Integrated genomic analyses of de novo pathways underlying atypical meningiomas

Harmancı, Akdes Serin; Youngblood, Mark W.; Clark, Victoria; Coşkun, Şahin; Henegariu, Octavian; Durán, Daniel; Erson‐Omay, E. Zeynep; Kaulen, Leon D.; Lee, Tong Ihn; Abraham, Brian J.; Simon, Matthias; Krischek, Boris; Timmer, Marco; Goldbrunner, Roland; Omay, Sacit Bulent; Baranoski, Jacob F; Baran, Burçin; Carrión-Grant, Geneive; Bai, Hanwen; Mishra-Gorur, Ketu; Schramm, Johannes; Moliterno, Jennifer; Vortmeyer, Alexander O.; Bilgüvar, Kaya; Yasuno, Katsuhito; Young, Richard A.; Günel, Murat

doi:10.1038/ncomms14433

Cited by 159 publications

(179 citation statements)

References 66 publications

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“…A major difference between our study and previous explorations of the genomic landscape of meningioma is that those studies maintained the framework of the existing WHO histopathological classification for their molecular analysis (13,(15)(16)(17)(18)(19)44). For example, one study of atypical (grade II) tumors found the majority to have NF2/chr22q loss and genomic instability along with overexpression of the E2F2 and FOXM1 transcriptional networks (13).…”

Section: Discussionmentioning

confidence: 80%

“…Since high-grade meningiomas have more chromosomal abnormalities (13,18), we analyzed the three types of tumors for genomic instability using copy number data derived from whole-exome sequencing (WES) ( Fig. 4).…”

Section: Copy Number and Somatic Alterations In Meningiomasmentioning

confidence: 99%

“…The first hint of an underlying genetic mechanism came from the observation that meningiomas frequently arise in the context of neurofibromatosis type 2 (NF2) (12). In fact, half of sporadic meningiomas and a majority of higher-grade tumors involve loss of NF2 function or loss of heterozygosity of chromosome 22q, where NF2 is located (13,14). Several whole exome/genome sequencing studies have identified recurrent somatic mutations in TRAF7, KLF4, AKT1, SMO, and POLR2A in benign (grade I) tumors (15)(16)(17).…”

Section: Introductionmentioning

confidence: 99%

“…Several whole exome/genome sequencing studies have identified recurrent somatic mutations in TRAF7, KLF4, AKT1, SMO, and POLR2A in benign (grade I) tumors (15)(16)(17). Harmanci et al found that a majority of primary atypical meningiomas have loss of NF2 along with either genomic instability or SMARCB1 mutations (13); this combination of features was not able to completely separate atypical from benign tumors, but the addition of the top 25 most differentially expressed genes raised the prediction accuracy of the model to 91% for atypical tumors with a high or medium Ki-67 index. Bi et al found that grade III tumors are less likely to have TRAF7, KL4, AKT1, or SMO mutations but more likely to show genomic instability (copy number variation or CNV) (18).…”

Section: Introductionmentioning

confidence: 99%

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

Patel

Wan

Al‐Ouran

et al. 2019

Preprint

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Meningiomas account for one-third of all primary brain tumors. Although typically benign, about 20% of meningiomas are aggressive, and despite the rigor of the current histopathological classification system, there remains considerable uncertainty in predicting tumor behavior. Here, we analyzed 160 tumors from all three WHO grades (I-III) using clinical, gene expression and sequencing data. Unsupervised clustering analysis identified three molecular types (A, B, and C) that reliably predicted recurrence. These groups did not directly correlate with the WHO grading system, which would classify more than half of the tumors in the most aggressive molecular type as benign. Transcriptional and biochemical analyses revealed that aggressive meningiomas involve loss of the repressor function of the DREAM complex, which results in cell cycle activation; only tumors in this category tend to recur after full resection. These findings should improve our ability to predict recurrence and develop targeted treatments for these clinically challenging tumors. Significance StatementMeningiomas are the most common primary brain tumors. Although most of these tumors are benign, one-fifth will recur despite apparently complete resection. Several studies have demonstrated that genomic approaches can yield important insights into the biology of these tumors. We performed RNA sequencing and whole-exome sequencing of 160 tumors from 140 patients, which identified three distinct groups of meningioma that correlate with recurrence better than the current WHO grading system. Our analysis also revealed that the most aggressive type was characterized by loss of the repressive DREAM complex. These findings should improve prognostication for patients and lead to viable therapeutic targets.

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Section: Discussionmentioning

confidence: 80%

Section: Copy Number and Somatic Alterations In Meningiomasmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Patel

Wan

Al‐Ouran

et al. 2019

Preprint

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“…We validated CaSpER algorithm on publicly available TCGA-GBM (n=171) and another separate meningioma cancer study (n=17), where both bulk RNA sequencing and genotyping data is available 24,25 . We explain below the outputs and accuracy of CaSpER on these datasets.…”

Section: Evaluation Of the Accuracy Of Cnv Events Detected From Bulk mentioning

confidence: 99%

CaSpER: Identification, visualization and integrative analysis of CNV events in multiscale resolution using single-cell or bulk RNA sequencing data

Harmancı

Harmanci

Zhou

2018

Preprint

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RNA sequencing experiments generate large amounts of information about expression levels of genes. Although they are mainly used for quantifying expression levels, they contain much more biologically important information such as copy number variants (CNV). Here, we propose CaSpER, a signal processing approach for identification, visualization, and integrative analysis of focal and large-scale CNV events in multiscale resolution using either bulk or single-cell RNA sequencing data. CaSpER performs smoothing of the genome-wide RNA sequencing signal profiles in different multiscale resolutions, identifying CNV events at different length scales. CaSpER also employs a novel methodology for generation of genome-wide B-allele frequency (BAF) signal profile from the reads and utilizes it in multiscale fashion for correction of CNV calls. The shift in allelic signal is used to quantify the loss-of-heterozygosity (LOH) which is valuable for CNV identification. CaSpER uses Hidden Markov Models (HMM) to assign copy number states to regions. The multiscale nature of CaSpER enables comprehensive analysis of focal and large-scale CNVs and LOH segments. CaSpER performs well in accuracy compared to gold standard SNP genotyping arrays. In particular, analysis of single cell Glioblastoma (GBM) RNA sequencing data with CaSpER reveals novel mutually exclusive and co-occurring CNV sub-clones at different length scales. Moreover, CaSpER discovers gene expression signatures of CNV sub-clones, performs gene ontology (GO) enrichment analysis and identifies potential therapeutic targets for the sub-clones. CaSpER increases the utility of RNAsequencing datasets and complements other tools for complete characterization and visualization of the genomic and transcriptomic landscape of single cell and bulk RNA sequencing data, especially in cancer research.

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Integrated systems‐genetic analyses reveal a network target for delaying glioma progression

Laaniste

Srivastava

Stylianou

et al. 2019

Ann Clin Transl Neurol

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Objective To identify a convergent, multitarget proliferation characteristic for astrocytoma transformation that could be targeted for therapy discovery. Methods Using an integrated functional genomics approach, we prioritized networks associated with astrocytoma progression using the following criteria: differential co‐expression between grade II and grade III IDH1‐mutated and 1p/19q euploid astrocytomas, preferential enrichment for genetic risk to cancer, association with patient survival and sample‐level genomic features. Drugs targeting the identified multitarget network characteristic for astrocytoma transformation were computationally predicted using drug transcriptional perturbation data and validated using primary human astrocytoma cells. Results A single network, M2, consisting of 177 genes, was associated with glioma progression on the basis of the above criteria. Functionally, M2 encoded physically interacting proteins regulating cell cycle processes and analysis of genome‐wide gene‐regulatory interactions using mutual information and DNA–protein interactions revealed the known regulators of cell cycle processes FoxM1, B‐Myb, and E2F2 as key regulators of M2. These results suggest functional disruption of M2 via gene mutation or altered expression as a convergent pathway regulating astrocytoma transformation. By considering M2 as a multitarget drug target regulating astrocytoma transformation, we identified several drugs that are predicted to restore M2 expression in anaplastic astrocytoma toward its low‐grade profile and of these, we validated the known antiproliferative drug resveratrol as down‐regulating multiple nodes of M2 including at nanomolar concentrations achievable in human cerebrospinal fluid by oral dosing. Interpretation Our results identify M2 as a multitarget network characteristic for astrocytoma progression and encourage M2‐based drug screening to identify new compounds for preventing glioma transformation.

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Integrated genomic analyses of de novo pathways underlying atypical meningiomas

Cited by 159 publications

References 66 publications

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

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

CaSpER: Identification, visualization and integrative analysis of CNV events in multiscale resolution using single-cell or bulk RNA sequencing data

Integrated systems‐genetic analyses reveal a network target for delaying glioma progression

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