The expression of fatty acid metabolism-associated proteins is correlated with the prognosis of meningiomas

Prediction of WHO grade and methylation class of aggressive meningiomas: Extraction of diagnostic information from infrared spectroscopic data

Background

Infrared (IR) spectroscopy allows intraoperative, optical brain tumor diagnosis. Here, we explored it as a translational technology for the identification of aggressive meningioma types according to both, the WHO CNS grading system and the methylation classes (MC).

Methods

Frozen sections of 47 meningioma were examined by IR spectroscopic imaging and different classification approaches were compared to discern samples according to WHO grade or MC.

Results

IR spectroscopic differences were more pronounced between WHO grade 2 and 3 than between MC intermediate and MC malignant, although similar spectral ranges were affected. Aggressive types of meningioma exhibited reduced bands of carbohydrates (at 1024 cm-1) and nucleic acids (at 1080 cm-1), along with increased bands of phospholipids (at 1240 and 1450 cm-1). While linear discriminant analysis was able to discern spectra of WHO grade 2 and 3 meningiomas (AUC 0.89), it failed for MC (AUC 0.66). However, neural network classifiers were effective for classification according to both WHO grade (AUC 0.91) and MC (AUC 0.83), resulting in the correct classification of 20/23 meningiomas of the test set.

Conclusions

IR spectroscopy proved capable of extracting information about the malignancy of meningiomas, not only according to the WHO grade, but also for a diagnostic system based on molecular tumor characteristics. In future clinical use, physicians could assess the goodness of the classification by considering classification probabilities and cross-measurement validation. This might enhance the overall accuracy and clinical utility, reinforcing the potential of IR spectroscopy in advancing precision medicine for meningioma characterization.

Integration and Comparison of Transcriptomic and Proteomic Data for Meningioma

Meningioma are the most frequent primary intracranial tumour. Management of aggressive meningioma is complex, and development of effective biomarkers or pharmacological interventions is hampered by an incomplete knowledge of molecular landscape. Here, we present an integrated analysis of two complementary omics studies to investigate alterations in the "transcriptome-proteome" profile of high-grade (III) compared to low-grade (I) meningiomas. We identified 3598 common transcripts/proteins and revealed concordant up- and downregulation in grade III vs. grade I meningiomas. Concordantly upregulated genes included FABP7, a fatty acid binding protein and the monoamine oxidase MAOB, the latter of which we validated at the protein level and established an association with Food and Drug Administration (FDA)-approved drugs. Notably, we derived a plasma signature of 21 discordantly expressed genes showing positive changes in protein but negative in transcript levels of high-grade meningiomas, including the validated genes CST3, LAMP2, PACS1 and HTRA1, suggesting the acquisition of these proteins by tumour from plasma. Aggressive meningiomas were enriched in processes such as oxidative phosphorylation and RNA metabolism, whilst concordantly downregulated genes were related to reduced cellular adhesion. Overall, our study provides the first transcriptome-proteome characterisation of meningioma, identifying several novel and previously described transcripts/proteins with potential grade III biomarker and therapeutic significance.

Accuracy of conventional MRI for preoperative diagnosis of intracranial tumors: A retrospective cohort study of 762 cases

BACKGROUND

Conventional magnetic resonance imaging (MRI) is considered a valuable tool for preoperative diagnosis of intracranial tumors. We assessed its accuracy in the diagnosis of intracranial tumors in usual clinical practice.

MATERIALS AND METHODS

MRI reports of 762 patients who had undergone conventional brain MRI prior to surgery were retrospectively reviewed. A 4-grade scoring system was devised to establish diagnostic agreement. Each tumor type was compared with the corresponding pathological diagnoses by dichotomization. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated for the overall patient population as well as for each tumor type.

RESULTS

664 cases (87.1%) were tumor-positive, and 98 cases (12.9%) were tumor-negative. The most common tumor types were meningiomas, gliomas, pituitary adenomas and schwannomas. These four types together comprised 74.5% of all cases reviewed. Sensitivity and PPV for the overall population were 72.0-90.7% and 91.9-95.4%, respectively. Diagnostic accuracy differed among tumor types. Meningiomas, pituitary adenomas, schwannomas and cholesteatomas were more likely to be diagnosed correctly (sensitivities were 82.6-96.9%, 86.1-96.7%, 88.9-98.2% and 91.3-100.0%, respectively); while some other types like solitary fibrous tumors (SFTs) seemed difficult to identify. Gliomas tended to be confused with metastases, meningiomas with SFTs, and pituitary adenomas with craniopharyngiomas.

CONCLUSION

The accuracy of conventional MRI for diagnosing intracranial tumors is generally satisfactory but should not be too heavily relied upon, especially for certain tumor types. In cases of discrepancy, neurosurgeons are encouraged to confer with the reporting neuroradiologists to achieve optimal preoperative diagnoses.

Posttranscriptional deregulation of signaling pathways in meningioma subtypes by differential expression of miRNAs

BACKGROUND

Micro (mi)RNAs are key regulators of gene expression and offer themselves as biomarkers for cancer development and progression. Meningioma is one of the most frequent primary intracranial tumors. As of yet, there are limited data on the role of miRNAs in meningioma of different histological subtypes and the affected signaling pathways.

METHODS

In this study, we compared expression of 1205 miRNAs in different meningioma grades and histological subtypes using microarrays and independently validated deregulation of selected miRNAs with quantitative real-time PCR. Clinical utility of a subset of miRNAs as biomarkers for World Health Organization (WHO) grade II meningioma based on quantitative real-time data was tested. Potential targets of deregulated miRNAs were discovered with an in silico analysis.

RESULTS

We identified 13 miRNAs deregulated between different subtypes of benign meningiomas, and 52 miRNAs deregulated in anaplastic meningioma compared with benign meningiomas. Known and putative target genes of deregulated miRNAs include genes involved in epithelial-to-mesenchymal transition for benign meningiomas, and Wnt, transforming growth factor-β, and vascular endothelial growth factor signaling for higher-grade meningiomas. Furthermore, a 4-miRNA signature (miR-222, -34a*, -136, and -497) shows promise as a biomarker differentiating WHO grade II from grade I meningiomas with an area under the curve of 0.75.

CONCLUSIONS

Our data provide novel insights into the contribution of miRNAs to the phenotypic spectrum in benign meningiomas. By deregulating translation of genes belonging to signaling pathways known to be important for meningioma genesis and progression, miRNAs provide a second in line amplification of growth promoting cellular signals. MiRNAs as biomarkers for diagnosis of aggressive meningiomas might prove useful and should be explored further in a prospective manner.

Pathology and molecular genetics of meningioma: recent advances

Meningiomas are the most common intracranial primary neoplasm in adults. Although the spectrum of clinical and molecular genetic issues regarding meningiomas remains undefined, novel genetic alterations that are associated with tumor morphology, malignancy, or location have recently been discovered. This review focuses on recent advances in understanding of the heterogenous pathology of meningiomas, particularly on associations between the clinical, histological, etiological, epidemiological, and molecular genetical aspects of the neoplasm.