Molecular profiling predicts meningioma recurrence and reveals loss of DREAM complex repression in aggressive tumors

Patel, Akash J.; Wan, Ying-Wooi; Al‐Ouran, Rami; Revelli, Jean‐Pierre; Cardenas, Maria F.; Oneissi, Mazen; Liu, Xi; Jalali, Ali; Magnotti, John F.; Doddapaneni, Harshavardhan; Sebastian, Sherly; Heck, Kent A.; Goodman, J. Clay; Gopinath, Shankar P.; Liu, Zhandong; Rao, Ganesh; Plon, Sharon E.; Yoshor, Daniel; Wheeler, David A.; Zoghbi, Huda Y.; Klisch, Tiemo J.

doi:10.1101/679480

Cited by 20 publications

(49 citation statements)

References 46 publications

(58 reference statements)

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“…Please refer to Table 1 for details of our study cohort. In brief, we included six microarray series [GSE100534 ( 43 ), GSE77259 ( 44 ), GSE54934 ( 45 ), GSE43290 ( 46 ), GSE16581 ( 47 ), GSE74385 ( 48 )] with a combined 212 patients and one RNA-seq series [GSE136661 ( 49 )] with 145 patients. The distribution of histopathologic subtypes are illustrated in Supplementary Figure S2 .…”

Section: Resultsmentioning

confidence: 99%

Gene Expression Signatures Identify Biologically Homogenous Subgroups of Grade 2 Meningiomas

et al. 2020

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Introduction: Meningiomas are the most common brain tumor, with prevalence of approximately 3%. Histological grading has a major role in determining treatment choice and predicting outcome. While indolent grade 1 and aggressive grade 3 meningiomas exhibit relatively homogeneous clinical behavior, grade 2 meningiomas are far more heterogeneous, making outcome prediction challenging. We hypothesized two subgroups of grade 2 meningiomas which biologically resemble either World Health Organization (WHO) grade 1 or WHO grade 3. Our aim was to establish gene expression signatures that separate grade 2 meningiomas into two homogeneous subgroups: a more indolent subtype genetically resembling grade 1 and a more aggressive subtype resembling grade 3. Methods: We carried out an observational meta-analysis on 212 meningiomas from six distinct studies retrieved from the open-access platform Gene Expression Omnibus. Microarray data was analyzed with systems-level gene co-expression network analysis. Fuzzy C-means clustering was employed to reclassify 34 of the 46 grade 2 meningiomas (74%) into a benign "grade 1-like" (13/46), and malignant "grade 3like" (21/46) subgroup based on transcriptomic profiles. We verified shared biology between matching subgroups based on meta-gene expression and recurrence rates. These results were validated further using an independent RNA-seq dataset with 160 meningiomas, with similar results. Results: Recurrence rates of "grade 1-like" and "grade 3-like" tumors were 0 and 75%, respectively, statistically similar to recurrence rates of grade 1 (17%) and 3 (85%). We also found overlapping biological processes of new subgroups with their adjacent grades 1 and 3. Conclusion: These results underpin molecular signatures as complements to histological grading systems. They may help reshape prediction, follow-up planning, treatment decisions and recruitment protocols for future and ongoing clinical trials.

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Section: Resultsmentioning

confidence: 99%

Gene Expression Signatures Identify Biologically Homogenous Subgroups of Grade 2 Meningiomas

et al. 2020

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“…Recent studies have focused on molecular and genome-associated prognostic markers in meningioma ( 23 , 24 ). Sahm et al devised a DNA methylation-based grading system for meningioma that accurately stratified risk of recurrence in meningiomas more accurately than current WHO grading by analyzing methylation patterns in 40 genes known to contribute to meningioma genesis and progression ( 23 ).…”

Section: Prognostic Factors For Meningiomasmentioning

confidence: 99%

“…Similarly, Katz et al also demonstrate that methylation patterns on the H3 histone could predict recurrence of WHO grade I and II meningiomas ( 25 ). One recent study highlighted the use of RNA sequencing and whole-exome sequencing to predict recurrence more accurately than current WHO criteria ( 24 ). Interestingly, in all these studies, the authors report that their methods accurately predicted recurrence in a significant subset of WHO Grade I tumors where recurrence is typically low ( 23 – 25 ).…”

Section: Prognostic Factors For Meningiomasmentioning

confidence: 99%

Basis for Immunotherapy for Treatment of Meningiomas

et al. 2020

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Meningiomas are common tumors that account for approximately one third of CNS tumors diagnosed every year. They are classified by the World Health Organization in grades I-III. Higher grades have an increased rate of growth, invasiveness, rate of recurrence, and worse outcomes than lower grades. Most meningiomas are grade I, while ~18% of meningiomas are grade II and III in hospital-based series. Meningiomas are typically “benign” tumors that are treated with surgery and radiation. However, when they recur or are unresectable, treatment options are very limited, especially since they are chemotherapy-resistant. Recent advances in the treatment of cancers with immunotherapy have focused on checkpoint blockade as well as other types of immunotherapy. There is emerging evidence supporting the use of immunotherapy as a potentially effective treatment strategy for meningioma patients. The immune microenvironment of meningiomas is a complex interplay of genetic alterations, immunomodulatory protein expression, and tumor-immune cell interactions. Meningiomas are known to be infiltrated by immune cells including microglia, macrophages, B-cells, and T-cells. Several mechanisms contribute to decreased an ti-tumor immune response, allowing tumor growth and evasion of the immune system. We discuss the most current knowledge on the immune micro-environment of meningiomas, preclinical findings of immunotherapy in meningiomas, meningioma immunotherapy clinical trials, and also offer insight into future prospects for immunotherapies in meningiomas.

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“…For example, FOXM1 has been shown to be a critical driver of meningioma aggressiveness and is associated with the activating DREAM complex, thereby allowing cell-cycle progression and cell proliferation 8 . SUZ12 is known as an element in PRC2, which is involved in chromatin silencing and appears to be lost in a subset of comparatively indolent meningioma 8 . EP300, an apoptosis-associated transcription factor, has been shown to be downregulated in meningioma when compared to normal arachnoid 27 though it's role in meningioma prognostication is not well understood.…”

Section: Discussionmentioning

confidence: 99%

“…The genetic landscape of meningiomas is the next frontier to our understanding of its biology and its relation to disease recurrence, and many studies have begun to elucidate important molecular associations with aggressiveness and recurrence. For example, previous studies have identified chromosomal rearrangements 4 , mutations in genes TERT 5 , AKT1 6 , SMO 7 , DREAM complex repression 8 , and DNA methylation [9][10][11]…”

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confidence: 99%

Meta-gene markers predict meningioma recurrence with high accuracy

Zádor

Landry

Haibe‐Kains

et al. 2020

Sci Rep

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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.

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Molecular profiling predicts meningioma recurrence and reveals loss of DREAM complex repression in aggressive tumors

Cited by 20 publications

References 46 publications

Gene Expression Signatures Identify Biologically Homogenous Subgroups of Grade 2 Meningiomas

Gene Expression Signatures Identify Biologically Homogenous Subgroups of Grade 2 Meningiomas

Basis for Immunotherapy for Treatment of Meningiomas

Meta-gene markers predict meningioma recurrence with high accuracy

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