DNA Methylation Associates With Clinical Courses of Atypical Meningiomas: A Matched Case-Control Study

Evolving concepts in meningioma management in the era of genomics

Meningioma is the most common type of primary brain tumor. Surgical resection followed by surveillance is the first-line treatment for the majority of symptomatic meningiomas; however, recent advances in molecular sequencing, DNA methylation, proteomics, and single-cell sequencing provide insights into further characterizing this heterogeneous group of tumors with a wide range of prognoses. A subset of these tumors are highly aggressive and cause severe morbidity and mortality. Therefore, identifying those individuals with a poor prognosis and intervening are critical. This review aims to help readers interpret the molecular profiling of meningiomas to identify patients with worse prognoses and guide the management and strategy for surveillance.

Secreted clusterin inhibits tumorigenesis by modulating tumor cells and macrophages in human meningioma

BACKGROUND

Meningioma is the most common primary intracranial tumor with a high frequency of postoperative recurrence, yet the biology of the meningioma malignancy process is still obscure.

METHODS

To identify potential therapeutic targets and tumor suppressors, we performed single-cell transcriptome analysis through meningioma malignancy, which included 18 samples spanning normal meninges, benign and high-grade in situ tumors, and lung metastases, for extensive transcriptome characterization. Tumor suppressor candidate gene and molecular mechanism were functionally validated at the animal model and cellular levels.

RESULTS

Comprehensive analysis and validation in mice and clinical cohorts indicated clusterin (CLU) had suppressive function for meningioma tumorigenesis and malignancy by inducing mitochondria damage and triggering type 1 interferon pathway dependent on its secreted isoform, and the inhibition effect was enhanced by TNFα as TNFα also induced type 1 interferon pathway. Meanwhile, both intra- and extracellular CLU overexpression enhanced macrophage polarization towards M1 phenotype and TNFα production, thus promoting tumor killing and phagocytosis.

CONCLUSIONS

CLU might be a key brake of meningioma malignance by synchronously modulating tumor cells and their microenvironment. Our work provides comprehensive insights into meningioma malignancy and a potential therapeutic strategy.

A comprehensive correlation of the KI-67 proliferation index to patient´s, imaging and tumor features and its value in predicting long-term course of patients with newly diagnosed intracranial meningiomas

To analyze the correlation of KI-67-Proliferation Index (KI-67-PI) with preoperative patients and MRI characteristics, WHO grading, histological subtype and long-term-course of patients with newly diagnosed intracranial meningiomas (IM). In this single-center retrospective study, all consecutive patients with IM were analyzed from January 2007 to August 2019. Patient´s demographics (age, sex), imaging parameters (location, volume, edema, necrosis), and tumor features (WHO grade, histology) were assessed and correlated with KI-67-PI. Long-term data were retrieved from patient's last follow-up visits. This study included 463 IM in 457 surgically treated patients. Males exhibited a higher KI-67-PI than females (7.31 ± 0.22 vs. 5.37 ± 0.53; p < 0.01, Mann-Whitney U Test). Age positively correlated with KI-67-PI in both sexes (p < 0.01, Spearman), with older patients having a higher KI-67-PI. KI-67-PI was significantly higher in convexity IM compared to frontobasal IM (7.15 ± 5.56 vs. 4.66 ± 2.94; p < 0.05, ANOVA, Tukey´s HSD), while no difference in KI-67-PI expression was found when other locations were compared to each other (Tukey´s HSD). Higher KI-67-PI was significantly correlated with larger tumor volume (p < 0.01, Spearman), larger tumor necrosis and larger peritumoral edema (p < 0.01, Kruskal-Wallis). Patients with recurrent IM had a significantly higher KI-67-PI than patients without recurrence (8.24 ± 5.88 vs. 5.14 ± 3.53; p < 0.01, ANOVA, Tukey´s HSD) during a mean follow-up period of 80.92 ± 38.1 months. Atypical and anaplastic IM exhibited significantly higher KI-67-PI compared to all other WHO grade 1 histological subtypes (12.09 ± 0.73 vs. 4.51 ± 0.13; p < 0.01, Kruskal-Wallis test) and KI-67-PI was significantly higher in anaplastic IM compared to atypical meningioma (19.67 ± 1.41 vs. 11.01 ± 0.38; p < 0.01, ANOVA). Higher KI-67-PI is not only associated with atypical and anaplastic subtypes of IM, but is also significantly higher in males, positively correlates with patients age, larger tumor volume, lager peritumoral edema and necrosis on preoperative MRI and predicts tumor recurrence. Therefore, KI-67-PI may serve as a decision indicator for adjuvant treatment in patients with IM.

Molecular classification and grading of meningioma

PURPOSE

Meningiomas are the most common primary intracranial tumor in older adults (Ostrom et al. in Neuro Oncol 21(Suppl 5):v1-v100, 2019). Treatment is largely driven by, in addition to patient characteristics and extent of resection/Simpson grade, the World Health Organization (WHO) grading of meningiomas. The current grading scheme, based predominantly on histologic features and only limited molecular characterization of these tumors (WHO Classification of Tumours Editorial Board, in: Central nervous system tumours, International Agency for Research on Cancer, Lyon, 2021), (Mirian et al. in J Neurol Neurosurg Psychiatry 91(4):379-387, 2020), does not consistently reflect the biologic behavior of meningiomas. This leads to both under-treatment and over-treatment of patients, and hence, suboptimal outcomes (Rogers et al. in Neuro Oncol 18(4):565-574). The goal of this review is to synthesize studies to date investigating molecular features of meningiomas as they relate to patient outcomes, in order to clarify best practices in assessing and, therefore, treating meningiomas.

METHODS

The available literature of genomic landscape and molecular features of in meningioma was screened using PubMed.

RESULTS

Greater understanding of meningiomas is reached by integrating histopathology, mutational analysis, DNA copy number changes, DNA methylation profiles, and potentially additional modalities to fully capture the clinical and biologic heterogeneity of these tumors.

CONCLUSION

Diagnosis and classification of meningioma is best accomplished using a combination of histopathology with genomic and epigenomic factors. Future classification schemes may benefit from such an integrated approach.

Spatial heterogeneity in DNA methylation and chromosomal alterations in diffuse gliomas and meningiomas

Adult-type diffuse gliomas and meningiomas are the most common primary intracranial tumors of the central nervous system. DNA methylation profiling is a novel diagnostic technique increasingly used also in the clinic. Although molecular heterogeneity is well described in these tumors, DNA methylation heterogeneity is less studied. We therefore investigated the intratumor genetic and epigenetic heterogeneity in diffuse gliomas and meningiomas, with focus on potential clinical implications. We further investigated tumor purity as a source for heterogeneity in the tumors. We analyzed genome-wide DNA methylation profiles generated from 126 spatially separated tumor biopsies from 39 diffuse gliomas and meningiomas. Moreover, we evaluated five methods for measurement of tumor purity and investigated intratumor heterogeneity by assessing DNA methylation-based classification, chromosomal copy number alterations and molecular markers. Our results demonstrated homogeneous methylation-based classification of IDH-mutant gliomas and further corroborates subtype heterogeneity in glioblastoma IDH-wildtype and high-grade meningioma patients after excluding samples with low tumor purity. We detected a large number of differentially methylated CpG sites within diffuse gliomas and meningiomas, particularly in tumors of higher grades. The presence of CDKN2A/B homozygous deletion differed in one out of two patients with IDH-mutant astrocytomas, CNS WHO grade 4. We conclude that diffuse gliomas and high-grade meningiomas are characterized by intratumor heterogeneity, which should be considered in clinical diagnostics and in the assessment of methylation-based and molecular markers.