Literature DB >> 27837434

Prediction of genetic subgroups in adult supra tentorial gliomas by pre- and intraoperative parameters.

Shunsuke Nakae1, Kazuhiro Murayama2, Hikaru Sasaki3, Masanobu Kumon1, Yuya Nishiyama1, Shigeo Ohba1, Kazuhide Adachi1, Shinya Nagahisa1, Takuro Hayashi1, Joji Inamasu1, Masato Abe4, Mitsuhiro Hasegawa1, Yuichi Hirose5.   

Abstract

Recent progress in neuro-oncology has validated the significance of genetic diagnosis in gliomas. We previously investigated IDH1/2 and TP53 mutations via Sanger sequencing for adult supratentorial gliomas and reported that PCR-based sequence analysis classified gliomas into three genetic subgroups that have a strong association with patient prognosis: IDH mutant gliomas without TP53 mutations, IDH and TP53 mutant gliomas, and IDH wild-type gliomas. Furthermore, this analysis had a strong association with patient prognosis. To predict genetic subgroups prior to initial surgery, we retrospectively investigated preoperative radiological data using CT and MRI, including MR spectroscopy (MRS), and evaluated positive 5-aminolevulinic acid (5-ALA) fluorescence as an intraoperative factor. We subsequently compared these factors to differentiate each genetic subgroup. Multiple factors such as age at diagnosis, tumor location, gadolinium enhancement, 5-ALA fluorescence, and several tumor metabolites according to MRS, such as myo-inositol (myo-inositol/total choline) or lipid20, were statistically significant factors for differentiating IDH mutant and wild-type, suggesting that these two subtypes have totally distinct characteristics. In contrast, only calcification, laterality, and lipid13 (lipid13/total Choline) were statistically significant parameters for differentiating TP53 wild-type and mutant in IDH mutant gliomas. In this study, we detected several pre- and intraoperative factors that enabled us to predict genetic subgroups for adult supratentorial gliomas and clarified that lipid13 quantified by MRS is the key tumor metabolite that differentiates TP53 wild-type and mutant in IDH mutant gliomas. These results suggested that each genetic subtype in gliomas selects the distinct lipid synthesis pathways in the process of tumorigenesis.

Entities:  

Keywords:  Genetic subtypes; Gliomas; MRS; Predictive parameters

Mesh:

Substances:

Year:  2016        PMID: 27837434     DOI: 10.1007/s11060-016-2313-8

Source DB:  PubMed          Journal:  J Neurooncol        ISSN: 0167-594X            Impact factor:   4.130


  27 in total

1.  Mutational landscape and clonal architecture in grade II and III gliomas.

Authors:  Hiromichi Suzuki; Kosuke Aoki; Kenichi Chiba; Yusuke Sato; Yusuke Shiozawa; Yuichi Shiraishi; Teppei Shimamura; Atsushi Niida; Kazuya Motomura; Fumiharu Ohka; Takashi Yamamoto; Kuniaki Tanahashi; Melissa Ranjit; Toshihiko Wakabayashi; Tetsuichi Yoshizato; Keisuke Kataoka; Kenichi Yoshida; Yasunobu Nagata; Aiko Sato-Otsubo; Hiroko Tanaka; Masashi Sanada; Yutaka Kondo; Hideo Nakamura; Masahiro Mizoguchi; Tatsuya Abe; Yoshihiro Muragaki; Reiko Watanabe; Ichiro Ito; Satoru Miyano; Atsushi Natsume; Seishi Ogawa
Journal:  Nat Genet       Date:  2015-04-13       Impact factor: 38.330

Review 2.  The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary.

Authors:  David N Louis; Arie Perry; Guido Reifenberger; Andreas von Deimling; Dominique Figarella-Branger; Webster K Cavenee; Hiroko Ohgaki; Otmar D Wiestler; Paul Kleihues; David W Ellison
Journal:  Acta Neuropathol       Date:  2016-05-09       Impact factor: 17.088

3.  Whole genome analysis from microdissected tissue revealed adult supratentorial grade II-III gliomas are divided into clinically relevant subgroups by genetic profile.

Authors:  Yuichi Hirose; Hikaru Sasaki; Tomoru Miwa; Shigeo Ohba; Eiji Ikeda; Masato Abe; Shunya Ikeda; Mia Kobayashi; Tsukasa Kawase; Mitsuhiro Hasegawa; Kazunari Yoshida
Journal:  Neurosurgery       Date:  2011-08       Impact factor: 4.654

Review 4.  MR-visible lipids and the tumor microenvironment.

Authors:  E James Delikatny; Sanjeev Chawla; Daniel-Joseph Leung; Harish Poptani
Journal:  NMR Biomed       Date:  2011-04-27       Impact factor: 4.044

5.  Preoperative grading of gliomas by using metabolite quantification with high-spatial-resolution proton MR spectroscopic imaging.

Authors:  Andreas Stadlbauer; Stephan Gruber; Christopher Nimsky; Rudolf Fahlbusch; Thilo Hammen; Rolf Buslei; Bernd Tomandl; Ewald Moser; Oliver Ganslandt
Journal:  Radiology       Date:  2006-01-19       Impact factor: 11.105

6.  Pre- and Posttreatment Glioma: Comparison of Amide Proton Transfer Imaging with MR Spectroscopy for Biomarkers of Tumor Proliferation.

Authors:  Ji Eun Park; Ho Sung Kim; Kye Jin Park; Sang Joon Kim; Jeong Hoon Kim; Seth A Smith
Journal:  Radiology       Date:  2015-08-19       Impact factor: 11.105

7.  IDH1 R132H mutation generates a distinct phospholipid metabolite profile in glioma.

Authors:  Morteza Esmaeili; Bob C Hamans; Anna C Navis; Remco van Horssen; Tone F Bathen; Ingrid S Gribbestad; William P Leenders; Arend Heerschap
Journal:  Cancer Res       Date:  2014-07-08       Impact factor: 12.701

8.  IDH1 mutations are early events in the development of astrocytomas and oligodendrogliomas.

Authors:  Takuya Watanabe; Sumihito Nobusawa; Paul Kleihues; Hiroko Ohgaki
Journal:  Am J Pathol       Date:  2009-02-26       Impact factor: 4.307

9.  Magnetic resonance spectroscopy metabolite profiles predict survival in paediatric brain tumours.

Authors:  Martin Wilson; Carole L Cummins; Lesley Macpherson; Yu Sun; Kal Natarajan; Richard G Grundy; Theodoros N Arvanitis; Risto A Kauppinen; Andrew C Peet
Journal:  Eur J Cancer       Date:  2012-10-01       Impact factor: 9.162

10.  PCR-Based Simple Subgrouping Is Validated for Classification of Gliomas and Defines Negative Prognostic Copy Number Aberrations in IDH Mutant Gliomas.

Authors:  Shunsuke Nakae; Hikaru Sasaki; Saeko Hayashi; Natsuki Hattori; Masanobu Kumon; Yuya Nishiyama; Kazuhide Adachi; Shinya Nagahisa; Takuro Hayashi; Joji Inamasu; Masato Abe; Mitsuhiro Hasegawa; Yuichi Hirose
Journal:  PLoS One       Date:  2015-11-11       Impact factor: 3.752

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  9 in total

Review 1.  Neuro-Oncology and Radiogenomics: Time to Integrate?

Authors:  A Lasocki; M A Rosenthal; S J Roberts-Thomson; A Neal; K J Drummond
Journal:  AJNR Am J Neuroradiol       Date:  2020-09-10       Impact factor: 3.825

2.  Molecular Subtype Classification in Lower-Grade Glioma with Accelerated DTI.

Authors:  E Aliotta; H Nourzadeh; P P Batchala; D Schiff; M B Lopes; J T Druzgal; S Mukherjee; S H Patel
Journal:  AJNR Am J Neuroradiol       Date:  2019-08-14       Impact factor: 3.825

3.  Integrative analysis of CBR1 as a prognostic factor associated with IDH-mutant glioblastoma in the Chinese population.

Authors:  Pengxiang Ji; Xueshi Shan; Jian Wang; Ping Zhang; Zhan Cai
Journal:  Am J Transl Res       Date:  2022-08-15       Impact factor: 3.940

4.  High Myoinositol on Proton MR Spectroscopy Could Be a Potential Signature of Papillary Tumors of the Pineal Region-Case Report of Two Patients.

Authors:  Albert Pons-Escoda; Juan Jose Sánchez Fernández; Àlex de Vilalta; Noemí Vidal; Carles Majós
Journal:  Brain Sci       Date:  2022-06-19

5.  Preoperative and Noninvasive Prediction of Gliomas Histopathological Grades and IDH Molecular Types Using Multiple MRI Characteristics.

Authors:  Ningfang Du; Xiaotao Zhou; Renling Mao; Weiquan Shu; Li Xiao; Yao Ye; Xinxin Xu; Yilang Shen; Guangwu Lin; Xuhao Fang; Shihong Li
Journal:  Front Oncol       Date:  2022-05-27       Impact factor: 5.738

6.  Imaging prediction of isocitrate dehydrogenase (IDH) mutation in patients with glioma: a systemic review and meta-analysis.

Authors:  Chong Hyun Suh; Ho Sung Kim; Seung Chai Jung; Choong Gon Choi; Sang Joon Kim
Journal:  Eur Radiol       Date:  2018-07-12       Impact factor: 5.315

Review 7.  Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis.

Authors:  Robin W Jansen; Paul van Amstel; Roland M Martens; Irsan E Kooi; Pieter Wesseling; Adrianus J de Langen; Catharina W Menke-Van der Houven van Oordt; Bernard H E Jansen; Annette C Moll; Josephine C Dorsman; Jonas A Castelijns; Pim de Graaf; Marcus C de Jong
Journal:  Oncotarget       Date:  2018-04-13

8.  Qualitative and Quantitative MRI Analysis in IDH1 Genotype Prediction of Lower-Grade Gliomas: A Machine Learning Approach.

Authors:  Mengqiu Cao; Shiteng Suo; Xiao Zhang; Xiaoqing Wang; Jianrong Xu; Wei Yang; Yan Zhou
Journal:  Biomed Res Int       Date:  2021-01-22       Impact factor: 3.411

9.  Remote intracranial recurrence of IDH mutant gliomas is associated with TP53 mutations and an 8q gain.

Authors:  Shunsuke Nakae; Takema Kato; Kazuhiro Murayama; Hikaru Sasaki; Masato Abe; Masanobu Kumon; Tadashi Kumai; Kei Yamashiro; Joji Inamasu; Mitsuhiro Hasegawa; Hiroki Kurahashi; Yuichi Hirose
Journal:  Oncotarget       Date:  2017-09-15
  9 in total

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