Dataset Information

Multi-Omics Data Integration Analysis of an Immune-Related Gene Signature in LGG Patients With Epilepsy.

ABSTRACT:

Background

The tumor immune microenvironment significantly affects tumor occurrence, progression, and prognosis, but its impact on the prognosis of low-grade glioma (LGG) patients with epilepsy has not been reported. Hence, the purpose of this study is to explore its effect on LGG patients with epilepsy.

Methods

The data of LGG patients derived from the TCGA database. The level of immune cell infiltration and the proportion of 22 immune cells were evaluated by ESTIMATE and CIBERSORT algorithms, respectively. The Cox and LASSO regression analysis was adopted to determine the DEGs, and further established the clustering and risk score models. The association between genomic alterations and risk score was investigated using CNV and somatic mutation data. GSVA was adopted to identify the immunological pathways, immune infiltration and inflammatory profiles related to the signature genes. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and GDSC database were used to predict the patient's response to immunotherapy and chemotherapy, respectively.

Results

The prognosis of LGG patients with epilepsy was associated with the immune score. Three prognostic DEGs (ABCC3, PDPN, and INA) were screened out. The expression of signature genes was regulated by DNA methylation. The clustering and risk score models could stratify glioma patients into distinct prognosis groups. The risk score was an independent predictor in prognosis, with a high risk-score indicating a poor prognosis, more malignant clinicopathological and genomic aberration features. The nomogram had the better predictive ability. Patients at high risk had a higher level of macrophage infiltration and increased inflammatory activities associated with T cells and macrophages. While the higher percentage of NK CD56bright cell and more active inflammatory activity associated with B cell were present in the low-risk patients. The signature genes participated in the regulation of immune-related pathways, such as IL6-JAK-STAT3 signaling, IFN-α response, IFN-γ response, and TNFA-signaling-via-NFKB pathways. The high-risk patients were more likely to benefit from anti-PD1 and temozolomide (TMZ) treatment.

Conclusion

An immune-related gene signature was established based on ABCC3, PDPN, and INA, which can be used to predict the prognosis, immune infiltration status, immunotherapy and chemotherapy response of LGG patients with epilepsy.

SUBMITTER: Cheng Q

PROVIDER: S-EPMC8322853 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Immunotherapy for neuroblastoma remains unsatisfactory due to heterogeneity and weak immunogenicity. Exploring powerful signatures for the evaluation of immunotherapy outcomes remain the primary purpose. We constructed a ferroptosis-related gene (FRG) signature by least absolute shrinkage and selection operator and Cox regression, identified 10 independent prognostic FRGs in a training cohort (GSE62564), and then verified them in an external validation cohort (TCGA). Associated with clinical factors, the signature accurately predicts overall survival of 3, 5, and 10 years. An independent prognostic nomogram, which included FRG risk, age, stage of the International Neuroblastoma Staging System, and an MYCN status, was constructed. The area under the curves showed satisfactory prognostic predicting performance. Through bulk RNA-seq and proteomics data, we revealed the relationship between hub genes and the key onco-promoter MYCN gene and then validated the results in MYCN-amplified and MYCN-non-amplified cell lines with qRT-PCR. The FRG signature significantly divided patients into high- and low-risk groups, and the differentially expressed genes between the two groups were enriched in immune actions, autophagy, and carcinogenesis behaviors. The low-risk group embodied higher positive immune component infiltration and a higher expression of immune checkpoints with a more favorable immune cytolytic activity (CYT). We verified the predictive power of this signature with data from melanoma patients undergoing immunotherapy, and the predictive power was satisfactory. Gene mutations were closely related to the signature and prognosis. AURKA and PRKAA2 were revealed to be nodal hub FRGs in the signature, and both were shown to have significantly different expressions between the INSS stage IV and other stages after immunohistochemical validation. With single-cell RNA-seq analysis, we found that genes related to T cells were enriched in TNFA signaling and interferon-γ hallmark. In conclusion, we constructed a ferroptosis-related gene signature that can predict the outcomes and work in evaluating the effects of immunotherapy.

Project description:BackgroundThe plasticity of monocytes enables them to exert multiple roles during an immune response, including promoting immune tolerance. How monocytes alter their functions to convey immune tolerance in the context of lower respiratory tract infections in humans is not well understood. Here, we sought to identify epigenetic and transcriptomic features of cytokine production capacity in circulating monocytes during community-acquired pneumonia (CAP).MethodsCirculating CD14+ monocytes were obtained from the blood of CAP patients included in a longitudinal, observational cohort study, on hospitalization (acute stage, n=75), and from the same patients after a 1-month follow-up (recovery stage, n=56). Age and sex-matched non-infectious participants were included as controls (n=41). Ex vivo cytokine production after lipopolysaccharide (LPS) exposure was assessed by multiplex assay. Transcriptomes of circulating monocytes were generated by RNA-sequencing, and DNA methylation levels in the same monocytes were measured by reduced representation bisulfite sequencing. Data were integrated by fitting projection-to-latent-structure models, and signatures derived by partial least squares discrimination.ResultsMonocytes captured during the acute stage exhibited impaired TNF, IL-1β, IL-6, and IL-10 production after ex vivo stimulation with LPS, relative to controls. IL-6 production was not resolved in recovery monocytes. Multivariate analysis of RNA-sequencing data identified 2938 significantly altered RNA transcripts in acute-stage monocytes (fold expression ≤-1.5 or ≥1.5; adjusted p ≤ 0.01), relative to controls. Comparing DNA methylation levels in circulating monocytes of CAP patients to controls revealed minimal differences, specifically in DNAse hypersensitive sites (HS) of acute-stage monocytes. Data integration identified a cholesterol biosynthesis gene signature and DNAse HS axis of IL-1β and IL-10 production (R2 =0.51).ConclusionsCirculating monocytes obtained from CAP patients during the acute stage exhibited impaired cytokine production capacities, indicative of reprogramming to a state of immune tolerance, which was not fully resolved after 1 month. Our split-sample study showed that 51% of the immune tolerance phenotype can be explained, at least in part, by coordinated shifts in cholesterol biosynthesis gene expression and DNAse HS methylation levels. A multi-scale model identified an epigenetic and transcriptomic signature of immune tolerance in monocytes, with implications for future interventions in immunosuppression.Trial registrationNCT number NCT02928367.

Project description:BackgroundLung adenocarcinoma (LUAD) has emerged as one of the most aggressive lethal cancers. Anoikis serves as programmed apoptosis initiated by the detachment of cells from the extracel-lular matrix. Cuproptosis is distinct from traditional cell death modalities. The above two modes are both closely related to tumor progression, prognosis, and treatment. However, whether they have synergistic effects in LUAD deserves further investigation.MethodsThe anoikis-related prognostic genes (ANRGs) co-expressed with cuproptosis-associated genes (CAGs) were screened using correlation analysis, analysis of variance, least absolute shrinkage, and selection operator (LASSO), and COX regression followed by functional analysis, and then LUAD risk score model was constructed. Using consensus clustering, the relationship between different subtypes and clinicopathological features, immune infiltration characteristics, and somatic mutations was analyzed. A nomogram was developed by incorporating clinical information, which provided a prediction of the survival of patients. Finally, a comprehensive analysis of ANRGs was performed and verified by the HPA database.ResultsA total of 27 ANRGs associated with cuproptosis were obtained. On this basis, three distinct ANRGs subtypes were identified, and the differences between clinical prognosis and immune infiltration were observed. A risk score model has been constructed by incorporating seven ANRGs signatures (EIF2AK3, IKZF3, ITGAV, OGT, PLK1, TRAF2, XRCC5). A highly reliable nomogram was developed to help formulate treatment strategies based on risk score and the clinicopathological features of LUAD. The seven-gene signature was turned out to be strongly linked to immune cells and validated in single-cell data. Immunohistochemistry proved that all of them are highly expressed in LUAD tissues.ConclusionThis study reveals the potential relationship between cuproptosis-related ANRGs and clinicopathological features, tumor microenvironment (TME), and mutation characteristics, which can be applied for predicting the prognosis of LUAD and help develop individualized treatment strategies.