Ligen Mo

Background: Glioma develops within a strongly immunosuppressive tumor microenvironment (TME), which contributes to poor therapeutic response and unfavorable prognosis. Although C-C Chemokine Receptor Type 5 (CCR5) has previously been associated with glioma progression, prognosis, and tumor microenvironment remodeling, its cell-type-specific expression pattern and spatial context within the heterogeneous glioma microenvironment remain incompletely characterized. Methods: A comprehensive multi-omics analysis was conducted by integrating bulk transcriptomic profiles from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) cohorts with single-cell RNA sequencing and spatial transcriptomics datasets. The expression pattern, prognostic value, and immune-related functions of CCR5 were systematically evaluated. To estimate immune infiltration, Tumor Immune Estimation Resource (TIMER), Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT), and Single-sample Gene Set Enrichment Analysis (ssGSEA) algorithms computational approaches were applied. A prognostic nomogram incorporating CCR5 and clinical variables was constructed and validated. Experimental validation was performed using immunohistochemistry, Western blotting, and dual immunofluorescence staining. Results: CCR5 expression was markedly elevated in glioma and associated with more aggressive clinicopathological characteristics, including advanced WHO grade, Isocitrate Dehydrogenase (IDH) wild-type status, and 1p/19q non-codeletion. Elevated CCR5 expression predicted significantly worse overall survival across the TCGA and CGGA cohorts, while remaining independently associated with patient prognosis following multivariate analysis. Functional annotation indicated that CCR5 was predominantly associated with immune-related biological processes and signaling pathways, particularly cytokine–cytokine receptor interactions. Immune infiltration analyses demonstrated that CCR5 expression was closely associated with macrophage-related immune features, regulatory T cells, and multiple inhibitory immune checkpoint molecules. Single-cell transcriptomic analysis showed that detectable CCR5 transcripts were preferentially distributed in macrophage-associated populations. Spatial transcriptomic analysis further revealed sparse and heterogeneous CCR5 distribution, with context-dependent spatial relationships between CCR5-detectable regions and macrophage-associated transcriptional features. Experimental validation confirmed increased CCR5 protein expression in high-grade glioma tissues, while dual immunofluorescence demonstrated CCR5 colocalization with CD163-positive macrophages in glioma tissues. Conclusions: Our integrative analyses associate elevated CCR5 expression with unfavorable prognosis and a macrophage-enriched immunosuppressive microenvironment in glioma. By resolving CCR5 expression across bulk, single-cell, and spatial transcriptomic levels, this study provides additional cellular and spatial context for its previously reported clinical and immunological relevance. These findings support further investigation of the potential role of CCR5 in macrophage-associated immune remodeling in glioma.

Background: Metabolic dysfunction and hepatic steatosis-related phenotypes have increasingly been linked to extrahepatic malignancies, including breast cancer. The association between the Framingham Steatosis Index (FSI), a composite index incorporating age and multiple metabolic components, and prevalent breast cancer in women has not been well characterized. Methods: We conducted a cross-sectional analysis of female participants in the National Health and Nutrition Examination Survey (NHANES) 1999–2018. Multivariable logistic regression models were used to evaluate the association between FSI and prevalent breast cancer, with FSI analyzed as both a continuous variable and by quartiles. Restricted cubic spline analysis and generalized additive modeling were applied to assess potential non-linearity, and two-piecewise logistic regression was used to explore a possible threshold effect. Component-level and AUC analyses compared FSI with its individual components. An exploratory hospital-based supportive dataset was analyzed to assess whether the continuous association showed a similar direction in a different clinical setting. Results: Among 21,042 women in NHANES, 531 (2.5%) reported a history of breast cancer. In the fully adjusted model, each 1-unit increase in FSI was associated with higher odds of prevalent breast cancer (OR 1.10, 95% CI 1.05–1.16). After additional adjustment for age, the association was substantially attenuated and no longer statistically significant (OR 1.02, 95% CI 0.96–1.07). Higher FSI quartiles were also associated with greater odds of prevalent breast cancer. Restricted cubic spline analysis suggested a non-linear association. In component-level analyses, age showed the strongest association and discriminatory performance among the FSI components, whereas adding FSI to the base model only modestly increased the AUC. In the exploratory hospital-based dataset, FSI was positively associated with breast cancer case status when modeled continuously, but the quartile-based dose-response pattern was not reproduced after full adjustment. Conclusions: In the primary NHANES analysis, higher FSI was associated with prevalent breast cancer status in women; however, this association was substantially attenuated after additional adjustment for age. FSI should therefore be interpreted as a composite marker of metabolic-hepatic burden rather than as an age-independent hepatic steatosis effect or causal biomarker.

Metabolic–inflammatory dysregulation contributes to cerebrovascular vulnerability, yet accessible composite indices for population-level stratification remain under active investigation. Using nationally representative data from U. S. adults in NHANES 1999–2018, we investigated the association between the uric acid to high-density lipoprotein cholesterol ratio (UHR) and prevalent stroke. Survey-weighted multivariable logistic regression and restricted cubic spline models were applied with comprehensive adjustment for demographic, metabolic, and socioeconomic factors. Higher UHR levels were independently associated with increased odds of prevalent stroke [1.02 (1.01–1.03)]. Individuals within the top UHR quartile exhibited roughly a 37% higher stroke prevalence compared with those in the lowest quartile [1.37 (1.17–1.61)]. Restricted Cubic Spline analyses demonstrated an approximately linear association between UHR and stroke prevalence (P for nonlinearity = 0.62). Cross-sectional discrimination assessed by survey-weighted ROC analysis yielded an AUC of 0.825, which should be interpreted as differentiation of prevalent stroke rather than prognostic prediction. Diabetes status significantly modified the association (P for interaction < 0.05), with a stronger relationship observed among non-diabetic individuals. To assess robustness across settings and phenotype definitions, we further evaluated UHR in an independent Chinese hospital-based cohort with imaging-confirmed hemorrhagic stroke, which showed directionally consistent associations. Collectively, these findings support UHR as a clinically accessible, hypothesis-generating marker capturing metabolic–inflammatory imbalance relevant to cerebrovascular pathology and motivate future longitudinal and mechanistic studies.

Formyl peptide receptor 3 (FPR3) is known to have implications in the progression of various cancer types. Despite this, its biological significance within pan-cancer datasets has yet to be investigated. In this investigation, we scrutinized FPR3’s expression profiles, genetic alterations, prognostic significance, immune-related characteristics, methylation status, tumor mutation burden (TMB), and microsatellite instability (MSI) across different types of cancer. We utilized TISCH’s single-cell data to identify immune cells closely associated with FPR3. The predictive significance of FPR3 was evaluated independently in gliomas using data from TCGA and CGGA datasets, leading to the development of a prognostic nomogram. Immunohistochemistry and Western blot analysis confirmed FPR3 expression in gliomas. Lastly, the CCK-8 and wound-healing assays were employed to assess the impact of FPR3 on the proliferation and metastasis of GBM cell lines. In numerous cancer types, heightened FPR3 expression correlated with adverse outcomes, immune cell infiltration, immune checkpoints, TMB, and MSI. In glioma, FPR3 emerged as a notable risk factor, with the prognostic model effectively forecasting patient results. The potential biological relevance of FPR3 was confirmed in glioma, and it was shown to have significant involvement in the processes of glioma growth, immune infiltration, and metastasis. Our results imply a potential association of FPR3 with tumor immunity, indicating its viability as a prognostic indicator in glioma.

Intracerebral hemorrhage (ICH) is the second-largest stroke subtype and has a high mortality and disability rate. Secondary brain injury (SBI) is delayed after ICH. The main contributors to SBI are inflammation, oxidative stress, and excitotoxicity. Harmful substances from blood and hemolysis, such as hemoglobin, thrombin, and iron, induce SBI. When cells suffer stress, a critical protective mechanism called “autophagy” help to maintain the homeostasis of damaged cells, remove harmful substances or damaged organelles, and recycle them. Autophagy plays a critical role in the pathology of ICH, and its function remains controversial. Several lines of evidence demonstrate a pro-survival role for autophagy in ICH by facilitating the removal of damaged proteins and organelles. However, many studies have found that heme and iron can aggravate SBI by enhancing autophagy. Autophagy and inflammation are essential culprits in the progression of brain injury. It is a fascinating hypothesis that autophagy regulates inflammation in ICH-induced SBI. Autophagy could degrade and clear pro-IL-1β and apoptosis-associated speck-like protein containing a CARD (ASC) to antagonize NLRP3-mediated inflammation. In addition, mitophagy can remove endogenous activators of inflammasomes, such as reactive oxygen species (ROS), inflammatory components, and cytokines, in damaged mitochondria. However, many studies support the idea that autophagy activates microglia and aggravates microglial inflammation via the toll-like receptor 4 (TLR4) pathway. In addition, autophagy can promote ICH-induced SBI through inflammasome-dependent NLRP6-mediated inflammation. Moreover, some resident cells in the brain are involved in autophagy in regulating inflammation after ICH. Some compounds or therapeutic targets that regulate inflammation by autophagy may represent promising candidates for the treatment of ICH-induced SBI. In conclusion, the mutual regulation of autophagy and inflammation in ICH is worth exploring. The control of inflammation by autophagy will hopefully prove to be an essential treatment target for ICH.

Stroke is the leading cause of disability and death worldwide, with ischemic stroke occurring in ~5% of the global population every year. Recently, many studies have been conducted on the inflammatory response after stroke. Microglial/macrophage polarization has a dual function and is critical to the pathology of ischemic stroke. Microglial/macrophage activation is important in reducing neuronal apoptosis, enhancing neurogenesis, and promoting functional recovery after ischemic stroke. In this review, we investigate the physiological characteristics and functions of microglia in the brain, the activation and phenotypic polarization of microglia and macrophages after stroke, the signaling mechanisms of polarization states, and the contribution of microglia to brain pathology and repair. We summarize recent advances in stroke-related microglia research, highlighting breakthroughs in therapeutic strategies for microglial responses after stroke, thereby providing new ideas for the treatment of ischemic stroke.

Background: The prognosis of lower-grade glioma (LGG) is highly variable, and more accurate predictors are still needed. The aim of our study was to explore the prognostic value of ferroptosis-related long non-coding RNAs (lncRNAs) in LGG and to develop a novel risk signature for predicting survival with LGG. Methods: We first integrated multiple datasets to screen for prognostic ferroptosis-related lncRNAs in LGG. A least absolute shrinkage and selection operator (LASSO) analysis was then utilized to develop a risk signature for prognostic prediction. Based on the results of multivariate Cox analysis, a prognostic nomogram model for LGG was constructed. Finally, functional enrichment analysis, single-sample gene set enrichment analysis (ssGSEA), immunity, and m6A correlation analyses were conducted to explore the possible mechanisms by which these ferroptosis-related lncRNAs affect survival with LGG. Results: A total of 11 ferroptosis-related lncRNAs related to the prognosis of LGG were identified. Based on prognostic lncRNAs, a risk signature consisting of 8 lncRNAs was constructed and demonstrated good predictive performance in both the training and validation cohorts. Correlation analysis suggested that the risk signature was closely linked to clinical features. The nomogram model we constructed by combining the risk signature and clinical parameters proved to be more accurate in predicting the prognosis of LGG. In addition, there were differences in the levels of immune cell infiltration, immune-related functions, immune checkpoints, and m6A-related gene expression between the high- and low-risk groups. Conclusion: In summary, our ferroptosis-related lncRNA signature exhibits good performance in predicting the prognosis of LGG. This study may provide useful insight into the treatment of LGG.

Background: C–C chemokine receptor type 1 (CCR1) and its endogenous ligand, CCL5, participate in the pathogenesis of neuroinflammatory diseases. However, much remains unknown regarding CCL5/CCR1 signaling in blood–brain barrier (BBB) permeability after intracerebral hemorrhage (ICH).Methods: A total of 250 CD1 male mice were used and ICH was induced via autologous whole blood injection. Either Met-RANTES, a selective CCR1 antagonist, or Met-RANTES combined with a Rac1 CRISPR activator was administered to the mice 1 h after ICH. Post-ICH assessments included neurobehavioral tests, brain water content, BBB integrity, hematoma volume, Western blot, and immunofluorescence staining. The CCR1 ligand, rCCL5, and SRC CRISPR knockout in naïve mice were used to further elucidate detrimental CCL5/CCR1/SRC signaling.Results: Brain endogenous CCR1 and CCL5 were upregulated after ICH in mice with a peak at 24 h, and CCR1 was expressed in endothelial cells, astrocytes, and neurons. Met-R treatment reduced brain edema and neurobehavioral impairment, as well as preserved BBB integrity and tight junction protein expression in ICH mice. Met-R treatment decreased expression of p-SRC, Rac1, albumin, and MMP9, but increased claudin-5, occludin, and ZO-1 tight junction proteins after ICH. These effects were regressed using the Rac1 CRISPR activator. Administration of rCCL5 in naïve mice increased expression of p-SRC, Rac1, albumin, and MMP9, but decreased levels of claudin-5, occludin, and ZO-1 tight junction proteins. These effects in naïve mice were reversed with SRC CRISPR (KO).Conclusions: Our findings demonstrate that CCR5 inhibition by Met-R improves neurological deficits after ICH by preserving BBB integrity through inhibiting CCR1/SRC/Rac1 signaling pathway in mice. Thus, Met-R has therapeutic potential in the management of ICH patients.

Objective: The present study used the RNA sequencing (RNA-seq) dataset to identify prognostic snoRNAs and construct a prognostic signature of The Cancer Genome Atla (TCGA) lower grade glioma (LGG) cohort, and comprehensive analysis of this signature. Methods: RNA-seq dataset of 488 patients from TCGA LGG cohort were included in this study. Comprehensive analysis including function enrichment, gene set enrichment analysis (GSEA), immune infiltration, cancer immune microenvironment, and connectivity map (CMap) were used to evaluate the snoRNAs prognostic signature. Results: We identified 21 LGG prognostic snoRNAs and constructed a novel eleven-snoRNA prognostic signature for LGG patients. Survival analysis suggests that this signature is an independent prognostic risk factor for LGG, and the prognosis of LGG patients with a high-risk phenotype is poor (adjusted P = 0.003, adjusted hazard ratio = 2.076, 95% confidence interval = 1.290–3.340). GSEA and functional enrichment analysis suggest that this signature may be involved in the following biological processes and signaling pathways: such as cell cycle, Wnt, mitogen-activated protein kinase, janus kinase/signal transducer and activator of tran-ions, T cell receptor, nuclear factor-kappa B signaling pathway. CMap analysis screened out ten targeted therapy drugs for this signature: 15-delta prostaglandin J2, MG-262, vorinostat, 5155877, puromycin, anisomycin, withaferin A, ciclopirox, chloropyrazine and megestrol. We also found that high- and low-risk score phenotypes of LGG patients have significant differences in immune infiltration and cancer immune microenvironment. Conclusions: The present study identified a novel eleven-snoRNA prognostic signature of LGG and performed a integrative analysis of its molecular mechanisms and relationship with tumor immunity.