Multiscale, multimodal analysis of tumor heterogeneity in IDH1 mutant vs wild-type diffuse gliomas.

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated data from protein, genomic and MR imaging from 20 treatment-naïve glioma cases and 16 recurrent GBM cases. Multiplexed immunofluorescence (MxIF) was used to generate single cell data for 43 protein markers representing all cancer hallmarks, Genomic sequencing (exome and RNA (normal and tumor) and magnetic resonance imaging (MRI) quantitative features (protocols were T1-post, FLAIR and ADC) from whole tumor, peritumoral edema and enhancing core vs equivalent normal region were also collected from patients. Based on MxIF analysis, 85,767 cells (glioma cases) and 56,304 cells (GBM cases) were used to generate cell-level data for 24 biomarkers. K-means clustering was used to generate 7 distinct groups of cells with divergent biomarker profiles and deconvolution was used to assign RNA data into three classes. Spatial and molecular heterogeneity metrics were generated for the cell data. All features were compared between IDH mt and IDHwt patients and were finally combined to provide a holistic/integrated comparison. Protein expression by hallmark was generally lower in the IDHmt vs wt patients. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion also differed between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. A coherent picture of enhanced angiogenesis in IDHwt tumors was derived from multiple platforms (genomic, proteomic and imaging) and scales from individual proteins to cell clusters and heterogeneity, as well as bulk tumor RNA and imaging features. Longer overall survival for IDH1mt glioma patients may reflect mutation-driven alterations in cellular, molecular, and spatial heterogeneity which manifest in discernable radiological manifestations

Landscape of genetic variants in sporadic meningiomas captured with clinical genomics.

BACKGROUND: Meningiomas are the most common primary central nervous system tumor. Previous studies have characterized recurrent genetic alterations that can predict patient prognosis and potentially provide new avenues for therapeutic intervention. Continued efforts to characterize the genomic changes in meningioma samples can aid in the discovery of therapeutic targets and appropriate patient stratification. METHODS: We performed targeted genomic sequencing on 25 primary and 2 recurrent meningiomas using a 500-gene panel, including canonical meningioma drivers. We further detail the genomic profiles and relevant clinical findings in three cases of angiomatous meningiomas and two recurrent atypical meningiomas. RESULTS: Our approach uncovers a diverse landscape of genomic variants in meningioma samples including mutations in established meningioma-related genes NF2, AKT1, PIK3CA, and TRAF7. In addition to known meningioma drivers, we uncover variants in genes encoding other PI3K subunits, Notch/hedgehog/Wnt signaling pathway components, and chromatin regulators. We additionally identify 22 genes mutated across multiple samples. Three patients included in the study were diagnosed with angiomatous WHO grade I meningiomas, all three of which contained variants in the PI3K-AKT signaling pathway previously described to regulate tumor angiogenesis. Analysis of patient-matched primary and recurrent atypical meningiomas revealed clonal enrichment for mutations in the SWI/SNF complex subunits ARID1A and SMARCA4. CONCLUSIONS: Targeted genomics implemented in neuro-oncology care can enhance our understanding of the genetic underpinnings of central nervous system tumors, including meningiomas. These molecular signatures may be clinically useful in dictating treatment strategies and patient follow-up

Hospital-based intervention to reduce tPA administration time

Objective: Ischemic strokes cause significant morbidity and mortality. Treatment with tissue plasminogen activator (tPA) is an important step to achieve reperfusion and minimize neuronal loss for those patients that qualify. Multiple studies have shown that there is a direct correlation between the timeliness of tPA administration after infarction has begun and improved health outcomes. Hospital process related barriers to tPA administration increase the time from the onset of stroke to treatment, leading to worse outcomes. Patients and methods: This retrospective review from a single stroke center looked at stroke patients across three years (July 2014–May 2017) and examined the temporal delay to treatment that potentially stemmed from the fact that tPA was given after transfer from the radiology suite (post-CT scan) back to the emergency department. This order of events is commonplace in stroke centers across the US. Results: Our results indicate there is a significant 26 minute delay with the commonly used protocol where tPA is given, not in the CT scanner, but rather after the scan when patients return to the emergency room. Conclusion: Our results imply that a change in the protocol (direct administration of tPA in the radiology suite) could improve health outcomes by decreasing the delay in tPA administration. Keywords: Stroke, tPA, Barriers to treatment, Vascular neurology, Quality improvement, Vascular neurosurger

Genomic characterization of an esthesioneuroblastoma with spinal metastases: illustrative case.

BACKGROUND: Esthesioneuroblastoma (ENB) is a rare neoplasm of the sinonasal tract. Currently, the optimal treatment includes maximal resection combined with radiotherapy and/or chemotherapy. Although ENBs often recur and have an aggressive clinical course, spinal metastases are extremely rare and the underlying molecular mechanisms are poorly understood. OBSERVATIONS: Here, the authors describe a 50-year-old male with an aggressive ENB, initially treated with resection and chemotherapy/radiation, who developed multiple thoracic and lumbar spinal metastases. The authors performed targeted exome sequencing on both the resected primary tumor and biopsied spinal metastases, which revealed 12 total variants of unknown clinical significance in genes associated with the PI3K/AKT/mTOR pathway, chromatin remodeling, DNA repair, and cell proliferation. Six of these variants were restricted to the metastatic lesion and included missense mutations with predicted functional effects in GRM3, DNMT3B, PLCG2, and SPEN. LESSONS: This report discusses the potential impact of these variants on tumor progression and metastasis, as well as the implications for identifying potential new biomarkers and therapies

DNA methylation provides diagnostic value for meningioma recurrence in clinical practice.

BACKGROUND: Meningiomas are the most common intracranial tumors. Recent advancements in the genetic profiling of tumors have allowed information including DNA copy number analysis, mutational analysis, and RNA sequencing to be more frequently reported, in turn allowing better characterization of meningiomas. In recent years, analysis of tumor methylomes that reflects both cell-origin methylation signatures and somatically acquired DNA methylation changes has been utilized to better classify meningiomas with great success. METHOD: We report DNA methylation profiling on meningiomas from 17 patients. Formalin-fixed paraffin-embedded (FFPE) meningioma tumor samples were processed, loaded onto the Infinium Methylation EPIC array, and scanned using the Illumina IScan system. Raw IDAT files were processed through the the CNS tumor classifier developed by the Molecular Neuropathology group at the German Cancer Research Center (DKFZ). Corresponding genomics were captured using targeted sequencing panels. RESULT: Among the meningioma samples, 13 samples were classified as benign, two samples as intermediate, and the remaining three samples (from two patients) as malignant, based on previously validated classification algorithms. In addition to tumor methylation profiling, we also present information that includes patient demographics, clinical presentations, tumor characteristics (including size and location), surgical approaches, and mutational analysis. The two patients who provided the samples with malignant methylation classifications had tumor recurrence, reflecting a more aggressive disease course. CONCLUSION: In accordance with prior reports, our case series provides support that tumor DNA methylation profiling adds meaningful classification information and may be beneficial to incorporate in clinical practice. Our report also reveals that DNA methylation combined with WHO histology classification can more accurately predict tumor behavior than WHO classification alone

Multiscale, multimodal analysis of tumor heterogeneity in IDH1 mutant vs wild-type diffuse gliomas.

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated data from protein, genomic and MR imaging from 20 treatment-naïve glioma cases and 16 recurrent GBM cases. Multiplexed immunofluorescence (MxIF) was used to generate single cell data for 43 protein markers representing all cancer hallmarks, Genomic sequencing (exome and RNA (normal and tumor) and magnetic resonance imaging (MRI) quantitative features (protocols were T1-post, FLAIR and ADC) from whole tumor, peritumoral edema and enhancing core vs equivalent normal region were also collected from patients. Based on MxIF analysis, 85,767 cells (glioma cases) and 56,304 cells (GBM cases) were used to generate cell-level data for 24 biomarkers. K-means clustering was used to generate 7 distinct groups of cells with divergent biomarker profiles and deconvolution was used to assign RNA data into three classes. Spatial and molecular heterogeneity metrics were generated for the cell data. All features were compared between IDH mt and IDHwt patients and were finally combined to provide a holistic/integrated comparison. Protein expression by hallmark was generally lower in the IDHmt vs wt patients. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion also differed between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. A coherent picture of enhanced angiogenesis in IDHwt tumors was derived from multiple platforms (genomic, proteomic and imaging) and scales from individual proteins to cell clusters and heterogeneity, as well as bulk tumor RNA and imaging features. Longer overall survival for IDH1mt glioma patients may reflect mutation-driven alterations in cellular, molecular, and spatial heterogeneity which manifest in discernable radiological manifestations