scholarly journals Metabolic Tumor Microenvironment Characterization of Contrast Enhancing Brain Tumors Using Physiologic MRI

Metabolites ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 668
Author(s):  
Andreas Stadlbauer ◽  
Franz Marhold ◽  
Stefan Oberndorfer ◽  
Gertraud Heinz ◽  
Max Zimmermann ◽  
...  

The tumor microenvironment is a critical regulator of cancer development and progression as well as treatment response and resistance in brain neoplasms. The available techniques for investigation, however, are not well suited for noninvasive in vivo characterization in humans. A total of 120 patients (59 females; 61 males) with newly diagnosed contrast-enhancing brain tumors (64 glioblastoma, 20 brain metastases, 15 primary central nervous system (CNS) lymphomas (PCNSLs), and 21 meningiomas) were examined with a previously established physiological MRI protocol including quantitative blood-oxygen-level-dependent imaging and vascular architecture mapping. Six MRI biomarker maps for oxygen metabolism and neovascularization were fused for classification of five different tumor microenvironments: glycolysis, oxidative phosphorylation (OxPhos), hypoxia with/without neovascularization, and necrosis. Glioblastoma showed the highest metabolic heterogeneity followed by brain metastasis with a glycolysis-to-OxPhos ratio of approximately 2:1 in both tumor entities. In addition, glioblastoma revealed a significant higher percentage of hypoxia (24%) compared to all three other brain tumor entities: brain metastasis (7%; p < 0.001), PCNSL (8%; p = 0.001), and meningioma (8%; p = 0.003). A more aggressive biological brain tumor behavior was associated with a higher percentage of hypoxia and necrosis and a lower percentage of remaining vital tumor tissue and aerobic glycolysis. The proportion of oxidative phosphorylation, however, was rather similar (17–26%) for all four brain tumor entities. Tumor microenvironment (TME) mapping provides insights into neurobiological differences of contrast-enhancing brain tumors and deserves further clinical cancer research attention. Although there is a long roadmap ahead, TME mapping may become useful in order to develop new diagnostic and therapeutic approaches.

2017 ◽  
Vol 35 (21) ◽  
pp. 2450-2456 ◽  
Author(s):  
John H. Sampson ◽  
Marcela V. Maus ◽  
Carl H. June

Glioblastoma (GBM) is the most lethal form of brain tumor and remains a large, unmet medical need. This review focuses on recent advances in the neurosciences that converge with the broader field of immuno-oncology. Recent findings in neuroanatomy provide a basis for new approaches of cellular therapies for tumors that involve the CNS. The ultimate success of immunotherapy in the CNS will require improved imaging technologies and methods for analysis of the tumor microenvironment in patients with GBM. It is likely that combinatorial approaches with targeted immunotherapies will be required to exploit the vulnerabilities of GBM and other brain tumors.


2021 ◽  
Author(s):  
◽  
Michael Schulz

Despite constant progress in basic and translational research, cancer is still one of the leading cause of death. In particular, tumors of the central nervous system (CNS) are usually associated with dismal prognosis. Although about 100 distinct subtypes of primary CNS tumors have been classified molecularly, metastases derived from primaries outside the CNS (= brain metastases, BrM) are more frequently observed across brain tumor patients. It is estimated that approximately 20 - 40 % of all cancer patients will develop BrM during their course of disease, and basically every tumor type is able to metastasize to the brain. Nevertheless, BrM are most frequently derived from primaries of the lung, breast, and skin (melanoma). Treatment options for patients with BrM are very limited, and standard of care therapies include surgery, ionizing radiation (e.g. whole brain radio-therapy, WBRT), and some systemic and immuno-therapeutic approaches. The brain represents a unique organ, which in part is due to the presence of the blood-brain barrier, a unit of the neuro-vascular interface ensuring tightly regulated exchange of nutrients, molecules, and cells. Furthermore, apart from microglia the brain parenchyma does not harbor other immune cells. Those cells however can be found at the borders of the CNS residing in the meninges, for instance. Based on recent insight on the immune landscape in the CNS, a paradigm shift occurred after which the brain is no longer regarded as immune-privileged but rather immune distinct. The phenomenon of immune cell infiltration has been described before in the context of neurological disorders including Multiple Sclerosis, as well as in brain tumors. Since the development of immune-therapeutic approaches for tumors outside the CNS that aim to evoke sustainable anti-tumor effects, it became increasingly interesting to understand and harness the immune landscape (= tumor microenvironment, TME) of brain tumors, as well. Interestingly, most of the knowledge about the TME is based on studies of primary brain tumors. However, it is known that BrM compared to primary brain tumors induce a different TME like e.g. the recruitment of much more lymphocytes, which is one of the reasons primary brain tumors are considered immunologically “cold” and poorly respond to immuno-therapies. Previous insight into the functional contribution of tumor-associated cells in BrM progression revealed for example that brain-resident cell types (e.g. astrocytes or microglia) promote BrM development and outgrowth. However, until recently a comprehensive view on the cellular composition and functional role of the brain metastases-associated TME was missing and little was known how it changes during tumor progression or standard therapy. Hence, within this thesis it was sought to describe novel aspects of the TME of preclinical BrM models, which include two xenograft and one syngeneic mouse model. BrM was induced via intra-cardiac injection of tumor cells with a high brain tropism. Both xenograft models were based on immuno-compromised nude mice (Balb/c nude) and included the melanoma-to-brain (M2B) model H1_DL2, and the lung-to-brain (L2B) model H2030. In addition the breast-to-brain model 99LN-BrM was used in wild-type mice (BL6), and therefore represented an immuno-competent, syngeneic model. First BrMs could be detected in the xenograft models at 3 weeks after injection, whereas first 99LN BrMs were detected at 5 weeks. BrM development and progression were monitored by bioluminescence imaging once per week in the xenograft models. Tumor progression in the 99LN model was examined by magnetic resonance imaging. Based on the measurement methods, and for further histologic and cytometric experiments, mice were stratified into groups with small or large BrMs, respectively. Some initial immuno-stainings confirmed previous findings, showing that brain-resident cells like astrocytes and microglia become activated in the presence of tumor cells, whereas neurons for example rather give the impression of passive bystanders. Importantly, an accumulation of IBA1+ cells was observed during BrM progression. IBA1 is a pan-macrophage marker that stains all tumor-associated macrophages (TAMs). However previous work suggested that the TAM population consists of at least two main subpopulations in BrM as well: the resident-infiltrating microglia (MG, TAM-MG), as well as the peripheral and monocytic-derived macrophages (TAM-MDM). Since both cell types within the tumor share morphological traits, and due to the lack of markers to distinguish them, an exact discrimination of both cell types was complicated in the past. Recently, an integrative lineage-tracing-based study identified the integrin CD49d as MDM-specific in the context of brain tumor-associated myeloid cells, hence enabling a reliable dissection of both TAM populations in e.g. flow cytometric experiments. One of the main aims of this thesis was to dissect the myeloid TME in the three different BrM models during tumor progression. Using a 5-marker flow cytometry (FCM) (CD45/CD11b/Ly6C/Ly6G/CD49d) approach, the following cell populations were examined in more detail: granulocytes, inflammatory monocytes, MDM, and MG. ...


2020 ◽  
Vol 11 ◽  
pp. 360
Author(s):  
Sabrina Araujo de Franca ◽  
Wagner Malago Tavares ◽  
Angela Salomao Macedo Salinet ◽  
Manoel Jacobsen Teixeira ◽  
Wellingson Silva Paiva

Background: Minimally invasive procedures are gaining widespread acceptance in difficult-to-access brain tumor treatment. Stereotactic radiosurgery (SRS) is the preferred choice, however, laser interstitial thermal therapy (LITT) has emerged as a tumor cytoreduction technique. The present meta-analysis compared current SRS therapy with LITT in brain tumors. Methods: A search was performed in Lilacs, PubMed, and Cochrane database. Patient’s demographics, tumor location, therapy used, Karnofsky performance status score before treatment, and patient’s outcome (median overall survival, progression-free survival, and adverse events) data were extracted from studies. The risk of bias was assessed by Cochrane collaboration tool. Results: Twenty-five studies were included in this meta-analysis. LITT and SRS MOS in brain metastasis patients were 12.8 months’ versus 9.8 months (ranges 9.3–16.3 and 8.3–9.8; P = 0.02), respectively. In a combined comparison of adverse effects among LITT versus SRS in brain metastasis, we found 15% reduction in absolute risk difference (−0.16; 95% confidence interval P < 0.0001). Conclusion: We could not state that LITT treatment is an optimal alternative therapy for difficult-to-access brain tumors due to the lack of systematic data that were reported in our pooled studies. However, our results identified a positive effect in lowering the absolute risk of adverse events compared with SRS therapy. Therefore, randomized trials are encouraged to ascertain LITT role, as upfront or postoperative/post-SRS therapy for brain tumor treatment.


Author(s):  
Ghazanfar Latif ◽  
Jaafar Alghazo ◽  
Fadi N. Sibai ◽  
D.N.F. Awang Iskandar ◽  
Adil H. Khan

Background: Variations of image segmentation techniques, particularly those used for Brain MRI segmentation, vary in complexity from basic standard Fuzzy C-means (FCM) to more complex and enhanced FCM techniques. Objective: In this paper, a comprehensive review is presented on all thirteen variations of FCM segmentation techniques. In the review process, the concentration is on the use of FCM segmentation techniques for brain tumors. Brain tumor segmentation is a vital step in the process of automatically diagnosing brain tumors. Unlike segmentation of other types of images, brain tumor segmentation is a very challenging task due to the variations in brain anatomy. The low contrast of brain images further complicates this process. Early diagnosis of brain tumors is indeed beneficial to patients, doctors, and medical providers. Results: FCM segmentation works on images obtained from magnetic resonance imaging (MRI) scanners, requiring minor modifications to hospital operations to early diagnose tumors as most, if not all, hospitals rely on MRI machines for brain imaging. In this paper, we critically review and summarize FCM based techniques for brain MRI segmentation.


Author(s):  
Shoaib Amin Banday ◽  
Mohammad Khalid Pandit

Introduction: Brain tumor is among the major causes of morbidity and mortality rates worldwide. According to National Brain Tumor Foundation (NBTS), the death rate has nearly increased by as much as 300% over last couple of decades. Tumors can be categorized as benign (non-cancerous) and malignant (cancerous). The type of the brain tumor significantly depends on various factors like the site of its occurrence, its shape, the age of the subject etc. On the other hand, Computer Aided Detection (CAD) has been improving significantly in recent times. The concept, design and implementation of these systems ascend from fairly simple ones to computationally intense ones. For efficient and effective diagnosis and treatment plans in brain tumor studies, it is imperative that an abnormality is detected at an early stage as it provides a little more time for medical professionals to respond. The early detection of diseases has predominantly been possible because of medical imaging techniques developed from past many decades like CT, MRI, PET, SPECT, FMRI etc. The detection of brain tumors however, has always been a challenging task because of the complex structure of the brain, diverse tumor sizes and locations in the brain. Method: This paper proposes an algorithm that can detect the brain tumors in the presence of the Radio-Frequency (RF) inhomoginiety. The algorithm utilizes the Mid Sagittal Plane as a landmark point across which the asymmetry between the two brain hemispheres is estimated using various intensity and texture based parameters. Result: The results show the efficacy of the proposed method for the detection of the brain tumors with an acceptable detection rate. Conclusion: In this paper, we have calculated three textural features from the two hemispheres of the brain viz: Contrast (CON), Entropy (ENT) and Homogeneity (HOM) and three parameters viz: Root Mean Square Error (RMSE), Correlation Co-efficient (CC), and Integral of Absolute Difference (IAD) from the intensity distribution profiles of the two brain hemispheres to predict any presence of the pathology. First a Mid Sagittal Plane (MSP) is obtained on the Magnetic Resonance Images that virtually divides brain into two bilaterally symmetric hemispheres. The block wise texture asymmetry is estimated for these hemispheres using the above 6 parameters.


2019 ◽  
Vol 21 (10) ◽  
pp. 1297-1309 ◽  
Author(s):  
Denise D Correa ◽  
Jaya Satagopan ◽  
Axel Martin ◽  
Erica Braun ◽  
Maria Kryza-Lacombe ◽  
...  

AbstractBackgroundPatients with brain tumors treated with radiotherapy (RT) and chemotherapy (CT) often experience cognitive dysfunction. We reported that single nucleotide polymorphisms (SNPs) in the APOE, COMT, and BDNF genes may influence cognition in brain tumor patients. In this study, we assessed whether genes associated with late-onset Alzheimer’s disease (LOAD), inflammation, cholesterol transport, dopamine and myelin regulation, and DNA repair may influence cognitive outcome in this population.MethodsOne hundred and fifty brain tumor patients treated with RT ± CT or CT alone completed a neurocognitive assessment and provided a blood sample for genotyping. We genotyped genes/SNPs in these pathways: (i) LOAD risk/inflammation/cholesterol transport, (ii) dopamine regulation, (iii) myelin regulation, (iv) DNA repair, (v) blood–brain barrier disruption, (vi) cell cycle regulation, and (vii) response to oxidative stress. White matter (WM) abnormalities were rated on brain MRIs.ResultsMultivariable linear regression analysis with Bayesian shrinkage estimation of SNP effects, adjusting for relevant demographic, disease, and treatment variables, indicated strong associations (posterior association summary [PAS] ≥ 0.95) among tests of attention, executive functions, and memory and 33 SNPs in genes involved in: LOAD/inflammation/cholesterol transport (eg, PDE7A, IL-6), dopamine regulation (eg, DRD1, COMT), myelin repair (eg, TCF4), DNA repair (eg, RAD51), cell cycle regulation (eg, SESN1), and response to oxidative stress (eg, GSTP1). The SNPs were not significantly associated with WM abnormalities.ConclusionThis novel study suggests that polymorphisms in genes involved in aging and inflammation, dopamine, myelin and cell cycle regulation, and DNA repair and response to oxidative stress may be associated with cognitive outcome in patients with brain tumors.


Diagnostics ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 1049
Author(s):  
Csaba Juhász ◽  
Sandeep Mittal

Epilepsy is a common clinical manifestation and a source of significant morbidity in patients with brain tumors. Neuroimaging has a pivotal role in neuro-oncology practice, including tumor detection, differentiation, grading, treatment guidance, and posttreatment monitoring. In this review, we highlight studies demonstrating that imaging can also provide information about brain tumor-associated epileptogenicity and assist delineation of the peritumoral epileptic cortex to optimize postsurgical seizure outcome. Most studies focused on gliomas and glioneuronal tumors where positron emission tomography (PET) and advanced magnetic resonance imaging (MRI) techniques can detect metabolic and biochemical changes associated with altered amino acid transport and metabolism, neuroinflammation, and neurotransmitter abnormalities in and around epileptogenic tumors. PET imaging of amino acid uptake and metabolism as well as activated microglia can detect interictal or peri-ictal cortical increased uptake (as compared to non-epileptic cortex) associated with tumor-associated epilepsy. Metabolic tumor volumes may predict seizure outcome based on objective treatment response during glioma chemotherapy. Advanced MRI, especially glutamate imaging, can detect neurotransmitter changes around epileptogenic brain tumors. Recently, developed PET radiotracers targeting specific glutamate receptor types may also identify therapeutic targets for pharmacologic seizure control. Further studies with advanced multimodal imaging approaches may facilitate development of precision treatment strategies to control brain tumor-associated epilepsy.


2021 ◽  
Vol 11 (2) ◽  
pp. 271
Author(s):  
Santiago Cepeda ◽  
Sergio García-García ◽  
María Velasco-Casares ◽  
Gabriel Fernández-Pérez ◽  
Tomás Zamora ◽  
...  

Intraoperative ultrasound elastography (IOUS-E) is a novel image modality applied in brain tumor assessment. However, the potential links between elastographic findings and other histological and neuroimaging features are unknown. This study aims to find associations between brain tumor elasticity, diffusion tensor imaging (DTI) metrics, and cell proliferation. A retrospective study was conducted to analyze consecutively admitted patients who underwent craniotomy for supratentorial brain tumors between March 2018 and February 2020. Patients evaluated by IOUS-E and preoperative DTI were included. A semi-quantitative analysis was performed to calculate the mean tissue elasticity (MTE). Diffusion coefficients and the tumor proliferation index by Ki-67 were registered. Relationships between the continuous variables were determined using the Spearman ρ test. A predictive model was developed based on non-linear regression using the MTE as the dependent variable. Forty patients were evaluated. The pathologic diagnoses were as follows: 21 high-grade gliomas (HGG); 9 low-grade gliomas (LGG); and 10 meningiomas. Cases with a proliferation index of less than 10% had significantly higher medians of MTE (110.34 vs. 79.99, p < 0.001) and fractional anisotropy (FA) (0.24 vs. 0.19, p = 0.020). We found a strong positive correlation between MTE and FA (rs (38) = 0.91, p < 0.001). A cubic spline non-linear regression model was obtained to predict tumoral MTE from FA (R2 = 0.78, p < 0.001). According to our results, tumor elasticity is associated with histopathological and DTI-derived metrics. These findings support the usefulness of IOUS-E as a complementary tool in brain tumor surgery.


2021 ◽  
Vol 22 (5) ◽  
pp. 2250
Author(s):  
Evita Athanasiou ◽  
Antonios N. Gargalionis ◽  
Fotini Boufidou ◽  
Athanassios Tsakris

The role of certain viruses in malignant brain tumor development remains controversial. Experimental data demonstrate that human herpesviruses (HHVs), particularly cytomegalovirus (CMV), Epstein–Barr virus (EBV) and human herpes virus 6 (HHV-6), are implicated in brain tumor pathology, although their direct role has not yet been proven. CMV is present in most gliomas and medulloblastomas and is known to facilitate oncomodulation and/or immunomodulation, thus promoting cancer cell proliferation, invasion, apoptosis, angiogenesis, and immunosuppression. EBV and HHV-6 have also been detected in brain tumors and high-grade gliomas, showing high rates of expression and an inflammatory potential. On the other hand, due to the neurotropic nature of HHVs, novel studies have highlighted the engagement of such viruses in the development of new immunotherapeutic approaches in the context of oncolytic viral treatment and vaccine-based strategies against brain tumors. This review provides a comprehensive evaluation of recent scientific data concerning the emerging dual role of HHVs in malignant brain pathology, either as potential causative agents or as immunotherapeutic tools in the fight against these devastating diseases.


2021 ◽  
Vol 11 (2) ◽  
pp. 125
Author(s):  
Melis Savasan Sogut ◽  
Chitra Venugopal ◽  
Basak Kandemir ◽  
Ugur Dag ◽  
Sujeivan Mahendram ◽  
...  

Elk-1, a member of the ternary complex factors (TCFs) within the ETS (E26 transformation-specific) domain superfamily, is a transcription factor implicated in neuroprotection, neurodegeneration, and brain tumor proliferation. Except for known targets, c-fos and egr-1, few targets of Elk-1 have been identified. Interestingly, SMN, SOD1, and PSEN1 promoters were shown to be regulated by Elk-1. On the other hand, Elk-1 was shown to regulate the CD133 gene, which is highly expressed in brain-tumor-initiating cells (BTICs) and used as a marker for separating this cancer stem cell population. In this study, we have carried out microarray analysis in SH-SY5Y cells overexpressing Elk-1-VP16, which has revealed a large number of genes significantly regulated by Elk-1 that function in nervous system development, embryonic development, pluripotency, apoptosis, survival, and proliferation. Among these, we have shown that genes related to pluripotency, such as Sox2, Nanog, and Oct4, were indeed regulated by Elk-1, and in the context of brain tumors, we further showed that Elk-1 overexpression in CD133+ BTIC population results in the upregulation of these genes. When Elk-1 expression is silenced, the expression of these stemness genes is decreased. We propose that Elk-1 is a transcription factor upstream of these genes, regulating the self-renewal of CD133+ BTICs.


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