Identification of Meningioma Patients at High Risk of Tumor Recurrence Using MicroRNA Profiling

Slavík, Hanuš; Balik, Vladimír; Vrbková, Jana; Řehulková, Alona; Vaverka, Miroslav; Hrabálek, Lumir; Ehrmann, Jiří; Vidlarova, Monika; Gurská, Soňa; Hajdúch, Marián; Srovnal, Josef

doi:10.1093/neuros/nyaa009

Cited by 19 publications

(19 citation statements)

References 34 publications

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“…Total RNA was purified from FFPE tumor samples in the same way as we previously reported. 8 RNA concentration and quality were assessed using a Nanodrop ND 1000 instrument (Thermo Fisher Scientific) and a Bioanalyzer 2100 using RNA Pico Kit and Chips (Agilent) according to the manufacturer's instructions. Only samples with DV 200 (%) ≥30 were selected for the subsequent RNA-seq analysis.…”

Section: Methodsmentioning

confidence: 99%

Transcriptomic Profiling Revealed Lnc-GOLGA6A-1 as a Novel Prognostic Biomarker of Meningioma Recurrence

et al. 2022

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BACKGROUND: Meningioma is the most common primary central nervous system neoplasm, accounting for about a third of all brain tumors. Because their growth rates and prognosis cannot be accurately estimated, biomarkers that enable prediction of their biological behavior would be clinically beneficial. OBJECTIVE: To identify coding and noncoding RNAs crucial in meningioma prognostication and pathogenesis. METHODS: Total RNA was purified from formalin-fixed and paraffin-embedded tumor samples of 64 patients with meningioma with distinct clinical characteristics (16 recurrent, 30 nonrecurrent with follow-up of >5 years, and 18 with follow-up of <5 years without recurrence). Transcriptomic sequencing was performed using the HiSeq 2500 platform (Illumina), and biological and functional differences between meningiomas of different types were evaluated by analyzing differentially expression of messenger RNA (mRNA) and long noncoding RNA (IncRNA). The prognostic value of 11 differentially expressed RNAs was then validated in an independent cohort of 90 patients using reverse transcription quantitative (real-time) polymerase chain reaction. RESULTS: In total, 69 mRNAs and 108 lncRNAs exhibited significant differential expression between recurrent and nonrecurrent meningiomas. Differential expression was also observed with respect to sex (12 mRNAs and 59 lncRNAs), World Health Organization grade (58 mRNAs and 98 lncRNAs), and tumor histogenesis (79 mRNAs and 76 lncRNAs). Lnc-GOLGA6A-1, ISLR2, and AMH showed high prognostic power for predicting meningioma recurrence, while lnc-GOLGA6A-1 was the most significant factor for recurrence risk estimation (1/hazard ratio = 1.31; P = .002). CONCLUSION: Transcriptomic sequencing revealed specific gene expression signatures of various clinical subtypes of meningioma. Expression of the lnc-GOLGA61-1 transcript was found to be the most reliable predictor of meningioma recurrence.

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Section: Methodsmentioning

confidence: 99%

Transcriptomic Profiling Revealed Lnc-GOLGA6A-1 as a Novel Prognostic Biomarker of Meningioma Recurrence

et al. 2022

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“…Thus, the presented models may allow for a more accurate prediction of time to recurrence of meningioma and, consequently, optimum postoperative therapy. Furthermore, combining this model with current knowledge of the molecular pathways behind recurrence should allow for the identification of distinct meningioma subtypes and more precise therapy [ 21 ].…”

Section: Reviewmentioning

confidence: 99%

Utilization of Cerebrospinal Fluid Proteome Analysis in the Diagnosis of Meningioma: A Systematic Review

Choudhary¹,

Elabbas²,

Vyas³

et al. 2021

Cureus

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Meningiomas have been classified as the most commonly occurring primary brain tumors. Although the majority of meningiomas are benign and slow-progressing, the tumors that grow to a larger size are associated with various risks during surgical procedures. Early detection of meningiomas is crucial to the treatment as those detected early can be treated through non-invasive methods. Due to their benign nature, meningiomas contain homogeneous protein biomarkers that can be easily identified. Cerebrospinal fluid (CSF) has a high protein composition which can be used to diagnose various brain tumors. Because CSF comes into direct contact with the brain during its functioning, it is one of the factors that makes it an important source of different biomarkers. An analysis of biochemical changes occurring in the CSF can be useful in assessing the condition of the periventricular white matter and the parenchyma. In this review, PubMed, Medline, PubMed Central, and Google Scholar were used to identify studies discussing meningiomas regarding their assessment, types, diagnosis, and treatment, with more attention directed towards the application of CSF proteome analysis in diagnosis. Priority was given to studies published within the last 15 years. The following keywords were used in the literature search: “cerebrospinal fluid,” “meningiomas,” “brain tumors,” “primary brain tumors,” “protein biomarkers,” “proteome analysis,” and “diagnosis.” Subsequently, the 15 most relevant studies were selected for inclusion in the review. We excluded studies discussing different types of non-brain tumors as well as older articles. The selected studies also underwent a quality appraisal process using corresponding assessment tools. The selected articles were highly informative about meningiomas and the processes of diagnosis and treatment that are currently in use as well as those that are being developed or implemented. The use of CSF proteins in the diagnostic process is also discussed in this review. The studies also describe proteomics as a less invasive procedure that allows for the analysis of entire proteins and the projection of diagnostic images with higher resolutions that aid in the diagnosis.

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“…Similarly, very recently the use of miRNAs profiling was proposed as novel tool to predict meningiomas recurrence, and improve patients' clinical management [161].…”

Section: Mirnas In Brain Tumorsmentioning

confidence: 99%

Brain Tumor-Derived Extracellular Vesicles as Carriers of Disease Markers: Molecular Chaperones and MicroRNAs

et al. 2020

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Primary and metastatic brain tumors are usually serious conditions with poor prognosis, which reveal the urgent need of developing rapid diagnostic tools and efficacious treatments. To achieve these objectives, progress must be made in the understanding of brain tumor biology, for example, how they resist natural defenses and therapeutic intervention. One resistance mechanism involves extracellular vesicles that are released by tumors to meet target cells nearby or distant via circulation and reprogram them by introducing their cargo. This consists of different molecules among which are microRNAs (miRNAs) and molecular chaperones, the focus of this article. miRNAs modify target cells in the immune system to avoid antitumor reaction and chaperones are key survival molecules for the tumor cell. Extracellular vesicles cargo reflects the composition and metabolism of the original tumor cell; therefore, it is a source of markers, including the miRNAs and chaperones discussed in this article, with potential diagnostic and prognostic value. This and their relatively easy availability by minimally invasive procedures (e.g., drawing venous blood) illustrate the potential of extracellular vesicles as useful materials to manage brain tumor patients. Furthermore, understanding extracellular vesicles circulation and interaction with target cells will provide the basis for using this vesicle for delivering therapeutic compounds to selected tumor cells.

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Identification of Meningioma Patients at High Risk of Tumor Recurrence Using MicroRNA Profiling

Cited by 19 publications

References 34 publications

Transcriptomic Profiling Revealed Lnc-GOLGA6A-1 as a Novel Prognostic Biomarker of Meningioma Recurrence

Transcriptomic Profiling Revealed Lnc-GOLGA6A-1 as a Novel Prognostic Biomarker of Meningioma Recurrence

Utilization of Cerebrospinal Fluid Proteome Analysis in the Diagnosis of Meningioma: A Systematic Review

Brain Tumor-Derived Extracellular Vesicles as Carriers of Disease Markers: Molecular Chaperones and MicroRNAs

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