Molecular Targets and Treatment of Meningioma

Das, Arabinda; Miller, Rickey; Decandio, Michele L

doi:10.19104/jnn.2014.101

Cited by 9 publications

(6 citation statements)

References 42 publications

(70 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…84 Decreasing MAPK levels can cause increased meningioma recurrence. 84 The VEGF family and PDGF play an important role in tumor development, such as angiogenesis and the vascular permeability regulatory system. 85 The role of VEGF in cancer cells is to induce angiogenesis by stimulating endothelial cell migration and proliferation.…”

Section: Related Higher Grade Meningiomasmentioning

confidence: 99%

“…It is a fundamental pathway that contributes to cancer development, and the activation of this pathway prevents neuronal cell apoptosis 115 . The tumor suppressor gene adenomatous polyposis coli (APC) regulates the Wnt/β‐catenin pathway; therefore, the loss of this gene causes tumor development 84 . High expression of frizzled class receptor 2 (FZD2) in this pathway upregulates oncogenic proteins such as c‐myc and cyclin D1 12 .…”

Section: Introductionmentioning

confidence: 99%

“…The mitogenic signal is often transduced by EGFR and PDGFR and is related to the signaling pathway of MAPK, which has been found to be abnormally active in meningiomas 12 . As a consequence of this, the PI3K/AKT/MAPK pathways also have a relationship with malignant meningiomas; high levels of phosphorylated Akt are identified in grade 2 and grade 3 meningiomas 84 . Decreasing MAPK levels can cause increased meningioma recurrence 84 .…”

Section: Introductionmentioning

confidence: 99%

“…As a consequence of this, the PI3K/AKT/MAPK pathways also have a relationship with malignant meningiomas; high levels of phosphorylated Akt are identified in grade 2 and grade 3 meningiomas 84 . Decreasing MAPK levels can cause increased meningioma recurrence 84 . The VEGF family and PDGF play an important role in tumor development, such as angiogenesis and the vascular permeability regulatory system 85 .…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Related mechanisms, current treatments, and new perspectives in meningioma

Inetas‐Yengin,

Bayrak

2024

Genes Chromosomes & Cancer

View full text Add to dashboard Cite

Meningiomas are non‐glial tumors that are the most common primary brain tumors in adults. Although meningioma can possibly be cured with surgical excision, variations in atypical/anaplastic meningioma have a high recurrence rate and a poor prognosis. As a result, it is critical to develop novel therapeutic options for high‐grade meningiomas. This review highlights the current histology of meningiomas, prevalent genetic and molecular changes, and the most extensively researched signaling pathways and therapies in meningiomas. It also reviews current clinical studies and novel meningioma treatments, including immunotherapy, microRNAs, cancer stem cell methods, and targeted interventions within the glycolysis pathway. Through the examination of the complex landscape of meningioma biology and the highlighting of promising therapeutic pathways, this review opens the way for future research efforts aimed at improving patient outcomes in this prevalent intracranial tumor entity.

show abstract

Section: Related Higher Grade Meningiomasmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Related mechanisms, current treatments, and new perspectives in meningioma

Inetas‐Yengin,

Bayrak

2024

Genes Chromosomes & Cancer

View full text Add to dashboard Cite

show abstract

“…For this reason, although benign meningiomas are typically non-cancerous and slow growing, physicians recommend immediate surgery. Early resection and treatment of meningioma is vital before malignancy and metastasis [20, 48].…”

Section: Introduction and Related Workmentioning

confidence: 99%

Multimodal CNN Models Allow for the Accurate Classification and Grading of Preoperative Meningioma Tumors

Rane

2023

Preprint

View full text Add to dashboard Cite

Magnetic resonance imaging (MRI) scanning and Computed Tomography (CT) proves to be a reliable form of imaging for modern medical use, providing clear images for physician and radiologist diagnosis. MRI and CT scans are especially important for neuroimaging of tumors for neuro-oncology after a patient lists symptoms indicating brain cancer. Although imaging does produce a lucid depiction of possible cancerous growth in the brain, inspection by a physician could be challenging due to subtleties in the image or human error. A diagnosis could also never be exact, as a biopsy is the only diagnostic test that can ascertain meningioma growth. A physician could confuse a noncancerous cyst located near the meninges of the brain for a meningioma tumor. Furthermore, World Health Organization (WHO) grading of each tumor could be complicated to differentiate. One possible solution to the human handicap is a Convolutional Neural Network (CNN), a commonly used machine learning method for image extrapolation and classification. For the purposes of this primary research, a multimodal CNN was given testing and training data of different types of brain cancers to test if it could properly classify different forms of CT and MRI scans of meningioma compared to glioma, pituitary, and scans with no tumor. The no tumor dataset included noncancerous cysts, as mentioned before, that could be confused with meningioma. Furthermore, a separate CNN was given different testing and training data on meningioma tumors with WHO grades one to three. The CNNs were run on a private GPU environment on Visual Studio Jupyter Notebook and were given input data in the form of standardized JPEG image files from research institutes around the world. The patient data came from various ages, different nationalities, and both genders. The concept of transfer learning was used to train the model, where the solution to one problem is used to solve another problem. The results of the models show high accuracies above 98\% with an upward trend through the twelve epochs ran, indicating stability. The recall and precision scores were also high, indicating quality. Finally, the AUC scores were all above .99, describing the CNN's capability to include threshold-invariance and scale-invariance. Finally, an attention study demonstrated the CNN's tendency to apply most attention to the tumor mass itself rather than extraneous variables.

show abstract

SSTR-2 as a potential tumour-specific marker for fluorescence-guided meningioma surgery

et al. 2018

View full text Add to dashboard Cite

BackgroundMeningiomas are the most frequently occurring primary intracranial tumours in adults. Surgical removal can only be curative by complete resection; however surgical access can be challenging due to anatomical localization and local invasion of bone and soft tissues. Several intraoperative techniques have been tried to improve surgical resection, including intraoperative fluorescence guided imaging; however, no meningioma-specific (fluorescent) targeting has been developed yet. Here, we aimed to identify the most promising biomarkers for targeted intra-operative fluorescence guided meningioma surgery.MethodsOne hundred forty-eight meningioma specimens representing all meningioma grades were analysed using immunohistochemistry (IHC) on tissue microarrays (TMAs) to determine expression patterns of meningioma biomarkers epithelial membrane antigen (EMA), platelet-derived growth factor β (PDGF-β), vascular endothelial growth factor α (VEGF-α), and somatostatin receptor type 2 (SSTR-2). Subsequently, the most promising biomarker was selected based on TArget Selection Criteria (TASC). Marker expression was examined by IHC in 3D cell culture models generated from freshly resected tumour material.ResultsTMA-IHC showed strongest staining for SSTR-2. All cases were positive, with 51.4% strong/diffuse, 30.4% moderate/diffuse and only 18.2% focal/weak staining patterns. All tested biomarkers showed at least weak positivity in all meningiomas, regardless of WHO grade. TASC analysis showed that SSTR-2 was the most promising target for fluorescence guided imaging, with a total score of 21 (out of 22). SSTR-2 expression was determined on original patient tumours and 3D cultures of three established cultures.ConclusionsSSTR-2 expression was highly sensitive and specific in all 148 meningiomas, regardless of WHO grade. According to TASC analysis, SSTR-2 is the most promising receptor for meningioma targeting. After establishing in vitro meningioma models, SSTR-2 cell membrane expression was confirmed in two of three meningioma cultures as well. This indicates that specific fluorescence in an experimental setting can be performed for the further development of targeted fluorescence guided meningioma surgery and near-infrared fluorescent tracers targeting SSTR-2.

show abstract

Molecular Targets and Treatment of Meningioma

Cited by 9 publications

References 42 publications

Related mechanisms, current treatments, and new perspectives in meningioma

Related mechanisms, current treatments, and new perspectives in meningioma

Multimodal CNN Models Allow for the Accurate Classification and Grading of Preoperative Meningioma Tumors

SSTR-2 as a potential tumour-specific marker for fluorescence-guided meningioma surgery

Contact Info

Product

Resources

About