Evolving evidence on tumor and germline genetic classification of gliomas: implications for etiology and survival studies

2016 ◽  
Vol 35 (01) ◽  
pp. 31-37 ◽  
Author(s):  
Kimberly J. Johnson ◽  
Michael E. Scheurer ◽  
Adelheid Woehrer ◽  
Joseph Wiemels
Keyword(s):  
Genetic Classification ◽  
Survival Studies ◽  
Classification Of Gliomas

scholarly journals RAPID GENETIC CLASSIFICATION OF GLIOMAS USING RAMAN SPECTROSCOPY

2018 ◽  
Vol 20 (suppl_5) ◽  
pp. v346-v346
Author(s):  
Laurent James Livermore ◽  
Martin Isabelle ◽  
Ian Bell ◽  
Puneet Plaha ◽  
Claire Vallance ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Genetic Classification ◽  
Classification Of Gliomas

scholarly journals Genetic Classification of Gliomas: Refining Histopathology

Cancer Cell ◽  
2015 ◽  
Vol 28 (1) ◽  
pp. 9-11 ◽  
Author(s):  
Michael B. Foote ◽  
Nickolas Papadopoulos ◽  
Luis A. Diaz
Keyword(s):  
Genetic Classification ◽  
Classification Of Gliomas

scholarly journals Rapid intraoperative molecular genetic classification of gliomas using Raman spectroscopy

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Laurent James Livermore ◽  
Martin Isabelle ◽  
Ian Mac Bell ◽  
Connor Scott ◽  
John Walsby-Tickle ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Molecular Genetic ◽  
Classification Model ◽  
Wild Type ◽  
Genetic Classification ◽  
Fresh Tissue ◽  
Tissue Samples ◽  
Genetic Subtypes ◽  
Classification Of Gliomas

Abstract Background The molecular genetic classification of gliomas, particularly the identification of isocitrate dehydrogenase (IDH) mutations, is critical for clinical and surgical decision-making. Raman spectroscopy probes the unique molecular vibrations of a sample to accurately characterize its molecular composition. No sample processing is required allowing for rapid analysis of tissue. The aim of this study was to evaluate the ability of Raman spectroscopy to rapidly identify the common molecular genetic subtypes of diffuse glioma in the neurosurgical setting using fresh biopsy tissue. In addition, classification models were built using cryosections, formalin-fixed paraffin-embedded (FFPE) sections and LN-18 (IDH-mutated and wild-type parental cell) glioma cell lines. Methods Fresh tissue, straight from neurosurgical theatres, underwent Raman analysis and classification into astrocytoma, IDH-wild-type; astrocytoma, IDH-mutant; or oligodendroglioma. The genetic subtype was confirmed on a parallel section using immunohistochemistry and targeted genetic sequencing. Results Fresh tissue samples from 62 patients were collected (36 astrocytoma, IDH-wild-type; 21 astrocytoma, IDH-mutated; 5 oligodendroglioma). A principal component analysis fed linear discriminant analysis classification model demonstrated 79%–94% sensitivity and 90%–100% specificity for predicting the 3 glioma genetic subtypes. For the prediction of IDH mutation alone, the model gave 91% sensitivity and 95% specificity. Seventy-nine cryosections, 120 FFPE samples, and LN18 cells were also successfully classified. Meantime for Raman data collection was 9.5 min in the fresh tissue samples, with the process from intraoperative biopsy to genetic classification taking under 15 min. Conclusion These data demonstrate that Raman spectroscopy can be used for the rapid, intraoperative, classification of gliomas into common genetic subtypes.

scholarly journals Multiple PET tracers for use in the classification of gliomas according to the 2016 WHO criteria

2020 ◽  
Author(s):  
Keisuke Miyake ◽  
Kenta Suzuki ◽  
Tomoya B Ogawa ◽  
Daisuke Ogawa ◽  
Tetsuhiro Hatakeyama ◽  
...  
Keyword(s):  
Who Classification ◽  
Standardized Uptake Value ◽  
Metabolic Tumor Volume ◽  
Who Criteria ◽  
Pet Tracers ◽  
Pet Tracer ◽  
Positron Emission ◽  
18F Fdg ◽  
Classification Of Gliomas

Abstract Background The molecular diagnosis of gliomas such as isocitrate dehydrogenase (IDH) status (wild-type [wt] or mutation [mut]) is especially important in the 2016 WHO classification. Positron emission tomography (PET) has afforded molecular and metabolic diagnostic imaging. The present study aimed to define the interrelationship between the 2016 WHO classification of gliomas and the integrated data from PET images using multiple tracers, including 18F-fluorodeoxyglucose ( 18F-FDG), 11C-methionine ( 11C-MET), 18F-fluorothymidine ( 18F-FLT), and 18F-fluoromisonidazole ( 18F-FMISO). Methods This retrospective, single-center study comprised 113 patients with newly diagnosed glioma based on the 2016 WHO criteria. Patients were divided into four glioma subtypes (Mut, Codel, Wt, and glioblastoma multiforme [GBM]). Tumor standardized uptake value (SUV) divided by mean normal cortical SUV (tumor-normal tissue ratio [TNR]) was calculated for 18F-FDG, 11C-MET, and 18F-FLT. Tumor-blood SUV ratio (TBR) was calculated for 18F-FMISO. To assess the diagnostic accuracy of PET tracers in distinguishing glioma subtypes, a comparative analysis of TNRs and TBR as well as the metabolic tumor volume (MTV) were calculated by Scheffe’s multiple comparison procedure for each PET tracer following the Kruskal–Wallis test. Results The differences in mean 18F-FLT TNR and 18F-FMISO TBR were significant between GBM and other glioma subtypes (p < 0.001). Regarding the comparison between Gd-T1WI volumes and 18F-FLT MTVs or 18F-FMISO MTVs, we identified significant differences between Wt and Mut or Codel (p < 0.01). Conclusion Combined administration of four PET tracers might aid in the preoperative differential diagnosis of gliomas according to the 2016 WHO criteria.

Abstract 2276: Genetic classification of colorectal cancer

2021 ◽  
Author(s):  
Yoshikage Inoue ◽  
Nobuyuki Kakiuchi ◽  
Kenichi Yoshida ◽  
Yasuhito Nanya ◽  
Yusuke Shiozawa ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Genetic Classification

WHO 2016 Classification of gliomas

2018 ◽  
Vol 44 (2) ◽  
pp. 139-150 ◽  
Author(s):  
P. Wesseling ◽  
D. Capper
Keyword(s):  
Classification Of Gliomas
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