The Prognostic Value of Methylation Signatures and NF2 Mutations in Atypical Meningiomas

The development of a combined clinico-radiomics model for predicting post-operative recurrence in atypical meningiomas: a multicenter study

PURPOSE

Atypical meningiomas could manifest early recurrence after surgery and even adjuvant radiotherapy. We aimed to construct a clinico-radiomics model to predict post-operative recurrence of atypical meningiomas based on clinicopathological and radiomics features.

MATERIALS AND METHODS

The study cohort was comprised of 224 patients from two neurosurgical centers. 164 patients from center I were divided to the training cohort for model development and the testing cohort for internal validation. 60 patients from center II were used for external validation. Clinicopathological characteristics, radiological semantic, and radiomics features were collected. A radiomic signature was comprised of four radiomics features. A clinico-radiomics model combining the radiomics signature and clinical characteristics was constructed to predict the recurrence of atypical meningiomas.

RESULTS

1920 radiomics features were extracted from the T1 Contrast and T2-FLAIR sequences of patients in center I. The radiomics signature was able to differentiate post-operative patients into low-risk and high-risk groups based on tumor recurrence (P < 0.001). A clinic-radiomics model was established by combining age, extent of resection, Ki-67 index, surgical history and the radiomics signature for recurrence prediction in atypical meningiomas. The model achieved a good prediction performance with the integrated AUC of 0.858 (0.802-0.915), 0.781 (0.649-0.912) and 0.840 (0.747-0.933) in the training, internal validation and external validation cohort, respectively.

CONCLUSIONS

The present study established a radiomics signature and a clinico-radiomics model with a favorable performance in predicting tumor recurrence for atypical meningiomas.

Favorable Long-Term Outcomes of Chordoid Meningioma Compared With the Other WHO Grade 2 Meningioma Subtypes

BACKGROUND

WHO grade 2 meningiomas, including atypical, chordoid, and clear cell subtypes, form a heterogenous group of meningiomas with varying aggressiveness and clinical behavior.

OBJECTIVE

To demonstrate the differences of clinical-histopathological characteristics and long-term outcomes among these 3 subtypes.

METHODS

A total of 609 consecutive patients diagnosed with WHO grade 2 meningiomas (543 atypical meningiomas [AMs], 36 chordoid meningiomas [CMs], and 30 clear cell meningiomas [CCMs]) from 2010 to 2018 were enrolled in this study. We compared the clinical-histopathological characteristics and long-term outcomes in these 3 subtypes and assessed survival differences among the subtypes. Targeted panel sequencing of meningioma-relevant genes was performed in the cases of CM.

RESULTS

The patients with CCM were significantly younger than those with AM ( P < .001) and CM ( P = .016). CMs were more likely to receive gross total resection than AMs and CCMs ( P = .033). The Ki-67 index was lower ( P < .001) while the progesterone receptors-positive rate was higher ( P = .034) in CM than in AM and CCM. Importantly, survival analysis demonstrated that CM had better progression-free survival ( P = .022) and overall survival ( P = .0056) than non-CM tumors. However, the PFS of CM was still worse than WHO grade 1 meningiomas ( P < .001). Alterations in NF2 (20.6%) and KMT2C (26.5%) were associated with poorer PFS in CM ( P = .013 for NF2 ; P = .021 for KMT2C ).

CONCLUSION

Patients with CM had better long-term postoperative outcomes than the other WHO grade 2 subtypes. A lower Ki-67 index, higher PR status, higher extent of resection, and lower frequency of NF2 alteration might contribute to favorable clinical outcomes of CM.

DNA methylation profiling of meningiomas highlights clinically distinct molecular subgroups

BACKGROUND

Introduction of the classification of brain tumours based on DNA methylation profile has significantly changed the diagnostic approach. Due to the paucity of data on the molecular profiling of meningiomas and their clinical implications, no effective therapies and new treatments have been implemented.

METHODS

DNA methylation profiling, copy number analysis, targeted sequencing and H3K27me3 expression was performed on 35 meningiomas and 5 controls.

RESULTS

Unsupervised hierarchical clustering (UHC) analysis revealed four distinct molecular subgroups: Malignant; Intermediate; Benign A, and Benign B. Molecular heterogeneity was observed within the same grade as the Intermediate, Benign A, and Benign B subgroups were composed of WHO grade 1 as well as grade 2 cases. There was association of mutations with distinct methylation subgroups (NF2, AKT1, SMO, TRAF7 and pTERT). Loss of chromosome 22q was observed across all subgroups. 1p/14q co-deletion was seen in 50% of malignant and intermediate while CDKN2A loss was predominantly observed in malignant subgroup (50%). Majority of malignant (75%) and a small proportion of other subgroups (Intermediate: 25%, Benign A: 38.5%, and Benign B: 20%) harboured H3K27me3 loss. 38,734 genes were dysregulated amongst the four subgroups. DKFZ classified 71% cases with acceptable score. On survival analysis, methylation profiling had significant impact on progression-free-survival in WHO grade1 and 2 meningiomas (p = 0.0051).

CONCLUSION

Genome-wide DNA methylation profiling highlights clinically distinct molecular subgroups and heterogeneity within the same grade of meningiomas. Molecular profiling can usher in a paradigm shift in meningioma classification, prognostic prediction, and treatment strategy.

Clinical significance of NF2 alteration in grade I meningiomas revisited; prognostic impact integrated with extent of resection, tumour location, and Ki-67 index

NF2 alteration is the most commonly-found genetic abnormality in meningiomas and is known to initiate events for aggressive-type meningiomas. Whereas the prognosis of meningiomas differs depending on their epigenomic/transcriptomic profile, the effect of NF2 alteration on the prognosis of benign meningiomas is not fully elucidated. This study aimed to probe the importance of NF2 alteration in prognosis of WHO grade I meningiomas. A long-term retrospective follow-up (5.3 ± 4.5 years) study involving 281 consecutive WHO grade I meningioma patients was performed. We assessed tumour recurrence in correlation with extent of resection (EOR), histopathological findings, tumour location, and NF2 alteration. "NF2 meningioma" was defined as meningiomas with presence of NF2 mutation and/or 22q loss. Overall, NF2 meningioma per se was not a predictor of prognosis in the whole cohort; however, it was a predictor of recurrence in supratentorial meningiomas, together with EOR and Ki-67. In a striking contrast, NF2 meningioma showed a better prognosis than non-NF2 meningioma in infratentorial lesion. Supratentorial NF2 meningiomas had higher Ki-67 and forkhead box protein M1 expression than those of others, possibly explaining the worse prognosis in this subtype. The combination of NF2 alteration, high Ki-67 and supratentorial location defines subgroup with the worst prognosis among WHO grade I meningiomas. Clinical connotation of NF2 alteration in terms of prognosis of WHO grade I meningioma differs in an opposite way between supratentorial and infratentorial tumors. Integrated anatomical, histopathological, and genomic classifications will provide the best follow-up schedule and proactive measures.

A Clinical Prognostic Model Based on Preoperative Hematological and Clinical Parameters Predicts the Progression of Primary WHO Grade II Meningioma

Purpose

The purpose was to explore the correlation between hematological parameters and the progression of WHO grade II meningioma, and establish a clinical prognostic model based on hematological parameters and clinical prognostic factors to predict the progression-free survival (PFS) of patients.

Methods

A total of 274 patients with WHO grade II meningiomas were included. Patients were randomly divided into a training cohort (192, 70%) and a test cohort (82, 30%). In the training cohort, the least absolute shrinkage and selection operator Cox regression analysis were used to screen for hematological parameters with prognostic value, and the hematological risk model (HRM) was constructed based on these parameters; univariate and multivariate Cox regression analyses were utilized to screen for clinical prognostic factors, and a clinical prognostic model was constructed based on clinical prognostic factors and HRM. The prognostic stability and accuracy of the HRM and clinical prognostic model were verified in the test cohort. Subgroup analysis was performed according to the patients' different clinical characteristics.

Results

Preoperative neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, platelet-to-lymphocyte ratio, albumin-to-globulin ratio, D-dimer, fibrinogen, and lactate dehydrogenase were associated with the PFS of patients. The areas under curve of the HRM were 0.773 (95% confidence interval [CI] 0.707-0.839) and 0.745 (95% CI 0.637-0.852) in the training cohort and test cohort, respectively. The progression risk was higher in the high-risk group than that in the low-risk group categorized by the optimal cutoff value (2.05) of hematological risk scores. The HRM, age, tumor location, tumor size, peritumoral edema, extent of resection, Ki-67 index, and postoperative radiotherapy were the prognostic factors for the progression of meningiomas. The corrected C-index of the clinical prognosis model was 0.79 in the training cohort. Clinical decision analysis showed that the clinical prognostic model could be used to obtain favorable clinical benefits. In the subgroup analysis, the HRM displayed excellent prognostic stability and general applicability in different subgroups.

Conclusions

Preoperative hematological parameters are associated with the postoperative progression of WHO grade II meningiomas. The clinical prognosis model constructed based on hematological parameters and clinical prognostic factors has favorable predictive accuracy and clinical benefits.