Genomic landscape of high-grade meningiomas

Neoantigens Derived from Recurrently Mutated Genes as Potential Immunotherapy Targets for Gastric Cancer

Neoantigens are optimal tumor-specific targets for T-cell based immunotherapy, especially for patients with “undruggable” mutated driver genes. T-cell immunotherapy can be a “universal” treatment for HLA genotype patients sharing same oncogenic mutations. To identify potential neoantigens for therapy in gastric cancer, 32 gastric cancer patients were enrolled in our study. Whole exome sequencing data from these patients was processed by TSNAD software to detect cancer somatic mutations and predict neoantigens. The somatic mutations between different patients suggested a high interpatient heterogeneity. C>A and C>T substitutions are common, suggesting an active nucleotide excision repair. The number of predicted neoantigens was significantly higher in patients at stage T1a compared to in patients at T2 or T4b. Six genes (PIK3CA, FAT4, BRCA2, GNAQ, LRP1B, and PREX2) were found as recurrently mutated driver genes in our study. Combining with highly frequent HLA alleles, several neoantigens derived from six recurrently mutated genes were considered as potential targets for further immunotherapy.

Comparative genomic analysis of driver mutations in matched primary and recurrent meningiomas

A significant proportion of low-grade WHO grade I and higher-grade WHO grade II or III meningiomas are at risk to develop post-resection recurrence. Though recent studies investigated genomic alterations within histological subtypes of meningiomas, few have compared genomic profiles of primary meningiomas matched to their recurrences. The present study aimed to identify oncogenic driver mutations that may indicate risk of meningioma recurrence and aggressive clinical course. Seventeen patients treated for low-grade (n = 8) or high-grade (n = 9) meningioma and underwent both primary and recurrent resection between 2007-2017 were reviewed. Tumor specimens (n = 38) underwent genomic sequencing of known oncogenic driver mutations. Primary and recurrent tumors were compared using matched-pair analyses for mutational associations with clinical outcomes including functional status, progression-free survival (PFS) and overall survival (OS). Most common driver mutations included POLE and NF2. There was no enrichment for any driver mutation from primary to recurrent tumor specimen. NF2 mutant meningiomas were associated with larger tumor size (8-fold increase), presence of vasogenic edema, and higher mitotic proliferation on univariate and independently on multivariate regression (p's < 0.05) after controlling for preoperative and tumor features. Tumors with POLE driver mutations were associated with decreased functional status at last postoperative follow-up (p = 0.022) relative to presentation. Mutation status was not associated with PFS or OS on multivariate Cox regression, but rather with grade of resection (p = 0.046) for PFS. While primary and recurrent tumors exhibited similar driver mutations within patients, the identification of driver mutations associated with clinical outcomes is crucial for guiding potential targeted treatments in recurrent meningiomas.

Transcriptome signatures associated with meningioma progression

Meningiomas are the most common primary brain tumor of adults. The majority are benign (WHO grade I), with a mostly indolent course; 20% of them (WHO grade II and III) are, however, considered aggressive and require a more complex management. WHO grade II and III tumors are heterogeneous and, in some cases, can develop from a prior lower grade meningioma, although most arise de novo. Mechanisms leading to progression or implicated in de novo grade II and III tumorigenesis are poorly understood. RNA-seq was used to profile the transcriptome of grade I, II, and III meningiomas and to identify genes that may be involved in progression. Bioinformatic analyses showed that grade I meningiomas that progress to a higher grade are molecularly different from those that do not. As such, we identify GREM2, a regulator of the BMP pathway, and the snoRNAs SNORA46 and SNORA48, as being significantly reduced in meningioma progression. Additionally, our study has identified several novel fusion transcripts that are differentially present in meningiomas, with grade I tumors that did not progress presenting more fusion transcripts than all other tumors. Interestingly, our study also points to a difference in the tumor immune microenvironment that correlates with histopathological grade.

DMD genomic deletions characterize a subset of progressive/higher-grade meningiomas with poor outcome

Progressive meningiomas that have failed surgery and radiation have a poor prognosis and no standard therapy. While meningiomas are more common in females overall, progressive meningiomas are enriched in males. We performed a comprehensive molecular characterization of 169 meningiomas from 53 patients with progressive/high-grade tumors, including matched primary and recurrent samples. Exome sequencing in an initial cohort (n = 24) detected frequent alterations in genes residing on the X chromosome, with somatic intragenic deletions of the dystrophin-encoding and muscular dystrophy-associated DMD gene as the most common alteration (n = 5, 20.8%), along with alterations of other known X-linked cancer-related genes KDM6A (n =2, 8.3%), DDX3X, RBM10 and STAG2 (n = 1, 4.1% each). DMD inactivation (by genomic deletion or loss of protein expression) was ultimately detected in 17/53 progressive meningioma patients (32%). Importantly, patients with tumors harboring DMD inactivation had a shorter overall survival (OS) than their wild-type counterparts [5.1 years (95% CI 1.3-9.0) vs. median not reached (95% CI 2.9-not reached, p = 0.006)]. Given the known poor prognostic association of TERT alterations in these tumors, we also assessed for these events, and found seven patients with TERT promoter mutations and three with TERT rearrangements in this cohort (n = 10, 18.8%), including a recurrent novel RETREG1-TERT rearrangement that was present in two patients. In a multivariate model, DMD inactivation (p = 0.033, HR = 2.6, 95% CI 1.0-6.6) and TERT alterations (p = 0.005, HR = 3.8, 95% CI 1.5-9.9) were mutually independent in predicting unfavorable outcomes. Thus, DMD alterations identify a subset of progressive/high-grade meningiomas with worse outcomes.

Genetic Abnormalities, Clonal Evolution, and Cancer Stem Cells of Brain Tumors

Brain tumors are highly heterogeneous and have been classified by the World Health Organization in various histological and molecular subtypes. Gliomas have been classified as ranging from low-grade astrocytomas and oligodendrogliomas to high-grade astrocytomas or glioblastomas. These tumors are characterized by a peculiar pattern of genetic alterations. Pediatric high-grade gliomas are histologically indistinguishable from adult glioblastomas, but they are considered distinct from adult glioblastomas because they possess a different spectrum of driver mutations (genes encoding histones H3.3 and H3.1). Medulloblastomas, the most frequent pediatric brain tumors, are considered to be of embryonic derivation and are currently subdivided into distinct subgroups depending on histological features and genetic profiling. There is emerging evidence that brain tumors are maintained by a special neural or glial stem cell-like population that self-renews and gives rise to differentiated progeny. In many instances, the prognosis of the majority of brain tumors remains negative and there is hope that the new acquisition of information on the molecular and cellular bases of these tumors will be translated in the development of new, more active treatments.

Preoperative and postoperative prediction of long-term meningioma outcomes

Background

Meningiomas are stratified according to tumor grade and extent of resection, often in isolation of other clinical variables. Here, we use machine learning (ML) to integrate demographic, clinical, radiographic and pathologic data to develop predictive models for meningioma outcomes.

Methods and findings

We developed a comprehensive database containing information from 235 patients who underwent surgery for 257 meningiomas at a single institution from 1990 to 2015. The median follow-up was 4.3 years, and resection specimens were re-evaluated according to current diagnostic criteria, revealing 128 WHO grade I, 104 grade II and 25 grade III meningiomas. A series of ML algorithms were trained and tuned by nested resampling to create models based on preoperative features, conventional postoperative features, or both. We compared different algorithms’ accuracy as well as the unique insights they offered into the data. Machine learning models restricted to preoperative information, such as patient demographics and radiographic features, had similar accuracy for predicting local failure (AUC = 0.74) or overall survival (AUC = 0.68) as models based on meningioma grade and extent of resection (AUC = 0.73 and AUC = 0.72, respectively). Integrated models incorporating all available demographic, clinical, radiographic and pathologic data provided the most accurate estimates (AUC = 0.78 and AUC = 0.74, respectively). From these models, we developed decision trees and nomograms to estimate the risks of local failure or overall survival for meningioma patients.

Conclusions

Clinical information has been historically underutilized in the prediction of meningioma outcomes. Predictive models trained on preoperative clinical data perform comparably to conventional models trained on meningioma grade and extent of resection. Combination of all available information can help stratify meningioma patients more accurately.

Towards Molecular Classification of Meningioma: Evolving Treatment and Diagnostic Paradigms

Meningioma, a common primary brain tumor in adults, is graded based on World Health Organization criteria that rely on histology alone. This approach is unable to determine conclusively which tumors, especially benign or atypical, will recur. Molecular characterization of meningioma has identified genetic biomarkers that can predict tumor behavior. Only a few genetic changes are known to classify >85% of all meningioma and clinical trials using targeted therapy to genetic subtypes of meningioma are under way. Immunotherapy is also being trialed in treating high-grade and recurrent meningioma. This review summarizes recent developments characterizing meningioma using genetic and immunologic biomarkers and how these molecular tools may be integrated into existing care together with current World Health Organization grading to improve diagnosis, prognosis, and therapy.

Loss of histone H3K27me3 identifies a subset of meningiomas with increased risk of recurrence

Epigenetic patterns on the level of DNA methylation have already been shown to separate clinically relevant subgroups of meningiomas. We here set out to identify potential prognostic implications of epigenetic modification on the level of histones with focus on H3K27 trimethylation (H3K27me3). H3K27me3 was assessed by immunohistochemistry on 232 meningiomas from 232 patients. In 194 cases, trimethylation was detected in tumor cells. In 25 cases, staining was limited to vessels while all tumor cells were negative. Finally, 13 cases yielded equivocal staining patterns. Reduced abundance of H3K27me3 in cases with staining limited to vessels was confirmed by mass spectrometry on a subset of cases. Lack of staining for H3K27me3 in all tumor cells was significantly associated with more rapid progression (p = 0.009). In line, H3K27me3-negative cases were associated with a DNA methylation pattern of the more aggressive types among the recently introduced DNA methylation groups. Also, NF2 and SUFU mutations were enriched among cases with complete lack of H3K27me3 staining in tumor cells (p < 0.0001 and p = 0.029, respectively). H3K27me3 staining pattern added significant prognostic insight into WHO grade II cases and in the compound subset of WHO grade I and II cases (p = 0.04 and p = 0.007, respectively). However, it did not further stratify within WHO grade III cases. Collectively, these data indicate that epigenetic modifications beyond DNA methylation are involved in the aggressiveness of meningioma. It also suggests that H3K27me3 immunohistochemistry might be a useful adjunct in meningioma diagnostics, particularly for cases with WHO grade II histology or at the borderline between WHO grade I and II.

Somatic mutation landscape of a meningioma and its pulmonary metastasis

Background

Extracranial metastasis (ENM) of meningiomas is extremely rare, and typically occurs several years after a primary tumor is diagnosed. However, the genetic changes underlying ENM events have not yet been investigated.

Case presentation

A 58-year-old male patient was sent to the emergency room of our hospital because of a sudden fall. Magnetic resonance imaging detected a mass at the right frontal sagittal sinus. He underwent tumor resection and recovered well, but post-operative computed tomography revealed three lumps on the right side of his chest. Thoracic surgery was performed to remove two of the lumps. Pathological findings revealed that the brain and lung tumors were grade I meningiomas. The patient received no additional radiation or chemotherapy post-surgery, and there was no sign of tumor recurrence in the brain or progression of the remaining lump in the chest 1 year after surgery. We performed whole exome sequencing of the patient’s blood, primary brain tumor, and lung metastatic tumor tissues to identify somatic genetic alterations that had occurred during ENM. This revealed that a frameshift deletion of the neurofibromin 2 gene likely drove formation of the meningioma. Surprisingly, we found that the brain tumor was relatively homogeneous and contained only one dominant clone; both the pulmonary metastasis and the original brain tumor were derived from the same clone, and no obvious additional driver mutations were detected in the metastatic tumor.

Conclusion

Although ENM of meningiomas is very rare, brain tumor cells appear to be more adaptable to tissue microenvironments outside of the central nervous system than was commonly thought.

High-grade meningiomas: biology and implications

The epochal developments in the treatment of meningioma—microsurgery, skull base techniques, and radiation therapy—will be appended to include the rational application of targeted and immune therapeutics, previously ill-fitting concepts for a tumor that has traditionally been a regarded as a surgical disease. The genomic and immunological architecture of these tumors continues to be defined in ever-greater detail. Grade I meningiomas are driven by NF2 alterations or mutations in AKT1, SMO, TRAF7, PIK3CA, KLF4, POLR2A, SUFU, and SMARCB1. Higher-grade tumors, however, are driven nearly exclusively by NF2/chr22 loss and are marked by infrequent targetable mutations, although they may harbor a greater mutation burden overall. TERT mutations may be more common in tumors that progress in histological grade; SMARCE1 alteration has become a signature of the clear cell subtype; and BAP1 in rhabdoid variants may confer sensitivity to pharmacological inhibition. Compared with grade I meningiomas, the most prominent alteration in grade II and III meningiomas is a significant increase in chromosomal gains and losses, or copy number alterations, which may have behavioral implications. Furthermore, integrated genomic analyses suggest phenotypic subgrouping by methylation profile and a specific role for PRC2 complex activation. Lastly, there exists a complex phylogenetic relationship among recurrent high-grade tumors, which continues to underscore a role for the most traditional therapy in our arsenal: surgery.

Advances in meningioma genetics: novel therapeutic opportunities

Meningiomas currently are among the most frequent intracranial tumours. Although the majority of meningiomas can be cured by surgical resection, ∼20% of patients have an aggressive clinical course with tumour recurrence or progressive disease, resulting in substantial morbidity and increased mortality of affected patients. During the past 3 years, exciting new data have been published that provide insights into the molecular background of meningiomas and link sites of tumour development with characteristic histopathological and molecular features, opening a new road to novel and promising treatment options for aggressive meningiomas. A growing number of the newly discovered recurrent mutations have been linked to a particular clinicopathological phenotype. Moreover, the updated WHO classification of brain tumours published in 2016 has incorporated some of these molecular findings, setting the stage for the improvement of future therapeutic efforts through the integration of essential molecular findings. Finally, an additional potential classification of meningiomas based on methylation profiling has been launched, which provides clues in the assessment of individual risk of meningioma recurrence. All of these developments are creating new prospects for effective molecularly driven diagnosis and therapy of meningiomas.

Patient-derived xenografts undergo mouse-specific tumor evolution

Patient-derived xenografts (PDXs) have become a prominent cancer model system, as they are presumed to faithfully represent the genomic features of primary tumors. Here we monitored the dynamics of copy number alterations (CNAs) in 1,110 PDX samples across 24 cancer types. We observed rapid accumulation of CNAs during PDX passaging, often due to selection of pre-existing minor clones. CNA acquisition in PDXs was correlated with the tissue-specific levels of aneuploidy and genetic heterogeneity observed in primary tumors. However, the particular CNAs acquired during PDX passaging differed from those acquired during tumor evolution in patients. Several CNAs recurrently observed in primary tumors gradually disappeared in PDXs, indicating that events undergoing positive selection in humans can become dispensable during propagation in mice. Importantly, the genomic stability of PDXs was associated with their response to chemotherapy and targeted drugs. These findings have important implications for PDX-based modeling of human cancer.

Osteoglycin promotes meningioma development through downregulation of NF2 and activation of mTOR signaling

BACKGROUND

Meningiomas are the most common primary intracranial tumors in adults. While a majority of meningiomas are slow growing neoplasms that may cured by surgical resection, a subset demonstrates more aggressive behavior and insidiously recurs despite surgery and radiation, without effective alternative treatment options. Elucidation of critical mitogenic pathways in meningioma oncogenesis may offer new therapeutic strategies. We performed an integrated genomic and molecular analysis to characterize the expression and function of osteoglycin (OGN) in meningiomas and explored possible therapeutic approaches for OGN-expressing meningiomas.

METHODS

OGN mRNA expression in human meningiomas was assessed by RNA microarray and RNAscope. The impact of OGN on cell proliferation, colony formation, and mitogenic signaling cascades was assessed in a human meningioma cell line (IOMM-Lee) with stable overexpression of OGN. Furthermore, the functional consequences of introducing an AKT inhibitor in OGN-overexpressing meningioma cells were assessed.

RESULTS

OGN mRNA expression was dramatically increased in meningiomas compared to a spectrum of other brain tumors and normal brain. OGN-overexpressing meningioma cells demonstrated an elevated rate of cell proliferation, cell cycle activation, and colony formation as compared with cells transfected with control vector. In addition, NF2 mRNA and protein expression were both attenuated in OGN-overexpressing cells. Conversely, mTOR pathway and AKT activation increased in OGN-overexpressing cells compared to control cells. Lastly, introduction of an AKT inhibitor reduced OGN expression in meningioma cells and resulted in increased cell death and autophagy, suggestive of a reciprocal relationship between OGN and AKT.

CONCLUSION

We identify OGN as a novel oncogene in meningioma proliferation. AKT inhibition reduces OGN protein levels in meningioma cells, with a concomitant increase in cell death, which provides a promising treatment option for meningiomas with OGN overexpression.