1p/19q codeletion, which leads to the abnormal expression of 1p19q genes in oligodendroglioma, is associated with chemosensitivity and favorable prognosis. Here, we aimed to explore the clinical implications of 1p19q gene expression in 1p/19q non-codel gliomas. We analyzed expression of 1p19q genes in 668 1p/19q non-codel gliomas obtained from The Cancer Genome Atlas (n = 447) and the Chinese Glioma Genome Atlas (n = 221) for training and validation, respectively. The expression of 1p19q genes was significantly correlated with the clinicopathological features and overall survival of 1p/19q non-codel gliomas. Then, we derived a risk signature of 25 selected 1p19q genes that not only had prognosis value in total 1p/19q non-codel gliomas but also had prognosis value in stratified gliomas. The prognosis value of the risk signature was superior than known clinicopathological features in 1p/19q non-codel gliomas and was also highly associated with the following features: loss of CDKN2A/B copy number in mutant-IDH-astrocytoma; telomerase reverse transcriptase (TERT) promoter mutation, combined chromosome 7 gain/chromosome 10 loss and epidermal growth factor receptor amplification in wild-type-IDH-astrocytoma; classical and mesenchymal subtypes in glioblastoma. Furthermore, genes enriched in the biological processes of cell division, extracellular matrix, angiogenesis significantly correlated to the signature risk score, and this is also supported by the immunohistochemistry and cell biology experiments. In conclusion, the expression profile of 1p19q genes is highly associated with the malignancy and prognosis of 1p/19q non-codel gliomas. A 25-1p19q-gene signature has powerfully predictive value for both malignant molecular pathological features and prognosis across distinct subgroups of 1p/19q non-codel gliomas.
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http://dx.doi.org/10.1093/carcin/bgz102 | DOI Listing |
Neurooncol Adv
December 2024
Division for Medical Image Computing (MIC), German Cancer Research Center (DKFZ), Heidelberg, Germany.
Background: This study aimed to explore the potential of the Advanced Data Analytics (ADA) package of GPT-4 to autonomously develop machine learning models (MLMs) for predicting glioma molecular types using radiomics from MRI.
Methods: Radiomic features were extracted from preoperative MRI of = 615 newly diagnosed glioma patients to predict glioma molecular types (IDH-wildtype vs IDH-mutant 1p19q-codeleted vs IDH-mutant 1p19q-non-codeleted) with a multiclass ML approach. Specifically, ADA was used to autonomously develop an ML pipeline and benchmark performance against an established handcrafted model using various MRI normalization methods (N4, Zscore, and WhiteStripe).
BMC Cancer
September 2023
School of Nursing, Nanjing Medical University, No.140 Hanzhong Road, Nanjing, Jiangsu Province, 210000, China.
Gliomas are the most common malignant primary brain tumors in adults with poor prognoses. The purpose of this study is to explore CACNG3 as a prognostic factor that is closely related to the progression and survival outcome of gliomas and to provide a potential new molecular target for the diagnosis and treatment of glioma patients. CACNG3 expression and related clinical data were collected from three major databases of The Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), and Gene Expression Omnibus (GEO).
View Article and Find Full Text PDFBMC Med
November 2021
Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jiyan Road 440, Jinan, 250117, Shandong, China.
Background: There is no consensus regarding the clinical target volume (CTV) margins in radiotherapy for glioma. In this study, we aimed to perform a complete macropathologic analysis examining microscopic tumor extension (ME) to more accurately define the CTV in glioma.
Methods: Thirty-eight supra-total resection specimens of glioma patients were examined on histologic sections.
Front Mol Biosci
August 2021
School of Nursing, Nanjing Medical University, Nanjing, China.
Gliomas are the most severe brain tumours with a poor prognosis. Although surgery, postoperative radiotherapy and chemotherapy can improve the survival rate of glioma patients, the prognosis of most glioma patients is still poor. In recent years, the influence of gene-targeted therapy on gliomas has been gradually discovered, and intervening the occurrence and development of brain gliomas from the perspective of the gene will significantly improve treatment prognosis.
View Article and Find Full Text PDFCancer Med
July 2021
Department of Neurosurgery, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Due to the extremely intrinsic heterogeneity among glioma patients, the outcomes of these patients are tremendously different. Therefore, the exploitation of novel biomarker classification of glioma is vitally important for deep insight into the essence and predicting the prognosis of glioma. We aim to analyze the correlation between TP73 mRNA expression, DNA methylated alteration and the prognosis of WHO grade II/III glioma, utilizing bioinformatics to evaluate its significance as a risk-factor in predicting the prognosis of these glioma patients.
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