Most current research on human brain tumors is focused on the molecular and cellular analysis of the bulk tumor mass. However, evidence in leukemia and more recently in solid tumors such as breast cancer suggests that the tumor cell population is heterogeneous with respect to proliferation and differentiation. Recently, several groups have described the existence of a cancer stem cell population in human brain tumors of different phenotypes from both children and adults. The finding of brain tumor stem cells (BTSCs) has been made by applying the principles for cell culture and analysis of normal neural stem cells (NSCs) to brain tumor cell populations and by identification of cell surface markers that allow for isolation of distinct tumor cell populations that can then be studied in vitro and in vivo. A population of brain tumor cells can be enriched for BTSCs by cell sorting of dissociated suspensions of tumor cells for the NSC marker CD133. These CD133+ cells, which also expressed the NSC marker nestin, but not differentiated neural lineage markers, represent a minority fraction of the entire brain tumor cell population, and exclusively generate clonal tumor spheres in suspension culture and exhibit increased self-renewal capacity. BTSCs can be induced to differentiate in vitro into tumor cells that phenotypically resembled the tumor from the patient. Here, we discuss the evidence for and implications of the discovery of a cancer stem cell in human brain tumors. The identification of a BTSC provides a powerful tool to investigate the tumorigenic process in the central nervous system and to develop therapies targeted to the BTSC. Specific genetic and molecular analyses of the BTSC will further our understanding of the mechanisms of brain tumor growth, reinforcing parallels between normal neurogenesis and brain tumorigenesis.
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http://dx.doi.org/10.1038/sj.onc.1207946 | DOI Listing |
Adv Sci (Weinh)
January 2025
The department of oncology, Xiangya Hospital, Central South University, Changsha, 410008, China.
Non-small cell lung cancer (NSCLC) frequently metastasizes to the brain, significantly worsened prognoses. This study aimed to develop an interpretable model for predicting survival in NSCLC patients with brain metastases (BM) integrating radiomic features and RNA sequencing data. 292 samples are collected and analyzed utilizing T1/T2 MRIs.
View Article and Find Full Text PDFObjective: To assist in the rapid clinical identification of brain tumor types while achieving segmentation detection, this study investigates the feasibility of applying the deep learning YOLOv5s algorithm model to the segmentation of brain tumor magnetic resonance images and optimizes and upgrades it on this basis.
Methods: The research institute utilized two public datasets of meningioma and glioma magnetic resonance imaging from Kaggle. Dataset 1 contains a total of 3,223 images, and Dataset 2 contains 216 images.
Front Neurosci
January 2025
Department of Neurology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Introduction: Amyotrophic lateral sclerosis (ALS) is a rare, devastating neurodegenerative disease that affects upper and lower motor neurons, resulting in muscle atrophy, spasticity, hyperreflexia, and paralysis. Inflammation plays an important role in the development of ALS, and associated with rapid disease progression. Current observational studies indicate the thinning of cortical thickness in patients with ALS is associated with rapid disease progression and cognitive changes.
View Article and Find Full Text PDFF1000Res
January 2025
Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Introduction: Magnetic resonance imaging (MRI) is essential for brain imaging, but conventional methods rely on qualitative contrast, are time-intensive, and prone to variability. Magnetic resonance finger printing (MRF) addresses these limitations by enabling fast, simultaneous mapping of multiple tissue properties like T1, T2. Using dynamic acquisition parameters and a precomputed signal dictionary, MRF provides robust, qualitative maps, improving diagnostic precision and expanding clinical and research applications in brain imaging.
View Article and Find Full Text PDFFront Oncol
January 2025
Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
Accurate preoperative mapping is crucial for maximizing tumor removal while minimizing damage to critical brain functions during brain tumor surgery. Navigated transcranial magnetic stimulation (nTMS), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) are established methods for assessing motor and language function. Following PRISMA guidelines, this systematic review analyzes the reliability, clinical utility, and accessibility of these techniques.
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