Somatic PDGFRB activating variants promote smooth muscle cell phenotype modulation in intracranial fusiform aneurysm.

BACKGROUND: The fusiform aneurysm is a nonsaccular dilatation affecting the entire vessel wall over a short distance. Although PDGFRB somatic variants have been identified in fusiform intracranial aneurysms, the molecular and cellular mechanisms driving fusiform intracranial aneurysms due to PDGFRB somatic variants remain poorly understood. METHODS: In this study, single-cell sequencing and immunofluorescence were employed to investigate the phenotypic changes in smooth muscle cells within fusiform intracranial aneurysms. Whole-exome sequencing revealed the presence of PDGFRB gene mutations in fusiform intracranial aneurysms. Subsequent immunoprecipitation experiments further explored the functional alterations of these mutated PDGFRB proteins. For the common c.1684 mutation site of PDGFRß, we established mutant smooth muscle cell lines and zebrafish models. These models allowed us to simulate the effects of PDGFRB mutations. We explored the major downstream cellular pathways affected by PDGFRBY562D mutations and evaluated the potential therapeutic effects of Ruxolitinib. RESULTS: Single-cell sequencing of two fusiform intracranial aneurysms sample revealed downregulated smooth muscle cell markers and overexpression of inflammation-related markers in vascular smooth muscle cells, which was validated by immunofluorescence staining, indicating smooth muscle cell phenotype modulation is involved in fusiform aneurysm. Whole-exome sequencing was performed on seven intracranial aneurysms (six fusiform and one saccular) and PDGFRB somatic mutations were detected in four fusiform aneurysms. Laser microdissection and Sanger sequencing results indicated that the PDGFRB mutations were present in smooth muscle layer. For the c.1684 (chr5: 149505131) site mutation reported many times, further cell experiments showed that PDGFRBY562D mutations promoted inflammatory-related vascular smooth muscle cell phenotype and JAK-STAT pathway played a crucial role in the process. Notably, transfection of PDGFRBY562D in zebrafish embryos resulted in cerebral vascular anomalies. Ruxolitinib, the JAK inhibitor, could reversed the smooth muscle cells phenotype modulation in vitro and inhibit the vascular anomalies in zebrafish induced by PDGFRB mutation. CONCLUSION: Our findings suggested that PDGFRB somatic variants played a role in regulating smooth muscle cells phenotype modulation in fusiform aneurysms and offered a potential therapeutic option for fusiform aneurysms.

High glutamine increases stroke risk by inducing the endothelial-to-mesenchymal transition in moyamoya disease.

At present, there is limited research on the mechanisms underlying moyamoya disease (MMD). Herein, we aimed to determine the role of glutamine in MMD pathogenesis, and 360 adult patients were prospectively enrolled. Human brain microvascular endothelial cells (HBMECs) were subjected to Integrin Subunit Beta 4 (ITGB4) overexpression or knockdown and atorvastatin. We assessed factors associated with various signaling pathways in the context of the endothelial-to-mesenchymal transition (EndMT), and the expression level of related proteins was validated in the superficial temporal arteries of patients. We found glutamine levels were positively associated with a greater risk of stroke (OR = 1.599, p = 0.022). After treatment with glutamine, HBMECs exhibited enhanced proliferation, migration, and EndMT, all reversed by ITGB4 knockdown. In ITGB4-transfected HBMECs, the MAPK-ERK-TGF-ß/BMP pathway was activated, with Smad4 knockdown reversing the EndMT. Furthermore, atorvastatin suppressed the EndMT by inhibiting Smad1/5 phosphorylation and promoting Smad4 ubiquitination in ITGB4-transfected HBMECs. We also found the protein level of ITGB4 was upregulated in the superficial temporal arteries of patients with MMD. In conclusion, our study suggests that glutamine may be an independent risk factor for hemorrhage or infarction in patients with MMD and targeting ITGB4 could potentially be therapeutic approaches for MMD.

Circulating immune cell landscape and T-cell abnormalities in patients with moyamoya disease.

BACKGROUND: Moyamoya disease (MMD) stands as a prominent cause of stroke among children and adolescents in East Asian populations. Although a growing body of evidence suggests that dysregulated inflammation and autoimmune responses might contribute to the development of MMD, a comprehensive and detailed understanding of the alterations in circulating immune cells associated with MMD remains elusive. METHODS: In this study, we employed a combination of single-cell RNA sequencing (scRNA-seq), mass cytometry and RNA-sequencing techniques to compare immune cell profiles in peripheral blood samples obtained from patients with MMD and age-matched healthy controls. RESULTS: Our investigation unveiled immune dysfunction in MMD patients, primarily characterized by perturbations in T-cell (TC) subpopulations, including a reduction in effector TCs and an increase in regulatory TCs (Tregs). Additionally, we observed diminished natural killer cells and dendritic cells alongside heightened B cells and monocytes in MMD patients. Notably, within the MMD group, there was an augmented proportion of fragile Tregs, whereas the stable Treg fraction decreased. MMD was also linked to heightened immune activation, as evidenced by elevated expression levels of HLA-DR and p-STAT3. CONCLUSIONS: Our findings offer a comprehensive view of the circulating immune cell landscape in MMD patients. Immune dysregulation in patients with MMD was characterized by alterations in T-cell populations, including a decrease in effector T-cells and an increase in regulatory T-cells (Tregs), suggest a potential role for disrupted circulating immunity in the aetiology of MMD.

Nonalcoholic fatty liver disease is an independent risk factor for ischemic stroke after revascularization in patients with Moyamoya disease: a prospective cohort study.

BACKGROUND: The study aimed to investigate the association between nonalcoholic fatty liver disease (NAFLD) and ischemic stroke events after revascularization in patients with Moyamoya disease (MMD). METHODS: This study prospectively enrolled 275 MMD patients from September 2020 to December 2021. Patients with alcoholism and other liver diseases were excluded. NAFLD was confirmed by CT imaging or abdominal ultrasonography. Stroke events and modified Rankin Scale (mRS) scores at the latest follow-up were compared between the two groups. RESULTS: A total of 275 patients were enrolled in the study, among which 65 were diagnosed with NAFLD. Univariate logistic regression analysis showed that NAFLD (P = 0.029) was related to stroke events. Multivariate logistic regression analysis showed that NAFLD is a predictor of postoperative stroke in MMD patients (OR = 27.145, 95% CI = 2.031-362.81, P = 0.013). Kaplan-Meier analysis showed that compared with MMD patients with NAFLD, patients in the control group had a longer stroke-free time (P = 0.004). Univariate Cox analysis showed that NAFLD (P = 0.016) was associated with ischemic stroke during follow-up in patients with MMD. Multivariate Cox analysis showed that NAFLD was an independent risk factor for stroke in patients with MMD (HR = 10.815, 95% CI = 1.259-92.881, P = 0.030). Furthermore, fewer patients in the NAFLD group had good neurologic status (mRS score ≤ 2) than the control group (P = 0.005). CONCLUSION: NAFLD was an independent risk factor for stroke in patients with MMD after revascularization and worse neurological function outcomes.

Mass cytometry revealed the circulating immune cell landscape across different Suzuki stages of Moyamoya disease.

Moyamoya disease (MMD) is a cerebrovascular disorder marked by progressive arterial narrowing, categorized into six stages known as Suzuki stages based on angiographic features. Growing evidence indicates a pivotal role of systemic immune and inflammatory responses in the initiation and advancement of MMD. This study employs high-dimensional mass cytometry to reveal the immunophenotypic characteristics of peripheral blood immune cells (PBMCs) at various Suzuki stages, offering insights into the progression of MMD. PBMC samples from eight patients with early-stage MMD (Suzuki stages II and III) and eight patients with later-stage MMD (Suzuki stages IV, V, and VI) were analyzed using high-dimensional mass cytometry to evaluate the frequency and phenotype of immune cell subtypes. We identified 15 cell clusters and found that the immunological features of early-stage MMD and later-stage MMD are composed of cluster variations. In this study, we confirmed that, compared to later-stage MMD, the early-stage MMD group exhibits an increase in non-classical monocytes. As the Suzuki stage level increases, the proportions of plasmacytoid DCs and monocyte-derived DCs decrease. Furthermore, T cells, monocytes, DCs, and PMN-MDSCs in the early-stage MMD group show activation of the canonical NF-κB signaling pathway. We summarized and compared the similarities and differences between early-stage MMD patients and later-stage MMD patients. There is a potential role of circulating immune dysfunction and inflammatory responses in the onset and development of MMD.

Multiomics and blood-based biomarkers of moyamoya disease: protocol of Moyamoya Omics Atlas (MOYAOMICS).

BACKGROUND: Moyamoya disease (MMD) is a rare and complex cerebrovascular disorder characterized by the progressive narrowing of the internal carotid arteries and the formation of compensatory collateral vessels. The etiology of MMD remains enigmatic, making diagnosis and management challenging. The MOYAOMICS project was initiated to investigate the molecular underpinnings of MMD and explore potential diagnostic and therapeutic strategies. METHODS: The MOYAOMICS project employs a multidisciplinary approach, integrating various omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, to comprehensively examine the molecular signatures associated with MMD pathogenesis. Additionally, we will investigate the potential influence of gut microbiota and brain-gut peptides on MMD development, assessing their suitability as targets for therapeutic strategies and dietary interventions. Radiomics, a specialized field in medical imaging, is utilized to analyze neuroimaging data for early detection and characterization of MMD-related brain changes. Deep learning algorithms are employed to differentiate MMD from other conditions, automating the diagnostic process. We also employ single-cellomics and mass cytometry to precisely study cellular heterogeneity in peripheral blood samples from MMD patients. CONCLUSIONS: The MOYAOMICS project represents a significant step toward comprehending MMD's molecular underpinnings. This multidisciplinary approach has the potential to revolutionize early diagnosis, patient stratification, and the development of targeted therapies for MMD. The identification of blood-based biomarkers and the integration of multiple omics data are critical for improving the clinical management of MMD and enhancing patient outcomes for this complex disease.

Identification of heterogeneous subtypes and a prognostic model for gliomas based on mitochondrial dysfunction and oxidative stress-related genes.

Objective: Mitochondrial dysfunction and oxidative stress are known to involved in tumor occurrence and progression. This study aimed to explore the molecular subtypes of lower-grade gliomas (LGGs) based on oxidative stress-related and mitochondrial-related genes (OMRGs) and construct a prognostic model for predicting prognosis and therapeutic response in LGG patients. Methods: A total of 223 OMRGs were identified by the overlap of oxidative stress-related genes (ORGs) and mitochondrial-related genes (MRGs). Using consensus clustering analysis, we identified molecular subtypes of LGG samples from TCGA database and confirmed the differentially expressed genes (DEGs) between clusters. We constructed a risk score model using LASSO regression and analyzed the immune-related profiles and drug sensitivity of different risk groups. The prognostic role of the risk score was confirmed using Cox regression and Kaplan-Meier curves, and a nomogram model was constructed to predict OS rates. We validated the prognostic role of OMRG-related risk score in three external datasets. Quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) staining confirmed the expression of selected genes. Furthermore, wound healing and transwell assays were performed to confirm the gene function in glioma. Results: We identified two OMRG-related clusters and cluster 1 was significantly associated with poor outcomes (P<0.001). The mutant frequencies of IDH were significantly lower in cluster 1 (P<0.05). We found that the OMRG-related risk scores were significantly correlated to the levels of immune infiltration and immune checkpoint expression. High-risk samples were more sensitive to most chemotherapeutic agents. We identified the prognostic role of OMRG-related risk score in LGG patients (HR=2.665, 95%CI=1.626-4.369, P<0.001) and observed that patients with high-risk scores were significantly associated with poor prognosis (P<0.001). We validated our findings in three external datasets. The results of qRT-PCR and IHC staining verified the expression levels of the selected genes. The functional experiments showed a significant decrease in the migration of glioma after knockdown of SCNN1B. Conclusion: We identified two molecular subtypes and constructed a prognostic model, which provided a novel insight into the potential biological function and prognostic significance of mitochondrial dysfunction and oxidative stress in LGG. Our study might help in the development of more precise treatments for gliomas.

High ECM2 Expression Predicts Poor Clinical Outcome and Promotes the Proliferation, Migration, and Invasiveness of Glioma.

OBJECTIVE: Glioma is the most prevalent and fatal intracranial malignant tumor. Extracellular matrix protein 2 (ECM2) has rarely been studied in gliomas. Therefore, we explored the role of ECM2 in lower-grade gliomas (LGGs). METHODS: The RNA-seq and clinicopathology data were obtained from the TCGA database. The immunohistochemical (IHC) staining was used to verify the expression of ECM2. Functional enrichment analyses, immune-related analyses, drug sensitivity, and mutation profile analyses were further conducted. Cox regression and Kaplan-Meier curves were utilized for survival analyses, while four external datasets were used to validate the prognostic role of ECM2. Furthermore, qRT-PCR, CCK-8, wound healing, and transwell assays were performed to confirm the function of ECM2 in gliomas. RESULTS: The study found a significant upregulation of ECM2 expression with increasing glioma grades and a significant association between ECM2 expression and tumor immune infiltration. Cox regression verified the prognostic role of ECM2 in LGG patients (HR = 1.656, 95%CI = 1.055-2.600, p = 0.028). High ECM2 expression was significantly associated with poor outcome (p < 0.001). Four external datasets validated its prognostic value. After the knockdown of ECM2, the functional experiments showed a significant decrease in proliferation, migration, and invasion in glioma cell lines. CONCLUSION: The study suggested the potential of ECM2 as a novel immune-associated prognostic biomarker and therapeutic target for glioma patients.

Heterogenous profiles between primary lung cancers and paired brain metastases reveal tumor evolution.

Background: Brain metastases (BMs) are the most common central nervous system (CNS) malignant tumors, with rapid disease progression and extremely poor prognosis. The heterogeneity between primary lung cancers and BMs leads to the divergent efficacy of the adjuvant therapy response to primary tumors and BMs. However, the extent of heterogeneity between primary lung cancers and BMs, and the evolutionary process remains little known. Methods: To deeply insight into the extent of inter-tumor heterogeneity at a single-patient level and the process of these evolutions, we retrospectively analyzed a total of 26 tumor samples from 10 patients with matched primary lung cancers and BMs. One patient underwent four times brain metastatic lesion surgery with diverse locations and one operation for the primary lesion. The genomic and immune heterogeneity between primary lung cancers and BMs were evaluated by utilizing whole-exome sequencing (WESeq) and immunohistochemical analysis. Results: In addition to inheriting genomic phenotype and molecular phenotype from the primary lung cancers, massive unique genomic phenotype and molecular phenotype were also observed in BMs, which revealed unimaginable complexity of tumor evolution and extensive heterogeneity among lesions at a single-patient level. By analysis of a multi-metastases case (Case 3) of cancer cells' subclonal composition, we found similar multiple subclonal clusters in the four spatial and temporal isolated brain metastatic focus, with the characteristics of polyclonal dissemination. Our study also verified that the expression level of immune checkpoints-related molecule Programmed Death-Ligand 1 (PD-L1) (P = 0.0002) and the density of tumor-infiltrating lymphocytes (TILs) (P = 0.0248) in BMs were significantly lower than that in paired primary lung cancers. Additionally, tumor microvascular density (MVD) also differed between primary tumors and paired BMs, indicating that temporal and spatial diversity profoundly contributes to the evolution of BMs heterogeneity. Conclusion: Our study revealed the significance of temporal and spatial factors to the evolution of tumor heterogeneity by multi-dimensional analysis of matched primary lung cancers and BMs, which also provided novel insight for formulating individualized treatment strategies for BMs.

Integrated analysis of the association between methionine cycle and risk of moyamoya disease.

OBJECTIVE: The role of methionine (Met) cycle in the pathogenesis and progression of cardiovascular and cerebrovascular diseases has been established, but its association with moyamoya disease (MMD) has rarely been studied. This study aimed to analyze the levels of Met cycle-related metabolites and constructed a risk model to explore its association with the risk of MMD. METHODS: In this prospective study, a total of 302 adult MMD patients and 88 age-matched healthy individuals were consecutively recruited. The serum levels of Met cycle-related metabolites were quantified by liquid chromatography-mass spectrometry (LC-MS). Participants were randomly divided into training set and testing set at a ratio of 1:1. The training set was used to construct the risk score model by LASSO regression. The association between Met cycle-related risk score and the risk of MMD was analyzed using logistic regression and assessed by ROC curves. The testing set was used for validation. RESULTS: The levels of methionine sulfoxide and homocysteine were significantly increased, while the levels of betaine and choline were significantly decreased in MMD and its subtypes compared to healthy controls (p < 0.05 for all). The training set was used to construct the risk model and the risk score of each participant has been calculated. After adjusting for potential confounders, the risk score was independently associated with the risk of MMD and its subtypes (p < 0.05 for all). We then divided the participants into low-risk and high-risk groups, the high-risk score was significantly associated with the risk of MMD and its subtypes (p < 0.05 for all). The risk scores were further assessed as tertiles, the highest tertile was significantly associated with a higher risk of MMD and its subtypes compared to the lowest (p < 0.05 for all). The results were validated in the testing set. CONCLUSION: This study has constructed and validated a risk model based on Met cycle-related metabolites, which was independently associated with the risk of MMD and its subtypes. The findings provided a new perspective on the risk evaluation and prevention of MMD.

Association between methionine sulfoxide and risk of moyamoya disease.

Objective: Methionine sulfoxide (MetO) has been identified as a risk factor for vascular diseases and was considered as an important indicator of oxidative stress. However, the effects of MetO and its association with moyamoya disease (MMD) remained unclear. Therefore, we performed this study to evaluate the association between serum MetO levels and the risk of MMD and its subtypes. Methods: We eventually included consecutive 353 MMD patients and 88 healthy controls (HCs) with complete data from September 2020 to December 2021 in our analyzes. Serum levels of MetO were quantified using liquid chromatography-mass spectrometry (LC-MS) analysis. We evaluated the role of MetO in MMD using logistic regression models and confirmed by receiver-operating characteristic (ROC) curves and area under curve (AUC) values. Results: We found that the levels of MetO were significantly higher in MMD and its subtypes than in HCs (p < 0.001 for all). After adjusting for traditional risk factors, serum MetO levels were significantly associated with the risk of MMD and its subtypes (p < 0.001 for all). We further divided the MetO levels into low and high groups, and the high MetO level was significantly associated with the risk of MMD and its subtypes (p < 0.05 for all). When MetO levels were assessed as quartiles, we found that the third (Q3) and fourth (Q4) MetO quartiles had a significantly increased risk of MMD compared with the lowest quartile (Q3, OR: 2.323, 95%CI: 1.088-4.959, p = 0.029; Q4, OR: 5.559, 95%CI: 2.088-14.805, p = 0.001). Conclusion: In this study, we found that a high level of serum MetO was associated with an increased risk of MMD and its subtypes. Our study raised a novel perspective on the pathogenesis of MMD and suggested potential therapeutic targets.

Protein disulfide-isomerase A4 confers glioblastoma angiogenesis promotion capacity and resistance to anti-angiogenic therapy.

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.

Establishment and validation of a novel prognostic model for lower-grade glioma based on senescence-related genes.

Objective: Increasing studies have indicated that senescence was associated with tumorigenesis and progression. Lower-grade glioma (LGG) presented a less invasive nature, however, its treatment efficacy and prognosis prediction remained challenging due to the intrinsic heterogeneity. Therefore, we established a senescence-related signature and investigated its prognostic role in LGGs. Methods: The gene expression data and clinicopathologic features were from The Cancer Genome Atlas (TCGA) database. The experimentally validated senescence genes (SnGs) from the CellAge database were obtained. Then LASSO regression has been performed to build a prognostic model. Cox regression and Kaplan-Meier survival curves were performed to investigate the prognostic value of the SnG-risk score. A nomogram model has been constructed for outcome prediction. Immunological analyses were further performed. Data from the Chinese Glioma Genome Atlas (CGGA), Repository of Molecular Brain Neoplasia Data (REMBRANDT), and GSE16011 were used for validation. Results: The 6-SnG signature has been established. The results showed SnG-risk score could be considered as an independent predictor for LGG patients (HR=2.763, 95%CI=1.660-4.599, P<0.001). The high SnG-risk score indicated a worse outcome in LGG (P<0.001). Immune analysis showed a positive correlation between the SnG-risk score and immune infiltration level, and the expression of immune checkpoints. The CGGA datasets confirmed the prognostic role of the SnG-risk score. And Kaplan-Meier analyses in the additional datasets (CGGA, REMBRANDT, and GSE16011) validated the prognostic role of the SnG-signature (P<0.001 for all). Conclusion: The SnG-related prognostic model could predict the survival of LGG accurately. This study proposed a novel indicator for predicting the prognosis of LGG and provided potential therapeutic targets.

Early 2 factor (E2F) transcription factors contribute to malignant progression and have clinical prognostic value in lower-grade glioma.

Early 2 factor (E2F) genes encoding a family of transcription factors are significantly associated with apoptosis, metabolism, and angiogenesis in several tumor types. However, the biological functions of E2F transcription factors (E2Fs) and their potential involvement in the malignancy of lower-grade glioma (LGG) remain unclear. We explored the effects of the expression of eight E2F family members on the clinical characteristics of LGG based on the Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), and GSE16011 datasets. Two LGG subgroups were identified according to the consensus clustering of the eight E2Fs. We employed the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm for further functional experiments and the development of a potential risk score. Two categories of patients with LGG were identified based on the median risk scores. We then developed a nomogram based on the results of the multivariate analysis. Real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry were performed to validate the bioinformatics results. Our results indicated that E2F family members were significantly involved in the malignancy of LGG and might serve as effective prognostic biomarkers of the disease.

Identification of an epithelial-mesenchymal transition related long non-coding RNA (LncRNA) signature in Glioma.

Epithelial-mesenchymal transition (EMT)-related long non-coding RNAs (lncRNAs) may be exploited as potential therapeutic targets in gliomas. However, the prognostic value of EMT-related lncRNAs in gliomas is unclear. We obtained lncRNAs from The Cancer Genome Atlas and constructed EMT-related lncRNA co-expression networks to identify EMT-related lncRNAs. The Chinese Glioma Genome Atlas (CGGA) was used for validation. Gene set enrichment and principal component analyses were used for functional annotation. The EMT-lncRNA co-expression networks were constructed. A real-time quantitative polymerase chain reaction assay was performed to validate the bioinformatics results. A nine-EMT-related lncRNAs (HAR1A, LINC00641, LINC00900, MIR210HG, MIR22HG, PVT1, SLC25A21-AS1, SNAI3-AS1, and SNHG18) signature was identified in patients with glioma. Patients in the low-risk group had a longer overall survival (OS) than those in the high-risk group (P < 0.0001). Additionally, patients in the high-risk group showed no deletion of chromosomal arms 1p and/or 19q, isocitrate dehydrogenase wild type, and higher World Health Organization grade. Moreover, the signature was identified as an independent factor and was significantly associated with OS (P = 0.041, hazard ratio = 1.806). These findings were further validated using the CGGA dataset. The low- and high-risk groups showed different EMT statuses based on principal component analysis. To study the regulatory function of lncRNAs, a lncRNA-mediated ceRNA network was constructed, which showed that complex interactions of lncRNA-miRNA-mRNA may be a potential cause of EMT progression in gliomas. This study showed that the nine-EMT-related lncRNA signature has a prognostic value in gliomas.

Prognostic and Predictive Value of Immune-Related Gene Pair Signature in Primary Lower-Grade Glioma Patients.

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.

A risk signature of four aging-related genes has clinical prognostic value and is associated with a tumor immune microenvironment in glioma.

An accumulation of studies has indicated aging to be a significant hazard factor for the development of tumors. Cellular senescence is positively associated with aging progress and aging-related genes (AGs) can regulate cellular senescence and tumor malignancy. While the association between AGs and the prognosis of patients with glioma is still unclear. In our study, we initially selected four survival-associated AGs and performed consensus clustering for these AGs based on The Cancer Genome Atlas (TCGA) database. We then explored the potential biological effects of four selected AGs. A prognostic risk model was constructed according to four selected AGs (LEP, TERT, PON1, and SSTR3) in the TCGA dataset and Chinese Glioma Genome Atlas (CGGA) database. Then we indicated the risk score was an independent prognostic index, and was also positively correlated with immune scores, estimate score, immune cell infiltration level, programmed death ligand 1 (PD-L1) expression, and expression of proinflammatory factors in patients with glioma. Finally, we performed the RT-qPCR and immunohistochemistry assay to validate our bioinformatics results. Thus, this study indicated the risk model was concluded to possibly have potential function as an immune checkpoint inhibitor and to provide promising targets for developing individualized immunotherapies for patients with glioma.

Systematic and Multi-Omics Prognostic Analysis of Lysine Acetylation Regulators in Glioma.

Lysine acetylation modification, which has key roles in cellular homeostasis as well as cancer malignancy, is dynamically regulated by lysine acetylation regulators (LARs). In our study, we found that most of 33 evaluated LARs were differentially expressed among 1,125 gliomas grouped by different clinicopathological characteristics. Consensus clustering was applied to 33 LARs, resulting in three glioma subtypes (LA1, 2, and 3). The LA3 subgroup was associated with the poorest clinical outcome, higher WHO grade, fewer isocitrate dehydrogenase mutations, and lower frequency of 1p/19q codeletion. Furthermore, gene set enrichment analysis indicated that eight tumor hallmarks were highly enriched in the LA3 subgroup. These results suggested that LARs are significantly related to glioma malignancy. We then designed a LAR-signature based on 14 overall survival (overall survival)-related LARs, and showed that the LAR-signature possesses strong and independent prognostic value for glioma patients in both training and validation datasets. Moreover, by interrogating single nucleotide polymorphism and copy number variation (CNV) data in The Cancer Genome Atlas dataset, we found that higher score of our risk signature is correlated with the hypermutation status of gliomas and that HDAC1(1p) was one of the oncogenes lost in 1p/19q codeletion events, while SIRT2(19q) and EP300(22q) may act as tumor suppressors in gliomas with 19q or 22q deletions, respectively. In conclusion, LARs are critical for the malignant development of gliomas, and our results are useful for prognostic stratification and development of novel assessment strategies for the prognosis of glioma patients.

Development of a prognostic index based on immunogenomic landscape analysis in glioma.

BACKGROUND: Glioma is the most common intracranial tumor. The inflammatory response actively participates in the malignancy of gliomas. There is still limited knowledge about the biological function of immune-related genes (IRGs) and their potential involvement in the malignancy of gliomas. METHODS: We screened differentially expressed and survival-associated IRGs, and explored their potential molecular characteristics. Then we developed a prognostic index derived from seven hub IRGs. A prognostic nomogram was built to indicate the prognostic value of the prognostic index and seven IRGs. We characterized the immune infiltration landscape to analyze tumor-immune interactions. The real-time quantitative polymerase chain reaction assay was performed to validate bioinformatics results. RESULTS: The differentially expressed IRGs are involved in cell chemotaxis, cytokine activity, and the chemokine-mediated signaling pathway. The prognostic index derived from seven IRGs had clinical prognostic value in glioma, and positively correlated with the malignant clinicopathological characteristics. A nomogram further indicated that the prognostic index and seven hub IRGs had clinical prognostic value for gliomas. We revealed that the prognostic index could reflect the state of the glioma immune microenvironment. CONCLUSION: This study demonstrates the importance of an IRG-based prognostic index as a potential biomarker for predicting malignancy in gliomas.

Identification of RNA: 5-Methylcytosine Methyltransferases-Related Signature for Predicting Prognosis in Glioma.

Background: Glioma is the most common primary intracranial tumor, accounting for the vast majority of intracranial malignant tumors. Aberrant expression of RNA:5-methylcytosine(m5C) methyltransferases have recently been the focus of research relating to the occurrence and progression of tumors. However, the prognostic value of RNA:m5C methyltransferases in glioma remains unclear. This study investigated RNA: m5C methyltransferase expression and defined its clinicopathological signature and prognostic value in gliomas. Methods: We obtained the RNA-sequence and Clinicopathological data of RNA:m5C methyltransferases underlying gliomas from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets. We analyzed the expression of RNA:m5C methyltransferase genes in gliomas with different clinicopathological characteristics and identified different subtypes using Consensus clustering analysis. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) was used to annotate the function of these genes. Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm analyses were performed to construct the risk signature. Kaplan-Meier method and Receiver operating characteristic (ROC) curves were used to assess the overall survival of glioma patients. Additionally, Cox proportional regression model analysis was developed to address the connections between the risk scores and clinical factors. Results: We revealed the differential expression of RNA:m5C methyltransferase genes in gliomas with different clinicopathological features. Consensus clustering of RNA:m5C methyltransferases identified three clusters of gliomas with different prognostic and clinicopathological features. Meanwhile, functional annotations demonstrated that RNA:m5C methyltransferases were significantly associated with the malignant progression of gliomas. Thereafter, five RNA:m5C methyltransferase genes were screened to construct a risk signature that can be used to predict not only overall survival but also clinicopathological features in gliomas. ROC curves revealed the significant prognostic ability of this signature. In addition, Multivariate Cox regression analyses indicated that the risk score was an independent prognostic factor for glioma outcome. Conclusion: We demonstrated the prognostic role of RNA:m5C methyltransferases in the initiation and progression of glioma. We have expanded on the understanding of the molecular mechanism involved, and provided a unique approach to predictive biomarkers and targeted therapy for gliomas.