An Integrative Survival Analysis for Multicentric Low-Grade Glioma

Wang, Tianwei; Yang, Yanping; Xu, Xiao-Ke; Niu, Xiaodong; Yang, Renhao; Gao, Ting; Kong, Lin; Mao, Qing; Qiu, Yongming

doi:10.1016/j.wneu.2019.10.001

Cited by 5 publications

(7 citation statements)

References 24 publications

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“…Most of the lesions have the same or similar pathological grade, such as GB, GB combined with AA, or all low-grade astrocytoma, but there are also a few cases diagnosed as high-grade glioma combined with low-grade glioma. In these cases, the median progression-free survival (PFS) time is 9 months ( 36 ), which is similar to high-grade MCG. Special types include epithelioid GB ( 37 ), optic glioma ( 37 – 39 ), ganglion glioma ( 40 , 41 ), pilocytic astrocytoma ( 28 , 29 ), and oligodendroglioma ( 28 ) (clinical and pathological features are summarized in Table 1 ).…”

Section: Pathological Typesmentioning

confidence: 89%

Multicentric Glioma: An Ideal Model to Reveal the Mechanism of Glioma

Yan

Dai²,

Mei³

2022

Front. Oncol.

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As a special type of glioma, multicentric glioma provides an ideal pathological model for glioma research. According to the stem-cell-origin theory, multiple lesions of multicentric glioma share the same neuro-oncological origin, both in gene level and in cell level. Although the number of studies focusing on genetic evolution in gliomas with the model of multicentric gliomas were limited, some mutations, including IDH1 mutations, TERTp mutations and PTEN deletions, are found to be at an early stage in the process of genetic aberrance during glioma evolution based on the results of these studies. This article reviews the clinical reports and genetic studies of multicentric glioma, and intends to explain the various clinical phenomena of multicentric glioma from the perspective of genetic aberrance accumulation and tumor cell evolution. The malignant degree of a glioma is determined by both the tumorigenicity of early mutant genes, and the stemness of early suffered cells.

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Section: Pathological Typesmentioning

confidence: 89%

Multicentric Glioma: An Ideal Model to Reveal the Mechanism of Glioma

Yan

Dai²,

Mei³

2022

Front. Oncol.

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“…An LGG compared with an HGG portends a more benign clinical course and better survival rates; it is well established that the early diagnosis and gross total resection of an LGG can achieve long-term remission in low risk patient groups [61,62]. The synergy of multidisciplinary teams (neurosurgery, neurology, epileptology, neurooncology and neuroradiology) in LGG patient management is paramount particularly with the addition of high dimensional quantitative datasets such as deep learning-based radiomics.…”

Section: Discussionmentioning

confidence: 99%

“…In DLR, deep neural networks are trained to recognize certain featural patterns, normalize the image information for an accurate segmentation and directly extract high throughput image features. This may overcome the need to manually delineate image segmentation and the lack of standardized image feature extraction seen in traditional radiomics [60,61]. Li et al delineated the IDH1 status in LGGs using both traditional radiomics and DLR to see if these two models distinguished tumors with different accuracies.…”

Section: Pushing the Envelope And Future Directions For Radiomics In Neurooncologymentioning

confidence: 99%

“…After extracting high throughput features from the convolutional neural network (CNN) of the DLR, they used statistical analyses to find a distinct radiomics signature that differentiated the IDH1 mutation status. This resulted in an AUC of 92% when one imaging modality was used (T2) and an AUC of 85% when multiple-modality MR images were used; both of these DLR methods were better at distinguishing an IDH1 mutation than traditional radiomics (AUC = 0.86) [61]. Diffusion tensor imaging (DTI) radiomics has also been shown to predict the IDH mutation status of LGGs (AUC = 0.9) greater than conventional radiomics (AUC = 0.835) [62].…”

Section: Pushing the Envelope And Future Directions For Radiomics In Neurooncologymentioning

confidence: 99%

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MRI-Based Radiomics and Radiogenomics in the Management of Low-Grade Gliomas: Evaluating the Evidence for a Paradigm Shift

Habib

Jovanovich

Hoppe

et al. 2021

JCM

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Low-grade gliomas (LGGs) are tumors that affect mostly adults. These neoplasms are comprised mainly of oligodendrogliomas and diffuse astrocytomas. LGGs remain vexing to current management and therapeutic modalities although they exhibit more favorable survival rates compared with high-grade gliomas (HGGs). The specific genetic subtypes that these tumors exhibit result in variable clinical courses and the need to involve multidisciplinary teams of neurologists, epileptologists, neurooncologists and neurosurgeons. Currently, the diagnosis of an LGG pivots mainly around the preliminary radiological findings and the subsequent definitive surgical diagnosis (via surgical sampling). The introduction of radiomics as a high throughput quantitative imaging technique that allows for improved diagnostic, prognostic and predictive indices has created more interest for such techniques in cancer research and especially in neurooncology (MRI-based classification of LGGs, predicting Isocitrate dehydrogenase (IDH) and Telomerase reverse transcriptase (TERT) promoter mutations and predicting LGG associated seizures). Radiogenomics refers to the linkage of imaging findings with the tumor/tissue genomics. Numerous applications of radiomics and radiogenomics have been described in the clinical context and management of LGGs. In this review, we describe the recently published studies discussing the potential application of radiomics and radiogenomics in LGGs. We also highlight the potential pitfalls of the above-mentioned high throughput computerized techniques and, most excitingly, explore the use of machine learning artificial intelligence technologies as standalone and adjunct imaging tools en route to enhance a personalized MRI-based tumor diagnosis and management plan design.

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“…1 Despite great efforts have dedicated to the therapeutic strategies for glioma over the past years, including surgery, radiotherapy and chemotherapy, the 5-year survival rate of glioma patients remains dismal. 2 Thus, elucidating the molecular mechanisms underlying glioma and identifying effective biomarkers are essential to developing effective treatment modalities for this deadly malignancy.…”

Section: Introductionmentioning

confidence: 99%

<p>Long Non-Coding RNA LINC00662 Regulated Proliferation and Migration by Targeting miR-34a-5p/LMAN2L Axis in Glioma</p>

Geng

et al. 2020

OTT

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Background: Numerous studies suggest that long non-coding RNAs (lncRNAs) participate in the biological process of diverse malignancies, including glioma. Although many differentially expressed lncRNAs have been identified in glioma, to our best knowledge, the role of LINC00662 and its potential underlying mechanism in glioma progression remains unclear. This study aimed to explore the function and regulatory network of LINC00662 in glioma. Methods: Expressions of LINC00662, miR-34a-5p and lectin mannose-binding 2-like (LMAN2L) in glioma tissues were analyzed using The Cancer Genome Atlas Program (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases. Colony formation, Celltiter-Glo and BrdU (5-bromo-2ʹ-deoxyuridine) incorporation assays were used to detect cell proliferation in vitro. Xenograft mouse models were established to determine cell proliferation in vivo. Transwell and wound healing assay was used to detect cell migration. In addition, epithelial-mesenchymal transition (EMT) markers were detected by Western blot. Annexin V and 7-AAD were used to stain apoptotic cells. Interactions between miR-34a-5p and LINC00662 or the 3′-UTR of LMAN2L were predicted and determined by bioinformatics analysis, luciferase reporter assay and RNA immunoprecipitation (RIP) assays. Results: High LINC00662 level predicted poor overall survival of glioma patients. Functional studies revealed that suppression of LINC00662 remarkably inhibited cell proliferation, clonogenicity and EMT pathway. Mechanistically, LINC00662 sponged miR-34a-5p to regulate LMAN2L expression. Furthermore, miR-34a-5p inhibitor reversed the anti-proliferation and anti-migration effect of LINC00662 knockdown, which could be rescued by downregulation of LMAN2L in glioma cells. Conclusion: Our study was the first to report that LINC00662 acted as a competing endogenous RNA (ceRNA) to regulate glioma progression by targeting miR-34a-5p/ LMAN2L axis, providing a new therapeutic target for glioma.

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An Integrative Survival Analysis for Multicentric Low-Grade Glioma

Cited by 5 publications

References 24 publications

Multicentric Glioma: An Ideal Model to Reveal the Mechanism of Glioma

Multicentric Glioma: An Ideal Model to Reveal the Mechanism of Glioma

MRI-Based Radiomics and Radiogenomics in the Management of Low-Grade Gliomas: Evaluating the Evidence for a Paradigm Shift

<p>Long Non-Coding RNA LINC00662 Regulated Proliferation and Migration by Targeting miR-34a-5p/LMAN2L Axis in Glioma</p>

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