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N1-methyladenosine (m1A) modification is a crucial post-transcriptional regulatory mechanism of messenger RNA (mRNA) in living organisms. Few studies have focused on analysis of m1A regulators in lower-grade gliomas (LGG). We employed the Nonnegative Matrix Factorization (NMF) technique on The Cancer Genome Atlas (TCGA) dataset to categorize LGG patients into 2 groups. These groups exhibited substantial disparities in terms of both overall survival (OS) and levels of infiltrating immune cells. We collected the significantly differentially expressed immune-related genes between the 2 clusters, and performed LASSO regression analysis to obtain m1AScores, and established an m1A-related immune-related gene signature (m1A-RIGS). Next, we categorized all patients with LGG into high- and low-risk subgroups, predictive significance of m1AScore was confirmed by conducting univariate/multivariate Cox regression analyses. Additionally, we confirmed variations in immune-related cells and ssGSEA and among the high-/low-risk subcategories in the TCGA dataset. Finally, our study characterized the effects of MSR1 and BIRC5 on LGG cells utilizing Edu assay and flow cytometry to explore the effects of modulation of these genes on glioma. The results of this study suggested that m1A-RIGS may be an excellent prognostic indicator for patients with LGG, and could also promote development of novel immune-based treatment strategies for LGG. Additionally, BIRC5 and MSR1 may be potential therapeutic targets for LGG.

Neutrophils are important inflammatory effector cells that protect against foreign invasion but also cause self-harm. Numerous neutrophils infiltrate the lungs in acute respiratory distress syndrome/acute lung injury (ARDS/ALI) patients. However, the exact impact of neutrophil infiltration on ARDS's onset and progression remains unclear. To investigate this, we analyzed two ARDS-related datasets from the Gene Expression Omnibus public database and discovered an association between CD177, a neutrophil-specific surface protein, and ARDS progression. We used quantitative flow cytometry to assess CD177+ neutrophils in the peripheral blood of clinical ARDS patients versus healthy controls, finding a significant increase in CD177+ neutrophils percentage among total neutrophils in ARDS patients. This finding was further confirmed in ALI mouse models. Subsequent animal experiments showed that anti-CD177 effectively reduces pulmonary edema, neutrophil infiltration, and inflammatory cytokine release, along with a decrease in reactive oxygen species (ROS) and myeloperoxidase (MPO) levels. We also established an in vitro co-culture system to mimic neutrophil and lung epithelial cell interactions. In the anti-CD177 group, we observed decreased expression of NLRP3, caspase 1, PAD4, MPO, and ROS, along with a reduction in certain inflammatory cytokines. These results indicate a crucial role for the CD177 gene in ARDS's development and progression. Inhibiting CD177 may help mitigate excessive activation of NLRP3 inflammasomes, ROS, and neutrophil extracellular traps (NETs), thus alleviating ARDS.

Abstract Introduction Increasing evidence has revealed the key activity of protein disulfide isomerase A4 (PDIA4) in the endoplasmic reticulum stress (ERS) response. However, the role of PDIA4 in regulating glioblastoma (GBM)-specific pro-angiogenesis is still unknown. Methods The expression and prognostic role of PDIA4 were analyzed using a bioinformatics approach and were validated in 32 clinical samples and follow-up data. RNA-sequencing was used to search for PDIA4-associated biological processes in GBM cells, and proteomic mass spectrum (MS) analysis was used to screen for potential PDIA4 substrates. Western blotting, real-time quantitative polymerase chain reaction (RT-qPCR), and enzyme-linked immunosorbent assays (ELISA) were used to measure the levels of the involved factors. Cell migration and tube formation assays determined the pro-angiogenesis activity of PDIA4 in vitro. An intracranial U87 xenograft GBM animal model was constructed to evaluate the pro-angiogenesis role of PDIA4 in vivo. Results Aberrant overexpression of PDIA4 was associated with a poor prognosis in patients with GBM, although PDIA4 could also functionally regulate intrinsic GBM secretion of vascular endothelial growth factor-A (VEGF-A) through its active domains of Cys-X-X-Cys (CXXC) oxidoreductase. Functionally, PDIA4 exhibits pro-angiogenesis activity both in vitro and in vivo, and can be upregulated by ERS through transcriptional regulation of X-box binding protein 1 (XBP1). The XBP1/PDIA4/VEGFA axis partially supports the mechanism underlying GBM cell survival under ER stress. Further, GBM cells with higher expression of PDIA4 showed resistance to antiangiogenic therapy in vivo. Conclusions Our findings revealed the pro-angiogenesis role of PDIA4 in GBM progression and its potential impact on GBM survival under a harsh microenvironment. Targeting PDIA4 might help to improve the efficacy of antiangiogenic therapy in patients with GBM.

Abstract Background The p21-activated kinase (PAK) family (PAKs) plays a key role in the formation and development of human tumors. However, a systematic analysis of PAKs in human cancers is lacking and the potential role of PAKs in cancer immunity has not been explored. Methods We used datasets from in The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression database (GTEx). Results Based on TCGA datasets most PAKs show noteworthy differences in expression between tumors and corresponding normal tissues or across different tumor tissues. Patients with high expression of PAKs often show a worse prognosis. However, copy number variation, mutation, and DNA methylation of PAKs have limited impact on tumor development. Further analysis showed that the impact of PAKs on immunity varies with the type of tumor and the respective tumor microenvironment. PAK1 and PAK4 may be stronger predictors of immune characteristics, and are more suitable as drugs and molecular therapeutic targets. Furthermore, Cox regression analysis revealed that a PAK gene signature could be used as an independent prognostic factor for lower grade glioma (LGG) and glioblastoma (GBM). Gene set enrichment analysis (GSEA) analysis indicated that PAK genes may affect the occurrence and development of GBM through the PI3K signaling pathway. Further experiments verified that PAK1 and AKT1 have a significant interaction in GBM cells, and inhibiting the overactivation of PAK1 can significantly inhibit the proliferation of GBM cells. Conclusions Our study provides a rationale for further research on the prognostic and therapeutic potential of PAKs in human tumors.

Abstract Background The therapeutic effects of conventional treatment on gliomas are not promising. The tumor microenvironment (TME) has a close association with the invasiveness of multiple types of tumors, including low‐grade gliomas (LGG). This study aims to validate the prognostic and immune‐related role of macrophage scavenger receptor 1 (MSR1) in LGG patients. Methods Data in this study were obtained from public databases. The differential expression of MSR1 was analyzed in LGG patients with different clinicopathological characteristics. Kaplan–Meier survival analysis, a time‐dependent receiver operating characteristic (ROC) curve, and Cox regression analysis were used to assess the prognostic value of MSR1. Differentially expressed genes (DEGs) were screened between the high and low expression groups of MSR1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to annotate the function of these DEGs. Hallmark gene sets were identified based on MSR1 by Gene Set Enrichment Analysis (GSEA). Difference analysis and correlation analysis were used to study the relationship between MSR1 and TME‐related scores, tumor‐infiltrating immune cells (TIICs), immune‐related gene sets, and immune checkpoints (ICPs). The single‐cell sequencing data were processed to identify the cell types expressing MSR1. The quantification of TIICs in TME was calculated by single‐sample gene set enrichment analysis (ssGSEA). The differential expression of MSR1 in LGG and control brain tissues was verified by experiments. Results There were significant differences in the expression level of MSR1 in different types of tissues and cells. MSR1 has a high prognostic value in LGG patients and can be used as an independent prognostic factor. MSR1 is closely related to TME and may play an important role in the immunotherapy of LGG patients. Conclusions The result of our study demonstrated that MSR1 is an independent prognostic biomarker in LGG patients and may play an important role in the TME of LGGs.

Diffuse gliomas are the most common malignant brain tumors with the highest mortality and recurrence rate in adults. Integrin alpha-2 (ITGA2) is involved in a series of biological processes, including cell adhesion, stemness regulation, angiogenesis, and immune/blood cell functions. The role of ITGA2 in lower-grade gliomas (LGGs) is not well defined. Firstly, we downloaded RNA sequencing and relevant clinical information from The Cancer Genome Atlas cohort, the Chinese Glioma Genome Atlas cohort, and related immune cohorts. Next, prognosis analysis, difference analysis, clinical model construction, enrichment analysis, and immune infiltration analysis are performed for this study. These analyses indicated that ITGA2 may have clinical application value and research value in LGG immunotherapy. We also detected the mRNA and protein expression of ITGA2 in three LGG cell lines and normal glial cells using quantitative real-time polymerase chain reaction assay and western blot assay. Our study not only offers a novel target for LGG immunotherapy but also can better comprehend the mechanism of the development and progression of patients with LGG. This study revealed that ITGA2 may be a potential prognostic and predictive biomarker for LGG, which can bring new insights into targeted immunotherapy.

Immune-related gene pairs (IRGPs) have been associated with prognosis in various cancer types, but few studies have examined their prognostic capabilities in glioma patients. Here, we gathered the gene expression and clinical profile data of primary lower-grade glioma (LGG) patients from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA, containing CGGAseq1 and CGGAseq2), the Gene Expression Omnibus (GEO: GSE16011), and Rembrandt datasets. In the TCGA dataset, univariate Cox regression was performed to detect overall survival (OS)-related IRGs, Lasso regression, and multivariate Cox regression were used to screen robust prognosis-related IRGs, and 19 IRGs were selected for the construction of an IRGP prognostic signature. All patients were allotted to high- and low-risk subgroups based on the TCGA dataset median value risk score. Validation analysis indicated that the IRGP signature returned a stable prognostic value among all datasets. Univariate and multivariate Cox regression analyses indicated that the IRG -signature could efficiently predict the prognosis of primary LGG patients. The IRGP-signature-based nomogram model was built, revealing the reliable ability of the IRGP signature to predict clinical prognosis. The single-sample gene set enrichment analysis (ssGSEA) suggested that high-risk samples contained higher numbers of immune cells but featured lower tumor purity than low-risk samples. Finally, we verified the prognostic ability of the IRGP signature using experiments performed in LGG cells. These results indicated that the IRGP signature could be regarded as a stable prognostic assessment predictor for identifying high-risk primary LGG patients.

Background: Glioma is a malignant intracranial tumor and the most fatal cancer. The role of ferroptosis in the clinical progression of gliomas is unclear. Method: Univariate and least absolute shrinkage and selection operator (Lasso) Cox regression methods were used to develop a ferroptosis-related signature (FRSig) using a cohort of glioma patients from the Chinese Glioma Genome Atlas (CGGA), and was validated using an independent cohort of glioma patients from The Cancer Genome Atlas (TCGA). A single-sample gene set enrichment analysis (ssGSEA) was used to calculate levels of the immune infiltration. Multivariate Cox regression was used to determine the independent prognostic role of clinicopathological factors and to establish a nomogram model for clinical application. Results: We analyzed the correlations between the clinicopathological features and ferroptosis-related gene (FRG) expression and established an FRSig to calculate the risk score for individual glioma patients. Patients were stratified into two subgroups with distinct clinical outcomes. Immune cell infiltration in the glioma microenvironment and immune-related indexes were identified that significantly correlated with the FRSig, the tumor mutation burden (TMB), copy number alteration (CNA), and immune checkpoint expression was also significantly positively correlated with the FRSig score. Ultimately, an FRSig-based nomogram model was constructed using the independent prognostic factors age, World Health Organization (WHO) grade, and FRSig score. Conclusion: We established the FRSig to assess the prognosis of glioma patients. The FRSig also represented the glioma microenvironment status. Our FRSig will contribute to improve patient management and individualized therapy by offering a molecular biomarker signature for precise treatment. [ABSTRACT FROM AUTHOR]