Amanpour S, Muhammadnejad S, Muhammadnejad A, Mazaheri Z, Kazem-Haghighi M, Oghabian M, Khoshnevisan A,
Volume 69, Issue 3 (6-2011)
Abstract
Background: Despite advances in cancer diagnosis and treatment, survival rate of
patients suffering from glioblastoma multiform (GBM) has not been significantly improved. Therefore, novel therapeutic adjuncts to routine therapies have been suggested over time. Inhibition of angiogenesis by antiangiogenic drugs is one of the new approaches to inhibit the growth of malignant cells. Microvessel density (MVD) assay is a technique performed by counting immunohistochemically-stained blood vessels. Nowadays, athymic nude mice are widely used for the establishment of xenograft tumor models in cancer research. The aim of this study was to evaluate the MVD of autochthonous xenograft models of GBM isolated from Iranian patients for use in pharmaceutical research on antiangiogenic drugs.Methods: Fresh tumor samples of GBM were obtained from three patients in Cancer Institute of Tehran University of Medical Sciences in Fall of 2010 and Winter of 2011. After preliminary processing, minced tumor samples were implanted heterotopically on flanks of athymic nude mice. Two months later, the animals were sacrificed and the xenograft tumor samples were sent to the pathology laboratory. After establishing the proof of the xenograft tumor type, MVD-CD34, an endothelial cell marker, was assessed by counting hot spot areas in 22 samples.Results: The mean number of microvessels in these xenograft tumor models was 30±2.1.
Conclusion: These autochthonous xenograft models of GBM can be used in preclinical settings for research on antiangiogenic drugs regarding a pharmacogenomics-based treatment regimen for the Iranian population. Moreover, such models can be used in future studies for determining the sensitivity or resistance to antiangiogenic drugs in individualized cancer therapy.
Hamidreza Saligheh Rad , Anahita Fathi Kazerooni , Mahnaz Nabil , Mohammadreza Alviri , Mehrdad Hadavand, Meysam Mohseni ,
Volume 76, Issue 3 (6-2018)
Abstract
Background: Due to intrinsic heterogeneity of cellular distribution and density within diffusion weighted images (DWI) of glioblastoma multiform (GBM) tumors, differentiation of active tumor and peri-tumoral edema regions within these tumors is challenging. The aim of this paper was to take advantage of the differences among heterogeneity of active tumor and edematous regions within the glioblastoma multiform tumors in order to discriminate these regions from each other.
Methods: The dataset of this retrospective study was selected from a database which was collected at the medical imaging center, Imam Khomeini Hospital, Tehran University of Medical Sciences, Iran. The quantification was performed as a part of a research study being supported by the Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Iran, between May and September 2017. Twenty patients with histopathologically-confirmed GBM tumors who had been imaged on a 3T MRI scanner prior to their surgery, were included. Conventional and diffusion weighted MR images had been carried out on the patients. The regions of interest including the regions of active tumor and edema were identified on MR images by an expert and overlaid on ADC-maps of the same patients. Histogram analysis was performed on each of these regions and 14 characteristic features were calculated and the best feature combination for discrimination of active tumor from edema was obtained.
Results: It was shown that by combining 8 out of 14 histogram features, including median, normalized mean, standard deviation, skewness, energy, 25th, 75th, and 95th percentiles, differentiation with accuracy of 96.4% and diagnostic performance of 100% can be achieved. Furthermore, by combining mean, energy, and 75th percentile features of histograms, the active tumor region can be discriminated from the edematous region by 92.7% of accuracy and 98.9% of diagnostic performance.
Conclusion: The present study confirms that the heterogeneity of cellular distribution can be a predictive biomarker for differentiation of edematous regions from active tumor part of GBM tumors.
Sima Ravaei, Fatemeh Rajabpour, Mina Tabrizi , Alireza Khoshnevisan,
Volume 79, Issue 7 (10-2021)
Abstract
Glioma is the most common type of brain tumor and according to the 2016 WHO classification, based on invasion level, it is divided into four categories. The most severe and invasive type is grade IV glioma or glioblastoma (GBM), which has a very poor prognosis and a survival rate of only 15 months. However, the molecular pathway of invasion in malignant glioma tumors has not yet been clearly elucidated. Like other cancers, brain tumors are thought to migrate and metastasize to other tissues via epithelial-to-mesenchymal transition (EMT). EMT is a process by which epithelial cells lose their cell polarity and cell-cell adhesion, and gain migratory and invasive properties to become mesenchymal stem cells. Studies have shown that EMT and angiogenesis can help brain tumors to migrate to other parts of the brain as well as surrounding tissues. Thus they can induce metastasis. EMT is controlled by three gene families, including SNAIL, TWIST, and ZEB. During EMT, the expression of epithelial-related genes is silenced, and, conversely, the expression of mesenchymal-related genes is increased. In this way, the cells acquire the mesenchymal tissue’s features and can be prepared for invasion and metastasis. On the other hand, only about 1% of the genome can take its role in the translation of functional proteins, and the large remaining part of the genome is made up of non-coding sequences. Therefore, much attention has recently been paid to the role of such noncoding transcripts, at the top of them, long non-coding RNAs (lncRNAs), in regulating the expression of genes involved in important molecular pathways such as apoptosis, proliferation, invasion, and migration in cancer progression and metastasis. Any interference in regulating the expression of genes involved in each of these molecular pathways leads to cancer in different ways. Understanding and identifying lncRNAs involved in tumorigenesis and invasion of brain tumors, while helping to better identify the molecular mechanisms of metastasis in glioma, can also be effective as biomarkers in the diagnosis, prognosis, treatment, and drug resistance of glioma. Therefore, in this review study, the most important lncRNAs involved in EMT in glioma have been investigated.
