All cancer cells need to maintain functional telomeres to sustain continuous cell division and proliferation. In human diffuse gliomas, functional telomeres are maintained due either to reactivation of telomerase expression, the main pathway in most cancer types, or to activation of a mechanism called the alternative lengthening of telomeres (ALT). The presence of IDH1/2 mutations (IDH-mutant) together with loss of ATRX expression (ATRX-lost) are frequently associated with ALT in diffuse gliomas. However, detection of ALT, and a fortiori its quantification, are rarely, if ever, measured in neuropathology laboratories. We measured the level of ALT activity using the previously described quantitative "C-circle" assay and analyzed it in a well characterized cohort of 104 IDH-mutant and ATRX-lost adult diffuse gliomas. We report that in IDH-mutant ATRX-lost anaplastic astrocytomas, the intensity of ALT was inversely correlated with age (p < 0.001), the younger the patient, the higher the intensity of ALT. Strikingly, glioblastomas having progressed from anaplastic astrocytomas did not exhibit this correlation. ALT activity level in the tumor did not depend on telomere length in healthy tissue cells from the same patient. In summary, we have uncovered the existence, in anaplastic astrocytomas but not in glioblastomas with the same IDH and ATRX mutations, of a correlation between patient age and the level of activity of ALT, a telomerase-independent pathway of telomere maintenance.
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http://dx.doi.org/10.1186/s40478-019-0833-0 | DOI Listing |
J Clin Med
January 2025
Department of Radiology, Medical Imaging Center, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands.
Diffusion weighted imaging (DWI) is used for monitoring purposes for lower-grade glioma (LGG). While the apparent diffusion coefficient (ADC) is clinically used, various DWI models have been developed to better understand the micro-environment. However, the validity of these models and how they relate to each other is currently unknown.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Pharmaceutical Biochemistry, Poznan University of Medical Sciences, Rokietnicka 3, 60-806 Poznań, Poland.
Adult-type diffuse gliomas are characterized by inevitable recurrence and very poor prognosis. Novel treatment options, including multimodal drugs or effective drug combinations, are therefore eagerly awaited. Tinostamustine is an alkylating and histone deacetylase inhibiting molecule with great potential in cancer treatment.
View Article and Find Full Text PDFEur J Cancer
January 2025
ACCELERATE, Europe; Gustave Roussy Cancer Centre, Paris, France.
Fewer than 10 % of children with diffuse midline glioma (DMG) survive 2 years from diagnosis. Radiation therapy remains the cornerstone of treatment and there are no medicinal products with regulatory approval. Although the biology of DMG is better characterized, this has not yet translated into effective treatments.
View Article and Find Full Text PDFJ Neurosurg
January 2025
Departments of1Neurological Surgery and.
The infiltrative and diffuse nature of gliomas makes complete resection unfeasible. Unfortunately, regions of brain parenchyma with residual, infiltrative tumor are protected by the blood-brain barrier (BBB), making systemic chemotherapies, small-molecule inhibitors, and immunotherapies of limited efficacy. Low-frequency focused ultrasound (FUS) in combination with intravascular microbubbles can be used to disrupt the BBB transiently and selectively within the tumor and peritumoral region.
View Article and Find Full Text PDFBioengineering (Basel)
December 2024
Department of Pathology, University of Yamanashi, Yamanashi 409-3898, Japan.
The latest World Health Organization (WHO) classification of central nervous system tumors (WHO2021/5th) has incorporated molecular information into the diagnosis of each brain tumor type including diffuse glioma. Therefore, an artificial intelligence (AI) framework for learning histological patterns and predicting important genetic events would be useful for future studies and applications. Using the concept of multiple-instance learning, we developed an AI framework named GLioma Image-level and Slide-level gene Predictor (GLISP) to predict nine genetic abnormalities in hematoxylin and eosin sections: , , mutations, promoter mutations, homozygous deletion (CHD), amplification (amp), 7 gain/10 loss (7+/10-), 1p/19q co-deletion, and promoter methylation.
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