scholarly journals Acanthosis nigricans and the sign of leser-trelat associated with primary brain tumor: Case report

2008 ◽  
Vol 16 (3-4) ◽  
pp. 81-83
Author(s):  
Slobodan Stojanovic ◽  
Pavle Jeremic ◽  
Mirjana Poljacki
Keyword(s):  
Brain Tumor ◽  
Acanthosis Nigricans ◽  
Neck Region ◽  
Primary Brain Tumor ◽  
Skin Tumors ◽  
Low Grade ◽  
Seborrheic Keratosis ◽  
Skin Changes ◽  
Clinical Changes ◽  
The Brain

The authors present a case of a female patient a 26-year old pensioner from Zmajevo, who developed skin changes in the neck region, armpits and groins, as well as in submammal folds during the 10 years period. The changes include dark-brown hyper?pigmentation associated with sudden eruption of a large number of benign skin tumors and dark-brown seborrheic keratosis on trunk and extremities. In 1998, after magnetic resonance imaging, primary brain tumor of astrocytoma type with low grade of malignity was discovered in thalamus region. The patient developed the above-mentioned skin changes since then. According to neurosurgical findings, the brain tumor is inoperable, so skin changes are persistent and stationary. Clinical changes correspond to paraneoplastic form of acanthosis nigricans. Numerous skin tumors histopathologically match seborrheic keratosis and reveal the clinical features of the sign of Leser-Trelat. It is interesting that in the same patient there are both, obligatory and optional, paraneoplastic dermatoses associated with malignant brain tumor.

scholarly journals Molecular Mechanisms of Drug Resistance in Glioblastoma

2021 ◽  
Vol 22 (12) ◽  
pp. 6385
Author(s):  
Maya A. Dymova ◽  
Elena V. Kuligina ◽  
Vladimir A. Richter
Keyword(s):  
Drug Resistance ◽  
Brain Tumor ◽  
Molecular Mechanisms ◽  
Primary Brain Tumor ◽  
Therapeutic Resistance ◽  
Molecular Characteristics ◽  
Blood Brain ◽  
Conventional Radiation ◽  
The Brain ◽  
Made In

Glioblastoma multiforme (GBM) is the most common and fatal primary brain tumor, is highly resistant to conventional radiation and chemotherapy, and is not amenable to effective surgical resection. The present review summarizes recent advances in our understanding of the molecular mechanisms of therapeutic resistance of GBM to already known drugs, the molecular characteristics of glioblastoma cells, and the barriers in the brain that underlie drug resistance. We also discuss the progress that has been made in the development of new targeted drugs for glioblastoma, as well as advances in drug delivery across the blood–brain barrier (BBB) and blood–brain tumor barrier (BBTB).

scholarly journals Opportunities and challenges of glioma organoids

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Xiangdong Xu ◽  
Lingfei Li ◽  
Linting Luo ◽  
Lingling Shu ◽  
Xiaoli Si ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Animal Models ◽  
3D Structure ◽  
Primary Brain Tumor ◽  
Surgical Removal ◽  
Human Tissues ◽  
Cell Models ◽  
Cell Dynamics ◽  
Research Platform ◽  
The Brain

AbstractGlioma is the most common primary brain tumor and its prognosis is poor. Despite surgical removal, glioma is still prone to recurrence because it grows rapidly in the brain, is resistant to chemotherapy, and is highly aggressive. Therefore, there is an urgent need for a platform to study the cell dynamics of gliomas in order to discover the characteristics of the disease and develop more effective treatments. Although 2D cell models and animal models in previous studies have provided great help for our research, they also have many defects. Recently, scientific researchers have constructed a 3D structure called Organoids, which is similar to the structure of human tissues and organs. Organoids can perfectly compensate for the shortcomings of previous glioma models and are currently the most suitable research platform for glioma research. Therefore, we review the three methods currently used to establish glioma organoids. And introduced how they play a role in the diagnosis and treatment of glioma. Finally, we also summarized the current bottlenecks and difficulties encountered by glioma organoids, and the current efforts to solve these difficulties.

Mapping the Brain for Primary Brain Tumor Surgery

2016 ◽  
pp. 63-79 ◽  
Author(s):  
Emmanuel Mandonnet ◽  
Hugues Duffau
Keyword(s):  
Brain Tumor ◽  
Primary Brain Tumor ◽  
Tumor Surgery ◽  
Brain Tumor Surgery ◽  
The Brain

scholarly journals The CNS and the Brain Tumor Microenvironment: Implications for Glioblastoma Immunotherapy

2020 ◽  
Vol 21 (19) ◽  
pp. 7358
Author(s):  
Fiona A. Desland ◽  
Adília Hormigo
Keyword(s):  
T Cells ◽  
Brain Tumor ◽  
Tumor Microenvironment ◽  
Immune Modulation ◽  
Primary Brain Tumor ◽  
Cellular Heterogeneity ◽  
Checkpoint Molecule ◽  
Engineered T Cells ◽  
Immunosuppressive Tumor Microenvironment ◽  
The Brain

Glioblastoma (GBM) is the most common and aggressive malignant primary brain tumor in adults. Its aggressive nature is attributed partly to its deeply invasive margins, its molecular and cellular heterogeneity, and uniquely tolerant site of origin—the brain. The immunosuppressive central nervous system (CNS) and GBM microenvironments are significant obstacles to generating an effective and long-lasting anti-tumoral response, as evidenced by this tumor’s reduced rate of treatment response and high probability of recurrence. Immunotherapy has revolutionized patients’ outcomes across many cancers and may open new avenues for patients with GBM. There is now a range of immunotherapeutic strategies being tested in patients with GBM that target both the innate and adaptive immune compartment. These strategies include antibodies that re-educate tumor macrophages, vaccines that introduce tumor-specific dendritic cells, checkpoint molecule inhibition, engineered T cells, and proteins that help T cells engage directly with tumor cells. Despite this, there is still much ground to be gained in improving the response rates of the various immunotherapies currently being trialed. Through historical and contemporary studies, we examine the fundamentals of CNS immunity that shape how to approach immune modulation in GBM, including the now revamped concept of CNS privilege. We also discuss the preclinical models used to study GBM progression and immunity. Lastly, we discuss the immunotherapeutic strategies currently being studied to help overcome the hurdles of the blood–brain barrier and the immunosuppressive tumor microenvironment.

Intraoperative Strain Elastosonography in Brain Tumor Surgery

2018 ◽  
Vol 17 (2) ◽  
pp. 227-236 ◽  
Author(s):  
Francesco Prada ◽  
Massimiliano Del Bene ◽  
Angela Rampini ◽  
Luca Mattei ◽  
Cecilia Casali ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Brain Tumor ◽  
Large Scale ◽  
Imaging Technique ◽  
Low Grade ◽  
Tumor Surgery ◽  
Brain Tumor Surgery ◽  
Mode Iii ◽  
Wide Range ◽  
The Brain

Abstract BACKGROUND Sonoelastography is an ultrasound imaging technique able to assess mechanical properties of tissues. Strain elastography (SE) is a qualitative sonoelastographic modality with a wide range of clinical applications, but its use in brain tumor surgery has been so far very limited. OBJECTIVE To describe the first large-scale implementation of SE in oncological neurosurgery for lesions discrimination and characterization. METHODS We analyzed retrospective data from 64 patients aiming at (i) evaluating the stiffness of the lesion and of the surrounding brain, (ii) assessing the correspondence between B-mode and SE, and (iii) performing subgroup analysis for gliomas characterization RESULTS (i) In all cases, we visualized the lesion and the surrounding brain with SE, permitting a qualitative stiffness assessment. (ii) In 90% of cases, lesion representations in B-mode and SE were superimposable with identical morphology and margins. In 64% of cases, lesion margins were sharper in SE than in B-mode. (iii) In 76% of cases, glioma margins were sharper in SE than in B-mode. Lesions morphology/dimensions in SE and in B-mode were superimposable in 89%. Low-grade (LGG) and high-grade (HGG) gliomas were significantly different in terms of stiffness and stiffness contrast between tumors and brain, LGG appearing stiffer while HGG softer than brain (all P < ·001). A threshold of 2.5 SE score had 85.7% sensitivity and 94.7% specificity in differentiating LGG from HGG. CONCLUSION SE allows to understand mechanical properties of the brain and lesions in examination and permits a better discrimination between different tissues compared to B-mode. Additionally, SE can differentiate between LGG and HGG.

372 Evolving Patterns in Clinical Utilization of Stereotactic Laser Ablation (SLA): An Analysis of the Multi-center Prospective Registry LAANTERN

Neurosurgery ◽  
2017 ◽  
Vol 64 (CN_suppl_1) ◽  
pp. 287-288
Author(s):  
Clark C Chen ◽  
Robert Rennert ◽  
Usman Khan ◽  
Stephen B Tatter ◽  
Melvin Field ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Laser Ablation ◽  
Invasive Procedure ◽  
Primary Brain Tumor ◽  
Low Grade ◽  
Newly Diagnosed ◽  
Minimally Invasive Procedure ◽  
Tumor Patients ◽  
Clinical Utilization ◽  
Neurosurgical Patients

Abstract INTRODUCTION Stereotactic laser ablation (SLA) is a minimally invasive procedure that is increasingly utilized in neurosurgery. We wished to understand how this procedure is changing the landscape of treatment option for neurosurgical patients. METHODS Patients undergoing stereotactic laser ablation were prospectively enrolled in the LAANTERN registry. Data from the first 100 enrolled patients are presented here. RESULTS >Clinical indications for SLA include treatment of high grade gliomas (HGG, 40%), brain metastases (BM, 34%), epilepsy (17%), low grade gliomas (5%), and meningioma/other primary brain tumor (4%). For HGGs, SLA was equally likely used in the up-front (45%) or the recurrent setting (55%, P = 0.54). In contrast, SLA was predominantly used as treatment for BMs that failed radiation therapy/radiosurgery (91%), with only 9% of SLAs performed as up-front treatment for newly diagnosed lesions (P < 0.001). Of all SLAs performed in brain tumor patients, 42.9% of the procedures were performed in lieu of surgical resection, and 21% were performed because the lesion was not accessible through conventional neurosurgery. Time trend analysis comparing the first and the latter cohort of 50 enrolled patient revealed expanding oncologic applications of SLA beyond treatment of HGG and BM (P = 0.02). CONCLUSION HGGs and BMs are the leading indications for SLA in the LAANTERN study. For HGGs, SLA is equally likely used in the up-front or recurrent setting. For BMs, SLA is typically used in the recurrent setting. There is an evolving trend toward expanding oncologic applications of SLA beyond treatment of HGGs and BMs

scholarly journals MNGI-11. HIGH-GRADE AND LOW-GRADE MENINGIOMAS HARBOR DIFFERING METABOLOMIC PROFILES

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi141-vi142
Author(s):  
Garrett Fitzpatrick ◽  
Maryam Rahman ◽  
Timothy Garrett ◽  
Jesse Kresak
Keyword(s):  
Brain Tumor ◽  
Treatment Options ◽  
Disease Free Survival ◽  
Metastatic Potential ◽  
Primary Brain Tumor ◽  
Sphingolipid Metabolism ◽  
Low Grade ◽  
Tumor Type ◽  
High Grade ◽  
Who Grade

Abstract BACKGROUND Meningiomas are the most common primary brain tumor in adults. While the majority of meningiomas are low-grade and effectively treated by resection alone, there is a subset of tumors that have a high incidence of recurrence, metastatic potential, and morbidity. Radiation has been employed with variable success for high-grade meningiomas. No chemotherapeutic approaches have proven effective against these tumors to date. There is a need for a better understanding of this tumor type in order to provide our patients with better treatment options. OBJECTIVE The purpose of this study is to investigate the metabolomic profile of meningiomas with a focus on comparing low- and high-grade tumors and identifying biologically significant metabolites which could correlate with overall and disease-free survival. METHODS Ten tumor samples of each meningioma grade (WHO grades I-III) were collected from the Florida Center for Brain Tumor Research. Global metabolomic profiling by liquid chromatography mass spectrometry was performed on the frozen tumor samples. Statistical analyses were performed using the Southeast Center for Integrated Metabolomics Galaxy interface. Select metabolites which significantly differed between low-grade (WHO Grade I) and high-grade (WHO grade II-III) were identified using the Human Metabolome Database. RESULTS Differing metabolomic profiles between low-grade and high-grade meningiomas were confirmed by multivariate analysis and demonstrated by unsupervised hierarchical clustering. Notably, lysophospholipid and sphingolipid metabolism was increased in the high-grade tumors, while FAPy-adenine, an oxidized nucleoside which may serve as a tumor marker, was decreased. Guanine was found to be consistently decreased in patients with negative outcomes. CONCLUSIONS High-grade and low-grade meningiomas harbor different metabolomic profiles. The significance of these specific differences requires further investigation.

scholarly journals COT-15 LITERATURE REVIEW ON THE DECISION MAKING OF THE BRAIN TUMOR PATIENT

2019 ◽  
Vol 1 (Supplement_2) ◽  
pp. ii43-ii43
Author(s):  
Tatsuya Kishi ◽  
Naoya Sakurada ◽  
Mayumi Horikawa ◽  
Haruaki Ohkubo ◽  
Kazumi Ishii ◽  
...  
Keyword(s):  
Decision Making ◽  
Brain Tumor ◽  
Brain Tumors ◽  
End Of Life ◽  
End Of Life Care ◽  
Primary Brain Tumor ◽  
Life Care ◽  
Tumor Patients ◽  
The Family ◽  
The Brain

Abstract BACKGROUND Patients with primary brain tumors find it difficult to make decisions during the advanced disease stage and experience decreased consciousness. It is important for patients to receive supported decision-making early. Medical staff should know what to do and when to do it,but there are no clear guidelines. Therefore,we reviewed the literature for supported decision-making for primary brain tumor patients,particularly to provide information for understanding trends reported in previous research. METHOD On January 1,2019,we conducted a search using keywords,such as “brain tumor”and “decision-making,” via PubMed and “Igakuchuo-zashi” in Japan. We extracted literature about treatment decision support and end-of-life care for patients with primary brain tumors. Furthermore,we studied and chose the documents for information provision. RESULT Upon observing 7 studies,we found: 1) about 50% of the patients want more prognostic information; 2) patients with brain tumor tend to be anxious,but they want more information to develop a good understanding of the disease and to lower their anxiety; 3) about half of the brain tumor patients in end-of-life care are unable to make decisions sooner owing to impaired consciousness,and hence are unable to share treatment preferences with their doctors; 4) when medical professionals provide information,such as adding video tools about end-of-life care to oral explanations,it facilitates supported decision-making; and 5) when the caregiver intends to notify patients,the family feels conflicted. DISCUSSION The results suggested that if the timing of the end-of-life conversation is late,it becomes difficult for the patient to make decisions and the burden of decision-making falls on the family. It is necessary to examine effective supported decision-making tools for patients by assessing and comprehending information needs and anxiety levels of primary brain tumor patients.

scholarly journals A Review on Brain Tumor Classification Methodologies

2019 ◽  
pp. 346-359 ◽  
Author(s):  
Bichitra Panda ◽  
Chandra Sekhar Panda
Keyword(s):  
Feature Extraction ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Brain Mri ◽  
Tumor Classification ◽  
Low Grade ◽  
High Grade ◽  
Mr Images ◽  
The Brain

Brain tumor is one of the leading disease in the world. So automated identification and classification of tumors are important for diagnosis. Magnetic resonance imaging (MRI)is widely used modality for imaging brain. Brain tumor classification refers to classify the brain MR images as normal or abnormal, benign or malignant, low grade or high grade or types. This paper reviews various techniques used for the classification of brain tumors from MR images. Brain tumor classification can be divided into three phases as preprocessing, feature extraction and classification. As segmentation is not mandatory for classification, hence resides in the first phase. The feature extraction phase also contains feature reduction. DWT is efficient for both preprocessing and feature extraction. Texture analysis based on GLCM gives better features for classification where PCA reduces the feature vector maintaining the accuracy of classification of brain MRI. Shape features are important where segmentation has already been performed. The use of SVM along with appropriate kernel techniques can help in classifying the brain tumors from MRI. High accuracy has been achieved to classify brain MRI as normal or abnormal, benign or malignant and low grade or high grade. But classifying the tumors into more particular types is more challenging.

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