment(TME)of lung adenocarcinoma in the high and low risk groups was explored using various tools such as gene set variation analysis(GSVA),single sample gene set enrichment analysis(ssGSEA),ESTIMATE algorithm and tumor immune dysfunction and exclusion(TIDE)analysis.Finally,the predictive performance of the models for immunotherapy efficacy was explored using multiple published immunotherapy cohorts.We screened the key regulator EPHB2 in the prognostic risk model,knocked down its expression by small interfering RNA(siRNA),and verified its regulation on malignant progression of lung adenocarcinoma by cell proliferation assay,Colony formation assay,wound healing assay,and transwell assay.RNA-seq high-throughput sequencing analysis was performed to explore the downstream pathways or targets of its regulation in lung adenocarcinoma cells.Single cell sequencing analysis,qRT-PCR,and immunofluorescence were used to explore the role played by EPHB2 in immune cells of lung adenocarcinoma.Results1.In the lung adenocarcinoma cohort,tumor tissue exhibited higher levels of Gln metabolism in patients with poorer overall survival and in patients with advanced stage and TNM stage.In lung adenocarcinoma tissue,tumors exhibited higher levels of Gln metabolism than paraneoplastic tissue.Tumor cells had significantly higher levels of Gln metabolism than immune cells and stromal cells.T cells were the immune cells with the highest levels of Gln metabolism,especially exhausted CD8+T cells and suppressive regulatory T cells(Tregs).2.Based on the lung adenocarcinoma cohort of TCGA,a prognostic risk model consisting of 10 Gln metabolism-related genes was constructed.In the training cohort,the GEO validation cohort and the validation cohort collected at our institution,patients in the low-risk group had a better prognosis than those in the high-risk group(p<0.01).Compared to the high-risk group,patients in the low-risk group had lower levels of Gln metabolism,higher levels of immune cell infiltration and activation of immune function,and were more likely to benefit from immunotherapy such as immune checkpoint inhibitors(ICI)and adoptive T-cell therapy(ACT).3.EPHB2 was identified as a key regulator of Gln metabolism from a prognostic risk model.In vitro experiments confirmed that EPHB2 was highly expressed in lung adenocarcinoma tissues and significantly correlated with poor prognosis(p<0.05).EPHB2 promoted malignant progression of lung adenocarcinoma cells such as proliferation,invasion and migration.Knockdown of EPHB2 significantly downregulated the expression of several Gln metabolism regulators such as GLS and GLUL.In addition,in immune cells,EPHB2 was mainly expressed in macrophages and was involved in the polarization of M2 macrophages.Conclusion1.This study verified that Gln metabolism levels were associated with poor prognosis in lung adenocarcinoma.Tumor cells in the tumor microenvironment and T cells represented by exhausted CD8+T cells and suppressive Tregs were highly dependent on Gln metabolism.2.A prognostic risk model based on Gln metabolism was constructed to accurately predict the prognosis and immunotherapy efficacy of patients with lung adenocarcinoma.Patients in the low-risk group had lower Gln metabolism levels,better prognosis and higher anti-tumor immune activity,and were more likely to benefit from immunotherapy.3.EPHB2,a regulator of Gln metabolism,was screened as a potential therapeutic target that promotes malignant progression and Gln metabolism in lung adenocarcinoma cells and is involved in the M2-phenotype polarization of macrophages. |
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