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  • 1
    In: Nature Genetics, Springer Science and Business Media LLC, Vol. 49, No. 8 ( 2017-8), p. 1211-1218
    Type of Medium: Online Resource
    ISSN: 1061-4036 , 1546-1718
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
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  • 2
    In: Cancer Discovery, American Association for Cancer Research (AACR), Vol. 11, No. 5 ( 2021-05-01), p. 1082-1099
    Abstract: Effective data sharing is key to accelerating research to improve diagnostic precision, treatment efficacy, and long-term survival in pediatric cancer and other childhood catastrophic diseases. We present St. Jude Cloud (https://www.stjude.cloud), a cloud-based data-sharing ecosystem for accessing, analyzing, and visualizing genomic data from & gt;10,000 pediatric patients with cancer and long-term survivors, and & gt;800 pediatric sickle cell patients. Harmonized genomic data totaling 1.25 petabytes are freely available, including 12,104 whole genomes, 7,697 whole exomes, and 2,202 transcriptomes. The resource is expanding rapidly, with regular data uploads from St. Jude's prospective clinical genomics programs. Three interconnected apps within the ecosystem—Genomics Platform, Pediatric Cancer Knowledgebase, and Visualization Community—enable simultaneously performing advanced data analysis in the cloud and enhancing the Pediatric Cancer knowledgebase. We demonstrate the value of the ecosystem through use cases that classify 135 pediatric cancer subtypes by gene expression profiling and map mutational signatures across 35 pediatric cancer subtypes. Significance: To advance research and treatment of pediatric cancer, we developed St. Jude Cloud, a data-sharing ecosystem for accessing & gt;1.2 petabytes of raw genomic data from & gt;10,000 pediatric patients and survivors, innovative analysis workflows, integrative multiomics visualizations, and a knowledgebase of published data contributed by the global pediatric cancer community. This article is highlighted in the In This Issue feature, p. 995
    Type of Medium: Online Resource
    ISSN: 2159-8274 , 2159-8290
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
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  • 3
    In: Nature Genetics, Springer Science and Business Media LLC, Vol. 51, No. 4 ( 2019-4), p. 694-704
    Type of Medium: Online Resource
    ISSN: 1061-4036 , 1546-1718
    RVK:
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
    detail.hit.zdb_id: 1494946-5
    SSG: 12
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  • 4
    In: Neuro-Oncology, Oxford University Press (OUP), ( 2023-07-28)
    Abstract: High-grade gliomas (HGG) in young children pose a challenge due to favorable but unpredictable outcomes. While retrospective studies broadened our understanding of tumor biology, prospective data is lacking. Methods A cohort of children with histologically diagnosed HGG from the SJYC07 trial was augmented with nonprotocol patients with HGG treated at St. Jude Children’s Research Hospital from November 2007 to December 2020. DNA methylome profiling and whole genome, whole exome, and RNA sequencing were performed. These data were integrated with histopathology to yield an integrated diagnosis. Clinical characteristics and preoperative imaging were analyzed. Results Fifty-six children (0.0–4.4 years) were identified. Integrated analysis split the cohort into four categories: infant-type hemispheric glioma (IHG), HGG, low-grade glioma (LGG), and other-central nervous system (CNS) tumors. IHG was the most prevalent (n = 22), occurred in the youngest patients (median age = 0.4 years), and commonly harbored receptor tyrosine kinase gene fusions (7 ALK, 2 ROS1, 3 NTRK1/2/3, 4 MET). The 5-year event-free (EFS) and overall survival (OS) for IHG was 53.13% (95%CI: 35.52–79.47) and 90.91% (95%CI: 79.66–100.00) vs. 0.0% and 16.67% (95%CI: 2.78–99.74%) for HGG (p = 0.0043, p = 0.00013). EFS and OS were not different between IHG and LGG (p = 0.95, p = 0.43). Imaging review showed IHGs are associated with circumscribed margins (p = 0.0047), hemispheric location (p = 0.0010), and intratumoral hemorrhage (p = 0.0149). Conclusions HGG in young children is heterogeneous and best defined by integrating histopathological and molecular features. Patients with IHG have relatively good outcomes, yet they endure significant deficits, making them good candidates for therapy de-escalation and trials of molecular targeted therapy.
    Type of Medium: Online Resource
    ISSN: 1522-8517 , 1523-5866
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
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  • 5
    In: Neuro-Oncology, Oxford University Press (OUP), Vol. 25, No. Supplement_1 ( 2023-06-12), p. i38-i39
    Abstract: High-grade gliomas (HGG) in young children pose a challenge due to favorable but unpredictable outcomes. While retrospective studies have broadened our understanding of tumor biology, prospective data regarding outcomes and molecular predictors is lacking. METHODS Young children (0-5 years) histologically diagnosed with HGG and enrolled on the SJYC07 trial or treated at St Jude Children’s Research Hospital from November 2007 to December 2020 were included. DNA methylation, whole genome (WGS), whole exome (WES), and RNA (RNA-seq) sequencing were performed on available samples and these data were integrated with standard histopathological tests to yield a diagnosis. Clinical characteristics and pre-operative imaging were analyzed. RESULTS Fifty-six children (0.0-4.4 years) were identified. Integrated molecular and histopathological analysis split the tumors into four categories: infant-type hemispheric glioma (IHG), HGG, low-grade glioma (LGG), and other-central nervous system (CNS) tumors (i.e., CNS embryonal tumors, CNS sarcomas, neuroepithelial tumors). IHG was the most prevalent (N=22), occurred in the youngest patients (median age 0.4 years; 0-4.4 years), and commonly harbored receptor tyrosine kinase gene fusions (7 ALK, 2 ROS1, 3 NTRK1/2/3, 4 MET). The 5-year event-free (EFS) and overall survival (OS) for IHG was 53.13% (95% CI: 35.52 -79.47) and 90.91% (95%CI: 79.66-100.00) vs. 0.0% and 16.67% (95% CI: 2.78-99.74%) for HGG (p= 0.0043, 0.00013). EFS and OS were not different between IHG and LGG (p=0.95, 0.43). Imaging review of HGG, LGG , IHG and Other CNS tumors showed that IHGs are associated with circumscribed margins (p=0.0047), hemispheric location (p=0.0010), and hemorrhage (p=0.0149). CONCLUSIONS HGG in young children is not a single-entity and is best defined by an integrated histopathological and molecular diagnosis. While patients with IHGs display good survival, as compared to other pediatric HGGs, they still suffer severe treatment-related morbidities. Therefore, prompt consideration for reduced adjuvant and molecularly targeted therapies is warranted.
    Type of Medium: Online Resource
    ISSN: 1522-8517 , 1523-5866
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
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  • 6
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 80, No. 16_Supplement ( 2020-08-15), p. 6149-6149
    Abstract: Despite making significant advances over the past 25 years in our understanding of the most common adult solid tumors, much less is known about childhood solid tumors. We have previously described a protocol to produce orthotopic patient-derived xenografts (O-PDX) at diagnosis, recurrence and autopsy. These O-PDX models provide both in vivo and in vitro systems to study mechanisms of disease origin, tumor progression and preclinical testing. Here, we present an innovative cloud-based all-in-one data portal to explore various biological features of these pediatric O-PDX models. The vast diversity of the collected childhood solid tumors is represented in 166 O-PDX models, consisting of 21 diagnoses including Neuroblastoma, Osteosarcoma, Rhabdomyosarcoma, and a large number of rare solid tumors including Ewing Sarcoma, Desmoplastic Small Cell Round Tumor, Fibrosarcoma, High Grade Sarcoma, Liposarcoma, Retinoblastoma, Rhabdoid Tumor and Synovial Sarcoma. The O-PDX models have been characterized and compared to the original patient tumor using various methods and assays including histology, electron microscopy, short tandem repeat DNA profiling, chemical compound screening as well as genomic sequencing (whole genome sequencing, whole exome sequencing, and RNA Sequencing) and clonal analysis to determine the clonal population in the O-PDX. Somatic genetic mutations as well as clonal architecture is retained in the majority of O-PDX tumors. The data on O-PDX models can now be visualized and compared in our web-based CSTN data portal on St Jude Cloud (www.stjude.cloud). The user-friendly interface allows both gene and sample level search and visualization. For genomics variations, the presence or absence of a particular variant can be observed through interactive heatmaps. In addition to genomic and transcriptomic profiles, some of these models have extensive epigenomic and proteomic profiling which are integrated into the portal. We have also included chemical sensitivity heatmaps and dose response curves for common oncology drugs using primary cultures of the O-PDXs and cell lines. Importantly, the raw genomics sequencing data is also available from St Jude Cloud, following a straightforward application and approval process for access. In summary, the integration of data from multi-omics and beyond at the CSTN data portal provides a rich resource for both academic and industrial research community to find the appropriate models to advance the knowledge and therapeutic solutions to the catastrophic childhood solid tumors. *co-first #co-corresponding Citation Format: Asa Karlstrom, Ti-Cheng Chang, Darrell Gentry, Xin Zhou, Elizabeth Stewart, Brittney Gordon, Sara M. Federico, Rachel Brennan, Michael R. Clay, Sharon Frase, Armita Bahrami, Xiang Chen, Anang A. Shelat, Nathaniel R. Twarog, Daniel Alford, Anthony Woodard, Edgar Sioson, Irina McGuire, Cynthia Williams, Nedra Robison, Brandon McMahan, Ashok K. Boddu, Swapnali Mohite, Kirby Birch, Clay McLeod, Michael Rusch, Alberto Pappo, Keith Perry, Gang Wu, Ed Suh, Michael A. Dyer. An innovative integrated cloud-based data portal for orthotopic patient-derived xenografts (O-PDX) available through the Childhood Solid Tumor Network (CSTN) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6149.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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  • 7
    In: Acta Neuropathologica, Springer Science and Business Media LLC, Vol. 144, No. 4 ( 2022-10), p. 733-746
    Type of Medium: Online Resource
    ISSN: 0001-6322 , 1432-0533
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 1458410-4
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  • 8
    In: Blood, American Society of Hematology, Vol. 135, No. 1 ( 2020-01-2), p. 41-55
    Abstract: Li and colleagues report the genomic landscape of over 100 patients with relapsed acute lymphoblastic leukemia. Analysis of diagnosis-relapse-remission trios suggest that whereas early relapse is mediated by retained subclones, late relapse is driven by mutations induced by and conferring resistance to chemotherapy.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2020
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    detail.hit.zdb_id: 80069-7
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  • 9
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 3671-3671
    Abstract: Whole-genome sequencing (WGS) is invaluable for investigating genetic abnormalities contributing to the initiation, progression and long-term clinical outcome of pediatric cancer. St. Jude Cloud (https://www.stjude.cloud/) hosts 10,000 (10K) harmonized WGS samples generated from: 1) St. Jude/Washington University Pediatric Cancer Genome Project, 2) the Genomes for Kids Clinical Trial, 3) the St. Jude Lifetime Cohort Study, and 4) the Childhood Cancer Survivor Study. To enable on-the-cloud discovery and eliminate the need for data download, we developed GenomePaint, an interactive genomics browser, to explore the somatic and germline variants of the 10K genomes with rich annotation. Germline variants in cancer predisposition genes were annotated for pathogenicity. Using GenomePaint, users can compare pathogenic variants from a locus of interest across multiple cancers or test for association of a germline variant with a specific cancer type on the fly. By matching germline variants to somatic mutation hotspots from www.cancerhotspots.org, we annotated potential germline mosaic mutations including IDH1 R132H, FBXW7 R465C, and KRAS A146T. For noncoding variants, we investigated overlap with ATAC and DNase peaks in 50 cancer cell lines along with transcription factor motif change predictions. These features will enable exploration of the functional impact of genetic variations with potential clinical status such as genetic risk for a specific cancer type, genetic association with age of onset, or development of subsequent malignancies for pediatric cancer survivors. GenomePaint also provides an integrated view of somatic SNV/indel, copy number variation, loss-of-heterozygosity, structural variation, and gene fusion. These are shown together with tumor gene expression at the single tumor level. GenomePaint also presents allele-specific expression (ASE) and outlier expression as an indicator for assessing dysfunction of regulatory regions caused by genomic variants. Cloud-based on-the-fly ASE analysis is also available for user’s samples with paired DNA and RNA sequencing results. Such gene expression integration will drive novel insights about the functional aspects of somatic coding and noncoding mutations in pediatric cancer. The innovative visualization of whole-genome sequencing data generated from 10K pediatric cancer patients on the St. Jude Cloud enables genomic discovery by scientists and clinicians through exploration of this unprecedented resource. Citation Format: Xin Zhou, Clay Mcleod, Scott Newman, Zhaoming Wang, Michael Rusch, Kirby Birch, Michael Macias, Jobin Sunny, Gang Wu, Jian Wang, Edgar Sioson, Shaohua Lei, Robert J. Michael, Aman Patel, Michael N. Edmonson, Stephen V. Rice, Andrew Frantz, Ed Suh, Keith Perry, Carmen Wilson, Leslie L. Robinson, Yutaka Yasui, Kim E. Nichols, Gregory T. Armstrong, James R. Downing, Jinghui Zhang. Visualize 10,000 whole-genomes from pediatric cancer patients on St. Jude Cloud [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3671.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
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    detail.hit.zdb_id: 410466-3
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  • 10
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 80, No. 16_Supplement ( 2020-08-15), p. 1198-1198
    Abstract: Clinical and basic research addressing the long-term outcomes of the increasing and high-risk population of pediatric cancer survivors requires large cohorts with high quality information. We have assembled the largest group of pediatric cancer survivors to date with comprehensive clinical characterization and germline whole-genome sequencing (WGS), and made these data available through the Survivorship Portal on St. Jude Cloud (https://survivorship.stjude.cloud). The Portal contains data from 7302 survivors from two large studies, including 4402 from the St. Jude Lifetime Cohort Study (SJLIFE) with clinically-assessed outcome phenotypes, and 2900 from the Childhood Cancer Survivor Study (CCSS) with self-reported outcome phenotypes. High-quality germline variants and genotype calls from WGS were generated and curated by an in-house pipeline with corrected indel alleles and read counts. Germline variants of individual survivors are linked with standardized phenotypes described by & gt;300 variables, spanning cancer-related data including diagnosis, length of follow-up, treatment (cumulative doses of chemotherapy, region-specific radiation therapy doses, surgery), demographic characteristics, selected health behaviors, and long-term outcomes (severity-graded chronic health conditions including second cancers). In addition, clinically-relevant genetic variables including ancestry admixture, HLA alleles, leukocyte telomere length, and blood type have been computed from WGS. Both phenotypic and genetic variables are represented by the Dictionary Browser that allows to quickly identify variables of interest, view summary graphics, cross-tabulate variables by default or user-defined categories and test for association between categories. Using GenomePaint on the Portal, investigators can navigate to a locus of interest and explore the presence and frequencies of variants in the cohort, filter variants with multiple criteria including LD r2 values, and identify DNA binding motif change for non-coding variants. Combining GenomePaint with Dictionary Browser, the real-time association analysis allows to identify trait-associated variants at a locus, through the definition of traits, covariates, and inclusion/exclusion criteria using the Dictionary Browser. Future implementation includes supporting copy number and structural variations, characterization of pharmacogenetic diplotypes, gene-level rare variant analysis, polygenic scores, time-to-event survival analysis, and data download and session management enabled by user login. We envision this cohort with high quality phenotypic and genetic information, together with an enabling software platform co-developed with multidisciplinary principal investigators, will accelerate the discovery in both survivorship research and human genetics in general. Citation Format: Xin Zhou, Nickhill Bhakta, Jian Wang, Edgar Sioson, Jaimin Patel, Kyla Shelton, Zhaoming Wang, Shaohua Lei, Alexander M. Gout, Carmen L. Wilson, Wendy Leisenring, Smita Bhatia, Yutaka Yasui, Melissa M. Hudson, Gregory T. Armstrong, Leslie L. Robison, Jinghui Zhang. The St. Jude Survivorship Portal links whole-genome genetic data with clinical therapy and outcome phenotypes for 7302 pediatric cancer survivors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1198.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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