Shared and malignancy-specific functional plasticity of dynamic brain properties for patients with left frontal glioma.

The time-varying brain activity may parallel the disease progression of cerebral glioma. Assessment of brain dynamics would better characterize the pathological profile of glioma and the relevant functional remodeling. This study aims to investigate the dynamic properties of functional networks based on sliding-window approach for patients with left frontal glioma. The generalized functional plasticity due to glioma was characterized by reduced dynamic amplitude of low-frequency fluctuation of somatosensory networks, reduced dynamic functional connectivity between homotopic regions mainly involving dorsal attention network and subcortical nuclei, and enhanced subcortical dynamic functional connectivity. Malignancy-specific functional remodeling featured a chaotic modification of dynamic amplitude of low-frequency fluctuation and dynamic functional connectivity for low-grade gliomas, and attenuated dynamic functional connectivity of the intrahemispheric cortico-subcortical connections and reduced dynamic amplitude of low-frequency fluctuation of the bilateral caudate for high-grade gliomas. Network dynamic activity was clustered into four distinct configuration states. The occurrence and dwell time of the weakly connected state were reduced in patients' brains. Support vector machine model combined with predictive dynamic features achieved an averaged accuracy of 87.9% in distinguishing low- and high-grade gliomas. In conclusion, dynamic network properties are highly predictive of the malignant grade of gliomas, thus could serve as new biomarkers for disease characterization.

Multi-scale brain attributes contribute to the distribution of diffuse glioma subtypes.

Gliomas are primary brain tumors and are among the most malignant types. Adult-type diffuse gliomas can be classified based on their histological and molecular signatures as IDH-wildtype glioblastoma, IDH-mutant astrocytoma, and IDH-mutant and 1p/19q-codeleted oligodendroglioma. Recent studies have shown that each subtype of glioma has its own specific distribution pattern. However, the mechanisms underlying the specific distributions of glioma subtypes are not entirely clear despite partial explanations such as cell origin. To investigate the impact of multi-scale brain attributes on glioma distribution, we constructed cumulative frequency maps for diffuse glioma subtypes based on T1w structural images and evaluated the spatial correlation between tumor frequency and diverse brain attributes, including postmortem gene expression, functional connectivity metrics, cerebral perfusion, glucose metabolism, and neurotransmitter signaling. Regression models were constructed to evaluate the contribution of these factors to the anatomic distribution of different glioma subtypes. Our findings revealed that the three different subtypes of gliomas had distinct distribution patterns, showing spatial preferences toward different brain environmental attributes. Glioblastomas were especially likely to occur in regions enriched with synapse-related pathways and diverse neurotransmitter receptors. Astrocytomas and oligodendrogliomas preferentially occurred in areas enriched with genes associated with neutrophil-mediated immune responses. The functional network characteristics and neurotransmitter distribution also contributed to oligodendroglioma distribution. Our results suggest that different brain transcriptomic, neurotransmitter, and connectomic attributes are the factors that determine the specific distributions of glioma subtypes. These findings highlight the importance of bridging diverse scales of biological organization when studying neurological dysfunction.

Structural changes in eloquent cortex secondary to glioma in sensorimotor area.

This study aims to investigate the structural reorganization in the sensorimotor area of the brain in patients with gliomas, distinguishing between those with impaired and unimpaired strength. Using voxel-based morphometry (VBM) and region of interest (ROI) analysis, gray matter volumes (GMV) were compared in the contralesional primary motor gyrus, primary sensory gyrus, premotor area, bilateral supplementary motor area, and medial Brodmann area 8 (BA8). The results revealed that in patients with right hemisphere gliomas, the right medial BA8 volume was significantly larger in the impaired group than in the unimpaired group, with both groups exceeding the volume in 16 healthy controls (HCs). In patients with left hemisphere gliomas, the right supplementary motor area (SMA) was more pronounced in the impaired group compared to the unimpaired group, and both groups were greater than HCs. Additionally, the volumes of the right medial BA8 in both the impaired group were greater than HCs. Contralateral expansions in the gray matter of hand- and trunk-related cortices of the premotor area, precentral gyrus, and postcentral gyrus were observed compared to HCs. Furthermore, a negative correlation was found between hand Medical Research Council (MRC) score and volumes of the contralateral SMA and bilateral medial BA8. Notably, our findings reveal consistent results across both analytical approaches in identifying significant structural reorganizations within the sensorimotor cortex. These consistent findings underscore the adaptive neuroplastic responses to glioma presence, highlighting potential areas of interest for further neurosurgical planning and rehabilitation strategies.

Decreasing distance from tumor to the language network causes language deficit.

Preoperative language deficits are associated with alterations in the language networks of patients with gliomas. This study investigated how gliomas affect language performance by altering the language network. Ninety patients with lower-grade gliomas were included, and their preoperative language performance was evaluated using the Western Aphasia Battery. We also calculated the topological properties based on resting state functional magnetic resonance imaging. All patients were classified according to aphasia quotient (AQ) into the aphasia (AQ < 93.8), mild anomia (AQ > 93.8 and naming section <9.8), and normal groups (AQ > 93.8). The shortest distance from the tumor to the language network (SDTN) was evaluated to identify the effect on language performance induced by the tumor. One-way analysis of variance and post hoc analysis with Sidak correction were used to analyze the differences in topological properties among the three groups. Causal mediation analysis was used to identify indirectly affected mediators. Compared with the mild anomia group, longer shortest path length (p = .0016), lower vulnerability (p = .0331), and weaker nodal efficiencies of three nodes (right caudal Brodmann area [BA] 45, right caudal BA 22, and left BA 41/42, all p < .05) were observed in the aphasia group. The SDTN mediated nodal degree centrality and nodal vulnerability (left rostroventral BA 39), which negatively affected the AQs. Conventional language eloquent and mirrored areas participated in the language network alterations induced by gliomas. The SDTN was a mediator that affected the preoperative language status in patients with gliomas.

Personalized fMRI Delineates Functional Regions Preserved within Brain Tumors.

OBJECTIVE: Accumulating evidence from invasive cortical stimulation mapping and noninvasive neuroimaging studies indicates that brain function may be preserved within brain tumors. However, a noninvasive approach to accurately and comprehensively delineate individual-specific functional networks in the whole brain, especially in brain tissues within and surrounding tumors, is still lacking. The purpose of the study is to develop a clinically useful technique that can map functional regions within tumoral brains. METHODS: We developed an individual-specific functional network parcellation approach using resting state functional magnetic resonance imaging (rsfMRI) that effectively captured functional networks within and nearby tumors in 20 patients. We examined the accuracy of the functional maps using invasive cortical stimulation and task response. RESULTS: We found that approximately 33.2% of the tumoral mass appeared to be functionally active and demonstrated robust functional connectivity with non-tumoral brain regions. Functional networks nearby tumors were validated by invasive cortical stimulation mapping. Intratumoral sensorimotor networks mapped by our technique could be distinguished by their distinct cortico-cerebellar connectivity patterns and were consistent with hand movement evoked fMRI task activations. Furthermore, in some patients, cognitive networks that were detected in the tumor mass showed long-distance and distributed functional connectivity. INTERPRETATION: Our noninvasive approach to mapping individual-specific functional networks using rsfMRI represents a promising new tool for identifying regions with preserved functional connectivity within and surrounding brain tumors, and could be used as a complement to presurgical planning for patients undergoing tumor resection surgery. ANN NEUROL 2022;91:353-366.

Development of an integrated predictive model for postoperative glioma-related epilepsy using gene-signature and clinical data.

BACKGROUND: This study aimed to develop an integrated model for predicting the occurrence of postoperative seizures in patients with diffuse high-grade gliomas (DHGGs) using clinical and RNA-seq data. METHODS: Patients with DHGGs, who received prophylactic anti-epileptic drugs (AEDs) for three months following surgery, were enrolled into the study. The patients were assigned randomly into training (n = 166) and validation (n = 42) cohorts. Differentially expressed genes (DEGs) were identified based on preoperative glioma-related epilepsy (GRE) history. Least absolute shrinkage and selection operator (LASSO) logistic regression analysis was used to construct a predictive gene-signature for the occurrence of postoperative seizures. The final integrated prediction model was generated using the gene-signature and clinical data. Receiver operating characteristic analysis and calibration curve method were used to evaluate the accuracy of the gene-signature and prediction model using the training and validation cohorts. RESULTS: A seven-gene signature for predicting the occurrence of postoperative seizures was developed using LASSO logistic regression analysis of 623 DEGs. The gene-signature showed satisfactory predictive capacity in the training cohort [area under the curve (AUC) = 0.842] and validation cohort (AUC = 0.751). The final integrated prediction model included age, temporal lobe involvement, preoperative GRE history, and gene-signature-derived risk score. The AUCs of the integrated prediction model were 0.878 and 0.845 for the training and validation cohorts, respectively. CONCLUSION: We developed an integrated prediction model for the occurrence of postoperative seizures in patients with DHGG using clinical and RNA-Seq data. The findings of this study may contribute to the development of personalized management strategies for patients with DHGGs and improve our understanding of the mechanisms underlying GRE in these patients.

Decision system for extent of resection in WHO grade 3 gliomas: a Chinese Glioma Genome Atlas database analysis.

BACKGROUND: Extensive surgical resection has been found to be associated with longer survival in patients with gliomas, but the interactive prognostic value of molecular pathology of the surgical resection is unclear. This study evaluated the impact of molecular pathology and clinical characteristics on the surgical benefit in WHO grade 3 IDH-mutant gliomas. METHODS: Clinical and pathological information of 246 patients with WHO grade 3 IDH-mutant gliomas were collected from the Chinese Glioma Genome Atlas database (2006-2020). The role of the extent of resection on overall survival, stratified by molecular pathology and clinical characteristics, was investigated. We then assessed prognostic factors using a univariate log-rank test and multivariate Cox proportional hazards model in the subgroups. RESULTS: The extent of resection was an independent prognostic factor in the entire cohort, even when adjusted for molecular pathology. Gross total resection was found to be associated with longer survival in all patients and in the astrocytoma group but not in the oligodendroglioma group. Compared with subtotal resections, gross total resections resulted in a longer survival time for astrocytoma patients aged ≤ 45 years. However, there was no survival benefit from total resection in patients with astrocytoma aged > 45 years. CONCLUSIONS: Extensive resection benefits only a proportion of patients with WHO grade 3 IDH-mutant gliomas. Younger patients with astrocytomas had survival benefits from extensive resection. In addition to clinical characteristics (especially age), molecular pathology impacted prognosis in patients with gliomas. Our findings provide guiding information to neurosurgeons while planning surgeries.

Epilepsy-related white matter network changes in patients with frontal lobe glioma.

PURPOSE: Epilepsy is a common symptom in patients with frontal lobe glioma. Tumor-related epilepsy was recently considered a type of network disease. Glioma can severely influence the integrity of the white matter network. The association between white matter network changes and presurgical epilepsy remains unclear in glioma patients. This study aims to identify alterations to the subcortical brain networks caused by glioma and glioma-related epilepsy. METHODS: Sixty-one patients with frontal lobe gliomas were enrolled and stratified into the epileptic and non-epileptic groups. Additionally, 14 healthy participants were enrolled after matching for age, sex, and education level. All participants underwent diffusion tensor imaging. Graph theoretical analysis was applied to reveal topological changes in their white matter networks. Regions affected by tumors were excluded from the analysis. RESULTS: Global efficiency was significantly decreased (p = 0.008), while the shortest path length increased (p = 0.02) in the left and right non-epileptic groups compared to the controls. A total of five edges exhibited decreased fiber count in the non-epileptic group (p < 0.05, false discovery rate-corrected). The topological properties and connectional edges showed no significant differences when comparing the epileptic groups and the controls. Additionally, the degree centrality of several nodes connected to the alternated edges was also diminished. CONCLUSIONS: Compared to the controls, the epilepsy groups showed raletively intact WM networks, while the non-epileptsy groups had damaged network with lower efficiency and longer path length. These findings indicated that the occurrence of glioma related epilepsy have association with white matter network intergrity.

Increasing nodal vulnerability and nodal efficiency implied recovery time prolonging in patients with supplementary motor area syndrome.

Supplementary motor area (SMA) syndrome is a surgery-related complication that commonly occurs after removing SMA glioma, and needs weeks to recover. However, susceptible factors of patients suffering from SMA syndrome remain unknown. Graphic theory was applied to reveal topological properties of sensorimotor network (SMN) by processing resting-state functional magnetic resonance images in 66 patients with SMA gliomas. Patients were classified into SMA and non-SMA groups based on whether they suffered from SMA syndrome. We collected recovery time and used causal mediation analysis to find association between topological properties and recovery time. Compared with the non-SMA group, higher vulnerability (left: p = .0018; right: p = .0033) and lower fault tolerance (left: p = .0022; right: p = .0248) of the whole SMN were found in the SMA group. Moreover, higher nodal properties of lesional-hemispheric cingulate cortex (nodal efficiency: left, p = .0389; right, p = .0169; nodal vulnerability: left, p = .0185; right, p = .0085) and upper limb region of primary motor cortex (PMC; nodal efficiency: left, p = .0132; right, p = .0001; nodal vulnerability: left, p = .0091; right, p = .0209) were found in the SMA group. Nodal efficiency and nodal vulnerability of cingulate cortex and upper limb region of PMC were important predictors for SMA syndrome occurring and recovery time prolonging. Neurosurgeons should carefully deal with upper limb region of PMC and cingulate cortex, and protect them if these two region were unnecessary to damage during SMA glioma resection.

Micro-Nanocarriers Based Drug Delivery Technology for Blood-Brain Barrier Crossing and Brain Tumor Targeting Therapy.

The greatest obstacle to using drugs to treat brain tumors is the blood-brain barrier (BBB), making it difficult for conventional drug molecules to enter the brain. Therefore, how to safely and effectively penetrate the BBB to achieve targeted drug delivery to brain tumors has been a challenging research problem. With the intensive research in micro- and nanotechnology in recent years, nano drug-targeted delivery technologies have shown great potential to overcome this challenge, such as inorganic nanocarriers, organic polymer-carriers, liposomes, and biobased carriers, which can be designed in different sizes, shapes, and surface functional groups to enhance their ability to penetrate the BBB and targeted drug delivery for brain tumors. In this review, the composition and overcoming patterns of the BBB are detailed, and then the hot research topics of drug delivery carriers for brain tumors in recent years are summarized, and their mechanisms of action on the BBB and the factors affecting drug delivery are described in detail, and the effectiveness of targeted therapy for brain tumors is evaluated. Finally, the challenges and dilemmas in developing brain tumor drug delivery systems are discussed, which will be promising in the future for targeted drug delivery to brain tumors based on micro-nanocarriers technology.

Molecular subtyping of diffuse gliomas using magnetic resonance imaging: comparison and correlation between radiomics and deep learning.

OBJECTIVES: The molecular subtyping of diffuse gliomas is important. The aim of this study was to establish predictive models based on preoperative multiparametric MRI. METHODS: A total of 1016 diffuse glioma patients were retrospectively collected from Beijing Tiantan Hospital. Patients were randomly divided into the training (n = 780) and validation (n = 236) sets. According to the 2016 WHO classification, diffuse gliomas can be classified into four binary classification tasks (tasks I-IV). Predictive models based on radiomics and deep convolutional neural network (DCNN) were developed respectively, and their performances were compared with receiver operating characteristic (ROC) curves. Additionally, the radiomics and DCNN features were visualized and compared with the t-distributed stochastic neighbor embedding technique and Spearman's correlation test. RESULTS: In the training set, areas under the curves (AUCs) of the DCNN models (ranging from 0.99 to 1.00) outperformed the radiomics models in all tasks, and the accuracies of the DCNN models (ranging from 0.90 to 0.94) outperformed the radiomics models in tasks I, II, and III. In the independent validation set, the accuracies of the DCNN models outperformed the radiomics models in all tasks (0.74-0.83), and the AUCs of the DCNN models (0.85-0.89) outperformed the radiomics models in tasks I, II, and III. DCNN features demonstrated more superior discriminative capability than the radiomics features in feature visualization analysis, and their general correlations were weak. CONCLUSIONS: Both the radiomics and DCNN models could preoperatively predict the molecular subtypes of diffuse gliomas, and the latter performed better in most circumstances. KEY POINTS: • The molecular subtypes of diffuse gliomas could be predicted with MRI. • Deep learning features tend to outperform radiomics features in large cohorts. • The correlation between the radiomics features and DCNN features was low.

Tumor location-based classification of surgery-related language impairments in patients with glioma.

INTRODUCTION: Many patients with glioma experience surgery-related language impairment. This study developed a classification system to predict postoperative language prognosis. METHODS: Sixty-eight patients were retrospectively reviewed. Based on their location, tumors were subtyped as follows: (I) inferior frontal lobe or precentral gyrus; (II) posterior central gyrus or supramarginal gyrus (above the lateral fissure level); (III) posterior region of the superior or middle temporal gyri or supramarginal gyrus (below the lateral fissure level); and (IV) insular lobe. The distance from the tumor to the superior longitudinal fasciculus/arcuate fasciculus was calculated. The recovery of language function was assessed using the Western Aphasia Battery before surgery, and a comprehensive language test was conducted on the day of surgery; 3, 7, and 14 days after surgery. Our follow-up information of was the comprehensive language test from telephone interviews in 3 months after surgery. RESULTS: Thirty-three patients experienced transient language impairment within 1 week of surgery. Fourteen patients had permanent language impairment. Type II tumors, shorter distance from the tumor to the posterior superior longitudinal fasciculus/arcuate fasciculus, and isocitrate dehydrogenase mutations were risk factors for surgery-related language impairment. Regarding the presence or absence of permanent surgery-related language impairments, the cut-off distance between the tumor and posterior superior longitudinal fasciculus/arcuate fasciculus was 2.75 mm. CONCLUSIONS: According to our classification, patients with type II tumors had the worst language prognosis and longest recovery time. Our classification, based on tumor location, can reliably predict postoperative language status and may be used to guide tumor resection.

Molecular docking-assisted screening reveals tannic acid as a natural protein disulphide isomerase inhibitor with antiplatelet and antithrombotic activities.

Protein disulphide isomerase (PDI) promotes platelet activation and constitutes a novel antithrombotic target. In this study, we reported that a PDI-binding plant polyphenol, tannic acid (TA), inhibits PDI activity, platelet activation and thrombus formation. Molecular docking using plant polyphenols from dietary sources with cardiovascular benefits revealed TA as the most potent binding molecule with PDI active centre. Surface plasmon resonance demonstrated that TA bound PDI with high affinity. Using Di-eosin-glutathione disulphide fluorescence assay and PDI assay kit, we showed that TA inhibited PDI activity. In isolated platelets, TA inhibited platelet aggregation stimulated by either GPVI or ITAM pathway agonists. Flow cytometry showed that TA inhibited thrombin- or CRP-stimulated platelet activation, as reflected by reduced granule secretion and integrin activation. TA also reduced platelet spreading on immobilized fibrinogen and platelet adhesion under flow conditions. In a laser-induced vascular injury mouse model, intraperitoneal injection of TA significantly decreased the size of cremaster arteriole thrombi. No prolongation of mouse jugular vein and tail-bleeding time was observed after TA administration. Therefore, we identified TA from natural polyphenols as a novel inhibitor of PDI function. TA inhibits platelet activation and thrombus formation, suggesting it as a potential antithrombotic agent.

Identification of herbal categories active in pain disorder subtypes by machine learning help reveal novel molecular mechanisms of algesia.

Chronic pain is highly prevalent and poorly controlled, of which the accurate underlying mechanisms need be further elucidated. Herbal drugs have been widely used for controlling various pain disorders. The systematic integration of pain herbal data resources might be promising to help investigate the molecular mechanisms of pain phenotypes. Here, we integrated large-scale bibliographic literatures and well-established data sources to obtain high-quality pain relevant herbal data (i.e. 426 pain related herbs with their targets). We used machine learning method to identify three distinct herb categories with their specific indications of symptoms, targets and enriched pathways, which were characterized by the efficacy of treatment to the chronic cough related neuropathic pain, the reproduction and autoimmune related pain, and the cancer pain, respectively. We further detected the novel pathophysiological mechanisms of the pain subtypes by network medicine approach to evaluate the interactions between herb targets and the pain disease modules. This work increased the understanding of the underlying molecular mechanisms of pain subtypes that herbal drugs are participating and with the ultimate aim of developing novel personalized drugs for pain disorders.

Awake craniotomy for gliomas involving motor-related areas: classification and function recovery.

PURPOSE: Motor mapping with direct cortical stimulation (DCS) is useful for motor function preservation. Nevertheless, many patients still experience postoperative motor dysfunction after motor mapping. This study aimed to provide a classification of gliomas involved in motor-related areas to help understand which types of gliomas are prone to induce postoperative motor impairments. METHODS: Sixty-four patients were retrospectively recruited. Based on tumor location, four types of gliomas were identified: (I) precentral gyrus; (II) premotor and/or supplementary motor areas but not invading pre-central gyrus; (III) adjacent to the posterior limb of the internal capsule; and (IV) other supra-tentorial area. The recovery of motor function was evaluated by muscle strength testing before surgery and 3 days, 7 days, 14 days, and 3 months after surgery. RESULTS: Half of the patients experienced postoperative transient motor impairment within a week. Six patients suffered from permanent motor dysfunction, and four of them had type III glioma. Compared with types I and IV, patients with type III gliomas took more than three times as long to recover. Furthermore, patients with types I and II gliomas were more susceptible to preoperative epilepsy than those with types III and IV. There was no difference in postoperative seizure control between the four types. CONCLUSIONS: Our classification of gliomas involving motor-related eloquent areas was useful for predicting postoperative motor functional prognosis in patients who underwent motor mapping with DCS. Even if no positive sites were detected, a conservative strategy of tumor resection is recommended in cases that gliomas located close to the posterior limb of the internal capsule.

MR imaging based fractal analysis for differentiating primary CNS lymphoma and glioblastoma.

OBJECTIVES: The aim of this study was to differentiate primary central nervous system lymphoma (PCNSL) from glioblastomas (GBM) using the fractal analysis of conventional MRI data. MATERIALS AND METHODS: Sixty patients with PCNSL and 107 patients with GBM with MRI data available were enrolled. Fractal dimension (FD) and lacunarity values of the tumour region were calculated using fractal analysis. A predictive model combining fractal parameters and anatomical characteristics was built using logistic regression. The role of FD, lacunarity and the predictive model in differential diagnosis was evaluated using receiver-operating characteristic (ROC) curve analysis. The association between fractal parameters and anatomical characteristics of tumours was also investigated. RESULTS: PCNSL had lower FD values (p < 0.001) and higher lacunarity values (p < 0.001) than GBM. ROC curve analysis revealed that FD, lacunarity, and the predictive model could distinguish PCNSL from GBM (area under the curve: 0.895, 0.776, and 0.969, respectively). The following associations were observed between fractal parameters and anatomical characteristics: multiple lesions were significantly associated with higher lacunarity (p = 0.024), necrosis with higher FD (p = 0.027), corpus callosum involvement with higher lacunarity (p < 0.001) in PCNSL and subventricular zone involvement with higher FD (p < 0.001) in GBM. CONCLUSIONS: The findings of the study indicate that fractal analysis on conventional MRI performs well in distinguishing PCNSL from GBM. KEY POINTS: • Fractal dimension and lacunarity were capable of differentiating PCNSL from GBM. • PCNSL and GBM exhibited different anatomical characteristics. • Fractal parameters were associated with some of these anatomical characteristics.

Vascular Semaphorin 7A Upregulation by Disturbed Flow Promotes Atherosclerosis Through Endothelial ß1 Integrin.

OBJECTIVE: Accumulating evidence suggests a role of semaphorins in vascular homeostasis. Here, we investigate the role of Sema7A (semaphorin 7A) in atherosclerosis and its underlying mechanism. APPROACH AND RESULTS: Using genetically engineered Sema7A-/-ApoE-/- mice, we showed that deletion of Sema7A attenuates atherosclerotic plaque formation primarily in the aorta of ApoE-/- mice on a high-fat diet. A higher level of Sema7A in the atheroprone lesser curvature suggests a correlation of Sema7A with disturbed flow. This notion is supported by elevated Sema7A expression in human umbilical venous endothelial cells either subjected to oscillatory shear stress or treated with the PKA (protein kinase A)/CREB (cAMP response element-binding protein) inhibitor H89 (N-[2-(p-bromocinnamylamino)ethyl]-5-isoquinolinesulfonamide·2HCl hydrate). Further studies using the partial carotid artery ligation model showed that disturbed flow in the left carotid artery of Sema7A+/+ApoE-/- mice promoted the expression of endothelial Sema7A and cell adhesion molecules, leukocyte adhesion, and plaque formation, whereas such changes were attenuated in Sema7A-/-ApoE-/- mice. Further studies showed that blockage of ß1 integrin, a known Sema7A receptor, or inhibition of FAK (focal adhesion kinase), MEK1/2 (mitogen-activated protein kinase kinase 1/2), or NF-κB (nuclear factor-κB) significantly reduced the expression of cell adhesion molecules and THP-1 (human acute monocytic leukemia cell line) monocyte adhesion in Sema7A-overexpressing human umbilical venous endothelial cells. Studies using chimeric mice suggest that vascular, most likely endothelial, Sema7A plays a major role in atherogenesis. CONCLUSIONS: Our findings indicate a significant role of Sema7A in atherosclerosis by mediating endothelial dysfunction in a ß1 integrin-dependent manner.

Radiogenomic analysis of PTEN mutation in glioblastoma using preoperative multi-parametric magnetic resonance imaging.

PURPOSE: PTEN mutation status is a pivotal biomarker for glioblastoma. This study aimed to establish a radiomic signature to predict PTEN mutation status in patients with glioblastoma, and to investigate the genetic background behind this radiomic signature. METHODS: In this study, a total of 862 radiomic features were extracted from each patient. The training (n = 69) and validation (n = 40) sets were retrospectively collected from the Cancer Genome Atlas and the Chinese Glioma Genome Atlas, respectively. The minimum redundancy maximum relevance (mRMR) algorithm was used to select the best predictive features of PTEN status. A machine learning model was then built with the selected features using a support vector machine classifier. The predictive performance of each selected feature and the complete model were evaluated via the area under the curve from receiver operating characteristic analysis in both the training and validation sets. The genetic background underlying the radiomic signature was determined using radiogenomic analysis. RESULTS: Six features were selected using the mRMR algorithm, including two features derived from contrast-enhanced images and four features derived from T2-weighted images. The predictive performance of the machine learning model for the training and validation sets were 0.925 and 0.787, respectively, which were better than the individual features. Radiogenomics analysis revealed that the PTEN-associated biological processes could be described using the radiomic signature. CONCLUSION: These results show that radiomic features derived from preoperative MRI can predict PTEN mutation status in glioblastoma patients, thus providing a novel noninvasive imaging biomarker.

Prognostic value of a microRNA signature as a novel biomarker in patients with lower-grade gliomas.

MicroRNAs (miRNAs) may act as prognostic biomarkers in a variety of cancers. The aim of this study was to identify and evaluate a prognostic miRNA signature in patients with lower-grade gliomas (LGGs). miRNA expression profiles and clinical data of patients with LGGs from the Chinese Glioma Genome Atlas (CGGA; the training cohort) and The Cancer Genome Atlas (TCGA; the validation cohort) were analyzed, and the least absolute shrinkage and selection operator Cox regression model was used to identify the miRNA signature, which was combined with clinical prognostic factors to develop an individualized survival prediction model. Gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were conducted to reveal the biological implications of the signature. We identified a four-miRNA signature that stratified patients in the training cohort into low- or high-risk groups according to overall survival time, a finding that was verified in the validation cohort. Multivariate Cox regression analysis indicated that the four-miRNA signature was an independent prognostic biomarker, and a nomogram combining this miRNA signature with clinicopathological and molecular factors showed high prognostic accuracy for individualized survival prediction in both TCGA (C-index = 0.83) and CGGA (C-index = 0.68) cohorts. Functional annotation indicated that the major biological processes of this prognostic miRNA signature were enriched in cell cycle and DNA repair-associated biological processes. Our findings indicated that our newly discovered four-miRNA signature may be an effective independent prognostic factor for the prediction of patients with LGGs.

Molecular profiles for insular low-grade gliomas with putamen involvement.

BACKGROUND: The newly proposed putamen classification system shows good prognostic value in patients with insular LGGs, yet no study towards the molecular profiles of putamen involved LGGs has been proposed. METHODS: Clinical information and imaging data of patients diagnosed with insular low-grade gliomas were collected retrospectively. Genetic information of the 34 tumors was assessed using RNA-sequencing. Gene set enrichment analysis was further performed to identify the genes showing differential expression between putamen-involved tumors and putamen non-involved tumors. The level of Ki-67 expression was also evaluated. RESULTS: There were 843 genes identified to be differentially expressed between putamen-involved and non-involved gliomas. Specifically, Gene set enrichment analysis discovered 13 Kyoto Encyclopedia of Genes and Genomes pathways and 37 Gene Ontology Biological Process term were upregulated in putamen-involved low-grade glioma cells. The enriched GO sets with the highest gene counts included cell cycle (42 genes), mitotic cell cycle (24 genes), and cell division (19 genes). Furthermore, high expression of Ki-67 was associated with putamen involvement in insular gliomas. CONCLUSIONS: There is clear genetic variation between putamen-involved and non-involved insular low-grade gliomas. The differential expression of genes related to the processes of cell proliferation, cell migration, or DNA repair may lead to putamen involvement. The findings suggest that among the two subtypes, putamen-involved insular low-grade gliomas have higher malignancy, and the clinical treatment towards the putamen-involved insular low-grade gliomas should be more active.