876 research outputs found
The children's brain tumor network (CBTN) - Accelerating research in pediatric central nervous system tumors through collaboration and open science
Pediatric brain tumors are the leading cause of cancer-related death in children in the United States and contribute a disproportionate number of potential years of life lost compared to adult cancers. Moreover, survivors frequently suffer long-term side effects, including secondary cancers. The Children's Brain Tumor Network (CBTN) is a multi-institutional international clinical research consortium created to advance therapeutic development through the collection and rapid distribution of biospecimens and data via open-science research platforms for real-time access and use by the global research community. The CBTN's 32 member institutions utilize a shared regulatory governance architecture at the Children's Hospital of Philadelphia to accelerate and maximize the use of biospecimens and data. As of August 2022, CBTN has enrolled over 4700 subjects, over 1500 parents, and collected over 65,000 biospecimen aliquots for research. Additionally, over 80 preclinical models have been developed from collected tumors. Multi-omic data for over 1000 tumors and germline material are currently available with data generation for > 5000 samples underway. To our knowledge, CBTN provides the largest open-access pediatric brain tumor multi-omic dataset annotated with longitudinal clinical and outcome data, imaging, associated biospecimens, child-parent genomic pedigrees, and in vivo and in vitro preclinical models. Empowered by NIH-supported platforms such as the Kids First Data Resource and the Childhood Cancer Data Initiative, the CBTN continues to expand the resources needed for scientists to accelerate translational impact for improved outcomes and quality of life for children with brain and spinal cord tumors
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Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design.
Accelerating cures for children with cancer remains an immediate challenge as a result of extensive oncogenic heterogeneity between and within histologies, distinct molecular mechanisms evolving between diagnosis and relapsed disease, and limited therapeutic options. To systematically prioritize and rationally test novel agents in preclinical murine models, researchers within the Pediatric Preclinical Testing Consortium are continuously developing patient-derived xenografts (PDXs)-many of which are refractory to current standard-of-care treatments-from high-risk childhood cancers. Here, we genomically characterize 261 PDX models from 37 unique pediatric cancers; demonstrate faithful recapitulation of histologies and subtypes; and refine our understanding of relapsed disease. In addition, we use expression signatures to classify tumors for TP53 and NF1 pathway inactivation. We anticipate that these data will serve as a resource for pediatric oncology drug development and will guide rational clinical trial design for children with cancer
Upfront Biology-Guided Therapy in Diffuse Intrinsic Pontine Glioma: Therapeutic, Molecular, and Biomarker Outcomes from PNOC003
PURPOSE
PNOC003 is a multicenter precision medicine trial for children and young adults with newly diagnosed diffuse intrinsic pontine glioma (DIPG).
PATIENTS AND METHODS
Patients (3-25 years) were enrolled on the basis of imaging consistent with DIPG. Biopsy tissue was collected for whole-exome and mRNA sequencing. After radiotherapy (RT), patients were assigned up to four FDA-approved drugs based on molecular tumor board recommendations. H3K27M-mutant circulating tumor DNA (ctDNA) was longitudinally measured. Tumor tissue and matched primary cell lines were characterized using whole-genome sequencing and DNA methylation profiling. When applicable, results were verified in an independent cohort from the Children's Brain Tumor Network (CBTN).
RESULTS
Of 38 patients enrolled, 28 patients (median 6 years, 10 females) were reviewed by the molecular tumor board. Of those, 19 followed treatment recommendations. Median overall survival (OS) was 13.1 months [95% confidence interval (CI), 11.2-18.4] with no difference between patients who followed recommendations and those who did not. H3K27M-mutant ctDNA was detected at baseline in 60% of cases tested and associated with response to RT and survival. Eleven cell lines were established, showing 100% fidelity of key somatic driver gene alterations in the primary tumor. In H3K27-altered DIPGs, TP53 mutations were associated with worse OS (TP53mut 11.1 mo; 95% CI, 8.7-14; TP53wt 13.3 mo; 95% CI, 11.8-NA; P = 3.4e-2), genome instability (P = 3.1e-3), and RT resistance (P = 6.4e-4). The CBTN cohort confirmed an association between TP53 mutation status, genome instability, and clinical outcome.
CONCLUSIONS
Upfront treatment-naïve biopsy provides insight into clinically relevant molecular alterations and prognostic biomarkers for H3K27-altered DIPGs
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Epigenomic profiling of neuroblastoma cell lines.
Understanding the aberrant transcriptional landscape of neuroblastoma is necessary to provide insight to the underlying influences of the initiation, progression and persistence of this developmental cancer. Here, we present chromatin immunoprecipitation sequencing (ChIP-Seq) data for the oncogenic transcription factors, MYCN and MYC, as well as regulatory histone marks H3K4me1, H3K4me3, H3K27Ac, and H3K27me3 in ten commonly used human neuroblastoma-derived cell line models. In addition, for all of the profiled cell lines we provide ATAC-Seq as a measure of open chromatin. We validate specificity of global MYCN occupancy in MYCN amplified cell lines and functional redundancy of MYC occupancy in MYCN non-amplified cell lines. Finally, we show with H3K27Ac ChIP-Seq that these cell lines retain expression of key neuroblastoma super-enhancers (SE). We anticipate this dataset, coupled with available transcriptomic profiling on the same cell lines, will enable the discovery of novel gene regulatory mechanisms in neuroblastoma
The Pediatric Cell Atlas:Defining the Growth Phase of Human Development at Single-Cell Resolution
Single-cell gene expression analyses of mammalian tissues have uncovered profound stage-specific molecular regulatory phenomena that have changed the understanding of unique cell types and signaling pathways critical for lineage determination, morphogenesis, and growth. We discuss here the case for a Pediatric Cell Atlas as part of the Human Cell Atlas consortium to provide single-cell profiles and spatial characterization of gene expression across human tissues and organs. Such data will complement adult and developmentally focused HCA projects to provide a rich cytogenomic framework for understanding not only pediatric health and disease but also environmental and genetic impacts across the human lifespan
Production of He-4 and (4) in Pb-Pb collisions at root(NN)-N-S=2.76 TeV at the LHC
Results on the production of He-4 and (4) nuclei in Pb-Pb collisions at root(NN)-N-S = 2.76 TeV in the rapidity range vertical bar y vertical bar <1, using the ALICE detector, are presented in this paper. The rapidity densities corresponding to 0-10% central events are found to be dN/dy4(He) = (0.8 +/- 0.4 (stat) +/- 0.3 (syst)) x 10(-6) and dN/dy4 = (1.1 +/- 0.4 (stat) +/- 0.2 (syst)) x 10(-6), respectively. This is in agreement with the statistical thermal model expectation assuming the same chemical freeze-out temperature (T-chem = 156 MeV) as for light hadrons. The measured ratio of (4)/He-4 is 1.4 +/- 0.8 (stat) +/- 0.5 (syst). (C) 2018 Published by Elsevier B.V.Peer reviewe
diskin-lab-chop/AutoGVP: Release v0.4.1
<h2>What's Changed</h2>
<ul>
<li>add clinvar cols to abridged output by @rjcorb in https://github.com/diskin-lab-chop/AutoGVP/pull/200</li>
<li>rm address_conflicting_interpretations() function and command by @rjcorb in https://github.com/diskin-lab-chop/AutoGVP/pull/202</li>
<li>Update README.md - figure commit by @jharenza in https://github.com/diskin-lab-chop/AutoGVP/pull/198</li>
</ul>
<p><strong>Full Changelog</strong>: https://github.com/diskin-lab-chop/AutoGVP/compare/v.0.4.0...v0.4.1</p>
diskin-lab-chop/AutoGVP: Release v0.4.2
<h2>What's Changed</h2>
<ul>
<li>readme-update-with-wiki by @jharenza in https://github.com/diskin-lab-chop/AutoGVP/pull/204</li>
<li>Update docker commands to numeric by @jharenza in https://github.com/diskin-lab-chop/AutoGVP/pull/205</li>
<li>add all clinvar disease concept ID file by @rjcorb in https://github.com/diskin-lab-chop/AutoGVP/pull/207</li>
<li>add cancer predisposition gene list by @rjcorb in https://github.com/diskin-lab-chop/AutoGVP/pull/209</li>
</ul>
<p><strong>Full Changelog</strong>: https://github.com/diskin-lab-chop/AutoGVP/compare/v0.4.1...v0.4.2</p>
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