Dataset Information

Genomic markers of recurrence risk in atypical meningioma following gross total resection.

ABSTRACT:

Background

Meningiomas are the most common primary central nervous system (CNS) tumor in adults and CNS World Health Organization grade 2 (atypical) meningiomas show an intermediate risk of recurrence/progression. Molecular parameters are needed to better inform management following gross total resection (GTR).

Methods

We performed comprehensive genomic analysis of tumor tissue from 63 patients who underwent radiologically confirmed GTR of a primary grade 2 meningioma, including a CLIA-certified target next-generation sequencing panel (n = 61), chromosomal microarray (n = 63), genome-wide methylation profiling (n = 62), H3K27me3 immunohistochemistry (n = 62), and RNA-sequencing (n = 19). Genomic features were correlated with long-term clinical outcomes (median follow-up: 10 years) using Cox proportional hazards regression modeling and published molecular prognostic signatures were evaluated.

Results

The presence of specific copy number variants (CNVs), including -1p, -10q, -7p, and -4p, was the strongest predictor of decreased recurrence-free survival (RFS) within our cohort (P < .05). NF2 mutations were frequent (51%) but did not show a significant association with RFS. DNA methylation-based classification assigned tumors to DKFZ Heidelberg benign (52%) or intermediate (47%) meningioma subclasses and was not associated with RFS. H3K27 trimethylation (H3K27me3) was unequivocally lost in 4 tumors, insufficient for RFS analysis. Application of published integrated histologic/molecular grading systems did not improve prediction of recurrence risk over the presence of -1p or -10q alone.

Conclusions

CNVs are strong predictors of RFS in grade 2 meningiomas following GTR. Our study supports incorporation of CNV profiling into clinical evaluation to better guide postoperative patient management, which can be readily implemented using existing, clinically validated technologies.

SUBMITTER: Vaubel RA

PROVIDER: S-EPMC9950854 | biostudies-literature | 2023 Jan-Dec

REPOSITORIES: biostudies-literature

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Publications

Genomic markers of recurrence risk in atypical meningioma following gross total resection.

Vaubel Rachael A RA Kumar Rahul R Weiskittel Taylor M TM Jenkins Sarah S Dasari Surendra S Uhm Joon H JH Lachance Daniel H DH Brown Paul D PD Van Gompel Jamie J JJ Jenkins Robert B RB Kipp Benjamin R BR Sukov William R WR Giannini Caterina C Johnson Derek R DR Raghunathan Aditya A

Neuro-oncology advances 20230110 1

<h4>Background</h4>Meningiomas are the most common primary central nervous system (CNS) tumor in adults and CNS World Health Organization grade 2 (atypical) meningiomas show an intermediate risk of recurrence/progression. Molecular parameters are needed to better inform management following gross total resection (GTR).<h4>Methods</h4>We performed comprehensive genomic analysis of tumor tissue from 63 patients who underwent radiologically confirmed GTR of a primary grade 2 meningioma, including a ...[more]

PMID: 36845294

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Project description:Meningiomas, the most common adult brain tumors, recur in up to half of cases. This requires timely intervention and therefore accurate risk assessment of recurrence is essential. Our current practice relies heavily on histological grade and extent of surgical excision to predict meningioma recurrence. However, prediction accuracy can be as poor as 50% for low or intermediate grade tumors which constitute the majority of cases. Moreover, attempts to find molecular markers to predict their recurrence have been impeded by low or heterogenous genetic signal. We therefore sought to apply systems-biology approaches to transcriptomic data to better predict meningioma recurrence. We apply gene co-expression networks to a cohort of 252 adult patients from the publicly available genetic repository Gene Expression Omnibus. Resultant gene clusters ("modules") were represented by the first principle component of their expression, and their ability to predict recurrence assessed with a logistic regression model. External validation was done using two independent samples: one merged microarray-based cohort with a total of 108 patients and one RNA-seq-based cohort with 145 patients, using the same modules. We used the bioinformatics database Enrichr to examine the gene ontology associations and driver transcription factors of each module. Using gene co-expression analysis, we were able predict tumor recurrence with high accuracy using a single module which mapped to cell cycle-related processes (AUC of 0.81 ± 0.09 and 0.77 ± 0.10 in external validation using microarray and RNA-seq data, respectively). This module remained predictive when controlling for WHO grade in all cohorts, and was associated with several cancer-associated transcription factors which may serve as novel therapeutic targets for patients with this disease. With the easy accessibility of gene panels in healthcare diagnostics, our results offer a basis for routine molecular testing in meningioma management and propose potential therapeutic targets for future research.

Dataset Information

Genomic markers of recurrence risk in atypical meningioma following gross total resection.

Background

Methods

Results

Conclusions

Publications

Genomic markers of recurrence risk in atypical meningioma following gross total resection.

Similar Datasets

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