Literature DB >> 29980868

A surgical strategy for lower grade gliomas using intraoperative molecular diagnosis.

Shunichi Koriyama1,2, Masayuki Nitta3, Tatsuya Kobayashi1,2, Yoshihiro Muragaki1,2, Akane Suzuki4, Takashi Maruyama1,2, Takashi Komori5,6, Kenta Masui5, Taiichi Saito1,2, Takayuki Yasuda1,2, Junji Hosono1,2, Saori Okamoto1,2, Takahiro Shioyama4, Hiroaki Yamatani7, Takakazu Kawamata1.   

Abstract

Lower grade gliomas are both treated and diagnosed via surgical resection. Maximum tumor resection is currently the standard of care; however, this risks the loss of brain function. Glioma can be genetically subdivided into three different types, based on isocitrate dehydrogenase (IDH) mutation status and the presence of 1p/19q codeletion, which have radically different prognoses and responses to adjuvant therapies. Therefore, the means to identify the subtype and evaluate the surrounding tissues during surgery would be advantageous. In this study, we have developed a new surgical strategy for lower grade glioma based on the fourth edition of the World Health Organization Brain Tumor Classification, involving intraoperative molecular diagnosis. High-resolution melting analysis was used to evaluate IDH mutational status, while rapid immunohistochemistry of p53 and alpha-thalassemia/mental retardation syndrome X-linked (ATRX) was used to evaluate the 1p/19q codeletion status, allowing genetic classification during surgery. In addition, intraoperative flow cytometry was used to evaluate the surgical cavity for additional tumor lesions, allowing maximal resection while mitigating the risk of functional losses. This strategy allows the rapid intraoperative diagnosis and mapping of lower grade gliomas, and its clinical use could dramatically improve its prognosis.

Entities:  

Keywords:  Intraoperative flow cytometry; Intraoperative molecular diagnosis; Lower grade glioma; Surgical cavity diagnosis; Surgical strategy

Mesh:

Substances:

Year:  2018        PMID: 29980868     DOI: 10.1007/s10014-018-0324-1

Source DB:  PubMed          Journal:  Brain Tumor Pathol        ISSN: 1433-7398            Impact factor:   3.298


  3 in total

1.  Ultra-rapid somatic variant detection via real-time targeted amplicon sequencing.

Authors:  Jack Wadden; Brandon S Newell; Joshua Bugbee; Vishal John; Amy K Bruzek; Robert P Dickson; Carl Koschmann; David Blaauw; Satish Narayanasamy; Reetuparna Das
Journal:  Commun Biol       Date:  2022-07-15

2.  Prediction of lower-grade glioma molecular subtypes using deep learning.

Authors:  Yutaka Matsui; Takashi Maruyama; Masayuki Nitta; Taiichi Saito; Shunsuke Tsuzuki; Manabu Tamura; Kaori Kusuda; Yasukazu Fukuya; Hidetsugu Asano; Takakazu Kawamata; Ken Masamune; Yoshihiro Muragaki
Journal:  J Neurooncol       Date:  2019-12-21       Impact factor: 4.130

3.  The diagnostic value of lower glucose consumption for IDH1 mutated gliomas on FDG-PET.

Authors:  Feng-Min Liu; Yu-Fei Gao; Yanyan Kong; Yihui Guan; Jinsen Zhang; Shuai-Hong Li; Dan Ye; Wenyu Wen; Chuantao Zuo; Wei Hua
Journal:  BMC Cancer       Date:  2021-01-20       Impact factor: 4.430

  3 in total

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