Developmental interneuron subtype deficits after targeted loss of Arx

Abstract Background Aristaless-related homeobox (ARX) is a paired-like homeodomain transcription factor that functions primarily as a transcriptional repressor and has been implicated in neocortical interneuron specification and migration. Given the role interneurons appear to play in numerous human conditions including those associated with ARX mutations, it is essential to understand the consequences of mutations in this gene on neocortical interneurons. Previous studies have examined the effect of germline loss of Arx, or targeted mutations in Arx, on interneuron development. We now present the effect of conditional loss of Arx on interneuron development. Results To further elucidate the role of Arx in forebrain development we performed a series of anatomical and developmental studies to determine the effect of conditional loss of Arx specifically from developing interneurons in the neocortex and hippocampus. Analysis and cell counts were performed from mouse brains using immunohistochemical and in situ hybridization assays at 4 times points across development. Our data indicate that early in development, instead of a loss of ventral precursors, there is a shift of these precursors to more ventral locations, a deficit that persists in the adult nervous system. The result of this developmental shift is a reduced number of interneurons (all subtypes) at early postnatal and later time periods. In addition, we find that X inactivation is stochastic, and occurs at the level of the neural progenitors. Conclusion These data provide further support that the role of Arx in interneuron development is to direct appropriate migration of ventral neuronal precursors into the dorsal cortex and that the loss of Arx results in a failure of interneurons to reach the cortex and thus a deficiency in interneurons.http://deepblue.lib.umich.edu/bitstream/2027.42/134595/1/12868_2016_Article_265.pd

Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas:results from the ReSPOND consortium

PURPOSE: While the T2-FLAIR mismatch sign is highly specific for isocitrate dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted astrocytomas among lower-grade gliomas, its utility in WHO grade 4 gliomas is not well-studied. We derived the partial T2-FLAIR mismatch sign as an imaging biomarker for IDH mutation in WHO grade 4 gliomas. METHODS: Preoperative MRI scans of adult WHO grade 4 glioma patients (n = 2165) from the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium were analyzed. Diagnostic performance of the partial T2-FLAIR mismatch sign was evaluated. Subset analyses were performed to assess associations of imaging markers with overall survival (OS). RESULTS: One hundred twenty-one (5.6%) of 2165 grade 4 gliomas were IDH-mutant. Partial T2-FLAIR mismatch was present in 40 (1.8%) cases, 32 of which were IDH-mutant, yielding 26.4% sensitivity, 99.6% specificity, 80.0% positive predictive value, and 95.8% negative predictive value. Multivariate logistic regression demonstrated IDH mutation was significantly associated with partial T2-FLAIR mismatch (odds ratio [OR] 5.715, 95% CI [1.896, 17.221], p = 0.002), younger age (OR 0.911 [0.895, 0.927], p < 0.001), tumor centered in frontal lobe (OR 3.842, [2.361, 6.251], p < 0.001), absence of multicentricity (OR 0.173, [0.049, 0.612], p = 0.007), and presence of cystic (OR 6.596, [3.023, 14.391], p < 0.001) or non-enhancing solid components (OR 6.069, [3.371, 10.928], p < 0.001). Multivariate Cox analysis demonstrated cystic components (p = 0.024) and non-enhancing solid components (p = 0.003) were associated with longer OS, while older age (p < 0.001), frontal lobe center (p = 0.008), multifocality (p < 0.001), and multicentricity (p < 0.001) were associated with shorter OS. CONCLUSION: Partial T2-FLAIR mismatch sign is highly specific for IDH mutation in WHO grade 4 gliomas

Developmental interneuron subtype deficits after targeted loss of Arx

Background: Aristaless-related homeobox (ARX) is a paired-like homeodomain transcription factor that functions primarily as a transcriptional repressor and has been implicated in neocortical interneuron specification and migration. Given the role interneurons appear to play in numerous human conditions including those associated with ARX mutations, it is essential to understand the consequences of mutations in this gene on neocortical interneurons. Previous studies have examined the effect of germline loss of Arx, or targeted mutations in Arx, on interneuron development. We now present the effect of conditional loss of Arx on interneuron development. Results: To further elucidate the role of Arx in forebrain development we performed a series of anatomical and developmental studies to determine the effect of conditional loss of Arx specifically from developing interneurons in the neocortex and hippocampus. Analysis and cell counts were performed from mouse brains using immunohistochemical and in situ hybridization assays at 4 times points across development. Our data indicate that early in development, instead of a loss of ventral precursors, there is a shift of these precursors to more ventral locations, a deficit that persists in the adult nervous system. The result of this developmental shift is a reduced number of interneurons (all subtypes) at early postnatal and later time periods. In addition, we find that X inactivation is stochastic, and occurs at the level of the neural progenitors. Conclusion: These data provide further support that the role of Arx in interneuron development is to direct appropriate migration of ventral neuronal precursors into the dorsal cortex and that the loss of Arx results in a failure of interneurons to reach the cortex and thus a deficiency in interneurons

Integrated deep learning model for predicting DNA methylation profiles and tumor types from histopathology in central nervous system tumors

DEPLOY codes in the manuscript "Integrated deep learning model for predicting DNA methylation and tumor types from histopathology in central nervous system tumors" are uploaded here. Please see the README for details

Abstract 3428: Validation and utilization of next generation sequencing in the clinical assessment of gliomas

Abstract Background. Identifying prognostic and potentially therapeutic genetic alterations in gliomas is crucial to improve clinical outcome and guide future targeted therapies in this devastating disease. Here, we establish the feasibility of next generation sequencing (NGS) profiling of glioma samples in a clinical setting. Methods. We optimized and validated a 47 gene panel for use on both fresh and Formalin Fixed Paraffin embedded (FFPE) tissue specimens in a CLIA-certified laboratory. Validation was performed in 27 samples by comparing mutation detection on two different NGS platforms, and we have since incorporated routine molecular tumor profiling into the standard workup of glioma patients seen at our institution. Results. From analysis of 120 clinical samples, we found disease-associated changes in 90 patients (75%). Overall 184 changes including disease-associated point mutations and variants of unclear significance were identified across 98 samples, resulting in an average of 1.85 mutations per sample and a range of 1- 6 mutations. This included 49 amplifications across several genes (EGFR, PDGFRA and KIT). Conclusions. The final validated assay allows for a cost effective and efficient analysis of a spectrum of clinically relevant and actionable biomarkers including point mutations, insertions, deletions and gene amplifications. Given the high fraction of tumors presenting with known disease associated changes, routine genomic profiling has the promise of improving patient outcomes and allow for access to targeted therapies. Citation Format: MacLean P. Nasrallah, Maria Martinez-Lage, Alan Fox, Shrey Sukhadia, Arati Desai, Donald M. O'Rourke, Steven Brem, David Roth, Jennifer J.D. Morrissette, Robert D. Daber. Validation and utilization of next generation sequencing in the clinical assessment of gliomas. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3428. doi:10.1158/1538-7445.AM2014-3428</jats:p

Robust Image Population Based Stain Color Normalization: How Many Reference Slides Are Enough?

Histopathologic evaluation of Hematoxylin &amp; Eosin (H&amp;E) stained slides is essential for disease diagnosis, revealing tissue morphology, structure, and cellular composition. Variations in staining protocols and equipment result in images with color nonconformity. Although pathologists compensate for color variations, these disparities introduce inaccuracies in computational whole slide image (WSI) analysis, accentuating data domain shift and degrading generalization. Current state-of-the-art normalization methods employ a single WSI as reference, but selecting a single WSI representative of a complete WSI-cohort is infeasible, inadvertently introducing normalization bias. We seek the optimal number of slides to construct a more representative reference based on composite/aggregate of multiple H&amp;E density histograms and stain-vectors, obtained from a randomly selected WSI population (WSI-Cohort-Subset). We utilized 1,864 IvyGAP WSIs as a WSI-cohort, and built 200 WSI-Cohort-Subsets varying in size (from 1 to 200 WSI-pairs) using randomly selected WSIs. The WSI-pairs&#x0027; mean Wasserstein Distances and WSI-Cohort-Subsets&#x0027; standard deviations were calculated. The Pareto Principle defined the optimal WSI-Cohort-Subset size. The WSI-cohort underwent structure-preserving color normalization using the optimal WSI-Cohort-Subset histogram and stain-vector aggregates. Numerous normalization permutations support WSI-Cohort-Subset aggregates as representative of a WSI-cohort through WSI-cohort CIELAB color space swift convergence, as a result of the law of large numbers and shown as a power law distribution. We show normalization at the optimal (Pareto Principle) WSI-Cohort-Subset size and corresponding CIELAB convergence: a) Quantitatively, using 500 WSI-cohorts; b) Quantitatively, using 8,100 WSI-regions; c) Qualitatively, using 30 cellular tumor normalization permutations. Aggregate-based stain normalization may contribute in increasing computational pathology robustness, reproducibility, and integrity

Clinical activity of the EGFR tyrosine kinase inhibitor osimertinib in EGFR-mutant glioblastoma

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults and carries a dismal prognosis. The EGFR gene is among the most commonly deranged genes in GBM and thus an important therapeutic target. We report the case of a young female with heavily pretreated EGFR-mutated GBM, for whom we initiated osimertinib, an oral, third-generation tyrosine kinase inhibitor that irreversibly inhibits EGFR and has significant brain penetration. We then review some of the main challenges in targeting EGFR, including lack of central nervous system penetration with most tyrosine kinase inhibitors, molecular heterogeneity of GBM and the need for enhanced specificity for the EGFR mutations relevant in GBM

Molecular Neuropathology in Practice: Clinical Profiling and Integrative Analysis of Molecular Alterations in Glioblastoma

Molecular profiling of glioblastoma has revealed complex cytogenetic, epigenetic, and molecular abnormalities that are necessary for diagnosis, prognosis, and treatment. Our neuro-oncology group has developed a data-driven, institutional consensus guideline for efficient and optimal workup of glioblastomas based on our routine performance of molecular testing. We describe our institution’s testing algorithm, assay development, and genetic findings in glioblastoma, to illustrate current practices and challenges in neuropathology related to molecular and genetic testing. We have found that coordination of test requisition, tissue handling, and incorporation of results into the final pathologic diagnosis by the neuropathologist improve patient care. Here, we present analysis of O 6 -methylguanine-DNA-methyltransferase promoter methylation and next-generation sequencing results of 189 patients, obtained utilizing our internal processes led by the neuropathology team. Our institutional pathway for neuropathologist-driven molecular testing has streamlined the management of glioblastoma samples for efficient return of results for incorporation of genomic data into the pathological diagnosis and optimal patient care