The role of neutrophil extracellular traps (NETs) in procoagulant activity (PCA) in stroke patients caused by thromboembolic occlusion of the internal carotid artery (ICA) remains unclear. Our objectives were to evaluate the critical role of NETs in the induction of hypercoagulability in stroke and to identify the functional significance of NETs during atherothrombosis. The levels of NETs, activated platelets (PLTs), and PLT-derived microparticles (PMPs) were detected in the plasma of 55 stroke patients and 35 healthy controls. NET formation and thrombi were analysed using immunofluorescence. Exposed phosphatidylserine (PS) was evaluated with flow cytometry and confocal microscopy. PCA was analysed using purified coagulation complex, thrombin, and fibrin formation assays. The plasma levels of NETs, activated PLTs, and PMP markers in the carotid lesion site (CLS) were significantly higher than those in the aortic blood. NETs were decorated with PS in thrombi and the CLS plasma of ICA occlusion patients. Notably, the complementary roles of CLS plasma and thrombin-activated PLTs were required for NET formation and subsequent PS exposure. PS-bearing NETs provided functional platforms for PMPs and coagulation factor deposition and thus increased thrombin and fibrin formation. DNase I and lactadherin markedly inhibited these effects. In addition, NETs were cytotoxic to endothelial cells, converting these cells to a procoagulant phenotype. Sivelestat, anti-MMP9 antibody, and activated protein C (APC) blocked this cytotoxicity by 25%, 39%, or 52%, respectively. NETs played a pivotal role in the hypercoagulability of stroke patients. Strategies that prevent NET formation may offer a potential therapeutic strategy for thromboembolism interventions. This study was supported by grants from the National Natural Science Foundation of China (61575058, 81873433 and 81670128) and Graduate Innovation Fund of Harbin Medical University (YJSKYCX2018-58HYD).

M6A RNA methylation is an emerging epigenetic modification, and its potential role in immunity and stemness remains unknown. Based on 17 widely recognized m6A regulators, the m6A modification patterns and corresponding characteristics of immune infiltration and stemness of 1152 low-grade glioma samples were comprehensively analyzed. Machine-learning strategies for constructing m6AScores were trained to quantify the m6A modification patterns of individual samples. Here, we reveal a significant correlation between the multi-omics data of regulators and clinicopathological parameters. We identified two distinct m6A modification patterns (an immune-activated differentiation pattern and an immune-desert dedifferentiation pattern) and four regulatory patterns of m6A methylation on immunity and stemness. We show that the m6AScores can predict the molecular subtype of low-grade glioma, the abundance of immune infiltration, the enrichment of signaling pathways, gene variation and prognosis. The concentration of high immunogenicity and clinical benefits in the low-m6AScore group confirmed the sensitive response to radio-chemotherapy and immunotherapy in patients with high-m6AScore. The results of the pan-cancer analyses illustrate the significant correlation between m6AScore and clinical outcome, the burden of neoepitope, immune infiltration and stemness. The assessment of individual tumor m6A modification patterns will guide us in improving treatment strategies and developing objective diagnostic tools.

The progression of most human cancers mainly involves the gradual accumulation of the loss of differentiated phenotypes and the sequential acquisition of progenitor and stem cell-like features. Glioblastoma multiforme (GBM) stem cells (GSCs), characterized by self-renewal and therapeutic resistance, play vital roles in GBM. However, a comprehensive understanding of GBM stemness remains elusive. Two stemness indices, mRNAsi and EREG-mRNAsi, were employed to comprehensively analyze GBM stemness. We observed that mRNAsi was significantly related to multi-omics parameters (such as mutant status, sample type, transcriptomics, and molecular subtype). Moreover, potential mechanisms and candidate compounds targeting the GBM stemness signature were illuminated. By combining weighted gene co-expression network analysis with differential analysis, we obtained 18 stemness-related genes, 10 of which were significantly related to survival. Moreover, we obtained a prediction model from both two independent cancer databases that was not only an independent clinical outcome predictor but could also accurately predict the clinical parameters of GBM. Survival analysis and experimental data confirmed that the five hub genes (CHI3L2, FSTL3, RPA3, RRM2, and YTHDF2) could be used as markers for poor prognosis of GBM. Mechanistically, the effect of inhibiting the proliferation of GSCs was attributed to the reduction of the ratio of CD133 and the suppression of the invasiveness of GSCs. The results based on an in vivo xenograft model are consistent with the finding that knockdown of the hub gene inhibits the growth of GSCs in vitro. Our approach could be applied to facilitate the development of objective diagnostic and targeted treatment tools to quantify cancer stemness in clinical tumors, and perhaps lead considerable benefits that could predict tumor prognosis, identify new stemness-related targets and targeted therapies, or improve targeted therapy sensitivity. The five genes identified in this study are expected to be the targets of GBM stem cell therapy.

Objective: We developed and validated a clinical-radiomics nomogram to predict the prognosis of basal ganglia hemorrhage patients.Methods: Retrospective analyses were conducted in 197 patients with basal ganglia hemorrhage (training cohort: n = 136, test cohort: n = 61) who were admitted to The First Affiliated Hospital of Shandong First Medical University (Shandong Provincial Qianfoshan Hospital) and underwent computed tomography (CT) scan. According to different prognoses, patients with basal ganglia hemorrhage were divided into two groups. Independent clinical risk factors were derived with univariate and multivariate regression analysis. Radiomics signatures were obtained using least absolute shrinkage and selection operator. A radiomics score (Rad-score) was generated by 12 radiomics signatures of perihematomal edema (PHE) from CT images that were correlated with the prognosis of basal ganglia hemorrhage patients. A clinical-radiomics nomogram was conducted by combing the Rad-score and clinical risk factors using logistic regression analysis. The prediction performance of the nomogram was tested in the training cohort and verified in the test cohort.Results: The clinical model conducted by four clinical risk factors and 12 radiomcis features were used to establish the Rad-score. The clinical-radiomics nomogram outperformed the clinical model in the training cohort [area under the curve (AUC), 0.92 vs. 0.85] and the test cohort (AUC, 0.91 vs 0.85). The clinical-radiomics nomogram showed good calibration and clinical benefit in both the training and test cohorts.Conclusion: Radiomics features of PHE in patients with basal ganglia hemorrhage could contribute to the outcome prediction. The clinical-radiomics nomogram may help first-line clinicians to make individual clinical treatment decisions for patients with basal ganglia hemorrhage.