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Whole genome, whole exome, and targeted sequencing of high-grade meningioma tumor samples.

ABSTRACT: High-grade meningiomas frequently recur and are associated with high rates of morbidity and mortality. To determine the factors that promote the development and evolution of these tumors, we analyzed the genomes of 274 high-grade meningiomas and compared this information with data from 456 low-grade meningiomas. High-grade meningiomas had a higher mutation burden than low-grade meningiomas but did not harbor any statistically significant mutated genes aside from NF2. High-grade meningiomas also possessed significantly elevated rates of chromosomal gains and losses, especially among tumors with monosomy 22. Meningiomas previously treated with adjuvant radiation had significantly more copy number alterations than radiation-induced or radiation-naïve meningiomas. Across serial recurrences, genomic disruption preceded the emergence of nearly all mutations, remained largely uniform across time, and when present in low-grade meningiomas, correlated with subsequent progression to a higher grade. In contrast to the largely stable copy number alterations, mutations were strikingly heterogeneous across tumor recurrences, likely due to extensive geographic heterogeneity in the primary tumor. While high-grade meningiomas harbored significantly fewer overtly targetable alterations than low-grade meningiomas, they contained numerous mutations that are predicted to be neoantigens, suggesting that immunologic targeting may be of therapeutic value.

PROVIDER: EGAS00001002294 | EGA |

REPOSITORIES: EGA

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High-grade NF2 mutant meningiomas downregulate oncogenic YAP signaling.

Project description:Meningiomas are the most common primary brain tumors in adults. Although generally benign, a subset is of higher grade, recurs even after multiple surgeries, and frequently fatal. Around half of meningiomas harbor inactivating mutations in NF2. While low-grade NF2 mutant meningiomas harbor few additional mutations in addition to NF2 inactivation, high-grade NF2 mutant tumors frequently harbor a highly aberrant genome. We and others have previously shown that NF2 inactivation leads to YAP1 activation and that YAP1 acts as an oncogene in NF2 mutant meningiomas. Here, we show that high-grade NF2 mutant meningiomas downregulate YAP1 signaling, in part through upregulating the expression of the YAP1 competitor VGLL4 and the YAP1 upstream regulators FAT3/4. Overexpression of VGLL4 resulted in the downregulation of YAP activity and the growth inhibition of low-grade NF2 mutant meningioma cells. Our results have important implications for the efficacy of therapies targeting oncogenic YAP1 in high-grade NF2 mutant meningiomas.

2024-08-26 | GSE263122 | GEO

Proteomic analysis of meningiomas reveals clinically-distinct molecular patterns

Project description:Meningiomas represent one of the most common and clinically heterogeneous brain tumor types that only modestly correlate with histopathologic features. While emerging molecular profiling efforts have linked specific genomic drivers to distinct clinical patterns, the proteomic landscape of meningiomas remains largely unexplored. We utilize mass spectrometry to profile a clinically well-annotated cohort (n=69) of meningiomas stratified to span all three World Health Organization (WHO) grades and various degrees of clinical aggressiveness. In total, we quantify 3042 unique proteins and compare the patterns across different clinical parameters. Unsupervised clustering analysis highlighted distinct proteomic (n=106 proteins, Welch’s t-test, P<0.01) and pathway-level (e.g. Notch and PI3K/AKT/mTOR) differences between convexity and skull base meningiomas. Supervised comparative analyses of different pathological grades revealed distinct patterns between benign (WHO Grade I) and atypical/malignant (WHO Grade II and III) meningiomas with classic oncogenes often enriched in higher grade lesions. Independent of WHO grade, clinically aggressive meningiomas, that rapidly recurred, also had distinctive protein patterns that converged on mRNA processing and impaired activation of the extracellular matrix naba matrisome complex. Larger sized meningiomas, and those with previous radiation exposure, also had distinct protein profiles. Collectively, we highlight distinct clinically-dependent proteomic patterns of meningiomas that may help better predict outcome and guide the development of more personalized and directed therapies.

2019-05-30 | PXD012923 | Pride

Transcriptomic analysis of aggressive meningiomas identifies PTTG1 and LEPR1 as prognostic biomarkers independent of WHO grade

Project description:Meningiomas are frequent central nervous system tumors. Although most meningiomas are benign (WHO grade I) and curable by surgery, WHO grade II and III tumors remain therapeutically challenging due to frequent recurrence. Interestingly, relapse also occurs in some WHO grade I meningiomas. Hence, we investigated the transcriptional features defining aggressive (recurrent, malignantly progressing or WHO grade III) meningiomas in 144 cases. Meningiomas were categorized into non-recurrent (NR), recurrent (R), and tumors undergoing malignant progression (M) in addition to their WHO grade. Unsupervised transcriptomic analysis in 62 meningiomas revealed transcriptional profiles lining up according to WHO grade and clinical subgroup. Notably aggressive subgroups (R+M tumors and WHO grade III) shared a large set of differentially expressed genes (n=332; p<0.01, FC>1.25). In an independent multicenter validation set (n=82), differential expression of 10 genes between WHO grades was confirmed. Additionally, among WHO grade I tumors differential expression between NR and aggressive R+M tumors was af rmed for PTTG1, AURKB, ECT2, UBE2C and PRC1, while MN1 and LEPR discriminated between NR and R+M WHO grade II tumors. Univariate survival analysis revealed a significant association with progression-free survival for PTTG1, LEPR, MN1, ECT2, PRC1, COX10, UBE2C expression, while multivariate analysis identified a prediction for PTTG1 and LEPR mRNA expression independent of gender, WHO grade and extent of resection. Finally, stainings of PTTG1 and LEPR confirmed malignancy-associated protein expression changes. In conclusion, based on the so far largest study sample of WHO grade III and recurrent meningiomas we report a comprehensive transcriptional landscape and two prognostic markers. Comparative transcriptomic analysis of 62 low- and high-grade meningiomas

2016-02-15 | E-GEOD-74385 | biostudies-arrayexpress

Genomic profiling of anaplastic meningioma identifies recurrent genetic alterations with relevance to lower-grade meningioma

Project description:Genomic profiling of anaplastic meningioma can inform prognostic gene level alterations in lower-grade meningiomas, potentially reflecting evolution of anaplastic meningioma from lowergrade precursor tumours. Larger scale studies in paired primary and recurrent meningiomas are warranted to unravel the evolutionary path to anaplastic meningiomas and prognostic genomic alterations in detail

2021-05-04 | GSE173825 | GEO

Single-cell transcriptomic characterization primary HNSCC tumors

Project description:Despite aggressive multi-modal treatment, advanced head and neck squamous cell carcinoma (HNSCC) patients are at high risk of recurrence. Matched pairs (n=38) of primary/recurrent tumors were subjected to whole exome and RNA sequencing. Mutational landscapes and genomic copy number alterations indicated diverging clonal origins in a subset of cases. Transcriptional subtyping (classical/CL, basal/BA, inflamed-mesenchymal/IMS) in primary and recurrent HNSCC (n=112) revealed more frequent CL and IMS in primary tumors with low recurrence rates and a prevalence of BA in recurrent tumors associated with p-EMT and early recurrence. 44% of matched cases underwent a subtype change from primary to recurrent tumors, preferably from IMS to BA or CL. In recurrences, HYPOXIA, P-EMT and RADIATION RESISTANCE signatures were up- and TUMOR INFLAMMATION down-regulated compared to index tumors. A therapy-induced selection of transcriptional subtypes demonstrates the importance of molecular characterization of recurrences for second-line therapy decisions to enable optimally tailored treatments.

2022-04-08 | GSE173964 | GEO

Transcriptomic characterization of paired primary and recurrent HNSCC tumors

2022-04-08 | GSE173855 | GEO

Meningioma transcriptomic landscape demonstrates novel subtypes with regional associated biology and patient outcome

Project description:Meningiomas are the most common primary intracranial tumors in humans. While most of these tumors are benign, some are malignant, rapidly recur after multimodal treatment with surgery and radiotherapy, and can ultimately be fatal. The current WHO grade system does not always identify high risk meningiomas, therefore better characterizations of the biology of aggressive tumors are needed. In order to address these challenges, we combined 13 bulk RNA-Seq datasets, corrected for batch effects, and applied Uniform Manifold Approximation and Projection (UMAP) to create a reference landscape of ~1300 meningioma tumors. Our analyses revealed multiple distinct meningioma subtypes with specific biological signatures. Clinical metadata, mutations, copy number alterations, and gene-fusion data effectively correlated with regions of the UMAP. Notably, regional distribution of time to recurrence identified major clusters as well as intra-cluster differences of meningiomas with varying patient outcomes. The most aggressive subtype, characterized by an enrichment of higher WHO grades, frequent tumor recurrences, and shorter time to recurrence, exhibited elevated proliferation rates and RNA expression resembling muscle development. To facilitate clinical applications, we developed a cross-validated nearest-neighbors-based algorithm that accurately maps new patients onto this UMAP landscape. Our study highlights the utility of transcriptomic analysis in discerning meningioma heterogeneity as well as successful combination of multiple datasets from various sources. We provide a valuable tool for understanding the disease, predicting tumor biology and patient prognosis. This resource is accessible via the open source, interactive online tool Oncoscape, where the scientific community can explore the landscape and mine clinical and genomic metadata.

2024-04-26 | GSE252291 | GEO

Metabolomic and Lipidomic Characterization of Meningioma Grades Using LC-HRMS and Machine Learning

Project description:Meningiomas are among the most common brain tumors that arise from the leptomeningeal cover of the brain and spinal cord and account for around 37% of all central nervous system tumors. According to the World Health Organization, meningiomas are classified into three histological subtypes: benign, atypical, and anaplastic. Sometimes, meningiomas with a histological diagnosis of benign tumors show clinical characteristics and behavior of aggressive tumors. In this study, we examined the metabolomic and lipidomic profiles of meningioma tumors, focusing on comparing low-grade and high-grade tumors and identifying potential markers that can discriminate between benign and malignant tumors. High-resolution mass spectrometry coupled to liquid chromatography was used for untargeted metabolomics and lipidomics analyses of 85 tumor biopsy samples with different meningioma grades. We then applied feature selection and machine learning techniques to find the features with the highest information to aid in the diagnosis of meningioma grades. Three biomarkers were identified to differentiate low- and high-grade meningioma brain tumors. The use of mass-spectrometry-based metabolomics and lipidomics combined with machine learning analyses to prospect and characterize biomarkers associated with meningioma grades may pave the way for elucidating potential therapeutic and prognostic targets.

2024-06-12 | MTBLS4938 | MetaboLights

Proteomic analysis of meningioma of different grades identifies potential therapeutic targets and biomarkers

Project description:Meningiomas are common brain tumours arising from meningeal tissue. Despite the majority of them displaying benign features, they can cause mild to severe morbidity. The current main therapeutic approach is complete tumour resection commonly with adjunct radiation therapy. However, tumour location can hamper complete resection and chemotherapies are ineffective. In this study we aim to elucidate dysregulated pathways in meningioma pathogenesis and identify novel molecular targets by deciphering the proteome and phosphoproteome of different grades of meningiomas. Tumour lysates were collected from grade I, II and III frozemeningioma specimens and three normal healthy human meninges.

2019-01-07 | PXD007044 | Pride

Proteomic analysis of meningioma of different grades identifies potential therapeutic targets and biomarkers

Project description:Meningiomas are common brain tumours arising from meningeal tissue. Despite the majority of them displaying benign features, they can cause mild to severe morbidity. The current main therapeutic approach is complete tumour resection commonly with adjunct radiation therapy. However, tumour location can hamper complete resection and chemotherapies are ineffective. In this study we aim to elucidate dysregulated pathways in meningioma pathogenesis and identify novel molecular targets by deciphering the proteome and phosphoproteome of different grades of meningiomas. Tumour lysates were collected from grade I, II and III frozenmeningioma specimens and three normal healthy human meninges.

2019-01-02 | PXD007073 | Pride

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