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Brain Tumor Research Highlights: March 2018

Published on March 23, 2018 in Research, Our Impact, Clinical Trials

Over the years, NBTS has given nearly $40 million to brain tumor research projects. We’re very proud of the impact this funding has made in advancing the neuro-oncology field closer to better treatments and ultimately a cure. And while NBTS is currently focused on driving our flagship research projects – like the Defeat GBM (glioblastoma) Research Collaborative – forward, there also continues to be great scientific research efforts happening in the neuro-oncology field, en masse. This is critical, as no one researcher, one lab, or one institution can cure this disease alone. Below are highlights of some newly published research from the brain tumor scientific and medical community, compiled by NBTS Research Programs Manager, Amanda Bates:

Age-Dependent Cellular and Behavioral Deficits Induced by Molecularly Targeted Drugs are Reversible
Scafidi J, Ritter J, Talbot BM, et al (2018) AACR Journals DOI: 10.1158/0008-5472.CAN-17-2254
> View the paper (PDF)


Newly developed targeted anticancer drugs inhibit signaling pathways commonly altered in adult and pediatric cancers. However, as these pathways are also essential for normal brain development, concerns have emerged of neurologic sequelae resulting specifically from their application in pediatric cancers. The neural substrates and age dependency of these drug-induced effects in vivo are unknown, and their long-term behavioral consequences have not been characterized. This study defines the age-dependent cellular and behavioral effects of these drugs on normally developing brains and determines their reversibility with post-drug intervention. Mice at different postnatal ages received short courses of molecularly targeted drugs in regimens analogous to clinical treatment. Analysis of rapidly developing brain structures important for sensorimotor and cognitive function showed that, while adult administration was without effect, earlier neonatal administration of targeted therapies attenuated white matter oligodendroglia and hippocampal neuronal development more profoundly than later administration, leading to long-lasting behavioral deficits. This functional impairment was reversed by rehabilitation with physical and cognitive enrichment. Our findings demonstrate age-dependent, reversible effects of these drugs on brain development, which are important considerations as treatment options expand for pediatric cancers.

Significance: Targeted therapeutics elicit age-dependent long-term consequences on the developing brain that can be ameliorated with environmental enrichment.

Predicting cancer outcomes from histology and genomics using convolutional networks
Mobadersany P, Yousefi S, Amgad M, et al (2018) Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.1717139115
> View the paper (PDF)


Cancer histology reflects underlying molecular processes and disease progression and contains rich phenotypic information that is predictive of patient outcomes. In this study, we show a computational approach for learning patient outcomes from digital pathology images using deep learning to combine the power of adaptive machine learning algorithms with traditional survival models. We illustrate how these survival convolutional neural networks (SCNNs) can integrate information from both histology images and genomic biomarkers into a single unified framework to predict time-to-event outcomes and show prediction accuracy that surpasses the current clinical paradigm for predicting the overall survival of patients diagnosed with glioma. We use statistical sampling techniques to address challenges in learning survival from histology images, including tumor heterogeneity and the need for large training cohorts. We also provide insights into the prediction mechanisms of SCNNs, using heat map visualization to show that SCNNs recognize important structures, like microvascular proliferation, that are related to prognosis and that are used by pathologists in grading. These results highlight the emerging role of deep learning in precision medicine and suggest an expanding utility for computational analysis of histology in the future practice of pathology.

Significance: Predicting the expected outcome of patients diagnosed with cancer is a critical step in treatment. Advances in genomic and imaging technologies provide physicians with vast amounts of data, yet prognostication remains largely subjective, leading to suboptimal clinical management. We developed a computational approach based on deep learning to predict the overall survival of patients diagnosed with brain tumors from microscopic images of tissue biopsies and genomic biomarkers. This method uses adaptive feedback to simultaneously learn the visual patterns and molecular biomarkers associated with patient outcomes. Our approach surpasses the prognostic accuracy of human experts using the current clinical standard for classifying brain tumors and presents an innovative approach for objective, accurate, and integrated prediction of patient outcomes.

Phase I Study of DNX-2401 (Delta-24-RGD) Oncolytic Adenovirus: Replication and Immunotherapeutic Effects in Recurrent Malignant Glioma
Lang FF, Conrad C, Gomex-Manzano C, et al (2018) Journal of Clinical Oncology DOI: 10.1200/JCO.2017.75.8219
> View the paper


DNX-2401 (Delta-24-RGD; tasadenoturev) is a tumor-selective, replication-competent oncolytic adenovirus. Preclinical studies demonstrated antiglioma efficacy, but the effects and mechanisms of action have not been evaluated in patients. To do so, a phase I, dose-escalation, biologic-end-point clinical trial of DNX-2401 was conducted in 37 patients with recurrent malignant glioma. Patients received a single intratumoral injection of DNX-2401 into biopsy-confirmed recurrent tumor to evaluate safety and response across eight dose levels (group A). To investigate the mechanism of action, a second group of patients (group B) underwent intratumoral injection through a permanently implanted catheter, followed 14 days later by en bloc resection to acquire post-treatment specimens.

In group A (n = 25), 20% of patients survived > 3 years from treatment, and three patients had a ≥ 95% reduction in the enhancing tumor (12%), with all three of these dramatic responses resulting in > 3 years of progression-free survival from the time of treatment. Analyses of post-treatment surgical specimens (group B, n = 12) showed that DNX-2401 replicates and spreads within the tumor, documenting direct virus-induced oncolysis in patients. In addition to radiographic signs of inflammation, histopathologic examination of immune markers in post-treatment specimens showed tumor infiltration by CD8+ and T-bet+ cells, and transmembrane immunoglobulin mucin-3 downregulation after treatment. Analyses of patient-derived cell lines for damage-associated molecular patterns revealed induction of immunogenic cell death in tumor cells after DNX-2401 administration.

In conclusion, treatment with DNX-2401 resulted in dramatic responses with long-term survival in recurrent high-grade gliomas that are probably due to direct oncolytic effects of the virus followed by elicitation of an immune-mediated antiglioma response.

 The first two studies noted above were directly funded by NBTS research grants. The first through our former pediatric initiative, the Developmental Neurobiology Grant program (funded partially in conjunction with the Brain Tumour Foundation of Canada), and the second through our Oligodendroglioma Community Research Fund. The final study was not funded directly by NBTS, but early research that led to this treatment approach was supported in part by NBTS research funding.

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