Develop Brain Tumors Research Articles

P10.02.B The fragile balance between proliferation and neoplasia in neural stem cells: role of DIAPH3 in glioblastoma

Abstract Background DIAPH3 belongs to the formin family of proteins that are master regulators of the cell cytoskeleton. DIAPH3 plays a key role in cytokinesis as well karyokinesis. Hence, in the mouse brain, DIAPH3-deficient neural stem cells exhibit abnormal cell division leading to aneuploidy and apoptosis of cells progeny. Given the importance of aneuploidy in cancer development and progression, we asked whether DIAPH3 loss could be involved in the genesis and the aggressiveness of brain tumors. Material and Methods We co-inactivated Diaph3 and Trp53 genes in the mouse cerebral cortex using the Emx1-Cre mouse line (Diaph3/Trp53 dcKO). As a control, we inactivated only Trp53 gene using the same Cre mouse line (Trp53 cKO). Mouse survival was analyzed, and tumors were collected for histological analysis as well as molecular characterization. Additionally, we measured DIAPH3 expression in human glioblastoma samples and studied its impact on patient overall survival. Results Diaph3/Trp53 dcKO develop brain tumors earlier compared to Trp53 cKO resulting in a decrease of mouse survival. Hematoxylin-eosin staining, as well as GFAP, OLIG2 and KI67 immunostainings strongly suggest that the tumors are glioblastomas. Quantitative reverse transcription PCR performed on biopsies from 73 patients uncover variable DIAPH3 expression levels in glioblastoma samples. Interestingly, multivariate Cox proportional-hazards analysis shows that low DIAPH3 expression predicts a worse overall survival, independently from other known prognosis factors. Conclusion On one hand, our study shows that DIAPH3 loss favors glioblastoma development in mouse, strongly suggesting a tumor-suppressor role for DIAPH3. On the other hand, the clinical study shows that DIAPH3 low expression has a negative impact on patient overall survival indicating that DIAPH3 loss may favor resistance to chemotherapy and/or radiotherapy.

Drug Repurposing, a Fast-Track Approach to Develop Effective Treatments for Glioblastoma.

Simple SummaryIntroducing novel and effective treatments against glioblastoma (GBM) remains an arduous journey as reflected in the negative outcome of most clinical trials. The blood–brain barrier and the tremendous heterogeneity of the disease comprise major obstacles in this process. Drug repurposing is a drug discovery approach that can accelerate the drug development timeline and identify promising candidates for GBM treatment. Obtaining insights already at preclinical stage into drug sensitivity and physicochemical properties for central nervous system (CNS) penetration of these candidates could shift research outcomes to more effective drugs for clinical investigation against GBM.Glioblastoma (GBM) remains one of the most difficult tumors to treat. The mean overall survival rate of 15 months and the 5-year survival rate of 5% have not significantly changed for almost 2 decades. Despite progress in understanding the pathophysiology of the disease, no new effective treatments to combine with radiation therapy after surgical tumor debulking have become available since the introduction of temozolomide in 1999. One of the main reasons for this is the scarcity of compounds that cross the blood–brain barrier (BBB) and reach the brain tumor tissue in therapeutically effective concentrations. In this review, we focus on the role of the BBB and its importance in developing brain tumor treatments. Moreover, we discuss drug repurposing, a drug discovery approach to identify potential effective candidates with optimal pharmacokinetic profiles for central nervous system (CNS) penetration and that allows rapid implementation in clinical trials. Additionally, we provide an overview of repurposed candidate drug currently being investigated in GBM at the preclinical and clinical levels. Finally, we highlight the importance of phase 0 trials to confirm tumor drug exposure and we discuss emerging drug delivery technologies as an alternative route to maximize therapeutic efficacy of repurposed candidate drug.

Could dietary erucic acid lower risk of brain tumors? An epidemiological look to Chinese population with implications for prevention and treatment.

Erucic acid, an omega-9 monounsaturated fatty acid present in Brassicaceae plants (rapeseed and mustard oils) is highly consumed by the Chinese population and according to several global survey studies, its highest levels are encountered in the Chinese women's milk. Erucic acid is an activating ligand of the transcription factor PPARδ and an inhibitor of the transcriptional activity of PPARγ, which drive tumorigenesis of glioblastomas and medulloblastomas. In this theoretical review, we propose that erucic acid in diet may associate with the risk of brain tumors. High grade brain tumors including medulloblastomas in children and glioblastomas in adults have devastating consequences for human health and the latter tumors are practically incurable. CONCORD-3 epidemiological study recently published in 2021 revealed a low ratio of medulloblastomas in the pediatric age group and also a low ratio of glioblastomas in adults in the Chinese population. It is certain that such profound differences can not be attributed to a single genetic factor or a single nurture pattern. It is very likely that multiple hereditary, nutritional and environmental factors are responsible for these lower ratios; yet here we propose that erucic acid may be one of the contributing factors. If future epidemiological studies and animal models show antitumor activity of erucic acid regarding brain neoplasias, it can be utilized as a preventive strategy for populations possessing very high risks to develop brain tumors such as those harbouring hereditary syndromes increasing the vulnerability to develop such malignancies.

Detection Of Brain Tumor In Magnetic Resonance Imaging

Brain tumor is comprised of strange & uncontrolled cell division inside the mind. Manual analyzation of brain tumor of MRI is a significant and tedious assignment. The exactness of brain tumor area and size assumes a significant part in powerful screening and tissue therapy. The location of a brain tumor, subsequently, should be done rapidly and precisely. Location of a brain tumor is viewed as a difficult undertaking in the utilization of clinical imaging. This paper is tied in with presenting a strategy that will assist with further developing brain tumor utilizing the secret techniques for VGG19 and move growing experience. The proposed approach will be created in this review determined to fabricate a mixture approach. The reason for this exploration paper is to present the growth recognition program in Magnetic Resonance Imaging (MRI) by utilizing VGG19 and Transfer learning procedures. These strategies have been applied on various arrangements of patients information. They have these properties of getting sorted out their cooling impact on the last piece of the body tissues related with the tissues.

CPRO: Competitive Poor and Rich Optimizer-Enabled Deep Learning Model and Holoentropy Weighted-Power K-Means Clustering for Brain Tumor Classification Using MRI

A brain tumor is a collection of irregular and needless cell development in the brain region, and it is considered a life-threatening disease. Therefore, early level segmentation and brain tumor detection with Magnetic Resonance Imaging (MRI) is more important to save the patient’s life. Moreover, MRI is more effective in identifying patients with brain tumors since the recognition of this modality is moderately larger than considering other imaging modalities. The classification of brain tumors is the most important, difficult task in medical imaging systems because of size, appearance and shape variations. In this paper, Competitive Poor and Rich Optimization (CPRO)-based Deep Quantum Neural Network (Deep QNN) is proposed for brain tumor classification. Additionally, the pre-processing process assists in eradicating noises and uses image intensity to eliminate the artifacts. The significant features are extracted from pre-processed image to perform a productive classification process. The Deep QNN classifier is employed for classifying the brain tumor regions. Besides, the Deep QNN classifier is trained by the developed CPRO approach, which is newly designed by integrating Poor and Rich Optimization (PRO) and Competitive Swarm Optimizer (CSO). The developed brain tumor detection model outperformed other existing models with accuracy, sensitivity and specificity of 94.44%, 97.60% and 93.78%.

Brain Tumor Detection using Hybrid Deep Learning with Genetic Algorithm

Brain tumor segmentation is a challenging task in the medical diagnosis. The primary aim of brain tumor segmentation is to produce precise characterizations of brain tumor areas using adequately placed masks. Deep learning techniques have shown great promise in recent years for solving various computer vision problems such as object detection, image classification, and semantic segmentation. Numerous deep learning-based approaches have been implemented to achieve excellent system performance in brain tumor segmentation. This article aims to comprehensively study the recently developed brain tumor segmentation technology based on deep learning in light of the most advanced technology and its performance. A genetic algorithm based on fuzzy C-means (FCM-GA) was used in this study to segment tumor regions from brain images. The input image is scaled to 256×256 during the preprocessing stage. FCM-GA segmented a preprocessed MRI image. This is a versatile advanced machine learning (ML) technique for locating objects in large datasets. The segmented image is then subjected to hybrid feature extraction (HFE) to improve the feature subset. To obtain the best feature value, Kernel Nearest Neighbor with a genetic algorithm (KNN-GA) is used in the feature selection process. The best feature value is fed into the RESNET classifier, which divides the MRI image into meningioma, glioma, and pituitary gland regions. Real-time data sets are used to validate the performance of the proposed hybrid method. The proposed method improves average classification accuracy by 7.99 % to existing Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) classification algorithms

Ionizing radiation exposure during adulthood and risk of developing brain cancer and neurocognitive disorders: a systematic review and meta-analysis

BACKGROUND AND AIM: Humans are daily exposed to low-dose ionizing radiation (IR), either from natural (cosmic, background radiation) or artificial (medical or industrial) sources. Many studies have suggested that low-dose IR could have a deleterious impact on the brain, but results are not consistent. This study aims to identify evidence from a wide range of literature and present a synthesis of findings on the impact of low-to-moderate doses IR exposure in adulthood on the risk of developing brain tumors and cognitive alterations. METHODS: We performed a systematic review and meta-analysis following the PRISMA guidelines. Searches were performed using PubMed, Scopus, Web of Science and Google Scholar databases. Articles dealing with IR exposure and brain tumors and/or cognitive disorders in adults were retrieved and screened by two independent reviewers. IR exposure sources and scenarios included space travel, Chernobyl disaster, atomic bomb, occupational exposures in nuclear energy and medical sectors. The Newcastle-Ottawa scale for cohort and case-control studies was used for quality assessment. Pooled estimators were computed when quantitative data was available. RESULTS:Out of the 3816 recorded articles, 83 studies were included in the systematic review. Most of the included studies did not demonstrate an increased risk or significant association between exposure to IR in adults and brain cancer. Likewise, there was no strong evidence that IR received during adulthood could have adverse effects on cognitive functions. CONCLUSIONS:The present review does not suggest higher risk of developing brain tumors nor a deleterious impact on cognitive functions after exposure to IR during adulthood among the studied populations. However, the high variability of the assessment tools used by the different studies concerning cognitive disorders made it difficult to synthesize the results. Also, further studies with adequate dosimetry and dose-response assessments would be needed to support these conclusions. Quantitative results of the meta-analysis will be presented at the congress. KEYWORDS: Ionizing radiation, cancer and cancer precursors, mental health outcomes, epidemiology

Metformin and Risk of Malignant Brain Tumors in Patients with Type 2 Diabetes Mellitus.

The risk of malignant brain tumors associated with metformin use has rarely been investigated in humans. This retrospective cohort study investigated such an association. Patients with new-onset type 2 diabetes mellitus diagnosed from 1999 to 2005 in the nationwide database of Taiwan’s national health insurance were used to enroll study subjects. We first identified an unmatched cohort of 153,429 ever users and 16,222 never users of metformin. A cohort of 16,222 ever users and 16,222 never users matched on propensity score was then created from this unmatched cohort. All patients were followed up from 1 January 2006 until 31 December 2011. The incidence density was calculated and hazard ratios were derived from Cox regression incorporated with the inverse probability of treatment weighting using a propensity score. The results showed that 27 never users and 155 ever users developed malignant brain tumors in the unmatched cohort. The incidence rate was 37.11 per 100,000 person-years in never users and 21.39 per 100,000 person-years in ever users. The overall hazard ratio comparing ever users versus never users was 0.574 (95% confidence interval: 0.381–0.863). The respective hazard ratios comparing the first (<27.13 months), second (27.13–58.33 months), and third (>58.33 months) tertiles of cumulative duration of metformin therapy versus never users were 0.897 (0.567–1.421), 0.623 (0.395–0.984), and 0.316 (0.192–0.518). In the matched cohort, the overall hazard ratio was 0.317 (0.149–0.673) and the respective hazard ratios were 0.427 (0.129–1.412), 0.509 (0.196–1.322), and 0.087 (0.012–0.639) for the first, second, and third tertile of cumulative duration of metformin therapy. In conclusion, this study shows a risk reduction of malignant brain tumors associated with metformin use in a dose–response pattern. The risk reduction is more remarkable when metformin has been used for approximately 2–5 years.

SURG-12. MALIGNANT BREAST NEOPLASM AND BRAIN METASTASES: SERIES OF CASES AND MAIN APPROACHES IN A HOSPITAL COMPLEX IN BRAZIL

Abstract Introduction With the advancement of clinical and surgical oncology, patients with breast cancer had an increase in survival. In this context, up to 30% of patients affected with metastases from this site will develop brain tumors. The latter is an important impacting factor for life quality and expectancy, therefore, it’s clinical and surgical management is essential in public health. We present some rare cases and their outcomes. Methods We describe a case series of 07 patients with breast cancer metastases to the brain, involving large portions of the dura, bone or skin. There were 64 surgical interventions of the disease in the period, but only those with more exuberant and atypical presentations were selected. The interventions were carried out in a hospital oncology complex in northeastern Brazil between 2016 and 2020.The diagnosis was based on the clinical description, laboratory and image exams, histopathology and surgical performance of the patients. Results The mean age of the patients was 49.7 years, with all patients being female. Rare presentations were observed, such as bone and skin meninges. Clinical presentations demonstrated advanced stages of the disease with a large tumor volume. Extra axial involvement was verified. All patients underwent neurosurgery for tumor removal and decompression. Biopsies were submitted to anatomopathological and immunohistochemistry examination. Corticotherapy was instituted in the immediate postoperative period and some cases had genetic analysis due to an important family history. There was a reduction in symptoms in most cases. Conclusion Although brain metastases are still a challenge for medical practice, their proper management can prolong and improve patients’ lives. Metastatic breast cancers seem to have a predilection for the central nervous system and their detection and intervention, even in an advanced clinical stage, sound as determinant for the control and severity of symptoms. Keywords Brain Neoplasms, Neoplasm Metastasis, Breast Neoplasms

Longitudinal Assessment of Enhancing Foci of Abnormal Signal Intensity in Neurofibromatosis Type 1

Patients with neurofibromatosis 1 are at increased risk of developing brain tumors, and differentiation from contrast-enhancing foci of abnormal signal intensity can be challenging. We aimed to longitudinally characterize rare, enhancing foci of abnormal signal intensity based on location and demographics. A total of 109 MR imaging datasets from 19 consecutive patients (7 male; mean age, 8.6 years; range, 2.3-16.8 years) with neurofibromatosis 1 and a total of 23 contrast-enhancing parenchymal lesions initially classified as foci of abnormal signal intensity were included. The mean follow-up period was 6.5 years (range, 1-13.8 years). Enhancing foci of abnormal signal intensity were followed up with respect to presence, location, and volume. Linear regression analysis was performed. Location, mean peak volume, and decrease in enhancing volume over time of the 23 lesions were as follows: 10 splenium of the corpus callosum (295 mm3, 5 decreasing, 3 completely resolving, 2 surgical intervention for change in imaging appearance later confirmed to be gangliocytoma and astrocytoma WHO II), 1 body of the corpus callosum (44 mm3, decreasing), 2 frontal lobe white matter (32 mm3, 1 completely resolving), 3 globus pallidus (50 mm3, all completely resolving), 6 cerebellum (206 mm3, 3 decreasing, 1 completely resolving), and 1 midbrain (34 mm3). On average, splenium lesions began to decrease in size at 12.2 years, posterior fossa lesions at 17.1 years, and other locations at 9.4 years of age. Albeit very rare, contrast-enhancing lesions in patients with neurofibromatosis 1 may regress over time. Follow-up MR imaging aids in ascertaining regression. The development of atypical features should prompt further evaluation for underlying tumors.

Segmentation of Brain Magnetic Resonance Images using Deep Learning Classification and Multi-modal Composition

Background: Accurate detection of brain tumor and its severity is a challenging task in the medical field. So there is a need for developing brain tumor detecting algorithms and it is an emerging one for diagnosis, planning the treatment and outcome evaluation. Materials and Methods: Brain tumor segmentation method using deep learning classification and multi-modal composition has been developed using the deep convolutional neural networks. The different modalities of MRI such as T1, flair, T1C and T2 are given as input for the proposed method. The MR images from the different modalities are used in proportion to the information contents in the particular modality. The weights for the different modalities are calculated blockwise and the standard deviation of the block is taken as a proxy for the information content of the block. Then the convolution is performed between the input image of the T1, flair, T1C and T2 MR images and corresponding to the weight of the T1, flair, T1C, and T2 images. The convolution is summed between the different modalities of the MR images and its corresponding weight of the different modalities of the MR images to obtain a new composite image which is given as an input image to the deep convolutional neural network. The deep convolutional neural network performs segmentation through the different layers of CNN and different filter operations are performed in each layer to obtain the enhanced classification and segmented spatial consistency results. The analysis of the proposed method shows that the discriminatory information from the different modalities is effectively combined to increase the overall accuracy of segmentation. Results: The proposed deep convolutional neural network for brain tumor segmentation method has been analysed by using the Brain Tumor Segmentation Challenge 2013 database (BRATS 2013). The complete, core and enhancing regions are validated with Dice Similarity Coefficient and Jaccard similarity index metric for the Challenge, Leaderboard, and Synthetic data set. To evaluate the classification rates, the metrics such as accuracy, precision, sensitivity, specificity, under-segmentation, incorrect segmentation and over segmentation also evaluated and compared with the existing methods. Experimental results exhibit a higher degree of precision in the segmentation compared to existing methods. Conclusion: In this work, deep convolution neural network with different modalities of MR image are used to detect the brain tumor. The new input image was created by convoluting the input image of the different modalities and their weights. The weights are determined using the standard deviation of the block. Segmentation accuracy is high with efficient appearance and spatial consistency. The assessment of segmented images is completely evaluated by using well-established metrics. In future, the proposed method will be considered and evaluated with other databases and the segmentation accuracy results should be analysed with the presence of different kind of noises.

Опухоли головного мозга и электромагнитные поля мобильных телефонов: радио­биоло­гические критерии оценки опасности для населения

Over the past ten years, the possibility of developing long-term consequences, in particular brain cancer in mobile phone users, has been actively discussed among the world scientific community. A number of international organizations still have the view that there is no absolute evidence for this. However, the International Agency for Research on Cancer (IARC) of the World Health Organization (WHO) issued an official press release No. 208 of May 31, 2011, which classified radio frequency electromagnetic fields as possibly carcinogenic to the public (Group 2B), which is associated with the use of a mobile phone. This decision was based on the increased risk of developing glioma brain cancer, high malignancy brain cancer.&#x0D; The IARC decision was preceded by a very long period of scientific confrontation. However, Russian radiobiologists predicted the possibility of developing brain tumors, auditory and vestibular analyzers.&#x0D; Two classical experiments conducted in the USA (2016) and Italy (2018) – total irradiation of animals for two years or throughout their life from the perinatal period to their natural death, strengthened the opinion of most scientists about the possibility of developing a tumor process with prolonged exposure to RF EMF .&#x0D; The article discusses the risks of developing brain cancer in users of mobile phones in the early stages of the development of cellular communications. No corresponding correlation was obtained. Further, the results of epidemiological studies obtained in a number of countries (USA, Sweden, Great Britain, Finland) were analyzed during the period of mass use of cellular communications by all segments of the population, including children.&#x0D; Until now, studies have not been conducted by the international scientific community to justify standards, taking into account the local effects of cellular EMF on the user’s brain. There is no corresponding scientific base. In our opinion, the population is at high risk. We consider it necessary to inform the population about the possible danger of developing a brain tumor. There are serious reasons to strengthen preventive measures aimed at reducing the electromagnetic effect on the population.

Evaluation of clinical, neuroradiologic, and genotypic features of patients with L-2-hydroxyglutaric aciduria.

Aim:L-2-hydroxyglutaric aciduria is a slowly progressive neurometabolic disorder caused by an enzymatic deficiency of L-2-hydroxyglutarate dehydrogenase. Here, we aimed to evaluate the clinical, neuroradiologic, and genotypic characteristics of patients with L-2-hydroxyglutaric aciduria who were followed in our outpatient clinic.Material and Methods:Twenty-five patients with L-2-hydroxyglutaric aciduria were enrolled in the study. Data regarding demographic, clinical, and neuroradiologic findings and molecular analysis were evaluated retrospectively.Results:The mean age of patients at the time of diagnosis was 12.09±8.02 years, whereas the mean age at the time of the first symptoms was 39.47±29.96 months. Diagnostic delay was found as 9.95±7.78 years. Developmental delay, decrease in school success, and seizures were the most common initial symptoms; however, behavioral problems and seizures became more prominent in the disease course. At the time of diagnosis, mental retardation and at least one pathologic cerebellar finding were detected in all symptomatic patients. Three patients developed brain tumors. The most common neuroimaging findings were subcortical white matter changes and cerebellar dentate nucleus involvement. In one patient, there was only isolated basal ganglia involvement without white matter lesions. Patients with similar genotypic features exhibited different clinical and radiologic findings.Conclusion:Although clinical symptoms appear early in L-2-hydroxyglutaric aciduria, there is approximately a ten-year delay in diagnosis. In subjects in whom brain tumor is detected in early childhood, L-2-hydroxyglutaric aciduria should be considered in the differential diagnosis in the presence of mental retardation accompanied by developmental delay, cerebellar and pyramidal findings, and behavior disorders in a wide spectrum ranging from autism spectrum disorder to psychosis. In patients with L-2-hydroxyglutaric aciduria, incipient headache, tinnitus, altered consciousness, and seizures can be indicative of brain tumors.

A proteomic clock for malignant gliomas: The role of the environment in tumorigenesis at the presymptomatic stage.

Malignant gliomas remain incurable with a poor prognosis despite of aggressive treatment. We have been studying the development of brain tumors in a glioma rat model, where rats develop brain tumors after prenatal exposure to ethylnitrosourea (ENU), and there is a sizable interval between when the first pathological changes are noted and tumors become detectable with MRI. Our aim to define a molecular timeline through proteomic profiling of the cerebrospinal fluid (CSF) such that brain tumor commitment can be revealed earlier than at the presymptomatic stage. A comparative proteomic approach was applied to profile CSF collected serially either before, at and after the time MRI becomes positive. Elastic net (EN) based models were developed to infer the timeline of normal or tumor development respectively, mirroring a chronology of precisely timed, “clocked”, adaptations. These CSF changes were later quantified by longitudinal entropy analyses of the EN predictive metric. False discovery rates (FDR) were computed to control the expected proportion of the EN models that are due to multiple hypothesis testing. Our ENU rat brain tumor dating EN model indicated that protein content in CSF is programmed even before tumor MRI detection. The findings of the precisely timed CSF tumor microenvironment changes at presymptomatic stages, deviation from the normal development timeline, may provide the groundwork for the understanding of adaptation of the brain environment in tumorigenesis to devise effective brain tumor management strategies.

От электромагнитного смога до электромагнитного хаоса. К оценке опасности мобильной связи для здоровья населения

Over the past 25 years, there has been a global change in the electromagnetic environment on the Earth, associated with the widest use of wireless communications by the population, which significantly changed the situation of artificial electromagnetic pollution of the external environment and the methodology for assessing the health risks of all population groups. In these difficult conditions, nevertheless, many authors in their conclusions neglect the views established in radiobiology in assessing the danger of exposure to electromagnetic radiation of ultrahigh frequencies (EMR microwave), which is associated, for example, with the notions of a critical organ or critical system, the possibility of accumulating adverse effects and the formation of residual damage (long-term consequences). Almost daily brain irradiation of the EMR of the microwave does not attract their attention. The work uses classical radiobiological approaches to assess the danger of electromagnetic radiation in the microwave range of low non-thermal intensities, including mobile communication for the population and presents some data on the negative impact on public health, including children – mobile phone users. On specific examples, the facts of the relative increase in the risk of developing brain tumors after a long period of active use of cell phones are considered. In many countries, there is a complete disregard for the precautionary principle proposed by the WHO. Children for the first time in the entire period of civilization are included in the risk group. At the same time, in many countries there is a complete disregard for this principle and the recommendations of the International Agency for Research on Cancer (IARC) are ignored. Even before the era of the development of mobile communications, there were significant differences in the approaches to developing acceptable doses for microwave EMR, but discussions on the possible adverse biological effects of non-thermal low levels of these emissions are still ongoing. At the same time, we can note a positive trend associated with the fact that almost all the leading countries of Europe are already correctly assessing the real danger of the MP and have their own more stringent regulations than in Russia (Austria, France, Italy etc.). At the same time, we observe the silence of some scientists and important officials in many countries about the possible danger to the population of EMP mobile communications. As a fact, opposite decisions are made about the prevention and protection of the population, including children. At present, the current situation can be described as electromagnetic chaos in the habitat of the population. In our opinion, in the conditions of the existing electromagnetic chaos, it is necessary to inform the population that mobile communication in the absence of self-limitation can be dangerous to health. The population should have an independent choice of the type and the mode of mobile communication. This choice is his voluntary risk.

Long-term exposure to ambient air pollution and incidence of brain tumor: the European Study of Cohorts for Air Pollution Effects (ESCAPE).

BackgroundEpidemiological evidence on the association between ambient air pollution and brain tumor risk is sparse and inconsistent.MethodsIn 12 cohorts from 6 European countries, individual estimates of annual mean air pollution levels at the baseline residence were estimated by standardized land-use regression models developed within the ESCAPE and TRANSPHORM projects: particulate matter (PM) ≤2.5, ≤10, and 2.5–10 μm in diameter (PM2.5, PM10, and PMcoarse), PM2.5 absorbance, nitrogen oxides (NO2 and NOx) and elemental composition of PM. We estimated cohort-specific associations of air pollutant concentrations and traffic intensity with total, malignant, and nonmalignant brain tumor, in separate Cox regression models, adjusting for risk factors, and pooled cohort-specific estimates using random-effects meta-analyses.ResultsOf 282194 subjects from 12 cohorts, 466 developed malignant brain tumors during 12 years of follow-up. Six of the cohorts also had data on nonmalignant brain tumor, where among 106786 subjects, 366 developed brain tumor: 176 nonmalignant and 190 malignant. We found a positive, statistically nonsignificant association between malignant brain tumor and PM2.5 absorbance (hazard ratio and 95% CI: 1.67; 0.89–3.14 per 10–5/m3), and weak positive or null associations with the other pollutants. Hazard ratio for PM2.5 absorbance (1.01; 0.38–2.71 per 10–5/m3) and all other pollutants were lower for nonmalignant than for malignant brain tumors.ConclusionWe found suggestive evidence of an association between long-term exposure to PM2.5 absorbance indicating traffic-related air pollution and malignant brain tumors, and no association with overall or nonmalignant brain tumors.

Abstract 1356: Variable drug responses characterize the functional heterogeneity of Nf1 null tumors

Abstract Introduction: Neurofibromatosis type 1 (NF1) is a autosomal dominant disease with a predisposition to cancer. Biallelic inactivation of the NF1 gene increases risk of developing brain tumors, leukemia, neurofibromas and malignant peripheral nerve sheath tumors (MPNSTs). Somatic mutations in the NF1 gene are also associated with sporadic malignancies including glioblastoma, neuroblastoma, and melanoma. The NF1 tumor suppressor gene encodes the RAS GTPase-activating protein (GAP) neurofibromin. Loss of NF1 results hyperactivation of Ras, MAPK and PI3K signaling pathways components, representing potential therapeutic targets. However, the variable response of NF1 mutant tumors to MAPK and mTOR inhibitors suggests the intrinsic heterogeneity of NF1 mutant tumors. We hypothesized that defining alternative mechanisms and functional sub-classes of Nf1-mutant tumors on the basis of their variable drug sensitivity will produce pre-clinical therapeutics data that will inform clinical trials. Methods: We previously generated mouse models in which we mutagenized Nf1 heterozygous mice with radiation, recapitulating the susceptibility of patients with NF1 to radiation-induced cancers. These models produced solid tumors such as mammary carcinomas, squamous cell carcinomas, and soft tissue sarcomas, which we determined to be Nf1 null. Cell lines established from these tumors were characterized by a drug sensitivity screen using a custom 94 compound drug library. Drug responses indicate that Nf1 mutant tumor cell lines organize into functional groups sharing similar drug sensitivities. Six candidate drugs each targeting distinct components of MAPK and PI3K signaling pathways were selected from the drug library. After 24 hours of exposure to each inhibitor or control, cells were analyzed for cell proliferation, cell cycle changes, and cell death. Western blotting were performed to determine whether drug exposures produce alterations in their predicted biochemical pathways such as PI3K/Akt, and MAPK pathways. Results: Nf1 loss did not predict uniform sensitivity of cell lines to treatment with MAPK and mTOR inhibitors. Each compound induced differential effects on viability of Nf1 null tumors cell lines. High variability and cell line-dependent cytotoxic and cytostatic effects were also observed. Although phosphorylated Akt(S473), S6, and p44/42 MAPK varied widely among all untreated Nf1 null cell lines, this did not predict their drug sensitivity. In vitro drug sensitivity data indicates heterogeneous differential sensitivities of Nf1 mutant tumor cells to different drug classes, independent of tumor histology, permitting segregation into functional groups. Conclusion: Tumor cell lines driven by Nf1 loss demonstrate heterogeneous responses to Ras pathway inhibition, which may be explained by mechanisms of tumor formation after Nf1 loss involve multiple alternative pathways. Citation Format: Daniela Pucciarelli, Ganesh Krishnamurthi, Steve Braunstein, Jean L. Nakamura. Variable drug responses characterize the functional heterogeneity of Nf1 null tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1356. doi:10.1158/1538-7445.AM2017-1356

Analysis of Brain Tumors Due to the Usage of Mobile Phones

The impact of cellular phone radiation on human health is the subject of current mindfulness and is an outcome of the huge increase in phone usage throughout the world. Phones use electromagnetic radiation in the microwave range. The issue is associated with wireless use for 50 minutes and above. The excessive use of mobile phone may cause brain tumors. Nowadays the most commonly developed brain tumor type is GBM (Glioblastoma) in multiform and Malignant Astrocytoma. In this paper, we focus on the causes of brain tumor (cancer) due to the cell phone as this increase in glucose metabolism. The aim of the study is to address the aforementioned problems associated with the cell phone. MATLAB programming to detect a brain tumor has been used. We have conducted MRI (Magnetic Resonance Imaging) study to get the best images and results.

LGG-12. THE RATE OF GROWTH OF UNTREATED PEDIATRIC BRAIN TUMORS – A CASE SERIES

Abstract INTRODUCTION: Radiological imaging (MRI or CT scan) provides the first line for diagnosis of brain tumors. Given the uniform fatality of malignant brain tumors, no ethical studies of rate of tumor growth without treatment are possible. Therefore, only observations from natural events can provide a clue to the rate of growth of untreated tumors. A case series of children with earlier brain scans who subsequently developed brain tumors is therefore being presented to gain an understanding of the natural evolution of these tumors. METHOD: Institutional Review Board approval was obtained. About 435 tumors treated between January 2005 and December 2015 were screened. All children with previous normal or abnormal brain imaging prior to the “diagnostic scan” were included in the study. Seven patients met the inclusion criteria and their demographic data, histology, and date of previous and diagnostic scan, clinical data including date of surgery were abstracted on to a spread sheet and analyzed for this study. The radiological evolution was reviewed with two attending radiologists. RESULTS: There were 6 males and 1 female. The mean age was 5.95 years (range 6 months to 17 years). Two patients (29%) had gangliogliomas and five patients (71%) had malignant tumors (3 medulloblastomas, one glioblastoma multiforme and one pineoblastoma). The median time from the normal scan to the diagnostic scan was 7 months for the malignant tumors and 64.75 months for the benign tumors (p = 0.37). It was observed that the gangliogliomas also started as diffuse non-enhancing lesions that evolved into the discretely enhancing tumors. CONCLUSION: The time for the evolution of malignant brain tumors is short and WHO I tumors like gangliogliomas are more diffuse than the MRI appearances may suggest.

Roles of purinergic P2X7 receptor in glioma and microglia in brain tumors

This review considers evidence suggesting that activation of the ionotropic purinergic receptor P2X7 (P2X7R) is a contributing factor in the growth of brain tumors. Importantly, expression of P2X7R may be upregulated in both glioma cells and in immune responding microglial cells with possible differential effects on tumor progression. The recruitment of immune cells into tumor regions may not only be involved in supporting an immunosuppressive environment aiding tumor growth but activated microglia could secrete inflammatory factors promoting neoangiogenesis in expanding tumors. The subtype P2X7R exhibits a number of unique properties including activation of the receptor in pathological conditions associated with developing brain tumors. In particular, the tumor microenvironment includes elevated levels of ATP required for activation of P2X7R and the sustained tumor and immune cell P2X7R-mediated responses which in total contribute to overall tumor growth and viability. Studies on cultured rat and human glioma show marked increases in expression of P2X7R and enhanced cell mobility relative to control. Glioma cell animal models demonstrate enhanced expression of P2X7R in both glioma and microglia with antagonism of receptor showing differential effects on tumor growth. Overall, P2X7R activation is associated with a complexity of modulatory actions on tumor growth in part due to ubiquitous expression of the receptor in glioma and immune responsive cells.