Molecular characteristics and clinical outcomes of elderly patients with IDH-wildtype glioblastomas: comparative study of older and younger cases in Kansai Network cohort

[1]  H. Kishima,et al.  Distribution differences in prognostic copy number alteration profiles in IDH-wild-type glioblastoma cause survival discrepancies across cohorts , 2019, Acta Neuropathologica Communications.

[2]  S. Chanock,et al.  Age‐specific genome‐wide association study in glioblastoma identifies increased proportion of ‘lower grade glioma’‐like features associated with younger age , 2018, International journal of cancer.

[3]  Y. Kodama,et al.  Characteristics and outcomes of elderly patients with diffuse gliomas: a multi-institutional cohort study by Kansai Molecular Diagnosis Network for CNS Tumors , 2018, Journal of Neuro-Oncology.

[4]  H. Bolouri,et al.  Copy number profiling across glioblastoma populations has implications for clinical trial design , 2018, Neuro-Oncology.

[5]  Naoki Kagawa,et al.  Introduction of High Throughput Magnetic Resonance T2-Weighted Image Texture Analysis for WHO Grade 2 and 3 Gliomas , 2016, PloS one.

[6]  H. Mizushima,et al.  National Registry of Designated Intractable Diseases in Japan: Present Status and Future Prospects , 2016, Neurologia medico-chirurgica.

[7]  E. Miyaoka,et al.  A combination of TERT promoter mutation and MGMT methylation status predicts clinically relevant subgroups of newly diagnosed glioblastomas , 2016, Acta neuropathologica communications.

[8]  M. Balbín,et al.  Prognostic factors and survival study in high-grade glioma in the elderly , 2016, British journal of neurosurgery.

[9]  Steven J. M. Jones,et al.  Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas. , 2015, The New England journal of medicine.

[10]  Alexander R. Pico,et al.  Glioma Groups Based on 1p/19q, IDH, and TERT Promoter Mutations in Tumors. , 2015, The New England journal of medicine.

[11]  Satoru Miyano,et al.  Mutational landscape and clonal architecture in grade II and III gliomas , 2015, Nature Genetics.

[12]  Gabriele Schackert,et al.  Molecular classification of diffuse cerebral WHO grade II/III gliomas using genome- and transcriptome-wide profiling improves stratification of prognostically distinct patient groups , 2015, Acta Neuropathologica.

[13]  Y. Kodama,et al.  11C-methinine uptake correlates with MGMT promoter methylation in nonenhancing gliomas , 2014, Clinical Neurology and Neurosurgery.

[14]  G. Reifenberger,et al.  MGMT testing—the challenges for biomarker-based glioma treatment , 2014, Nature Reviews Neurology.

[15]  Serdar Bozdag,et al.  Age-specific signatures of glioblastoma at the genomic, genetic, and epigenetic levels. , 2013, PloS one.

[16]  David T. W. Jones,et al.  Hotspot mutations in H3F3A and IDH1 define distinct epigenetic and biological subgroups of glioblastoma. , 2012, Cancer cell.

[17]  Didier Frappaz,et al.  Temozolomide versus standard 6-week radiotherapy versus hypofractionated radiotherapy in patients older than 60 years with glioblastoma: the Nordic randomised, phase 3 trial. , 2012, The Lancet. Oncology.

[18]  R. Wilson,et al.  Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma. , 2010, Cancer cell.

[19]  R. McLendon,et al.  Robust Detection of EGFR Copy Number Changes and EGFR Variant III: Technical Aspects and Relevance for Glioma Diagnostics , 2009, Brain pathology.

[20]  S. Horvath,et al.  Gene expression analysis of glioblastomas identifies the major molecular basis for the prognostic benefit of younger age , 2008, BMC Medical Genomics.

[21]  P. Wesseling,et al.  Multiplex ligation-dependent probe amplification: a diagnostic tool for simultaneous identification of different genetic markers in glial tumors. , 2006, The Journal of molecular diagnostics : JMD.

[22]  M. Chougule.  Diffuse Astrocytic and Oligodendroglial Tumors , 2020 .

[23]  R. Arceci.  Identification of a CpG Island Methylator Phenotype that Defines a Distinct Subgroup of Glioma , 2010 .