Targeting brain tumors with innovative nanocarriers:bridging the gap through the blood-brain barrier

Background:Glioblastoma multiforme(GBM)is recognized as the most lethal and most highly invasive tumor.The high likelihood of treatment failure arises fromthe presence of the blood-brain barrier(BBB)and stemcells around GBM,which avert the entry of chemotherapeutic drugs into the tumormass.Objective:Recently,several researchers have designed novel nanocarrier systems like liposomes,dendrimers,metallic nanoparticles,nanodiamonds,and nanorobot approaches,allowing drugs to infiltrate the BBB more efficiently,opening up innovative avenues to prevail over therapy problems and radiation therapy.Methods:Relevant literature for this manuscript has been collected from a comprehensive and systematic search of databases,for example,PubMed,Science Direct,Google Scholar,and others,using specific keyword combinations,including“glioblastoma,”“brain tumor,”“nanocarriers,”and several others.Conclusion:This review also provides deep insights into recent advancements in nanocarrier-based formulations and technologies for GBM management.Elucidation of various scientific advances in conjunction with encouraging findings concerning the future perspectives and challenges of nanocarriers for effective brain tumor management has also been discussed.

Fetal brain tumors:Prenatal diagnosis by ultrasound and magnetic resonance imaging

Congenital central nervous system tumors diagnosed during pregnancy are rare, and often have a poor prognosis. The most frequent type is the teratoma. Use of ultrasound and magnetic resonance image allows the suspicion of brain tumors during pregnancy. However, the definitive diagnosis is only confirmed after birth by histology. The purpose of this mini-review article is to describe the general clinical aspects of intracranial tumors and describe the main fetal brain tumors.

Immunolocalization of the oligodendrocyte transcription factor 1(Olig1) in brain tumors

Recent in situ hybridization studies showed that mRNA levels of OLIGl and OLIG2 transcription factors are elevatedin oligodendrogliomas.We raised polyclonal antibodies against a synthetic peptide homologous to the human tran-scription factor Oligl and studied by immunohistochemistry the expression of Oligl in 84 brain tumors and in non-neoplastic brain tissues.All oligodendrogliomas,oligoastrocytomas,and dysembryoplastic neuroepithelial tumorsshowed moderate to strong intranuclear immunoreactivity in cells morphologically identified as oligodendrocytes.

BRAIN TUMORS OF THE FIRST YEAR OF LIFE:CLINICAL AND SURGICAL MANAGEMENT

Brain tumors incidence in pediatric age hasbeen estimated between 1.3 to 5% with a relativeincidence of 1.4 to 11% during the first year oflife; the improvement in instrumental deviceshas lead to a relative increase in precocious diag-nosis. The choice to study brain tumors of the firstyear of life as a separate topic from pediatric ageones depends on the observation that these le-sions have peculiar clinical, topographic and tis-sular characteristics. The survival rate of thesepatients is very poor if compared with that found

Molecular neuro-oncology and development of targeted therapeutic strategies for brain tumors

Brain tumors are a diverse group of malignancies that remain refractory to conventional treatment approaches.Molecular neuro-oncologyhas now begun to clarify the transformed phenotype of brain tumors and identify oncogenic pathways that might be amenable to targetedtherapy.Activity of the phosphoinositide 3;kinase(PI3K)/Akt pathway is often upregulated in brain tumors due to excessive stimu-lation by growth factor receptors and Ras.Loss of function of the tumor suppressor gene PTEN also frequently contributesto

Precision radiotherapy for brain tumors A 10-year bibliometric analysis

OBJECTIVE： Precision radiotherapy plays an important role in the management of brain tumors. This study aimed to identify global research trends in precision radiotherapy for brain tumors using a bibliometric analysis of the Web of Science. DATA RETRIEVAL： We performed a bibliometric analysis of data retrievals for precision radiotherapy for brain tumors containing the key words cerebral tumor, brain tumor, intensity-modulated radiotherapy, stereotactic body radiation therapy, stereotactic ablative radiotherapy, imaging-guided radiotherapy, dose-guided radiotherapy, stereotactic brachytherapy, and stereotactic radiotherapy using the Web of Science. SELECTION CRITERIA： Inclusion criteria： （a） peer-reviewed articles on precision radiotherapy for brain tumors which were published and indexed in the Web of Science; （b） type of articles： original research articles and reviews; （c） year of publication： 2002-2011. Exclusion criteria： （a） articles that required manual searching or telephone access; （b） Corrected papers or book chapters. MAIN OUTCOME MEASURES： （1） Annual publication output; （2） distribution according to country; （3） distribution according to institution; （4） top cited publications; （5） distribution according to journals; and （6） comparison of study results on precision radiotherapy for brain tumors. RESULTS： The stereotactic radiotherapy, intensity-modulated radiotherapy, and imaging-guided radiotherapy are three major methods of precision radiotherapy for brain tumors. There were 260 research articles addressing precision radiotherapy for brain tumors found within the Web of Science. The USA published the most papers on precision radiotherapy for brain tumors, followed by Germany and France. European Synchrotron Radiation Facility, German Cancer Research Center and Heidelberg University were the most prolific research institutes for publications on precision radiotherapy for brain tumors. Among the top 13 research institutes publishing in this field, seven are in the USA, three are in Germany, two are in France, and there is one institute in India. Research interests including urology and nephrology, clinical neurology, as well as rehabilitation are involved in precision radiotherapy for brain tumors studies. CONCLUSION： Precision radiotherapy for brain tumors remains a highly active area of research and development.

Cytomegalovirus in human brain tumors:Role in pathogenesis and potential treatment options

During the last years increasing evidence implies that human cytomegalovirus(CMV) can be attributed to human malignancies arising from numerous tissues. In this perspective, we will review and discuss the potential mechanisms through which CMV infection may contribute to brain tumors by affecting tumor cell initiation, progression and metastasis formation. Recent evidence also suggests that anti-CMV treatment results in impaired tumor growth of CMV positive xenografts in animal models and potentially increased survival in CMV positive glioblastoma patients. Based on these observations and the high tumor promoting capacity of this virus, the classical and novel antiviral therapies against CMV should be revisited as they may represent a great promise for halting tumor progression and lower cancer deaths.

Application of Intraoperative Contrast-Enhanced Ultrasound in the Resection of Brain Tumors

Objective:To investigate the value of routine intraoperative ultrasound(IU)and intraoperative contrast-enhanced ultrasound(ICEUS)in the surgical treatment of brain tumors,and to explore the utilization of ICEUS for the removal of the remnants surrounding the resection cavity.Methods:In total,51 patients who underwent operations from 2012 to 2018 due to different tumors in the brain were included in this study.The clinical data were evaluated retrospectively.IU was performed in all patients,among which 28 patients underwent ICEUS.The effects of IU and ICEUS on tumor resection and recurrence were evaluated.

Preoperative functional MRI localization of language areas in Chinese patients with brain tumors Validation with intraoperative electrocortical mapping

Ten Chinese patients with brain tumors involving language regions were selected. Preoperative functional MRI was performed to locate Broca＇s or Wernicke＇s area, and the cortex that was essential for language function was determined by electrocortical mapping. A site-by-site comparison between functional MRI and electrocortical mapping was performed with the aid of a neuronavigation device. Results showed that the sensitivity and specificity of preoperative functional MRI were 80.0% and 85.0% in Broca＇s area and 66.6% and 85.2% in Wemicke＇s area, respectively. These experimental findings indicate that functional MRI is an accurate, reliable technique with which to identify the location of Wernicke＇s area or Broca＇s area in patients with brain tumors.

EXPRESSION OF SV40 Tag AND FORMATION Tag-p53 AND Tag-Rb COMPLEXES IN CHINESE BRAIN TUMORS

Objective: To investigate the expression of SV40 Tag and formation of Tag-p53 and Tag-Rb complexes in Chinese brain tumors. Methods: SV40 large tumor antigen (Tag) were investigated by immunoprecipitation, silver staining and Western blot in 65 cases of Chinese brain tumors and 8 cases of normal brain tissues. Tag-p53 and Tag-Rb complexes were screened by the same way in 20 and 15 Tag positive tumor tissues respectively. Results: Tag was found in all of 8 ependymomas and 2 choroid plexus papillomas, 90% (9/10) of pituitary adenomas, 73% (11/15) of astrocytomas, 70% (7/10) of meningiomas, 50% (4/8) of glioblastoma multiform, 33% (2/6) of medulloblastomas, 5 oligodendrogliomas, 1 pineocytoma and 8 normal brain tissues were negative for Tag. Tag-p53 complex was detected in all of 20 Tag positive tumors as well as Tag-Rb complex in all of 15 Tag positive tumors. Conclusion: SV40 Tag is not only expressed in human brain tumors, but also it can form specific complexes with tumor suppressors p53 and Rb. SV40 is correlated to human brain tumorigenesis. The inactivation of p53 and Rb due to the formation of Tag-p53 and Tag-Rb complexes is possibly an important mechanism in the etiopathogenesis of human brain tumors.

Brain tumors:Cancer stem-like cells interact with tumor microenvironment

Cancer stem-like cells(CSCs)with potential of self-renewal drive tumorigenesis.Brain tumor microenvironment(TME)has been identified as a critical regulator of malignancy progression.Many researchers are searching new ways to characterize tumors with the goal of predicting how they respond to treatment.Here,we describe the striking parallels between normal stem cells and CSCs.We review the microenvironmental aspects of brain tumors,in particular composition and vital roles of immune cells infiltrating glioma and medulloblastoma.By highlighting that CSCs cooperate with TME via various cellular communication approaches,we discuss the recent advances in therapeutic strategies targeting the components of TME.Identification of the complex and interconnected factors can facilitate the development of promising treatments for these deadly malignancies.

EXPRESSION OF IL-13Ra2 GENE IN HUMAN BRAIN TUMORS

Objective： To investigate the expression of IL-13Ra2 gene in brain tumors. Methods： Seventy-nine human brain tumors were obtained from the department of Neurosurgery of China Medical University. Human IL-13Ra2 expression was evaluated by reverse transcriptase polymerase chain reaction and immunohistochemical analysis. Results： IL-13Ra2 gene was highly expressed in glioblastoma, medulloblastoma, malignant meningioma and benign meningioma. Conclusion： Human IL-13Ra2 gene is expressed in brain tumors in addition to gliomas, and our result indicates that the IL-13Ra2 gene promoter based gene therapy method can be used to treat brain tumors in addition to gliomas. Further studies involving larger numbers of samples are necessary to fully understand the expression profile of IL-13Ra2 gene in the brain tumors.

Photodynamic therapy of brain tumors and novel optical coherence tomography strategies for in vivo monitoring of cerebral°uid dynamics

Photodynamic therapy(PDT)is a promising tool for least-invasive alternative methods for the treatment of brain tumors.The newly discovered PDT-induced opening of the blood–brain barrier(BBB)permeability open novel strategies for drug-brain delivery during post-surgical treatment of glioblastoma GBM.Here we discuss mechanisms of PDT-mediated opening of the BBB and age differences in PDT-related increase in BBB permeability,including with formation of brain edema.The meningeal lymphatic system plays a crucial role in the mechanism of brain drainage and clearance from metabolites and toxic molecules.We discuss that noninvasive photonic stimulation of°uid clearance via meningeal lymphatic vessels,and application of optical coherence tomography(OCT)for bed-side monitoring of meningeal lymphatic drainage has the promising perspective to be widely applied in both experimental and clinical studies of PDT and improving guidelines of PDT of brain tumors.

A Qualitative Study on the Negative Emotions of Mothers during Chemotherapy of Their Children with Malignant Brain Tumors

Objective: To explore the negative emotions of mothers during chemotherapy of their children with malignant brain tumors. Methods: The phenomenological method for qualitative studies was adopted;convenience sampling was used to conduct semi-structured interviews to the mothers of 9 children with malignant brain tumors who received chemotherapy from June 2019 to December 2019;the Colaizzi 7-step analytical method was implemented to collate and analyze the original data. Results: The results were summarized into six subjects: stressed, exhausted because of trying to control everything in home care, prone to excessive care, financially burdened, desperate for knowledge of patient care, and desperate for psychosocial support. Conclusions: Understanding the real experiences and inner feelings of mothers during chemotherapy of their children with malignant brain tumors is helpful for medical staff to learn about the psychological distress and needs of mothers of children with malignant brain tumors, so as to give them psychological support and even social support, and help the mothers and the families of children with malignant brain tumors get through a special period.

Clinical-Pathological Features and Treatment Modalities of Primary Brain Tumors in Tanzania—4 Years of Institutional Experience

Background: The profile of primary brain tumors and treatment modalities employed in Tanzania remains largely unknown. The study aimed to describe the baseline clinical-pathological profile and treatment modalities for primary brain tumors in adults treated at the Ocean Road Cancer Institute (ORCI) from 2017 to 2020. Materials and Methods: This was a retrospective study conducted at ORCI by reviewing 61 medical records of patients with primary brain tumors over the age of 15 from January 2017 to December 2020. A structured questionnaire was used to retrieve information on sociodemographic, clinical-pathological characteristics, and treatment modalities. The 2007 WHO classification system and the International Classification of Cancer Diseases (ICD-0-3) were used for classification and diagnosis. The X2 test and Fisher’s exact test were used to compare the proportions and an independent t-test was used to compare the means. A P-value less than 0.05 was deemed statistically significant. The Results: The mean age of the females was 41.8 years and the mean age of males was 42.9 years. Overall M: F ratio was 1:1.2. Meningioma was the only tumor that was more commonly found in women with M:F of 1:2.1. The most prevalent symptom was headache (57.4%). Glioblastoma (GBM) was the most common tumor among adults (38%), followed by astrocytomas (23%) and meningioma (18%). Approximately 91.8% of all tumors occurred in the supratentorial region. The Frontal lobe was the most common site (29.5%). Approximately 81.9% of patients received surgery. The gross tumor resection (GTR) rate was 26.2%, and the subtotal tumor resection (STR) rate was 55.7%. Roughly 18% of the tumors were inoperable. An estimated 80.3% of respondents received radiation therapy. The radiotherapy technique was 3DCRT in two-thirds of the patients and the rest received conventional 2D radiotherapy. The mean equivalent dose in the 2 Gy fractions (EQD2) was 43.9 Gy. Respondents with low-grade intracranial tumors were treated with a mean EQD2 of 47.3 Gy, while those with high-grade intracranial tumors were treated with a mean EQD2 of 44.3 Gy and the difference was statistically significant. Only half of the patients who received adjuvant radiotherapy received it concurrently with chemotherapy. Temozolomide was the most widely used cytotoxic medication. Conclusion: Mean age of the patients was 41 years old. Most tumors were in the supratentorial area and GBM was the most common tumor. Only meningioma was a bit more common amongst females. Overall, radiotherapy doses and the gross tumor resection rates were low. Concurrent chemotherapy with radiotherapy was given to a few patients.

Neurocognitive Dysfunction After Treatment for Pediatric Brain Tumors:Subtype-Specific Findings and Proposal for Brain Network-Informed Evaluations

The increasing number of long-term survivors of pediatric brain tumors requires us to incorporate the most recent knowledge derived from cognitive neuroscience into their oncological treatment.As the lesion itself,as well as each treatment,can cause specific neural damage,the long-term neurocognitive outcomes are highly complex and challenging to assess.The number of neurocognitive studies in this population grows exponentially worldwide,motivating modern neuroscience to provide guidance in follow-up before,during and after treatment.In this review,we provide an overview of structural and functional brain connectomes and their role in the neuropsychological outcomes of specific brain tumor types.Based on this information,we propose a theoretical neuroscientific framework to apply appropriate neuropsychological and imaging follow-up for future clinical care and rehabilitation trials.

Contrast Normalization Strategies in Brain Tumor Imaging:From Preprocessing to Classification

Cancer-related to the nervous system and brain tumors is a leading cause of mortality in various countries.Magnetic resonance imaging(MRI)and computed tomography(CT)are utilized to capture brain images.MRI plays a crucial role in the diagnosis of brain tumors and the examination of other brain disorders.Typically,manual assessment of MRI images by radiologists or experts is performed to identify brain tumors and abnormalities in the early stages for timely intervention.However,early diagnosis of brain tumors is intricate,necessitating the use of computerized methods.This research introduces an innovative approach for the automated segmentation of brain tumors and a framework for classifying different regions of brain tumors.The proposed methods consist of a pipeline with several stages:preprocessing of brain images with noise removal based on Wiener Filtering,enhancing the brain using Principal Component Analysis(PCA)to obtain well-enhanced images,and then segmenting the region of interest using the Fuzzy C-Means(FCM)clustering technique in the third step.The final step involves classification using the Support Vector Machine(SVM)classifier.The classifier is applied to various types of brain tumors,such as meningioma and pituitary tumors,utilizing the Contrast-Enhanced Magnetic Resonance Imaging(CE-MRI)database.The proposed method demonstrates significantly improved contrast and validates the effectiveness of the classification framework,achieving an average sensitivity of 0.974,specificity of 0.976,accuracy of 0.979,and a Dice Score(DSC)of 0.957.Additionally,this method exhibits a shorter processing time of 0.44 s compared to existing approaches.The performance of this method emphasizes its significance when compared to state-of-the-art methods in terms of sensitivity,specificity,accuracy,and DSC.To enhance the method further in the future,it is feasible to standardize the approach by incorporating a set of classifiers to increase the robustness of the brain classification method.

L_(1)-Smooth SVM with Distributed Adaptive Proximal Stochastic Gradient Descent with Momentum for Fast Brain Tumor Detection

Brain tumors come in various types,each with distinct characteristics and treatment approaches,making manual detection a time-consuming and potentially ambiguous process.Brain tumor detection is a valuable tool for gaining a deeper understanding of tumors and improving treatment outcomes.Machine learning models have become key players in automating brain tumor detection.Gradient descent methods are the mainstream algorithms for solving machine learning models.In this paper,we propose a novel distributed proximal stochastic gradient descent approach to solve the L_(1)-Smooth Support Vector Machine(SVM)classifier for brain tumor detection.Firstly,the smooth hinge loss is introduced to be used as the loss function of SVM.It avoids the issue of nondifferentiability at the zero point encountered by the traditional hinge loss function during gradient descent optimization.Secondly,the L_(1) regularization method is employed to sparsify features and enhance the robustness of the model.Finally,adaptive proximal stochastic gradient descent(PGD)with momentum,and distributed adaptive PGDwithmomentum(DPGD)are proposed and applied to the L_(1)-Smooth SVM.Distributed computing is crucial in large-scale data analysis,with its value manifested in extending algorithms to distributed clusters,thus enabling more efficient processing ofmassive amounts of data.The DPGD algorithm leverages Spark,enabling full utilization of the computer’s multi-core resources.Due to its sparsity induced by L_(1) regularization on parameters,it exhibits significantly accelerated convergence speed.From the perspective of loss reduction,DPGD converges faster than PGD.The experimental results show that adaptive PGD withmomentumand its variants have achieved cutting-edge accuracy and efficiency in brain tumor detection.Frompre-trained models,both the PGD andDPGD outperform other models,boasting an accuracy of 95.21%.

Multi-Level Parallel Network for Brain Tumor Segmentation

Accurate automatic segmentation of gliomas in various sub-regions,including peritumoral edema,necrotic core,and enhancing and non-enhancing tumor core from 3D multimodal MRI images,is challenging because of its highly heterogeneous appearance and shape.Deep convolution neural networks(CNNs)have recently improved glioma segmentation performance.However,extensive down-sampling such as pooling or stridden convolution in CNNs significantly decreases the initial image resolution,resulting in the loss of accurate spatial and object parts information,especially information on the small sub-region tumors,affecting segmentation performance.Hence,this paper proposes a novel multi-level parallel network comprising three different level parallel subnetworks to fully use low-level,mid-level,and high-level information and improve the performance of brain tumor segmentation.We also introduce the Combo loss function to address input class imbalance and false positives and negatives imbalance in deep learning.The proposed method is trained and validated on the BraTS 2020 training and validation dataset.On the validation dataset,ourmethod achieved a mean Dice score of 0.907,0.830,and 0.787 for the whole tumor,tumor core,and enhancing tumor core,respectively.Compared with state-of-the-art methods,the multi-level parallel network has achieved competitive results on the validation dataset.

ARGA-Unet:Advanced U-net segmentation model using residual grouped convolution and attention mechanism for brain tumor MRI image segmentation

Background Magnetic resonance imaging(MRI)has played an important role in the rapid growth of medical imaging diagnostic technology,especially in the diagnosis and treatment of brain tumors owing to its non invasive characteristics and superior soft tissue contrast.However,brain tumors are characterized by high non uniformity and non-obvious boundaries in MRI images because of their invasive and highly heterogeneous nature.In addition,the labeling of tumor areas is time-consuming and laborious.Methods To address these issues,this study uses a residual grouped convolution module,convolutional block attention module,and bilinear interpolation upsampling method to improve the classical segmentation network U-net.The influence of network normalization,loss function,and network depth on segmentation performance is further considered.Results In the experiments,the Dice score of the proposed segmentation model reached 97.581%,which is 12.438%higher than that of traditional U-net,demonstrating the effective segmentation of MRI brain tumor images.Conclusions In conclusion,we use the improved U-net network to achieve a good segmentation effect of brain tumor MRI images.