Prediction of prognosis, immunogenicity and efficacy of immunotherapy based on glutamine metabolism in lung adenocarcinoma
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ABSTRACT:
PROVIDER: PRJNA863251 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR20693911_1.fastq.gz | Fastqsanger.gz | |||
| SRR20693911_2.fastq.gz | Fastqsanger.gz | |||
| SRR20693912_1.fastq.gz | Fastqsanger.gz | |||
| SRR20693912_2.fastq.gz | Fastqsanger.gz | |||
| SRR20693913_1.fastq.gz | Fastqsanger.gz |
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Project description:Glutamine (Gln) metabolism has been reported to play an essential role in cancer. However, a comprehensive analysis of its role in lung adenocarcinoma is still unavailable. This study established a novel system of quantification of Gln metabolism to predict the prognosis and immunotherapy efficacy in lung cancer. Further, the Gln metabolism in tumor microenvironment (TME) was characterized and the Gln metabolism-related genes were identified for targeted therapy. We comprehensively evaluated the patterns of Gln metabolism in 513 patients diagnosed with lung adenocarcinoma (LUAD) based on 73 Gln metabolism-related genes. Based on differentially expressed genes (DEGs), a risk model was constructed using Cox regression and Lasso regression analysis. The prognostic efficacy of the model was validated using an individual LUAD cohort form Shandong Provincial Hospital, an integrated LUAD cohort from GEO and pan-cancer cohorts from TCGA databases. Five independent immunotherapy cohorts were used to validate the model performance in predicting immunotherapy efficacy. Next, a series of single-cell sequencing analyses were used to characterize Gln metabolism in TME. Finally, single-cell sequencing analysis, transcriptome sequencing, and a series of in vitro experiments were used to explore the role of EPHB2 in LUAD. Patients with LUAD were eventually divided into low- and high-risk groups. Patients in low-risk group were characterized by low levels of Gln metabolism, survival advantage, “hot” immune phenotype and benefit from immunotherapy. Compared with other cells, tumor cells in TME exhibited the most active Gln metabolism. Among immune cells, tumor-infiltrating T cells exhibited the most active levels of Gln metabolism, especially CD8 T cell exhaustion and Treg suppression. EPHB2, a key gene in the model, was shown to promote LUAD cell proliferation, invasion and migration, and regulated the Gln metabolic pathway. Finally, we found that EPHB2 was highly expressed in macrophages, especially M2 macrophages. It may be involved in the M2 polarization of macrophages and mediate the negative regulation of M2 macrophages in NK cells. This study revealed that the Gln metabolism-based model played a significant role in predicting prognosis and immunotherapy efficacy in lung cancer. We further characterized the Gln metabolism of TME and investigated the Gln metabolism-related gene EPHB2 to provide a theoretical framework for anti-tumor strategy targeting Gln metabolism.
2022-07-31 | GSE209973 | GEO
Project description:BackgroundGlutamine (Gln) metabolism has been reported to play an essential role in cancer. However, a comprehensive analysis of its role in lung adenocarcinoma is still unavailable. This study established a novel system of quantification of Gln metabolism to predict the prognosis and immunotherapy efficacy in lung cancer. Further, the Gln metabolism in tumor microenvironment (TME) was characterized and the Gln metabolism-related genes were identified for targeted therapy.MethodsWe comprehensively evaluated the patterns of Gln metabolism in 513 patients diagnosed with lung adenocarcinoma (LUAD) based on 73 Gln metabolism-related genes. Based on differentially expressed genes (DEGs), a risk model was constructed using Cox regression and Lasso regression analysis. The prognostic efficacy of the model was validated using an individual LUAD cohort form Shandong Provincial Hospital, an integrated LUAD cohort from GEO and pan-cancer cohorts from TCGA databases. Five independent immunotherapy cohorts were used to validate the model performance in predicting immunotherapy efficacy. Next, a series of single-cell sequencing analyses were used to characterize Gln metabolism in TME. Finally, single-cell sequencing analysis, transcriptome sequencing, and a series of in vitro experiments were used to explore the role of EPHB2 in LUAD.ResultsPatients with LUAD were eventually divided into low- and high-risk groups. Patients in low-risk group were characterized by low levels of Gln metabolism, survival advantage, "hot" immune phenotype and benefit from immunotherapy. Compared with other cells, tumor cells in TME exhibited the most active Gln metabolism. Among immune cells, tumor-infiltrating T cells exhibited the most active levels of Gln metabolism, especially CD8 T cell exhaustion and Treg suppression. EPHB2, a key gene in the model, was shown to promote LUAD cell proliferation, invasion and migration, and regulated the Gln metabolic pathway. Finally, we found that EPHB2 was highly expressed in macrophages, especially M2 macrophages. It may be involved in the M2 polarization of macrophages and mediate the negative regulation of M2 macrophages in NK cells.ConclusionThis study revealed that the Gln metabolism-based model played a significant role in predicting prognosis and immunotherapy efficacy in lung cancer. We further characterized the Gln metabolism of TME and investigated the Gln metabolism-related gene EPHB2 to provide a theoretical framework for anti-tumor strategy targeting Gln metabolism.
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Project description:Abstract: Immunotherapy has emerged as a crucial treatment approach for lung adenocarcinoma (LUAD), yet a notable percentage of patients do not exhibit the anticipated prognosis and therapeutic response. In this study, we embarked on a comprehensive analysis of immune infiltration-related genes in LUAD by integrating transcriptome sequencing data and TCGA dataset. And an immune risk prognosis model was developed, which accurately forecasts the prognosis and predicts the immunotherapy efficacy in LUAD. Patients with LUAD were categorized into high-risk and low-risk groups based on the model's risk value. The high-risk group exhibited a poorer prognosis, higher tumor mutation burden (TMB), greater genomic heterogeneity and lower immune scores. In contrast, the low-risk group manifested characteristics conducive to immunotherapy, including a more favorable prognosis, heightened sensitivity to immunotherapy and reduced likelihood of immune escape. The robustness of the model's predictive capability was corroborated using the GEO dataset, Nomogram and an independent immunotherapy cohort. Furthermore, the model risk value was found to be significantly associated with the prognosis of LUAD patients, genomic heterogeneity, immune cell infiltration, immune regulation and immunotherapy outcomes. Additionally, we characterized the significance of the model's feature factors using single-cell clustering and pseudo-temporal analysis, revealing that the model's feature genes are predominantly located in tumor-infiltrating T cells, particularly in the exhausted and effector subtypes. TNFRSF11A emerged as a key gene in the model, promoting LUAD cell proliferation, migration, and apoptosis, and involvement in LUAD M6A methylation and PD-L1-mediated immune escape. TNFRSF11A was mainly expressed in T cell clusters and represented a potential immune system regulatory factor associated with T cell exhaustion, fostering malignant progression in LUAD cells. Our study offers new mechanistic insights and therapeutic targets for the biological behaviors and immune suppression in LUAD.
2024-09-30 | GSE270711 | GEO
Project description:Alzheimer's disease (AD) is characterized as a distinct onset and progression of cognitive and functional decline associated with age, as well as a specific neuropathology. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. However, a full investigation of its role in Alzheimer's disease is still missing. This study intended to find and confirm potential Gln-related genes associated with AD using bioinformatics analysis. The discovery of GlnMgs was made possible by the intersection of the WGCNA test and 26 Gln-metabolism genes (GlnMgs). GlnMgs' putative biological functions and pathways were identified using GSVA. The LASSO method was then used to identify the hub genes as well as the diagnostic efficiency of the four GlnMgs in identifying AD. The association between hub GlnMgs and clinical characteristics was also studied. Finally, the GSE63060 was utilized to confirm the levels of expression of the four GlnMgs. Four GlnMgs were discovered (ATP5H, NDUFAB1, PFN2, and SPHKAP). For biological function analysis, cell fate specification, atrioventricular canal development, and neuron fate specification were emphasized. The diagnostic ability of the four GlnMgs in differentiating AD exhibited a good value. This study discovered four GlnMgs that are linked to AD. They shed light on potential new biomarkers for AD and tracking its progression.
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Project description:Despite the importance of immunity against neuraminidase (NA), NA content and immunogenicity is neglected in current influenza vaccines. To address this, a novel recombinant N1/N2 NA vaccine (NAV) was developed. Stability assays were used to determine optimal temperature and buffer conditions for vaccine storage. The effect of calcium-related enhancement of NA stability and activity on N1 and N2 immunogenicity and efficacy against viral challenge was assessed. Differences in activity between N1 and N2 and calcium-related activity enhancement did not translate into differences in immunogenicity or efficacy. NAV vaccinated mice showed robust antibody titers against N1 and N2, decreased viral titers, and decreased antiviral and inflammatory responses by transcriptomic analysis.
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Project description:BackgroundBladder cancer is the most common malignancy of the urinary system. However, patient prognosis and treatment outcomes in bladder cancer are difficult to predict owing to high tumor heterogeneity. Given that abnormal glutamine metabolism has been identified as a key factor driving the progression of bladder cancer, it is necessary to assess the prognosis and therapeutic efficacy of bladder cancer treatments based on an analysis of glutamine metabolism-related genes.MethodsWe used bladder cancer sample data downloaded from The Cancer Genome Atlas to identify glutamine metabolism-related genes as prognostic markers, and established a novel Glutamine Metabolism Immunity Index (GMII) based on univariate and multivariate COX regression analyses. On the basis of GMII values, bladder cancer patients were divided into high- and low-risk groups, and systematic analysis was conducted for clinical features, somatic mutations, immune cell infiltration, chemotherapeutic response, and immunotherapeutic efficacy. Candidate small-molecule drugs targeting the GMII core target proteins were identified based on molecular docking analysis.ResultsThe GMII consisting of eight independent prognostic genes was established to be an excellent tool for predicting the survival in patients with bladder cancer and was validated using multiple datasets. Compared with patients in the high-risk group, those in the low-risk group had significantly better responses to gemcitabine and immune checkpoint blockade. In addition, we predicted 12 potential small-molecule drugs that could bind to three of the GMII core target proteins.ConclusionsThe GMII can be used to accurately predict the prognosis and immunotherapeutic response of bladder cancer patients, as well as candidate small-molecule drugs. Furthermore, the novel "Glutamine Metabolism-related Gene"-guided strategy for predicting survival and chemo-immunotherapeutic efficacy may also be applicable for cancers other than bladder cancer.
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Project description:To understand the effects of glutamine deprivation on cell physiology we performed global analysis of gene expression in response to glutamine deprivation. U2OS cells were subjected to glutamine deprivation for 24h followed by RNA extraction and microarray analysis. U2OS cells were plated overnight followed by treatment for 24h with glutamine-containing and glutamine-depleted media. Three biological replicates were assayed for each condition.
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