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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
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
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  • 4
    In: Blood Advances, American Society of Hematology, Vol. 5, No. 14 ( 2021-07-27), p. 2839-2851
    Abstract: Individuals with monogenic disorders can experience variable phenotypes that are influenced by genetic variation. To investigate this in sickle cell disease (SCD), we performed whole-genome sequencing (WGS) of 722 individuals with hemoglobin HbSS or HbSβ0-thalassemia from Baylor College of Medicine and from the St. Jude Children’s Research Hospital Sickle Cell Clinical Research and Intervention Program (SCCRIP) longitudinal cohort study. We developed pipelines to identify genetic variants that modulate sickle hemoglobin polymerization in red blood cells and combined these with pain-associated variants to build a polygenic score (PGS) for acute vaso-occlusive pain (VOP). Overall, we interrogated the α-thalassemia deletion −α3.7 and 133 candidate single-nucleotide polymorphisms (SNPs) across 66 genes for associations with VOP in 327 SCCRIP participants followed longitudinally over 6 years. Twenty-one SNPs in 9 loci were associated with VOP, including 3 (BCL11A, MYB, and the β-like globin gene cluster) that regulate erythrocyte fetal hemoglobin (HbF) levels and 6 (COMT, TBC1D1, KCNJ6, FAAH, NR3C1, and IL1A) that were associated previously with various pain syndromes. An unweighted PGS integrating all 21 SNPs was associated with the VOP event rate (estimate, 0.35; standard error, 0.04; P = 5.9 × 10−14) and VOP event occurrence (estimate, 0.42; standard error, 0.06; P = 4.1 × 10−13). These associations were stronger than those of any single locus. Our findings provide insights into the genetic modulation of VOP in children with SCD. More generally, we demonstrate the utility of WGS for investigating genetic contributions to the variable expression of SCD-associated morbidities.
    Type of Medium: Online Resource
    ISSN: 2473-9529 , 2473-9537
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2021
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  • 5
    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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  • 6
    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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  • 7
    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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  • 8
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 922-922
    Abstract: While whole-genome (WGS), whole-exome (WES), and RNA-Seq data of patient samples are key resources for the development of precision medicine, major computing infrastructure is typically required to use them effectively. The St Jude Cloud (SJCloud, https://stjude.cloud), built in collaboration with DNAnexus and Microsoft, aims to remove this barrier by sharing genomic sequencing data generated at St Jude Children's Research Hospital, making complex bioinformatics pipelines easily accessible, and providing intuitive visualizations for data mining in the cloud. Over 5000 WGS, 6000 WES and 1500 RNA-Seq from & gt;5,000 pediatric cancer patients mapped to the latest reference genome are securely available in SJCloud. These data were generated from three St Jude-funded genomic initiatives: the Pediatric Cancer Genome Project (PCGP), the St Jude Life Genome Project, and the Genomes for Kids Clinical Trial. SJCloud hosts BAM files, coding and non-coding somatic and germline SNVs and indels, copy number (CNV) and structural alterations (SV). Non-identifiable data (e.g. somatic alterations, genotype frequency, cancer diagnosis and demographics) can be viewed immediately using our interactive genome browser, while raw data and individual genotype access requires a simple online approval. Data synchronization and visualization enables novel discoveries by non-bioinformaticians. For example, a genomic view of the TERT locus shows enrichment of CNVs and SVs in neuroblastoma (NBL), consistent with reports of activation via rearrangement. The same view also shows a somatic promoter mutation, C228T, in one NBL; such mutations have not been reported in primary samples to our knowledge. This integrated view across somatic mutation types enables evaluation of the diverse genetic mechanisms deregulating cancer genes. SJCloud also facilitates data re-analysis. We ported the “MutationalPatterns” R package (Blokzijl et al. 2017) to the cloud to elucidate major mutational signatures in & gt;500,000 PCGP WGS somatic variants. Inclusion of non-coding mutations was critical as the low number of exonic mutations in some pediatric cancers is insufficient for robust analysis. A surprising finding was a signature consistent with ultraviolet-induced DNA damage in a subset of B-acute lymphoblastic leukemia. End-to-end workflows to detect gene fusions, predict neoepitopes, classify mutations, process ChIP-seq, and identify differentially expressed genes are also freely accessible. By integrating analytic tools with the world's largest set of pediatric genomics data, SJCloud enables data sharing and mining, innovative genomic analysis, and development of new analytic methods. We anticipate that in 2019 we will host data from over 10,000 pediatric cancer patients, and we are actively exploring approaches to make this a federated data repository capable of interchange with the global pediatric cancer research community. Citation Format: Scott Newman, Xin Zhou, Clay McLeod, Michael Rusch, Gang Wu, Edgar Sioson, Shuoguo Wang, J. Robert Michael, Aman Patel, Michael N. Edmonson, Andrew Frantz, Ti-Cheng Chang, Yongjin Li, Robert I. Davidson, Singer Ma, Irina McGuire, Nedra Robison, Xing Tang, Lance Palmer, Ed Suh, Leigh Tanner, James McMurry, Keith Perry, Zhaoming Wang, Carmen Wilson, Yong Cheng, Mitch Weiss, Leslie L. Robison, Yutaka Yasui, Kim E. Nichols, David W. Ellison, James R. Downing, Jinghui Zhang. Access, visualize and analyze 5,000 whole-genomes from pediatric cancer patients on St. Jude Cloud [abstract]. In: Proceedings of the Amer ican Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 922.
    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: 2018
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  • 9
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 2872-2872
    Abstract: Acute lymphoblastic leukemia (ALL) is a leading cause of cancer-associated death in children. To study the mechanisms of drug resistance in ALL, we performed whole-genome sequencing of diagnosis-relapse-germline trios from 103 Chinese patients and ultra-deep sequencing of 208 serial bone marrow samples from 17 of them. Relapse-specific somatic alterations were enriched in 12 genes (NR3C1, NR3C2, TP53, NT5C2, FPGS, CREBBP, MSH2, MSH6, PMS2, WHSC1, PRPS1, and PRPS2), which were predominantly involved in response to thiopurines, glucocorticoids, methotrexate, and other drugs. Four lines of evidence indicate that these resistance mutations frequently developed during treatment, rather than pre-existing at diagnosis. First, two novel, relapse-specific mutational signatures (novel signatures 1 and 2), most likely caused by chemotherapeutic regimens, were detected in 15% and 14% of relapsed cases, respectively. Drug resistance mutations frequently appeared at novel signature-associated trinucleotide contexts, indicating that chemotherapy may directly cause drug resistance mutations in ALL. The signatures were validated in NCI TARGET relapsed ALL samples, 2% and 23% of which harbored novel signatures 1 and 2, respectively. The varying signature prevalence between cohorts may reflect treatment differences. The novel signatures were not detected in & gt;2,000 adult cancers from the PCAWG study. Novel signature 1 induced C & gt;G transversions, particularly at GCC and TCT trinucleotides, and showed transcription-strand bias indicating guanine adducts. Novel signature 2 favored C & gt;T and C & gt;G mutations at CCG, and correlated with relapse-specific dinucleotide variants and structural variants, indicating an agent causing multiple mutation types. The drugs inducing these novel signatures are being explored in vitro. Second, mathematical modeling using growth curves of drug-resistant ALL indicated that drug resistance mutations occur, in some cases, long after diagnosis, during active treatment. Third, some patients acquired multiple drug resistance mutations sequentially through successive relapses, a finding inconsistent with their pre-existence at diagnosis. Indeed, 20% of relapses had multiple drug resistance mutations targeting different drug classes. Fourth, most relapsed ALLs derived from a subclone detected at diagnosis, which then evolved additional mutations, including drug resistance mutations, not detectable at diagnosis using 2000X targeted sequencing. Drug resistance mutations were often subclonal at relapse, suggesting later appearance. Together these data indicate that fully drug-resistant clones may not necessarily pre-exist at diagnosis in ALL, but may be acquired later during treatment. Thus, early intensive or targeted treatment strategies in slow responders may forestall the subsequent development of drug resistance mutations. Citation Format: Benshang Li, Samuel W. Brady, Xiaotu Ma, Shuhong Shen, Yingchi Zhang, Yongjin Li, Yu Liu, Ningling Wang, Diane Flasch, Matthew Myers, Heather Mulder, Lixia Ding, Yanling Lu, Liqing Tian, Kohei Hagiwara, Ke Xu, Edgar Sioson, Tianyi Wang, Liu Yang, Jie Zhao, Hui Zhang, Ying Shao, Hongye Sun, Lele Sun, Jiaoyang Cai, Ting-Nien Lin, Lijuan Du, Fan Yang, Michael Rusch, Michael Edmonson, John Easton, Xiaofan Zhu, Jingliao Zhang, Cheng Cheng, Benjamin Raphael, Jingyan Tang, James Downing, Bin-Bing Zhou, Ching-Hon Pui, Jun Yang, Jinghui Zhang. Acquisition of drug resistance mutations during chemotherapy treatment in pediatric acute lymphoblastic leukemia [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 2872.
    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: 2019
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  • 10
    In: Nature Genetics, Springer Science and Business Media LLC, Vol. 54, No. 9 ( 2022-09), p. 1376-1389
    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: 2022
    detail.hit.zdb_id: 1494946-5
    SSG: 12
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