Glioma cells release exosomes in culture and into the extracellular matrix . These nanobodies transport an array of biomolecules and are capable of mediating cell-cell communication. Circulating exosomes in cancer patients may be indicative of disease status and response to therapy. The inhibitor of apoptosis protein (IAP) survivin (SVN) promotes cancer cell proliferation, local immune suppression and resistance to chemotherapy and it is a potential cancer biomarker. We used imaging flow cytometry to perform quantitative measurements of circulating SVN+ exosomes in the serum of malignant glioma patients undergoing investigational treatment with an anti-survivin vaccine (SurVaxM). Serum from glioma patients contained abundant CD9+ exosomes with both SVN and glial fibrillary acidic protein (GFAP) on their surface. Survivin and GFAP were evaluated both independently and together as possible tumor markers on CD9+ exosomes. Patients with longer time to tumor progression generally exhibited a decrease in circulating CD9+/SVN+ and CD9+/GFAP+/SVN+ exosomes immediately following survivin vaccination; whereas, those with early tumor progression had an increase in exosomes, despite anti-survivin immunotherapy. Serum from non-cancer healthy control individuals had very few detectable CD9+/GFAP+/SVN+ exosomes, although CD9+/GFAP+ exosomes were detectable in small numbers. This study demonstrates that patients with malignant gliomas have CD9+/GFAP+/SVN+ and CD9+/SVN+ exosomes that are released into the circulation and that early reductions in their numbers following anti-survivin immunotherapy might be associated with longer progression-free survival.
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http://dx.doi.org/10.18632/oncotarget.21773 | DOI Listing |
Childs Nerv Syst
January 2025
Ph.D. Human Genetics Program, Molecular Biology and Genomics Department, Human Genetics Institute "Dr. Enrique Corona-Rivera", University Center of Health Sciences, University of Guadalajara, Guadalajara, Mexico.
Background: Central nervous system tumors (CNSTs) represent a significant oncological challenge in pediatric populations, particularly in developing regions where access to diagnostic and therapeutic resources is limited.
Methods: This research investigates the epidemiology, histological classifications, and survival outcomes of CNST in a cohort of pediatric patients aged 0 to 19 years within a 25-year retrospective study at the Civil Hospital of Guadalajara, Mexico, from 1999 to 2024.
Results: Data was analyzed from 273 patients who met inclusion criteria, revealing a higher incidence in males (51.
Acta Neurochir (Wien)
January 2025
Department of Neurosurgery, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, 226014, Uttar Pradesh, India.
Background: Reaching parenchymal segments of the lateral lenticulostriate artery (LSA) perforators, which represent the medial resection limit in insular gliomas (IG), remains a challenge. The currently described methods are indirect and sometimes, imprecise.
Methods: We report an antegrade direct skeletonization technique to identify these tiny arteries at the medial end of IGs with an illustrative case of grade 2 astrocytoma.
Cancers (Basel)
January 2025
Department of Rehabilitation, Greater Poland Cancer Centre, 61-866 Poznan, Poland.
Understanding the role of personality traits in shaping treatment outcomes is crucial given the multifaceted challenges posed by brain tumors and the significant adverse impact of radiotherapy (RT) on patients' well-being. This study aimed to provide insights into how personality traits affect psychosocial well-being and quality of life during RT in patients with high-grade malignant brain tumors. Personality traits in patients with high-grade glioma were assessed using the Eysenck Personality Questionnaire-Revised (EPQ-R).
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January 2025
Department of Computer Science, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, 2815 Gjøvik, Norway.
Background/objectives: Brain tumor classification is a crucial task in medical diagnostics, as early and accurate detection can significantly improve patient outcomes. This study investigates the effectiveness of pre-trained deep learning models in classifying brain MRI images into four categories: Glioma, Meningioma, Pituitary, and No Tumor, aiming to enhance the diagnostic process through automation.
Methods: A publicly available Brain Tumor MRI dataset containing 7023 images was used in this research.
Cancers (Basel)
December 2024
Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, MD 21205, USA.
: CSCs are critical drivers of the tumor and stem cell phenotypes of glioblastoma (GBM) cells. Chromatin modifications play a fundamental role in driving a GBM CSC phenotype. The goal of this study is to further our understanding of how stem cell-driving events control changes in chromatin architecture that contribute to the tumor-propagating phenotype of GBM.
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