CSIG-25. BAI1/ADGRB1 REGULATES TGFβ1-INDUCED MESENCHYMAL SWITCH IN MEDULLOBLASTOMA

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi38-vi39
Author(s):  
Satoru Osuka ◽  
Liquan Yang ◽  
Dan Zhu ◽  
Hideharu Hashimoto ◽  
Erwin G Van Meir
Keyword(s):  
Brain Tumor ◽  
Tumor Invasion ◽  
Angiogenesis Inhibitor ◽  
Leptomeningeal Metastasis ◽  
Epigenetic Silencing ◽  
Normal Brain ◽  
Molecular Defects ◽  
Poor Outcome ◽  
Pathway Activation ◽  
Adhesion Gpcr

Abstract Medulloblastoma (MB) is the most common malignant brain tumor in children. MB tends to metastasize to the brain meninges and subarachnoid space and the spinal cord. Leptomeningeal metastasis is frequently found at initial diagnosis and leads to tumor relapse after standard treatment. Leptomeningeal metastasis remains a major challenge and is related with poor outcome. Acquiring a better knowledge of molecular defects underlying metastatic disease is essential for the development of effective therapies. Brain-specific Angiogenesis Inhibitor 1 (BAI1/ADGRB1) is a transmembrane receptor of the adhesion GPCR family widely expressed in normal brain, but its expression is lost in the majority of medulloblastoma through epigenetic silencing. We reported that BAI1 protects p53 from Mdm2-mediated degradation and regulate tumor growth in medulloblastoma (Zhu D. et al, Cancer Cell, 2018). However, it is unclear whether BAI1 loss is important for tumor invasion and the mesenchymal phenotype in MB. Microarray analysis of the published MB dataset revealed that low BAI1 mRNA expression correlates with poor outcome and with expression of many key mesenchymal genes, including Fibronectin1, SLUG, and TWIST1. Restoration of BAI1 expression in human MB cells suppresses mesenchymal gene expression in culture, and dramatically decreases brain tumor invasion. Mechanistically, we found that the N-terminal thrombospondin type 1 repeat (TSR#1) of BAI1 inhibits the maturation process of TGFβ1, a key growth factor involved in EMT. BAI1 is silenced epigenetically in MB cells by methylated CpG-binding protein MBD2, and its expression can be reactivated by KCC-07, a blood-brain barrier permeable MBD2 inhibitor. We found that restoration of BAI1 expression by KCC-07 treatment dramatically reduced tumor cell invasion of MB cells. These experiments demonstrate that epigenetic silencing of BAI1 is important for activation of the MB invasive phenotype through TGFβ1 pathway activation. Epigenetic targeting of this process by KCC-07 can reduce MB invasion.

Production of matrix metalloproteinases and tissue inhibitor of metalloproteinases-1 by human brain tumors

1994 ◽  
Vol 81 (1) ◽  
pp. 69-77 ◽  
Author(s):  
Takao Nakagawa ◽  
Toshihiko Kubota ◽  
Masanori Kabuto ◽  
Kazufumi Sato ◽  
Hirokazu Kawano ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Matrix Metalloproteinases ◽  
Brain Tumors ◽  
Human Brain ◽  
Tumor Cells ◽  
Tumor Invasion ◽  
Gelatinolytic Activity ◽  
Normal Brain ◽  
Tissue Inhibitor Of Metalloproteinases ◽  
Human Brain Tumor

✓ The role of matrix metalloproteinases (MMP's) and their inhibitor, tissue inhibitor of metalloproteinases-1 (TIMP-1), in human brain tumor invasion was investigated. Gelatinolytic activity was assayed via gelatin zymography, and four MMP's (MMP-1, MMP-2, MMP-3, and MMP-9) and TIMP-1 were immunolocalized in human brain tumors and in normal brain tissues using monoclonal antibodies. The tissue was surgically removed from 44 patients: glioblastoma (five cases), anaplastic astrocytoma (six cases), astrocytoma (four cases), metastatic tumor (six cases), neurinoma (10 cases), meningioma (10 cases), and normal brain tissue (three cases). Glioblastomas, anaplastic astrocytomas, and metastatic tumors showed high gelatinolytic activity and positive immunostaining for MMP's; TIMP-1 was also expressed in these tumors, but some tumor cells were negative for the antibody. Astrocytomas had low gelatinolytic activity and the tumor cells showed no immunoreactivity for MMP's and TIMP-1. Although neurinomas and meningiomas had only moderate proteinase activity and exhibited positive immunoreactivity for MMP-9, intense expression of TIMP-1 was simultaneously observed in these tumor cells. These findings suggest that MMP's play an important role in human brain tumor invasion, probably due to an imbalance between the production of MMP's and TIMP-1 by the tumor cells.

A Survey on Detection and Classification of Brain Tumor Using Image Processing Techniques

2020 ◽  
pp. 967-973
Author(s):  
V. Deepika ◽  
T. Rajasenbagam
Keyword(s):  
Image Processing ◽  
Brain Tumor ◽  
Soft Tissues ◽  
Tumor Detection ◽  
Tumor Classification ◽  
Normal Brain ◽  
Image Processing Techniques ◽  
Normal Brain Function ◽  
Processing Techniques ◽  
The Brain

A brain tumor is an uncontrolled growth of abnormal brain tissue that can interfere with normal brain function. Although various methods have been developed for brain tumor classification, tumor detection and multiclass classification remain challenging due to the complex characteristics of the brain tumor. Brain tumor detection and classification are one of the most challenging and time-consuming tasks in the processing of medical images. MRI (Magnetic Resonance Imaging) is a visual imaging technique, which provides a information about the soft tissues of the human body, which helps identify the brain tumor. Proper diagnosis can prevent a patient's health to some extent. This paper presents a review of various detection and classification methods for brain tumor classification using image processing techniques.

scholarly journals LPTO-06. A NOVEL BRAIN-PERMEANT CHEMOTHERAPEUTIC AGENT FOR THE TREATMENT OF BREAST CANCER LEPTOMENINGEAL METASTASIS

2019 ◽  
Vol 1 (Supplement_1) ◽  
pp. i7-i7
Author(s):  
Jiaojiao Deng ◽  
Sophia Chernikova ◽  
Wolf-Nicolas Fischer ◽  
Kerry Koller ◽  
Bernd Jandeleit ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Brain Tumors ◽  
Cell Lines ◽  
Chemotherapeutic Agent ◽  
Leptomeningeal Metastasis ◽  
Breast Cancer Cell Lines ◽  
Normal Brain ◽  
Breast Cancers

Abstract Leptomeningeal metastasis (LM), a spread of cancer to the cerebrospinal fluid and meninges, is universally and rapidly fatal due to poor detection and no effective treatment. Breast cancers account for a majority of LMs from solid tumors, with triple-negative breast cancers (TNBCs) having the highest propensity to metastasize to LM. The treatment of LM is challenged by poor drug penetration into CNS and high neurotoxicity. Therefore, there is an urgent need for new modalities and targeted therapies able to overcome the limitations of current treatment options. Quadriga has discovered a novel, brain-permeant chemotherapeutic agent that is currently in development as a potential treatment for glioblastoma (GBM). The compound is active in suppressing the growth of GBM tumor cell lines implanted into the brain. Radiolabel distribution studies have shown significant tumor accumulation in intracranial brain tumors while sparing the adjacent normal brain tissue. Recently, we have demonstrated dose-dependent in vitro and in vivo anti-tumor activity with various breast cancer cell lines including the human TNBC cell line MDA-MB-231. To evaluate the in vivo antitumor activity of the compound on LM, we used the mouse model of LM based on the internal carotid injection of luciferase-expressing MDA-MB-231-BR3 cells. Once the bioluminescence signal intensity from the metastatic spread reached (0.2 - 0.5) x 106 photons/sec, mice were dosed i.p. twice a week with either 4 or 8 mg/kg for nine weeks. Tumor growth was monitored by bioluminescence. The compound was well tolerated and caused a significant delay in metastatic growth resulting in significant extension of survival. Tumors regressed completely in ~ 28 % of treated animals. Given that current treatments for LM are palliative with only few studies reporting a survival benefit, Quadriga’s new agent could be effective as a therapeutic for both primary and metastatic brain tumors such as LM. REF: https://onlinelibrary.wiley.com/doi/full/10.1002/pro6.43

Quantitative Measurements of Regional Glucose Utilization and Rate of Valine Incorporation into Proteins by Double-Tracer Autoradiography in the Rat Brain Tumor Model

1989 ◽  
Vol 9 (1) ◽  
pp. 87-95 ◽  
Author(s):  
Michihiro Kirikae ◽  
Mirko Diksic ◽  
Y. Lucas Yamamoto
Keyword(s):  
Protein Synthesis ◽  
Brain Tumor ◽  
Rat Brain ◽  
Brain Tissue ◽  
Glucose Utilization ◽  
Tumor Model ◽  
Normal Brain ◽  
Normal Brain Tissue ◽  
Rat Brain Tumor ◽  
Brain Tumor Model

We examined the rate of glucose utilization and the rate of valine incorporation into proteins using 2-[18F]fluoro-2-deoxyglucose and L-[1-14C]-valine in a rat brain tumor model by quantitative double-tracer autoradiography. We found that in the implanted tumor the rate of valine incorporation into proteins was about 22 times and the rate of glucose utilization was about 1.5 times that in the contralateral cortex. (In the ipsilateral cortex, the tumor had a profound effect on glucose utilization but no effect on the rate of valine incorporation into proteins.) Our findings suggest that it is more useful to measure protein synthesis than glucose utilization to assess the effectiveness of antitumor agents and their toxicity to normal brain tissue. We compared two methods to estimate the rate of valine incorporation: “kinetic” (quantitation done using an operational equation and the average brain rate coefficients) and “washed slices” (unbound labeled valine removed by washing brain slices in 10% thrichloroacetic acid). The results were the same using either method. It would seem that the kinetic method can thus be used for quantitative measurement of protein synthesis in brain tumors and normal brain tissue using [11C]-valine with positron emission tomography.

Abstract TMP23: Inflammasome-derived Caspase-1 is Elevated in the Cerebrospinal Fluid of Subarachnoid Hemorrhage Patients and Correlated to Outcome

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Yonatan Hirsch ◽  
Joseph R Geraghty ◽  
Eitan A Katz ◽  
Jeffrey A Loeb ◽  
Fernando Testai
Keyword(s):  
Cerebrospinal Fluid ◽  
Subarachnoid Hemorrhage ◽  
External Ventricular Drain ◽  
Analysis Of Covariance ◽  
Control Group ◽  
Normal Brain ◽  
Poor Outcome ◽  
Caspase 1 ◽  
Initial Severity ◽  
Poor Outcomes

Introduction: The role of neuroinflammation following aneurysmal subarachnoid hemorrhage (SAH) and its relationship to outcome is the subject of many ongoing studies. The proteolytic enzyme, caspase-1, activated by the inflammasome complex, is known to contribute to numerous downstream pro-inflammatory effects. In this study, we investigated caspase-1 activity in the cerebrospinal fluid (CSF) of SAH patients and its association to outcome. Methods: SAH patients were recruited from a regional stroke referral center. CSF samples from 18 SAH subjects were collected via an external ventricular drain and obtained within 72 hours of the onset of symptoms. For control subjects, we collected the CSF from 9 patients undergoing lumbar puncture with normal CSF and normal brain MRI. Caspase-1 activity was measured using commercially available luminescence assays. SAH subjects were categorized at hospital discharge into those with good outcomes (Glasgow Outcome Scale, GOS, of 4-5) and poor outcomes (GOS of 1-3). The levels of caspase-1 activity in various groups were analyzed using Mann-Whitney and Pearson correlation tests. Caspase-1 activity was also adjusted by initial severity of bleed using analysis of covariance (ANCOVA). Results: Caspase-1 levels from SAH patients were significantly higher than that measured from the control group (mean 1.06x10-2 vs 1.90x10-3 counts per second (CPS)/μl*min), p = 0.0002). Within the SAH group, 10 patients (55.6%) had good outcomes and 8 patients (44.4%) had poor outcomes. Caspase-1 activity was significantly higher in the poor outcome group (mean 1.54x10-2 vs 1.60x10-3 CPS/μl*min), p = 0.0012). Additionally, caspase-1 activity had a statistically significant correlation with GOS score (r = -0.60; p = 0.0100). When adjusted for initial severity of bleed, the difference in caspase-1 activity in good vs. poor outcome remained significant (adjusted mean 7.10x10-3 vs. 2.54x10-2 CPS/μl*min, p=0.004). Conclusions: The inflammasome-dependent protein caspase-1 is elevated in CSF early after SAH and higher in those with poor functional outcome. Inflammasome activity therefore may serve as a novel biomarker to predict outcome shortly after aneurysm rupture.

scholarly journals Perfusion Magnetic Resonance Imaging to Assess Brain Tumor Responses to New Therapies

1998 ◽  
Vol 5 (2) ◽  
pp. 115-123 ◽  
Author(s):  
Michael H. Lev ◽  
Fred Hochberg
Keyword(s):  
Magnetic Resonance Imaging ◽  
Brain Tumor ◽  
Magnetic Resonance ◽  
Imaging Techniques ◽  
Perfusion Mri ◽  
Perfusion Magnetic Resonance Imaging ◽  
Normal Brain ◽  
Resonance Imaging ◽  
New Therapies ◽  
Magnetic Resonance Imaging Mri

Background: Although magnetic resonance imaging (MRI) is effective in detecting the location of intracranial tumors, new imaging techniques have been studied that may enhance the specificity for the prediction of histologic grade of tumor and for the distinction between recurrence and tumor necrosis associated with cancer therapy. Methods: The authors review their experience and that of others on the use of perfusion magnetic resonance imaging to evaluate responses of brain tumors to new therapies. Results: Functional imaging techniques that can distinguish tumor from normal brain tissue using physiological parameters. These new approaches provide maps of tumor perfusion to monitor the effects of novel compounds that restrict tumor angiogenesis. Conclusions: Perfusion MRI not only may be as effective as radionuclide-based techniques in sensitivity and specificity in assessing brain tumor responses to new therapies, but also may offer higher resolution and convenient co-registration with conventional MRI, as well as time- and cost-effectiveness. Further study is needed to determine the role of perfusion MRI in assessing brain tumor responses to new therapies.

scholarly journals Kinetic Analysis of 2-[11C]Thymidine PET Imaging Studies of Malignant Brain Tumors: Compartmental Model Investigation and Mathematical Analysis

2002 ◽  
Vol 1 (3) ◽  
pp. 153535002002021
Author(s):  
Joanne M. Wells ◽  
David A. Mankoff ◽  
Mark Muzi ◽  
Finbarr O'Sullivan ◽  
Janet F. Eary ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Cellular Proliferation ◽  
Compartment Model ◽  
Response To Therapy ◽  
Model Parameters ◽  
Normal Brain ◽  
Identifiability Analysis ◽  
Pet Tracer ◽  
Thymidine Transport

2-[11C]Thymidine (TdR), a PET tracer for cellular proliferation, may be advantageous for monitoring brain tumor progression and response to therapy. We previously described and validated a five-compartment model for thymidine incorporation into DNA in somatic tissues, but the effect of the blood–brain barrier on the transport of TdR and its metabolites necessitated further validation before it could be applied to brain tumors. Methods: We investigated the behavior of the model under conditions experienced in the normal brain and brain tumors, performed sensitivity and identifiability analysis to determine the ability of the model to estimate the model parameters, and conducted simulations to determine whether it can distinguish between thymidine transport and retention. Results: Sensitivity and identifiability analysis suggested that the non-CO2 metabolite parameters could be fixed without significantly affecting thymidine parameter estimation. Simulations showed that K1t and KTdR could be estimated accurately ( r = .97 and .98 for estimated vs. true parameters) with standard errors < 15%. The model was able to separate increased transport from increased retention associated with tumor proliferation. Conclusion: Our model adequately describes normal brain and brain tumor kinetics for thymidine and its metabolites, and it can provide an estimate of the rate of cellular proliferation in brain tumors.

Advancements of MRI-Based Brain Tumor Segmentation from Traditional to Recent Trends- A Review

2021 ◽  
Vol 17 ◽  
Author(s):  
Padmapriya Thiyagarajan ◽  
Sriramakrishnan Padmanaban ◽  
Kalaiselvi Thiruvenkadam ◽  
Somasundaram Karuppanagounder
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Brain Tumor ◽  
Human Head ◽  
Medical Community ◽  
Tumor Segmentation ◽  
Normal Brain ◽  
Learning Methods ◽  
Brain Tumor Segmentation ◽  
Mri Scans

Background: Among the brain-related diseases, brain tumor segmentation on magnetic resonance imaging (MRI) scans is one of the highly focused research domains in the medical community. Brain tumor segmentation is a very challenging task due to its asymmetric form and uncertain boundaries. This process segregates the tumor region into the active tumor, necrosis and edema from normal brain tissues such as white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF). Introduction: The proposed paper analyzed the advancement of brain tumor segmentation from conventional image processing techniques, to deep learning through machine learning on MRI of human head scans. Method: State-of-the-art methods of these three techniques are investigated, and the merits and demerits are discussed. Results: The prime motivation of the paper is to instigate the young researchers towards the development of efficient brain tumor segmentation techniques using conventional and recent technologies. Conclusion: The proposed analysis concluded that the conventional and machine learning methods were mostly applied for brain tumor detection, whereas deep learning methods were good at tumor substructures segmentation.

scholarly journals Towards Reinforced Brain Tumor Segmentation on MRI Images Based on Temperature Changes on Pathologic Area

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Abdelmajid Bousselham ◽  
Omar Bouattane ◽  
Mohamed Youssfi ◽  
Abdelhadi Raihani
Keyword(s):  
Brain Tumor ◽  
Level Set ◽  
False Negative ◽  
Ground Truth ◽  
Tumor Segmentation ◽  
Normal Brain ◽  
Bioheat Equation ◽  
Brain Tumor Segmentation ◽  
Temperature Changes ◽  
Negative Results

Brain tumor segmentation is the process of separating the tumor from normal brain tissues; in clinical routine, it provides useful information for diagnosis and treatment planning. However, it is still a challenging task due to the irregular form and confusing boundaries of tumors. Tumor cells thermally represent a heat source; their temperature is high compared to normal brain cells. The main aim of the present paper is to demonstrate that thermal information of brain tumors can be used to reduce false positive and false negative results of segmentation performed in MRI images. Pennes bioheat equation was solved numerically using the finite difference method to simulate the temperature distribution in the brain; Gaussian noises of ±2% were added to the simulated temperatures. Canny edge detector was used to detect tumor contours from the calculated thermal map, as the calculated temperature showed a large gradient in tumor contours. The proposed method is compared to Chan–Vese based level set segmentation method applied to T1 contrast-enhanced and Flair MRI images of brains containing tumors with ground truth. The method is tested in four different phantom patients by considering different tumor volumes and locations and 50 synthetic patients taken from BRATS 2012 and BRATS 2013. The obtained results in all patients showed significant improvement using the proposed method compared to segmentation by level set method with an average of 0.8% of the tumor area and 2.48% of healthy tissue was differentiated using thermal images only. We conclude that tumor contours delineation based on tumor temperature changes can be exploited to reinforce and enhance segmentation algorithms in MRI diagnostic.

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