scholarly journals ET-1 Translational research platform for malignant brain tumors

2021 ◽  
Vol 3 (Supplement_6) ◽  
pp. vi4-vi4
Author(s):  
Kensuke Tateishi ◽  
Yohei Miyake ◽  
Taishi Nakamura ◽  
Jo Sasame ◽  
Takahiro Hayashi ◽  
...  

Abstract Introduction: The standard therapy for malignant brain tumors includes surgery and combination therapy with radiation and chemotherapy, but to provide individualized treatment based on the biological and molecular genetic background of the tumor, integrate genetic information with various functional data are required. In this study, we present an overview of our integrated approaches for translational research and clinical management. Methods: In glioma, pre-and intra-operative clinical information, including intraoperative genetic diagnosis, and intraoperative rapid immunohistochemistry is obtained, then a multidisciplinary treatment approach is started based on these integrated data. Specimens collected intraoperatively are cryopreserved for future analysis, and primary cultured cells are routinely collected. The cultured cells are transplanted into the brain of immunodeficient mice to establish patient-derived xenograft model (PDX). Genetic screening, such as IDH, TERT, BRAF, H3F3A mutation and MGMT methylation analysis are routinely assessed within a few days after surgery and used as information for integrated diagnosis. In case of PDX establishment or recurrence, we perform whole exon sequencing or comprehensive genomic assessment to identify genetic abnormalities. If genomic alterations for possible molecular targeted therapy are identified, we assess drug sensitivity test in vitro and in vivo, which are utilized for research to develop optimal molecular targeted therapy. The results, such as the therapeutic effects of molecular targeted drugs, are used for clinical applications. Results: Since the platform was established, we have treated a total of 286 patients, including 189 gliomas and 37 central nervous system lymphomas based on the integrated information. We are currently collecting clinical data to examine if this integrated approach could provide clinical benefit.Conclusion: The translational research system for malignant brain tumors plays an important role in the promotion of clinical and basic research.

2020 ◽  
Vol 196 (10) ◽  
pp. 856-867 ◽  
Author(s):  
Martin Kocher ◽  
Maximilian I. Ruge ◽  
Norbert Galldiks ◽  
Philipp Lohmann

Abstract Background Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and functional information that can be analyzed by machine learning algorithms and radiomics for the use of radiotherapy in patients with malignant brain tumors. Methods This study is based on comprehensive literature research on machine learning and radiomics analyses in neuroimaging and their potential application for radiotherapy in patients with malignant glioma or brain metastases. Results Feature-based radiomics and deep learning-based machine learning methods can be used to improve brain tumor diagnostics and automate various steps of radiotherapy planning. In glioma patients, important applications are the determination of WHO grade and molecular markers for integrated diagnosis in patients not eligible for biopsy or resection, automatic image segmentation for target volume planning, prediction of the location of tumor recurrence, and differentiation of pseudoprogression from actual tumor progression. In patients with brain metastases, radiomics is applied for additional detection of smaller brain metastases, accurate segmentation of multiple larger metastases, prediction of local response after radiosurgery, and differentiation of radiation injury from local brain metastasis relapse. Importantly, high diagnostic accuracies of 80–90% can be achieved by most approaches, despite a large variety in terms of applied imaging techniques and computational methods. Conclusion Clinical application of automated image analyses based on radiomics and artificial intelligence has a great potential for improving radiotherapy in patients with malignant brain tumors. However, a common problem associated with these techniques is the large variability and the lack of standardization of the methods applied.


2016 ◽  
Vol 18 (suppl 3) ◽  
pp. iii27.4-iii28
Author(s):  
Bonnie Cole ◽  
Christina Lockwood ◽  
J. Russell Geyer ◽  
Sarah Leary

2007 ◽  
Vol 121 (12) ◽  
pp. 2637-2645 ◽  
Author(s):  
Toshio Sasajima ◽  
Naoya Shimada ◽  
Yuichiro Naitoh ◽  
Masataka Takahashi ◽  
Yi Hu ◽  
...  

2020 ◽  
Vol 35 (12) ◽  
pp. 791-798
Author(s):  
Roger J. Packer ◽  
Lindsay Kilburn

Molecular-targeted therapy is an attractive therapeutic approach for childhood brain tumors. Unfortunately, with some notable exceptions, such treatment has not yet made a major impact on survival or for that matter quality-of-life for children with brain tumors. Limitations include the specificity of any single agent to inhibit the target, the presence of multiple genetic abnormalities within a tumor, the likely presence of escape mechanisms and the frequent use of molecular-targeted therapies in relatively biologically unselected patient populations. Despite these limitations, the MEK inhibitors and the BRAF V600E inhibitors have already demonstrated efficacy and are being compared to standard therapy in trials of treatment-naïve patients. There is also great enthusiasm for molecular-targeted therapies that target selective gene fusions. Given the plasticity of epigenetic changes, the targeting of epigenetic aberrations is also a promising avenue of therapy. Because molecular-targeted therapies frequently target genes and pathways that are critical in normal brain development, the acute, subacute long-term sequelae of molecular-targeted therapies need to be carefully monitored.


Author(s):  
Mitsutoshi Nakada ◽  
Daisuke Kita ◽  
Yutaka Hayashi ◽  
Kazuyuki Kawakami ◽  
Jun-ichiro Hamada ◽  
...  

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