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      A pilot radiogenomic study of DIPG reveals distinct subgroups with unique clinical trajectories and therapeutic targets

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          Abstract

          An adequate understanding of the relationships between radiographic and genomic features in diffuse intrinsic pontine glioma (DIPG) is essential, especially in the absence of universal biopsy, to further characterize the molecular heterogeneity of this disease and determine which patients are most likely to respond to biologically-driven therapies. Here, a radiogenomics analytic approach was applied to a cohort of 28 patients with DIPG. Tumor size and imaging characteristics from all available serial MRIs were evaluated by a neuro-radiologist, and patients were divided into three radiographic response groups (partial response [PR], stable disease [SD], progressive disease [PD]) based on MRI within 2 months of radiotherapy (RT) completion. Whole genome and RNA sequencing were performed on autopsy tumor specimens. We report several key, therapeutically-relevant findings: (1) Certain radiologic features on first and subsequent post-RT MRIs are associated with worse overall survival, including PD following irradiation as well as present, new, and/or increasing peripheral ring enhancement, necrosis, and diffusion restriction. (2) Upregulation of EMT-related genes and distant tumor spread at autopsy are observed in a subset of DIPG patients who exhibit poorer radiographic response to irradiation and/or higher likelihood of harboring H3F3A mutations, suggesting possible benefit of upfront craniospinal irradiation. (3) Additional genetic aberrations were identified, including DYNC1LI1 mutations in a subgroup of patients with PR on post-RT MRI; further investigation into potential roles in DIPG tumorigenesis and/or treatment sensitivity is necessary. (4) Whereas most DIPG tumors have an immunologically “cold” microenvironment, there appears to be a subset which harbor a more inflammatory genomic profile and/or higher mutational burden, with a trend toward improved overall survival and more favorable radiographic response to irradiation, in whom immunotherapy should be considered. This study has begun elucidating relationships between post-RT radiographic response with DIPG molecular profiles, revealing radiogenomically distinct subgroups with unique clinical trajectories and therapeutic targets.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Near-optimal probabilistic RNA-seq quantification.

            We present kallisto, an RNA-seq quantification program that is two orders of magnitude faster than previous approaches and achieves similar accuracy. Kallisto pseudoaligns reads to a reference, producing a list of transcripts that are compatible with each read while avoiding alignment of individual bases. We use kallisto to analyze 30 million unaligned paired-end RNA-seq reads in <10 min on a standard laptop computer. This removes a major computational bottleneck in RNA-seq analysis.
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              The Immune Landscape of Cancer

              We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes-wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant-characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field.
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                Author and article information

                Contributors
                Rachid.Drissi@nationwidechildrens.org
                Journal
                Acta Neuropathol Commun
                Acta Neuropathol Commun
                Acta Neuropathologica Communications
                BioMed Central (London )
                2051-5960
                11 January 2021
                11 January 2021
                2021
                : 9
                : 14
                Affiliations
                [1 ]GRID grid.239573.9, ISNI 0000 0000 9025 8099, Brain Tumor Center, Division of Oncology, , Cincinnati Children’s Hospital Medical Center, ; Cincinnati, OH USA
                [2 ]GRID grid.24827.3b, ISNI 0000 0001 2179 9593, Department of Electrical Engineering and Computer Science, , University of Cincinnati College of Engineering and Applied Science, ; Cincinnati, OH USA
                [3 ]GRID grid.261331.4, ISNI 0000 0001 2285 7943, The Ohio State University College of Medicine, ; Columbus, OH USA
                [4 ]GRID grid.240344.5, ISNI 0000 0004 0392 3476, Center for Childhood Cancer & Blood Disorders, , Nationwide Children’s Hospital, ; Columbus, OH USA
                [5 ]GRID grid.239573.9, ISNI 0000 0000 9025 8099, Department of Biomedical Informatics, , Cincinnati Children’s Hospital Medical Center, ; Cincinnati, OH USA
                [6 ]GRID grid.411023.5, ISNI 0000 0000 9159 4457, Department of Pathology, , Upstate Medical University, ; Syracuse, NY USA
                [7 ]GRID grid.239573.9, ISNI 0000 0000 9025 8099, Department of Radiology and Medical Imaging, , Cincinnati Children’s Hospital Medical Center, ; Cincinnati, OH USA
                [8 ]GRID grid.24827.3b, ISNI 0000 0001 2179 9593, Department of Radiology, , University of Cincinnati College of Medicine, ; Cincinnati, OH USA
                [9 ]GRID grid.240344.5, ISNI 0000 0004 0392 3476, Pediatric Neuro-Oncology Program, , Nationwide Children’s Hospital, ; Columbus, OH USA
                Author information
                http://orcid.org/0000-0003-0564-0181
                Article
                1107
                10.1186/s40478-020-01107-0
                7798248
                33431066
                a0be1c0d-3a77-412e-8350-1bfbeaa53892
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 22 October 2020
                : 14 December 2020
                Funding
                Funded by: Cannonballs for Kayne Foundation
                Funded by: Sophie’s Angel Run
                Funded by: KylerStrong Foundation
                Funded by: Phoebe Louise Dooley Foundation
                Funded by: FundRef http://dx.doi.org/10.13039/100008221, Cure Starts Now Foundation;
                Funded by: The Cure Starts Now Australia
                Funded by: Brooke Healey Foundation
                Funded by: Wayland Villars Foundation
                Funded by: ChadTough Foundation
                Funded by: Aidan's Avengers
                Funded by: Austin Strong
                Funded by: Cure Brain Cancer
                Funded by: FundRef http://dx.doi.org/10.13039/100011187, Jeffrey Thomas Hayden Foundation;
                Funded by: Laurie’s Love Foundation
                Funded by: Love Chloe Foundation
                Funded by: Musella Foundation
                Funded by: Pray Hope Believe Foundation
                Funded by: Reflections Of Grace
                Funded by: Storm the Heavens Fund
                Funded by: Aubreigh’s Army
                Funded by: Whitley’s Wishes
                Funded by: Ryan's Hope
                Funded by: Benny's World
                Funded by: The Isabella and Marcus Foundation
                Funded by: Lauren's Fight for Cure
                Funded by: Robert Connor Dawes Foundation
                Funded by: The Gold Hope Project,
                Funded by: Julia Barbara Foundation
                Funded by: Lily Larue Foundation
                Funded by: American Childhood Cancer Organization
                Funded by: RUN DIPG
                Funded by: Gabriella’s Smile Foundation
                Funded by: The DIPG Collaborative
                Funded by: Snapgrant.com
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                radiogenomics,dipg,serial mr imaging,overall survival,molecular subgrouping

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