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| http://dx.doi.org/10.1016/j.tranon.2021.101173 | DOI Listing |
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A cross-species transcriptomic analysis reveals a novel 2-dimensional classification system explaining the invasiveness heterogeneity of pancreatic neuroendocrine tumor.
Cancer Lett
July 2024
Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China; State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China. Electronic address:
Article Synopsis
- Pancreatic neuroendocrine tumors (PanNETs) show a wide range of invasiveness, and existing genomic knowledge sheds some light on this variability, especially between different types like insulinomas and other PanNET variants.
- Researchers used a 2D classification system based on RNA sequencing of PanNETs from both mouse models and humans to categorize these tumors primarily into benign insulinomas and various invasive subtypes.
- By integrating the 2D classification, specific mutation status (DAXX/ATRX), and tumor size, they identified a subset of PanNETs with low recurrence risk, helping to clarify the complexity of these tumors and enhance their prognostic evaluation.
IDH1 mutation predicts seizure occurrence and prognosis in lower-grade glioma adults.
Pathol Res Pract
February 2024
Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing 100053, China; Clinical Research Center for Epilepsy, Capital Medical University, Beijing 100053, China; Beijing Municipal Geriatric Medical Research Center, Beijing 100053, China. Electronic address:
Article Synopsis
- Epileptic seizures are often the first sign of glioma, but the exact link between gliomas and seizures remains unclear beyond physical tumor effects.
- A study reviewed 320 glioma patients to identify seizure biomarkers using logistic regression, focusing on their treatment from January 2019 to July 2022.
- The findings revealed that the IDH1 R132H mutation is a significant risk factor for seizures in lower-grade glioma patients and is associated with better seizure control when combined with normal ATRX expression.
MRI characteristics of H3 G34-mutant diffuse hemispheric gliomas and possible differentiation from IDH-wild-type glioblastomas in adolescents and young adults.
J Neurosurg Pediatr
March 2024
2Department of Radiology, West China Hospital of Sichuan University, Chengdu.
Objective: H3 G34-mutant diffuse hemispheric gliomas (G34m-DHGs) are rare and constitute a new infiltrating brain tumor entity whose characteristics require elucidation, and their difference from isocitrate dehydrogenase-wild-type glioblastomas (IDH-WT-GBMs) needs to be clarified. In this study, the authors report the demographic, clinical, and neuroradiological features of G34m-DHG and investigate the capability of quantitative MRI features in differentiating them.
Methods: Twenty-three patients with G34m-DHG and 30 patients with IDH-WT-GBM were included in this retrospective study.
Detection of Glioma-Related Hotspot Mutations Through Sequencing of Cerebrospinal Fluid (CSF)-Derived Circulating Tumor DNA: A Pilot Study on CSF-Based Liquid Biopsy for Primary Spinal Cord Astrocytoma.
Neurospine
June 2023
Department of Neurosurgery, Xuanwu Hospital, China International Neuroscience Institute, Capital Medical University, Beijing, China.
Objective: Although cerebrospinal fluid (CSF)-based liquid biopsy was proved to be practical in molecular analysis of intracranial gliomas, liquid biopsy of primary intramedullary astrocytoma was rarely reported. Given the distinct genomic profiles between primary intramedullary glioma and intracranial astrocytoma, whether the feasibility of CSF-based molecular analysis of intracranial gliomas can be replicated in primary spinal cord astrocytoma needs to be investigated. The aim of this pilot study is to evaluate the feasibility of molecular analysis of primary intramedullary astrocytoma through sequencing CSF-derived circulating tumor DNA (ctDNA).
View Article and Find Full Text PDFMultimodal-based machine learning strategy for accurate and non-invasive prediction of intramedullary glioma grade and mutation status of molecular markers: a retrospective study.
BMC Med
May 2023
Department of Neurosurgery, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
Background: Determining the grade and molecular marker status of intramedullary gliomas is important for assessing treatment outcomes and prognosis. Invasive biopsy for pathology usually carries a high risk of tissue damage, especially to the spinal cord, and there are currently no non-invasive strategies to identify the pathological type of intramedullary gliomas. Therefore, this study aimed to develop a non-invasive machine learning model to assist doctors in identifying the intramedullary glioma grade and mutation status of molecular markers.
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