Dataset Information

Rapid determination of isocitrate dehydrogenase mutation status of human gliomas by extraction nanoelectrospray using a miniature mass spectrometer.

ABSTRACT: Isocitrate dehydrogenase (IDH) I and II mutations in gliomas cause an abnormal accumulation of 2-hydroxyglutarate (2-HG) in these tumor cells. These mutations have potential prognostic value in that knowledge of the mutation status can lead to improved surgical resection. Information on mutation status obtained by immunohistochemistry or genomic analysis is not available during surgery. We report a rapid extraction nanoelectrospray ionization (nESI) method of determining 2-HG. This should allow the determination of IDH mutation status to be performed intraoperatively, within minutes, using a miniature mass spectrometer. This study demonstrates that the combination of tandem mass spectrometry with low-resolution mass spectrometry allows this analysis to be performed with confidence. Graphical Abstract.

SUBMITTER: Pu F

PROVIDER: S-EPMC6450702 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Rapid determination of isocitrate dehydrogenase mutation status of human gliomas by extraction nanoelectrospray using a miniature mass spectrometer.

Pu Fan F Alfaro Clint M CM Pirro Valentina V Xie Zhuoer Z Ouyang Zheng Z Cooks R Graham RG

Analytical and bioanalytical chemistry 20190202 8

Isocitrate dehydrogenase (IDH) I and II mutations in gliomas cause an abnormal accumulation of 2-hydroxyglutarate (2-HG) in these tumor cells. These mutations have potential prognostic value in that knowledge of the mutation status can lead to improved surgical resection. Information on mutation status obtained by immunohistochemistry or genomic analysis is not available during surgery. We report a rapid extraction nanoelectrospray ionization (nESI) method of determining 2-HG. This should allow ...[more]

PMID: 30710208

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Project description:BackgroundIsocitrate dehydrogenase (IDH) mutation status is an important biomarker for the treatment strategy selection and prognosis evaluation of glioma. The purpose of this study is to predict the IDH mutation status of gliomas based on multicenter magnetic resonance (MR) images using radiomic models, which were composed from the selected radiomics features and logistic regression (LR), support vector machine (SVM), and LR least absolute shrinkage and selection operator (LASSO) classifiers.MethodsWe retrospectively reviewed the medical records of 205 patients with gliomas. We enrolled 78 patients from Shandong Provincial Hospital from January 2018 to December 2019 as testing sets and 127 patients from The Cancer Genome Atlas (TCGA) as training sets. Preoperative MR images were stratified according to their IDH status, and the participants formed a consecutive and random series. Four MR modalities, including T1C, T2, T1 fluid-attenuated inversion recovery (FLAIR), and T2 FLAIR, were used for analysis. Five-fold cross-validation was adopted to train the models, and the models' performances were verified through the testing set. Tumor volumes of interest (VOI) were delineated on the 4 MR modalities. A total of 428 radiomics features were extracted. Two feature selection algorithms, Pearson correlation coefficient (PCC) and recursive feature elimination (RFE), were used to select radiomics features. These features were fed into 3 machine learning classifiers, which were LR, SVM, and LR LASSO, to construct prediction models. The accuracy (ACC), sensitivity (SEN), specificity (SPEC), and area under the curve (AUC) were applied to measure the predictive performance of the radiomics models.ResultsThe LR (SVM and LR LASSO) classifier predicted IDH mutation status with an average testing set ACC of 80.77% (80.64% and 80.41%), a SEN of 73.68% (84.21% and 89.47%), a SPEC of 87.50% (67.50% and 62.50%), and an AUC of 0.8572 (0.8217 and 0.8164).ConclusionsThe radiomics models based on MR modalities demonstrated the potential to be used as tools across different data sets for the noninvasive prediction of the IDH mutation status in glioma.

Dataset Information

Rapid determination of isocitrate dehydrogenase mutation status of human gliomas by extraction nanoelectrospray using a miniature mass spectrometer.

Publications

Rapid determination of isocitrate dehydrogenase mutation status of human gliomas by extraction nanoelectrospray using a miniature mass spectrometer.

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