Dataset Information

Thin-Slice Magnetic Resonance Imaging-Based Radiomics Signature Predicts Chromosomal 1p/19q Co-deletion Status in Grade II and III Gliomas.

ABSTRACT: Objective: Chromosomal 1p/19q co-deletion is recognized as a diagnostic, prognostic, and predictive biomarker in lower grade glioma (LGG). This study aims to construct a radiomics signature to non-invasively predict the 1p/19q co-deletion status in LGG. Methods: Ninety-six patients with pathology-confirmed LGG were retrospectively included and randomly assigned into training (n = 78) and validation (n = 18) dataset. Three-dimensional contrast-enhanced T1 (3D-CE-T1)-weighted magnetic resonance (MR) images and T2-weighted MR images were acquired, and simulated-conventional contrast-enhanced T1 (SC-CE-T1)-weighted images were generated. One hundred and seven shape, first-order, and texture radiomics features were extracted from each imaging modality and selected using the least absolute shrinkage and selection operator on the training dataset. A 3D-radiomics signature based on 3D-CE-T1 and T2-weighted features and a simulated-conventional (SC) radiomics signature based on SC-CE-T1 and T2-weighted features were established using random forest. The radiomics signatures were validated independently and evaluated using receiver operating characteristic (ROC) curves. Tumors with IDH mutations were also separately assessed. Results: Four radiomics features were selected to construct the 3D-radiomics signature and displayed accuracies of 0.897 and 0.833, areas under the ROC curves (AUCs) of 0.940 and 0.889 in the training and validation datasets, respectively. The SC-radiomics signature was constructed with 4 features, but the AUC values were lower than that of the 3D signature. In the IDH-mutated subgroup, the 3D-radiomics signature presented AUCs of 0.950-1.000. Conclusions: The MRI-based radiomics signature can differentiate 1p/19q co-deletion status in LGG with or without predetermined IDH status. 3D-CE-T1-weighted radiomics features are more favorable than SC-CE-T1-weighted features in the establishment of radiomics signatures.

SUBMITTER: Kong Z

PROVIDER: S-EPMC7642873 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Thin-Slice Magnetic Resonance Imaging-Based Radiomics Signature Predicts Chromosomal 1p/19q Co-deletion Status in Grade II and III Gliomas.

Kong Ziren Z Jiang Chendan C Zhang Yiwei Y Liu Sirui S Liu Delin D Liu Zeyu Z Chen Wenlin W Liu Penghao P Yang Tianrui T Lyu Yuelei Y Zhao Dachun D You Hui H Wang Yu Y Ma Wenbin W Feng Feng F

Frontiers in neurology 20201022

Objective: Chromosomal 1p/19q co-deletion is recognized as a diagnostic, prognostic, and predictive biomarker in lower grade glioma (LGG). This study aims to construct a radiomics signature to non-invasively predict the 1p/19q co-deletion status in LGG. Methods: Ninety-six patients with pathology-confirmed LGG were retrospectively included and randomly assigned into training (n = 78) and validation (n = 18) dataset. Three-dimensional contrast-enhanced T1 (3D-CE-T1)-we ...[more]

PMID: 33192984

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Project description:High-grade gliomas are malignant neuroepithelial tumors. The current WHO classification for adult-type diffuse gliomas is based on IDH1/2 mutational and 1p/19q-codeletion status, which can be refined by emerging genomics, transcriptomics, and methylomics approaches. Nevertheless, therapy has been dominated by radiochemotherapy for about 15 years and progressed little in efficacy or precision through advanced molecular patient stratification. Glioma proteome alterations remain undercharacterized despite their promise for a better stratification and, in particular, the identification of therapeutic targets. Here, we used mass spectrometry (MS) to characterize 42 formalin-fixed, paraffin-embedded (FFPE) samples from IDH-wildtype (IDHwt), IDH-mutant (IDHmut) gliomas with and without 1p/19q-codeletion, and non-neoplastic brain tissue controls. Based on more than 5500 quantified proteins and 5000 phospho-sites, gliomas separated according to IDH1/2 mutational status and reflected loss of proteins encoded on 1p/19q in IDHmut, gains on chromosome 7 and losses on chromosome 10 in IDHwt. Unexpectedly, the 1p/19q-codeletion resulted in minor proteome changes. Instead, two proteomic subtypes of IDHmut gliomas showed major perturbations of mitochondrial DNA-encoded proteins, aerobic/anaerobic energy metabolism, RNA metabolism, chromatin dynamics, the extracellular matrix as well as tumor suppressor and oncoproteins. Reanalysis of three glioma proteomics studies independently validate the observed hallmarks and associate these proteomic subtypes with the well-established proneural and classic/mesenchymal IDHwt glioma subtypes. These results suggest an alternative stratification of IDHmut gliomas as part of common phenotypic subtypes independent of the IDH status, with broad therapeutic implications for patients with IDHmut gliomas in the future. Altogether, our study provides a rich protein and phospho-site resource restratifying glioma subtypes and supporting future mechanism of action and target discovery investigations.

Project description:BACKGROUND AND PURPOSE:Isocitrate dehydrogenase (IDH)-mutant lower grade gliomas are classified as oligodendrogliomas or diffuse astrocytomas based on 1p/19q-codeletion status. We aimed to test and validate neuroradiologists' performances in predicting the codeletion status of IDH-mutant lower grade gliomas based on simple neuroimaging metrics. MATERIALS AND METHODS:One hundred two IDH-mutant lower grade gliomas with preoperative MR imaging and known 1p/19q status from The Cancer Genome Atlas composed a training dataset. Two neuroradiologists in consensus analyzed the training dataset for various imaging features: tumor texture, margins, cortical infiltration, T2-FLAIR mismatch, tumor cyst, T2* susceptibility, hydrocephalus, midline shift, maximum dimension, primary lobe, necrosis, enhancement, edema, and gliomatosis. Statistical analysis of the training data produced a multivariate classification model for codeletion prediction based on a subset of MR imaging features and patient age. To validate the classification model, 2 different independent neuroradiologists analyzed a separate cohort of 106 institutional IDH-mutant lower grade gliomas. RESULTS:Training dataset analysis produced a 2-step classification algorithm with 86.3% codeletion prediction accuracy, based on the following: 1) the presence of the T2-FLAIR mismatch sign, which was 100% predictive of noncodeleted lower grade gliomas, (n = 21); and 2) a logistic regression model based on texture, patient age, T2* susceptibility, primary lobe, and hydrocephalus. Independent validation of the classification algorithm rendered codeletion prediction accuracies of 81.1% and 79.2% in 2 independent readers. The metrics used in the algorithm were associated with moderate-substantial interreader agreement (κ = 0.56-0.79). CONCLUSIONS:We have validated a classification algorithm based on simple, reproducible neuroimaging metrics and patient age that demonstrates a moderate prediction accuracy of 1p/19q-codeletion status among IDH-mutant lower grade gliomas.

Project description:Approximately 50-80% of oligodendrogliomas demonstrate a combined loss of chromosome 1p and 19q. Chromosome 1p/19q deletion, appearing early in tumorigenesis, is associated with improved clinical outcomes, including response to chemotherapy and radiation. Although many hypotheses have been proposed, the molecular mechanisms underlying improved clinical outcomes with 1p/19q deletion in oligodendrogliomas have not been characterized fully. To investigate the molecular differences between oligodendrogliomas, we employed an unbiased proteomic approach using microcapillary liquid chromatography mass spectrometry, along with a quantitative technique called isotope-coded affinity tags, on patient samples of grade II oligodendrogliomas. Following conventional biochemical separation of pooled tumor tissue from five samples of undeleted and 1p/19q deleted grade II oligodendrogliomas into nuclei-, mitochondria-, and cytosol-enriched fractions, relative changes in protein abundance were quantified. Among the 442 total proteins identified, 163 nonredundant proteins displayed significant changes in relative abundance in at least one of the three fractions between oligodendroglioma with and without 1p/19q deletion. Bioinformatic analyses of differentially regulated proteins supported the potential importance of metabolism and invasion/migration to the codeleted phenotype. A subset of altered proteins, including the pro-invasive extracellular matrix protein BCAN, was further validated by Western blotting as candidate markers for the more aggressive undeleted phenotype. These studies demonstrate the utility of proteomic analysis to identify candidate biological motifs and molecular mechanisms that drive differential malignancy related to 1p19q phenotypes. Future analysis of larger patient samples are warranted to further refine biomarker panels to predict biological behavior and assist in the identification of deleted gene products that define the 1p/19q phenotype.

Dataset Information

Thin-Slice Magnetic Resonance Imaging-Based Radiomics Signature Predicts Chromosomal 1p/19q Co-deletion Status in Grade II and III Gliomas.

Publications

Thin-Slice Magnetic Resonance Imaging-Based Radiomics Signature Predicts Chromosomal 1p/19q Co-deletion Status in Grade II and III Gliomas.

Similar Datasets

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