12 research outputs found

    Alternative lengthening of telomeres, ATRX loss and H3â K27M mutations in histologically defined pilocytic astrocytoma with anaplasia

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    Anaplasia may be identified in a subset of tumors with a presumed pilocytic astrocytoma (PA) component or piloid features, which may be associated with aggressive behavior, but the biologic basis of this change remains unclear. Fiftyâ seven resections from 36 patients (23 M, 13 F, mean age 32 years, range 3â 75) were included. A clinical diagnosis of NF1 was present in 8 (22%). Alternative lengthening of telomeres (ALT) was assessed by telomereâ specific FISH and/or CISH. A combination of immunohistochemistry, DNA sequencing and FISH were used to study BRAF, ATRX, CDKN2A/p16, mutant IDH1 p.R132H and H3â K27M proteins. ALT was present in 25 (69%) cases and ATRX loss in 20 (57%), mostly in the expected association of ALT+/ATRXâ (20/24, 83%) or ALTâ /ATRX+ (11/11, 100%). BRAF duplication was present in 8 (of 26) (31%). H3â K27M was present in 5 of 32 (16%) cases, all with concurrent ATRX loss and ALT. ALT was also present in 9 (of 11) cases in the benign PA precursor, 7 of which also had ATRX loss in both the precursor and the anaplastic tumor. In a single pediatric case, ALT and ATRX loss developed in the anaplastic component only, and in another adult case, ALT was present in the PAâ A component only, but ATRX was not tested. Features associated with worse prognosis included subtotal resection, adult vs. pediatric, presence of a PA precursor preceding a diagnosis of anaplasia, necrosis, presence of ALT and ATRX expression loss. ALT and ATRX loss, as well as alterations involving the MAPK pathway, are frequent in PA with anaplasia at the time of development of anaplasia or in their precursors. Additionally, a small subset of PA with anaplasia have H3â K27M mutations. These findings further support the concept that PA with anaplasia is a neoplasm with heterogeneous genetic features and alterations typical of both PA and diffuse gliomas.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147190/1/bpa12646_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147190/2/bpa12646.pd

    ATRX-Deficient High-Grade Glioma Cells Exhibit Increased Sensitivity to RTK and PDGFR Inhibitors

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    High-grade glioma, including anaplastic astrocytoma and glioblastoma (GBM) patients, have a poor prognosis due to the lack of effective treatments. Therefore, the development of new therapeutic strategies to treat these gliomas is urgently required. Given that high-grade gliomas frequently harbor mutations in the SNF2 family chromatin remodeler ATRX, we performed a screen to identify FDA-approved drugs that are toxic to ATRX-deficient cells. Our findings reveal that multi-targeted receptor tyrosine kinase (RTK) and platelet-derived growth factor receptor (PDGFR) inhibitors cause higher cellular toxicity in high-grade glioma ATRX-deficient cells. Furthermore, we demonstrate that a combinatorial treatment of RTKi with temozolomide (TMZ)–the current stand-ard of care treatment for GBM patients–causes pronounced toxicity in ATRX-deficient high-grade glioma cells. Our findings suggest that combinatorial treatments with TMZ and RTKi may increase the therapeutic window of opportunity in patients who suffer high-grade gliomas with ATRX mu-tations. Thus, we recommend incorporating the ATRX status into the analyses of clinical trials with RTKi and PDGFRi.This work was supported by grants from Danish National Research Foundation (DNRF115), Danish Cancer Society (KBVU-2017_R167-A11063), European Research Council (ERC-2015-STG- 679068), Nordea-fonden (02-2017-1749) and the Spanish Ministry of Science and Innovation (PID2020- 119329RB-I00). David Pladevall-Morera was supported with a PhD scholarship from the Lundbeck Foundation (R218-2016-415) and funding from Dansk Kræftforskningsfond. María Castejón-Griñán holds an Incorporación fellowship from the Junta de Andalucía. Paula Aguilera was supported with a Juan de la Cierva formación fellowship from the MICINN and an Incorporación fellowship from the Junta de Andalucía. Toyota Fonden and Læge Sofus Carl Emil Friis og hustru Olga Doris Fonden funded the acquisition of the high-content microscope used in this study

    AI powered quantification of nuclear morphology in cancers enables prediction of genome instability and prognosis

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    Abstract While alterations in nucleus size, shape, and color are ubiquitous in cancer, comprehensive quantification of nuclear morphology across a whole-slide histologic image remains a challenge. Here, we describe the development of a pan-tissue, deep learning-based digital pathology pipeline for exhaustive nucleus detection, segmentation, and classification and the utility of this pipeline for nuclear morphologic biomarker discovery. Manually-collected nucleus annotations were used to train an object detection and segmentation model for identifying nuclei, which was deployed to segment nuclei in H&E-stained slides from the BRCA, LUAD, and PRAD TCGA cohorts. Interpretable features describing the shape, size, color, and texture of each nucleus were extracted from segmented nuclei and compared to measurements of genomic instability, gene expression, and prognosis. The nuclear segmentation and classification model trained herein performed comparably to previously reported models. Features extracted from the model revealed differences sufficient to distinguish between BRCA, LUAD, and PRAD. Furthermore, cancer cell nuclear area was associated with increased aneuploidy score and homologous recombination deficiency. In BRCA, increased fibroblast nuclear area was indicative of poor progression-free and overall survival and was associated with gene expression signatures related to extracellular matrix remodeling and anti-tumor immunity. Thus, we developed a powerful pan-tissue approach for nucleus segmentation and featurization, enabling the construction of predictive models and the identification of features linking nuclear morphology with clinically-relevant prognostic biomarkers across multiple cancer types
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