Alternations and Applications of the Structural and Functional Connectome in Gliomas: A Mini-Review

Fiber Density and Structural Brain Connectome in Glioblastoma Are Correlated With Glioma Cell Infiltration

BACKGROUND

Glioblastoma (GBM) preferred to infiltrate into white matter (WM) beyond the recognizable tumor margin.

OBJECTIVE

To investigate whether fiber density (FD) and structural brain connectome can provide meaningful information about WM destruction and glioma cell infiltration.

METHODS

GBM cases were collected based on inclusion criteria, and baseline information and preoperative MRI results were obtained. GBM lesions were automatically segmented into necrosis, contrast-enhanced tumor, and edema areas. We obtained the FD map to compute the FD and lnFD values in each subarea and reconstructed the structural brain connectome to obtain the topological metrics in each subarea. We also divided the edema area into a nonenhanced tumor (NET) area and a normal WM area based on the contralesional lnFD value in the edema area, and computed the NET ratio.

RESULTS

Twenty-five GBM cases were included in this retrospective study. The FD/lnFD value and topological metrics (aCp, aLp, aEg, aEloc, and ar) were significantly correlated with GBM subareas, which represented the extent of WM destruction and glioma cell infiltration. The FD/lnFD values and topological parameters were correlated with the NET ratio. In particular, the lnFD value in the edema area was correlated with the NET ratio (coefficient, 0.92). Therefore, a larger lnFD value indicates more severe glioma infiltration in the edema area and suggests an extended resection for better clinical outcomes.

CONCLUSION

The FD and structural brain connectome in this study provide a new insight into glioma infiltration and a different consideration of their clinical application in neuro-oncology.

Investigation of neurophysiologic and functional connectivity changes following glioma resection using magnetoencephalography

Background

In patients with glioma, clinical manifestations of neural network disruption include behavioral changes, cognitive decline, and seizures. However, the extent of network recovery following surgery remains unclear. The aim of this study was to characterize the neurophysiologic and functional connectivity changes following glioma surgery using magnetoencephalography (MEG).

Methods

Ten patients with newly diagnosed intra-axial brain tumors undergoing surgical resection were enrolled in the study and completed at least two MEG recordings (pre-operative and immediate post-operative). An additional post-operative recording 6-8 weeks following surgery was obtained for six patients. Resting-state MEG recordings from 28 healthy controls were used for network-based comparisons. MEG data processing involved artifact suppression, high-pass filtering, and source localization. Functional connectivity between parcellated brain regions was estimated using coherence values from 116 virtual channels. Statistical analysis involved standard parametric tests.

Results

Distinct alterations in spectral power following tumor resection were observed, with at least three frequency bands affected across all study subjects. Tumor location-related changes were observed in specific frequency bands unique to each patient. Recovery of regional functional connectivity occurred following glioma resection, as determined by local coherence normalization. Changes in inter-regional functional connectivity were mapped across the brain, with comparable changes in low to mid gamma-associated functional connectivity noted in four patients.

Conclusion

Our findings provide a framework for future studies to examine other network changes in glioma patients. We demonstrate an intrinsic capacity for neural network regeneration in the post-operative setting. Further work should be aimed at correlating neurophysiologic changes with individual patients' clinical outcomes.

Interfering with CALCRL expression inhibits glioma proliferation, promotes apoptosis, and predicts prognosis in low-grade gliomas

Background

CALCRL is involved in a variety of key biological processes, including cell proliferation, apoptosis, angiogenesis, and inflammation. However, the role of CALCRL in glioma remains unknown. The purpose of this study was to investigate the effect of differential CALCRL expression on the malignant progression of glioma and its value in glioma prognosis.

Methods

Sequencing data from glioma and normal tissues were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, and the downloaded data were statistically analyzed using bioinformatics tools and the corresponding R package. The expression of CALCRL in normal brain tissue and different grades of glioma tissue was detected by pathological and immunohistochemical staining of clinical glioma specimens. The expression of CALCRL in different glioma cell lines was detected by quantitative real-time polymerase chain reaction (qRT-PCR), and the U87 cell line with high expression was selected to construct the CALCRL knockdown model by transfection with short hairpin (shRNA). The cell proliferation ability was detected by Celigo assay and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, the ability of cell clone formation was detected by clone formation assay, and the level of apoptosis was detected by flow cytometry.

Results

The expression of CALCRL in glioma was significantly upregulated compared with that of normal tissue, especially in low-grade glioma (LGG) compared to glioblastoma, and the differential expression of CALCRL correlated significantly with the prognosis of LGG. Clinical pathology and immunohistochemistry showed that the expression of CALCRL was related to the pathological grade of glioma, and the highest expression was found in World Health Organization (WHO) grade Ⅲ glioma. The results of qRT-PCR showed that CALCRL expression was highest in the U87 cell line. After knockdown of CALCRL expression, the proliferation and clonogenic ability of U87 cells were significantly decreased, and the apoptosis rate was significantly increased.

Conclusions

CALCRL is highly expressed in LGG. Interfering with CALCRL expression inhibits glioma cell proliferation and promotes apoptosis, and thus has potential as a biomarker and therapeutic target for the prognosis of those with LGGs.

Advanced Neuroimaging Approaches to Pediatric Brain Tumors

Simple Summary

After leukemias, brain tumors are the most common cancers in children, and early, accurate diagnosis is critical to improve patient outcomes. Beyond the conventional imaging methods of computed tomography (CT) and magnetic resonance imaging (MRI), advanced neuroimaging techniques capable of both structural and functional imaging are moving to the forefront to improve the early detection and differential diagnosis of tumors of the central nervous system. Here, we review recent developments in neuroimaging techniques for pediatric brain tumors.

Abstract

Central nervous system tumors are the most common pediatric solid tumors; they are also the most lethal. Unlike adults, childhood brain tumors are mostly primary in origin and differ in type, location and molecular signature. Tumor characteristics (incidence, location, and type) vary with age. Children present with a variety of symptoms, making early accurate diagnosis challenging. Neuroimaging is key in the initial diagnosis and monitoring of pediatric brain tumors. Conventional anatomic imaging approaches (computed tomography (CT) and magnetic resonance imaging (MRI)) are useful for tumor detection but have limited utility differentiating tumor types and grades. Advanced MRI techniques (diffusion-weighed imaging, diffusion tensor imaging, functional MRI, arterial spin labeling perfusion imaging, MR spectroscopy, and MR elastography) provide additional and improved structural and functional information. Combined with positron emission tomography (PET) and single-photon emission CT (SPECT), advanced techniques provide functional information on tumor metabolism and physiology through the use of radiotracer probes. Radiomics and radiogenomics offer promising insight into the prediction of tumor subtype, post-treatment response to treatment, and prognostication. In this paper, a brief review of pediatric brain cancers, by type, is provided with a comprehensive description of advanced imaging techniques including clinical applications that are currently utilized for the assessment and evaluation of pediatric brain tumors.