190 results on '"Michael Rusch"'
Search Results
2. NetBID2 provides comprehensive hidden driver analysis
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Xinran Dong, Liang Ding, Andrew Thrasher, Xinge Wang, Jingjing Liu, Qingfei Pan, Jordan Rash, Yogesh Dhungana, Xu Yang, Isabel Risch, Yuxin Li, Lei Yan, Michael Rusch, Clay McLeod, Koon-Kiu Yan, Junmin Peng, Hongbo Chi, Jinghui Zhang, and Jiyang Yu
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Science - Abstract
Abstract Many signaling and other genes known as “hidden” drivers may not be genetically or epigenetically altered or differentially expressed at the mRNA or protein levels, but, rather, drive a phenotype such as tumorigenesis via post-translational modification or other mechanisms. However, conventional approaches based on genomics or differential expression are limited in exposing such hidden drivers. Here, we present a comprehensive algorithm and toolkit NetBID2 (data-driven network-based Bayesian inference of drivers, version 2), which reverse-engineers context-specific interactomes and integrates network activity inferred from large-scale multi-omics data, empowering the identification of hidden drivers that could not be detected by traditional analyses. NetBID2 has substantially re-engineered the previous prototype version by providing versatile data visualization and sophisticated statistical analyses, which strongly facilitate researchers for result interpretation through end-to-end multi-omics data analysis. We demonstrate the power of NetBID2 using three hidden driver examples. We deploy NetBID2 Viewer, Runner, and Cloud apps with 145 context-specific gene regulatory and signaling networks across normal tissues and paediatric and adult cancers to facilitate end-to-end analysis, real-time interactive visualization and cloud-based data sharing. NetBID2 is freely available at https://jyyulab.github.io/NetBID .
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- 2023
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3. The landscape of coding RNA editing events in pediatric cancer
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Ji Wen, Michael Rusch, Samuel W. Brady, Ying Shao, Michael N. Edmonson, Timothy I. Shaw, Brent B. Powers, Liqing Tian, John Easton, Charles G. Mullighan, Tanja Gruber, David Ellison, and Jinghui Zhang
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RNA editing ,Pediatric cancer ,Genomics ,Immunotherapy ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Abstract Background RNA editing leads to post-transcriptional variation in protein sequences and has important biological implications. We sought to elucidate the landscape of RNA editing events across pediatric cancers. Methods Using RNA-Seq data mapped by a pipeline designed to minimize mapping ambiguity, we investigated RNA editing in 711 pediatric cancers from the St. Jude/Washington University Pediatric Cancer Genome Project focusing on coding variants which can potentially increase protein sequence diversity. We combined de novo detection using paired tumor DNA-RNA data with analysis of known RNA editing sites. Results We identified 722 unique RNA editing sites in coding regions across pediatric cancers, 70% of which were nonsynonymous recoding variants. Nearly all editing sites represented the canonical A-to-I (n = 706) or C-to-U sites (n = 14). RNA editing was enriched in brain tumors compared to other cancers, including editing of glutamate receptors and ion channels involved in neurotransmitter signaling. RNA editing profiles of each pediatric cancer subtype resembled those of the corresponding normal tissue profiled by the Genotype-Tissue Expression (GTEx) project. Conclusions In this first comprehensive analysis of RNA editing events in pediatric cancer, we found that the RNA editing profile of each cancer subtype is similar to its normal tissue of origin. Tumor-specific RNA editing events were not identified indicating that successful immunotherapeutic targeting of RNA-edited peptides in pediatric cancer should rely on increased antigen presentation on tumor cells compared to normal but not on tumor-specific RNA editing per se.
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- 2021
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4. Pan-neuroblastoma analysis reveals age- and signature-associated driver alterations
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Samuel W. Brady, Yanling Liu, Xiaotu Ma, Alexander M. Gout, Kohei Hagiwara, Xin Zhou, Jian Wang, Michael Macias, Xiaolong Chen, John Easton, Heather L. Mulder, Michael Rusch, Lu Wang, Joy Nakitandwe, Shaohua Lei, Eric M. Davis, Arlene Naranjo, Cheng Cheng, John M. Maris, James R. Downing, Nai-Kong V. Cheung, Michael D. Hogarty, Michael A. Dyer, and Jinghui Zhang
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Science - Abstract
Genomic analysis of neuroblastoma has revealed important disease etiology. In this study, the authors assembled whole genome, exome and transcriptome data from over 700 neuroblastomas and identified molecular signatures correlated with age, and rare, potentially targetable variants overlooked in smaller cohorts.
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- 2020
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5. Clinical cancer genomic profiling by three-platform sequencing of whole genome, whole exome and transcriptome
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Michael Rusch, Joy Nakitandwe, Sheila Shurtleff, Scott Newman, Zhaojie Zhang, Michael N. Edmonson, Matthew Parker, Yuannian Jiao, Xiaotu Ma, Yanling Liu, Jiali Gu, Michael F. Walsh, Jared Becksfort, Andrew Thrasher, Yongjin Li, James McMurry, Erin Hedlund, Aman Patel, John Easton, Donald Yergeau, Bhavin Vadodaria, Ruth G. Tatevossian, Susana Raimondi, Dale Hedges, Xiang Chen, Kohei Hagiwara, Rose McGee, Giles W. Robinson, Jeffery M. Klco, Tanja A. Gruber, David W. Ellison, James R Downing, and Jinghui Zhang
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Science - Abstract
Clinical oncology is rapidly adopting next-generation sequencing technology for nucleotide variant and indel detection. Here the authors present a three-platform approach (whole-genome, whole-exome, and whole-transcriptome) in pediatric patients for the detection of diverse types of germline and somatic variants.
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- 2018
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6. Cancer-associated DDX3X mutations drive stress granule assembly and impair global translation
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Yasmine A. Valentin-Vega, Yong-Dong Wang, Matthew Parker, Deanna M. Patmore, Anderson Kanagaraj, Jennifer Moore, Michael Rusch, David Finkelstein, David W. Ellison, Richard J. Gilbertson, Jinghui Zhang, Hong Joo Kim, and J. Paul Taylor
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Medicine ,Science - Abstract
Abstract DDX3X is a DEAD-box RNA helicase that has been implicated in multiple aspects of RNA metabolism including translation initiation and the assembly of stress granules (SGs). Recent genomic studies have reported recurrent DDX3X mutations in numerous tumors including medulloblastoma (MB), but the physiological impact of these mutations is poorly understood. Here we show that a consistent feature of MB-associated mutations is SG hyper-assembly and concomitant translation impairment. We used CLIP-seq to obtain a comprehensive assessment of DDX3X binding targets and ribosome profiling for high-resolution assessment of global translation. Surprisingly, mutant DDX3X expression caused broad inhibition of translation that impacted DDX3X targeted and non-targeted mRNAs alike. Assessment of translation efficiency with single-cell resolution revealed that SG hyper-assembly correlated precisely with impaired global translation. SG hyper-assembly and translation impairment driven by mutant DDX3X were rescued by a genetic approach that limited SG assembly and by deletion of the N-terminal low complexity domain within DDX3X. Thus, in addition to a primary defect at the level of translation initiation caused by DDX3X mutation, SG assembly itself contributes to global translation inhibition. This work provides mechanistic insights into the consequences of cancer-related DDX3X mutations, suggesting that globally reduced translation may provide a context-dependent survival advantage that must be considered as a possible contributor to tumorigenesis.
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- 2016
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7. Recurrent Somatic Structural Variations Contribute to Tumorigenesis in Pediatric Osteosarcoma
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Xiang Chen, Armita Bahrami, Alberto Pappo, John Easton, James Dalton, Erin Hedlund, David Ellison, Sheila Shurtleff, Gang Wu, Lei Wei, Matthew Parker, Michael Rusch, Panduka Nagahawatte, Jianrong Wu, Shenghua Mao, Kristy Boggs, Heather Mulder, Donald Yergeau, Charles Lu, Li Ding, Michael Edmonson, Chunxu Qu, Jianmin Wang, Yongjin Li, Fariba Navid, Najat C. Daw, Elaine R. Mardis, Richard K. Wilson, James R. Downing, Jinghui Zhang, and Michael A. Dyer
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Biology (General) ,QH301-705.5 - Abstract
Pediatric osteosarcoma is characterized by multiple somatic chromosomal lesions, including structural variations (SVs) and copy number alterations (CNAs). To define the landscape of somatic mutations in pediatric osteosarcoma, we performed whole-genome sequencing of DNA from 20 osteosarcoma tumor samples and matched normal tissue in a discovery cohort, as well as 14 samples in a validation cohort. Single-nucleotide variations (SNVs) exhibited a pattern of localized hypermutation called kataegis in 50% of the tumors. We identified p53 pathway lesions in all tumors in the discovery cohort, nine of which were translocations in the first intron of the TP53 gene. Beyond TP53, the RB1, ATRX, and DLG2 genes showed recurrent somatic alterations in 29%–53% of the tumors. These data highlight the power of whole-genome sequencing for identifying recurrent somatic alterations in cancer genomes that may be missed using other methods.
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- 2014
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8. RNAIndel: discovering somatic coding indels from tumor RNA-Seq data.
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Kohei Hagiwara, Liang Ding, Michael N. Edmonson, Stephen V. Rice, Scott Newman, John Easton, Juncheng Dai, Soheil Meshinchi, Rhonda E. Ries, Michael Rusch, and Jinghui Zhang
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- 2020
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9. Pan-cancer genome and transcriptome analyses of 1, 699 paediatric leukaemias and solid tumours.
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Xiaotu Ma, Yu Liu, Yanling Liu, Ludmil B. Alexandrov, Michael N. Edmonson, Charles Gawad, Xin Zhou, Yongjin Li, Michael Rusch, John Easton, Robert Huether, Veronica Gonzalez-Pena, Mark R. Wilkinson, Leandro Hermida, Sean Davis, Edgar Sioson, Stanley Pounds, Xueyuan Cao, Rhonda E. Ries, Zhaoming Wang, Xiang Chen, Li Dong, Sharon J. Diskin, Malcolm A. Smith, Jaime M. Guidry Auvil, Paul S. Meltzer, Ching C. Lau, Elizabeth J. Perlman, John M. Maris, Soheil Meshinchi, Stephen P. Hunger, Daniela S. Gerhard, and Jinghui Zhang
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- 2018
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10. Proposal of a new genomic framework for categorization of pediatric acute myeloid leukemia associated with prognosis
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Masayuki Umeda, Jing Ma, Tamara Westover, Yonghui Ni, Guangchun Song, Jamie Maciaszek, Michael Rusch, Delaram Rahbarinia, Scott Foy, Benjamin Huang, Michael Walsh, Priyadarshini Kumar, Yanling Liu, Yiping Fan, Gang Wu, Sharyn Baker, Xiaotu Ma, Lu Wang, Jeffrey rubnitz, Stanley Pounds, and Jeffery Klco
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Recent studies on pediatric acute myeloid leukemia (pAML) have revealed pediatric-specific driver alterations, many of which are underrepresented in the current classification schemas. To comprehensively define the genomic landscape of pAML, we systematically categorized 895 pAML into 23 molecular categories that are mutually distinct from one another, including new entities such as UBTF or BCL11B, covering 91.4% of the cohort. These molecular categories were associated with unique expression profiles and mutational patterns. For instance, molecular categories characterized by specific HOXA or HOXB expression signatures showed distinct mutation patterns of RAS pathway genes, FLT3, or WT1, suggesting shared biological mechanisms. We show that molecular categories were strongly associated with clinical outcomes using two independent cohorts, leading to the establishment of a prognostic framework for pAML based on molecular categories and minimal residual disease. Together, this comprehensive diagnostic and prognostic framework forms the basis for future classification of pAML and treatment strategies.
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- 2023
11. Data from Integrated Genomic Analysis Identifies UBTF Tandem Duplications as a Recurrent Lesion in Pediatric Acute Myeloid Leukemia
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Jeffery M. Klco, Xiaotu Ma, Soheil Meshinchi, Jeffrey E. Rubnitz, Jinghui Zhang, M. Madan Babu, Stanley Pounds, Charles G. Mullighan, James R. Downing, Todd A. Alonzo, Yi-Cheng Wang, Hiroto Inaba, Gang Wu, Michael Rusch, Delaram Rahbarinia, Evadnie Rampersaud, Jason R. Myers, Jonathan Miller, Ryan Hiltenbrand, Ilaria Iacobucci, Evan Parganas, Jenny L. Smith, Rhonda E. Ries, Yen-Chun Liu, Marcus B. Valentine, Virginia Valentine, Huiyun Wu, John Easton, Bengsheng Ju, Amanda R. Leonti, Andrew B. Kleist, Jamie L. Maciaszek, Scott G. Foy, Quang Tran, Pandurang Kolekar, Xiaolong Chen, Yanling Liu, Liqing Tian, Guangchun Song, Michael P. Walsh, Melvin E. Thomas, Juan M. Barajas, Sherif Abdelhamed, Tamara Westover, Kohei Hagiwara, Benjamin J. Huang, Jing Ma, and Masayuki Umeda
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The genetics of relapsed pediatric acute myeloid leukemia (AML) has yet to be comprehensively defined. Here, we present the spectrum of genomic alterations in 136 relapsed pediatric AMLs. We identified recurrent exon 13 tandem duplications (TD) in upstream binding transcription factor (UBTF) in 9% of relapsed AML cases. UBTF-TD AMLs commonly have normal karyotype or trisomy 8 with cooccurring WT1 mutations or FLT3-ITD but not other known oncogenic fusions. These UBTF-TD events are stable during disease progression and are present in the founding clone. In addition, we observed that UBTF-TD AMLs account for approximately 4% of all de novo pediatric AMLs, are less common in adults, and are associated with poor outcomes and MRD positivity. Expression of UBTF-TD in primary hematopoietic cells is sufficient to enhance serial clonogenic activity and to drive a similar transcriptional program to UBTF-TD AMLs. Collectively, these clinical, genomic, and functional data establish UBTF-TD as a new recurrent mutation in AML.Significance:We defined the spectrum of mutations in relapsed pediatric AML and identified UBTF-TDs as a new recurrent genetic alteration. These duplications are more common in children and define a group of AMLs with intermediate-risk cytogenetic abnormalities, FLT3-ITD and WT1 alterations, and are associated with poor outcomes.See related commentary by Hasserjian and Nardi, p. 173.This article is highlighted in the In This Issue feature, p. 171.
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- 2023
12. Supplementary Data from Integrated Genomic Analysis Identifies UBTF Tandem Duplications as a Recurrent Lesion in Pediatric Acute Myeloid Leukemia
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Jeffery M. Klco, Xiaotu Ma, Soheil Meshinchi, Jeffrey E. Rubnitz, Jinghui Zhang, M. Madan Babu, Stanley Pounds, Charles G. Mullighan, James R. Downing, Todd A. Alonzo, Yi-Cheng Wang, Hiroto Inaba, Gang Wu, Michael Rusch, Delaram Rahbarinia, Evadnie Rampersaud, Jason R. Myers, Jonathan Miller, Ryan Hiltenbrand, Ilaria Iacobucci, Evan Parganas, Jenny L. Smith, Rhonda E. Ries, Yen-Chun Liu, Marcus B. Valentine, Virginia Valentine, Huiyun Wu, John Easton, Bengsheng Ju, Amanda R. Leonti, Andrew B. Kleist, Jamie L. Maciaszek, Scott G. Foy, Quang Tran, Pandurang Kolekar, Xiaolong Chen, Yanling Liu, Liqing Tian, Guangchun Song, Michael P. Walsh, Melvin E. Thomas, Juan M. Barajas, Sherif Abdelhamed, Tamara Westover, Kohei Hagiwara, Benjamin J. Huang, Jing Ma, and Masayuki Umeda
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Supplementary Data from Integrated Genomic Analysis Identifies UBTF Tandem Duplications as a Recurrent Lesion in Pediatric Acute Myeloid Leukemia
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- 2023
13. Supplementary Figure from Integrated Genomic Analysis Identifies UBTF Tandem Duplications as a Recurrent Lesion in Pediatric Acute Myeloid Leukemia
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Jeffery M. Klco, Xiaotu Ma, Soheil Meshinchi, Jeffrey E. Rubnitz, Jinghui Zhang, M. Madan Babu, Stanley Pounds, Charles G. Mullighan, James R. Downing, Todd A. Alonzo, Yi-Cheng Wang, Hiroto Inaba, Gang Wu, Michael Rusch, Delaram Rahbarinia, Evadnie Rampersaud, Jason R. Myers, Jonathan Miller, Ryan Hiltenbrand, Ilaria Iacobucci, Evan Parganas, Jenny L. Smith, Rhonda E. Ries, Yen-Chun Liu, Marcus B. Valentine, Virginia Valentine, Huiyun Wu, John Easton, Bengsheng Ju, Amanda R. Leonti, Andrew B. Kleist, Jamie L. Maciaszek, Scott G. Foy, Quang Tran, Pandurang Kolekar, Xiaolong Chen, Yanling Liu, Liqing Tian, Guangchun Song, Michael P. Walsh, Melvin E. Thomas, Juan M. Barajas, Sherif Abdelhamed, Tamara Westover, Kohei Hagiwara, Benjamin J. Huang, Jing Ma, and Masayuki Umeda
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Supplementary Figure from Integrated Genomic Analysis Identifies UBTF Tandem Duplications as a Recurrent Lesion in Pediatric Acute Myeloid Leukemia
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- 2023
14. Supplementary Figure S4 from Genomes for Kids: The Scope of Pathogenic Mutations in Pediatric Cancer Revealed by Comprehensive DNA and RNA Sequencing
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Kim E. Nichols, Jinghui Zhang, James R. Downing, David W. Ellison, Ching-Hon Pui, Liza-Marie Johnson, Giles Robinson, Alberto S. Pappo, Stacy J. Hines-Dowell, Jessica M. Valdez, Leslie M. Taylor, Elsie L. Gerhardt, Roya Mostafavi, Regina Nuccio, Emily A. Quinn, Rose B. McGee, Charles G. Mullighan, Zhaohui Gu, Jian Wang, Alexander M. Gout, Jay Knight, Victor Pastor, Jamie L. Maciaszek, Manish Kubal, Delaram Rahbarinia, Mark R. Wilkinson, Aman Patel, Jared Becksfort, Eric Davis, Manjusha Pande, Ti-Cheng Chang, Xin Zhou, Samuel W. Brady, Yu Liu, Zhaojie Zhang, Yanling Liu, Antonina Silkov, Annastasia Ouma, Michael R. Clay, Lu Wang, Lynn W. Harrison, Jiali Gu, Jeffery M. Klco, Brent A. Orr, Armita Bahrami, Andrew Thrasher, Michael N. Edmonson, Scott G. Foy, Kayla V. Hamilton, Dale J. Hedges, Sheila Shurtleff, Michael Rusch, David A. Wheeler, Elizabeth M. Azzato, Chimene A. Kesserwan, Joy Nakitandwe, and Scott Newman
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Supplementary Figure S4
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- 2023
15. Supplementary Table S3 from Relapse-Fated Latent Diagnosis Subclones in Acute B Lineage Leukemia Are Drug Tolerant and Possess Distinct Metabolic Programs
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John E. Dick, Charles G. Mullighan, Quaid Morris, Mark D. Minden, Jinghui Zhang, Jayne S. Danska, Cynthia J. Guidos, John Easton, Gary Bader, Steven M. Chan, Geoffrey Neale, Scott R. Olsen, Ying Shao, Michael Rusch, Pankaj Gupta, Sagi Abelson, Mohsen Hosseini, Stephanie Z. Xie, Michelle Chan-Seng-Yue, Veronique Voisin, Yiping Fan, Xiaotu Ma, Michael N. Edmonson, Debbie Payne-Turner, Ildiko Grandal, Olga I. Gan, Jessica McLeod, Zhaohui Gu, Esmé Waanders, Jeffrey Wintersinger, Robert J. Vanner, Laura García-Prat, and Stephanie M. Dobson
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Targeted-sequencing analysis of PDX and PairTree predicted mutational population clusters
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- 2023
16. Data from Genomes for Kids: The Scope of Pathogenic Mutations in Pediatric Cancer Revealed by Comprehensive DNA and RNA Sequencing
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Kim E. Nichols, Jinghui Zhang, James R. Downing, David W. Ellison, Ching-Hon Pui, Liza-Marie Johnson, Giles Robinson, Alberto S. Pappo, Stacy J. Hines-Dowell, Jessica M. Valdez, Leslie M. Taylor, Elsie L. Gerhardt, Roya Mostafavi, Regina Nuccio, Emily A. Quinn, Rose B. McGee, Charles G. Mullighan, Zhaohui Gu, Jian Wang, Alexander M. Gout, Jay Knight, Victor Pastor, Jamie L. Maciaszek, Manish Kubal, Delaram Rahbarinia, Mark R. Wilkinson, Aman Patel, Jared Becksfort, Eric Davis, Manjusha Pande, Ti-Cheng Chang, Xin Zhou, Samuel W. Brady, Yu Liu, Zhaojie Zhang, Yanling Liu, Antonina Silkov, Annastasia Ouma, Michael R. Clay, Lu Wang, Lynn W. Harrison, Jiali Gu, Jeffery M. Klco, Brent A. Orr, Armita Bahrami, Andrew Thrasher, Michael N. Edmonson, Scott G. Foy, Kayla V. Hamilton, Dale J. Hedges, Sheila Shurtleff, Michael Rusch, David A. Wheeler, Elizabeth M. Azzato, Chimene A. Kesserwan, Joy Nakitandwe, and Scott Newman
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Genomic studies of pediatric cancer have primarily focused on specific tumor types or high-risk disease. Here, we used a three-platform sequencing approach, including whole-genome sequencing (WGS), whole-exome sequencing (WES), and RNA sequencing (RNA-seq), to examine tumor and germline genomes from 309 prospectively identified children with newly diagnosed (85%) or relapsed/refractory (15%) cancers, unselected for tumor type. Eighty-six percent of patients harbored diagnostic (53%), prognostic (57%), therapeutically relevant (25%), and/or cancer-predisposing (18%) variants. Inclusion of WGS enabled detection of activating gene fusions and enhancer hijacks (36% and 8% of tumors, respectively), small intragenic deletions (15% of tumors), and mutational signatures revealing of pathogenic variant effects. Evaluation of paired tumor–normal data revealed relevance to tumor development for 55% of pathogenic germline variants. This study demonstrates the power of a three-platform approach that incorporates WGS to interrogate and interpret the full range of genomic variants across newly diagnosed as well as relapsed/refractory pediatric cancers.Significance:Pediatric cancers are driven by diverse genomic lesions, and sequencing has proven useful in evaluating high-risk and relapsed/refractory cases. We show that combined WGS, WES, and RNA-seq of tumor and paired normal tissues enables identification and characterization of genetic drivers across the full spectrum of pediatric cancers.This article is highlighted in the In This Issue feature, p. 2945
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- 2023
17. Supplementary Table 1 from Genomic Landscape of Ewing Sarcoma Defines an Aggressive Subtype with Co-Association of STAG2 and TP53 Mutations
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Olivier Delattre, Jinghui Zhang, Michael Dyer, James Downing, Ivo Gut, Perrine Marec-Bérard, Jean Michon, Valérie Laurence, Sheila Shurtleff, Richard K. Wilson, Elaine R. Mardis, Li Ding, Marta Gut, John Easton, Bhavin Vadodaria, Pankaj Gupta, Gordon Lemmon, Sakina Zaidi, Odile Oberlin, Gaelle Pierron, Xiang Chen, Gang Wu, Erin Hedlund, Thomas Rio-Frio, Stéphanie Reynaud, Michael Rusch, Sandrine Grossetête-Lalami, Eve Lapouble, Zhaojie Zhang, Armita Bahrami, Marie Cécile Le Deley, Matthew Parker, Xiaotu Ma, Didier Surdez, and Franck Tirode
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Supplementary Table 1 describes the clinical characteristics of patients.
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- 2023
18. Data from St. Jude Cloud: A Pediatric Cancer Genomic Data-Sharing Ecosystem
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Jinghui Zhang, James R. Downing, Keith Perry, Richard Daly, Michael Rusch, Scott Newman, Geralyn Miller, Michael A. Dyer, Suzanne J. Baker, Charles G. Mullighan, Chaitanya Bangur, David W. Ellison, Kim E. Nichols, Yutaka Yasui, Leslie L. Robison, Gregory T. Armstrong, Mitchell J. Weiss, Ludmil B. Alexandrov, Soheil Meshinchi, Yong Cheng, Carmen L. Wilson, Zhaoming Wang, Alberto S. Pappo, Matthew Lear, James McMurry, Leigh Tanner, Ed Suh, Gang Wu, Lance E. Palmer, Xing Tang, Darrell Gentry, Nedra Robison, Irina McGuire, Omar Serang, Tuan Nguyen, Singer Ma, Vijay Kandali, Pamella Tater, Naina Thangaraj, Christopher Meyer, S.M. Ashiqul Islam, Shaohua Lei, Liqing Tian, Ti-Cheng Chang, Andrew M. Frantz, Mark R. Wilkinson, Michael N. Edmonson, Aman Patel, Xiaotu Ma, Yu Liu, J. Robert Michael, Shuoguo Wang, Edgar Sioson, Jian Wang, Scott Foy, Stephanie Wiggins, Andrew Swistak, Arthur Chiao, Tracy K. Ard, Bob Davidson, Madison Treadway, Brent A. Orr, Rahul Mudunuri, Jobin Sunny, David Finkelstein, Kirby Birch, Michael Macias, Samuel W. Brady, Delaram Rahbarinia, Andrew Thrasher, Xin Zhou, Alexander M. Gout, and Clay McLeod
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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 >10,000 pediatric patients with cancer and long-term survivors, and >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 >1.2 petabytes of raw genomic data from >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
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- 2023
19. Data from Relapse-Fated Latent Diagnosis Subclones in Acute B Lineage Leukemia Are Drug Tolerant and Possess Distinct Metabolic Programs
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John E. Dick, Charles G. Mullighan, Quaid Morris, Mark D. Minden, Jinghui Zhang, Jayne S. Danska, Cynthia J. Guidos, John Easton, Gary Bader, Steven M. Chan, Geoffrey Neale, Scott R. Olsen, Ying Shao, Michael Rusch, Pankaj Gupta, Sagi Abelson, Mohsen Hosseini, Stephanie Z. Xie, Michelle Chan-Seng-Yue, Veronique Voisin, Yiping Fan, Xiaotu Ma, Michael N. Edmonson, Debbie Payne-Turner, Ildiko Grandal, Olga I. Gan, Jessica McLeod, Zhaohui Gu, Esmé Waanders, Jeffrey Wintersinger, Robert J. Vanner, Laura García-Prat, and Stephanie M. Dobson
- Abstract
Disease recurrence causes significant mortality in B-progenitor acute lymphoblastic leukemia (B-ALL). Genomic analysis of matched diagnosis and relapse samples shows relapse often arising from minor diagnosis subclones. However, why therapy eradicates some subclones while others survive and progress to relapse remains obscure. Elucidation of mechanisms underlying these differing fates requires functional analysis of isolated subclones. Here, large-scale limiting dilution xenografting of diagnosis and relapse samples, combined with targeted sequencing, identified and isolated minor diagnosis subclones that initiate an evolutionary trajectory toward relapse [termed diagnosis Relapse Initiating clones (dRI)]. Compared with other diagnosis subclones, dRIs were drug-tolerant with distinct engraftment and metabolic properties. Transcriptionally, dRIs displayed enrichment for chromatin remodeling, mitochondrial metabolism, proteostasis programs, and an increase in stemness pathways. The isolation and characterization of dRI subclones reveals new avenues for eradicating dRI cells by targeting their distinct metabolic and transcriptional pathways before further evolution renders them fully therapy-resistant.Significance:Isolation and characterization of subclones from diagnosis samples of patients with B-ALL who relapsed showed that relapse-fated subclones had increased drug tolerance and distinct metabolic and survival transcriptional programs compared with other diagnosis subclones. This study provides strategies to identify and target clinically relevant subclones before further evolution toward relapse.See related video: https://vimeo.com/442838617See related article by E. Waanders et al.
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- 2023
20. Supplementary Data from St. Jude Cloud: A Pediatric Cancer Genomic Data-Sharing Ecosystem
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Jinghui Zhang, James R. Downing, Keith Perry, Richard Daly, Michael Rusch, Scott Newman, Geralyn Miller, Michael A. Dyer, Suzanne J. Baker, Charles G. Mullighan, Chaitanya Bangur, David W. Ellison, Kim E. Nichols, Yutaka Yasui, Leslie L. Robison, Gregory T. Armstrong, Mitchell J. Weiss, Ludmil B. Alexandrov, Soheil Meshinchi, Yong Cheng, Carmen L. Wilson, Zhaoming Wang, Alberto S. Pappo, Matthew Lear, James McMurry, Leigh Tanner, Ed Suh, Gang Wu, Lance E. Palmer, Xing Tang, Darrell Gentry, Nedra Robison, Irina McGuire, Omar Serang, Tuan Nguyen, Singer Ma, Vijay Kandali, Pamella Tater, Naina Thangaraj, Christopher Meyer, S.M. Ashiqul Islam, Shaohua Lei, Liqing Tian, Ti-Cheng Chang, Andrew M. Frantz, Mark R. Wilkinson, Michael N. Edmonson, Aman Patel, Xiaotu Ma, Yu Liu, J. Robert Michael, Shuoguo Wang, Edgar Sioson, Jian Wang, Scott Foy, Stephanie Wiggins, Andrew Swistak, Arthur Chiao, Tracy K. Ard, Bob Davidson, Madison Treadway, Brent A. Orr, Rahul Mudunuri, Jobin Sunny, David Finkelstein, Kirby Birch, Michael Macias, Samuel W. Brady, Delaram Rahbarinia, Andrew Thrasher, Xin Zhou, Alexander M. Gout, and Clay McLeod
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Involves Supplementary Table Legends and Supplementary Figures and associated legends
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- 2023
21. Supplementary Table 4 from Genomic Landscape of Ewing Sarcoma Defines an Aggressive Subtype with Co-Association of STAG2 and TP53 Mutations
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Olivier Delattre, Jinghui Zhang, Michael Dyer, James Downing, Ivo Gut, Perrine Marec-Bérard, Jean Michon, Valérie Laurence, Sheila Shurtleff, Richard K. Wilson, Elaine R. Mardis, Li Ding, Marta Gut, John Easton, Bhavin Vadodaria, Pankaj Gupta, Gordon Lemmon, Sakina Zaidi, Odile Oberlin, Gaelle Pierron, Xiang Chen, Gang Wu, Erin Hedlund, Thomas Rio-Frio, Stéphanie Reynaud, Michael Rusch, Sandrine Grossetête-Lalami, Eve Lapouble, Zhaojie Zhang, Armita Bahrami, Marie Cécile Le Deley, Matthew Parker, Xiaotu Ma, Didier Surdez, and Franck Tirode
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Supplementary Table 4 provides the precise description of all STAG2 mutations in Ewing sarcoma.
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- 2023
22. Supplementary Figures 1 - 5 from Genomic Landscape of Ewing Sarcoma Defines an Aggressive Subtype with Co-Association of STAG2 and TP53 Mutations
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Olivier Delattre, Jinghui Zhang, Michael Dyer, James Downing, Ivo Gut, Perrine Marec-Bérard, Jean Michon, Valérie Laurence, Sheila Shurtleff, Richard K. Wilson, Elaine R. Mardis, Li Ding, Marta Gut, John Easton, Bhavin Vadodaria, Pankaj Gupta, Gordon Lemmon, Sakina Zaidi, Odile Oberlin, Gaelle Pierron, Xiang Chen, Gang Wu, Erin Hedlund, Thomas Rio-Frio, Stéphanie Reynaud, Michael Rusch, Sandrine Grossetête-Lalami, Eve Lapouble, Zhaojie Zhang, Armita Bahrami, Marie Cécile Le Deley, Matthew Parker, Xiaotu Ma, Didier Surdez, and Franck Tirode
- Abstract
Supplementary Figure 1. Representative CIRCOS plots. Supplementary Figure 2. Scheme of copy number alterations. Indicates the copy number alterations in Ewing sarcoma. Supplementary Figure 3. Mutation spectrum in Ewing sarcoma. Indicates the proportion of each somatic base changes in Ewing sarcoma. Supplementary Figure 4. CDKN2A analysis across cell lines. RT-QPCR and western blot results in cell lines. Supplementary Figure 5. CDKN2A analysis across the extended cohort. QPCR analysis of the CDKN2A locus across the whole series of patients.
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- 2023
23. Supplementary Table 3 from Genomic Landscape of Ewing Sarcoma Defines an Aggressive Subtype with Co-Association of STAG2 and TP53 Mutations
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Olivier Delattre, Jinghui Zhang, Michael Dyer, James Downing, Ivo Gut, Perrine Marec-Bérard, Jean Michon, Valérie Laurence, Sheila Shurtleff, Richard K. Wilson, Elaine R. Mardis, Li Ding, Marta Gut, John Easton, Bhavin Vadodaria, Pankaj Gupta, Gordon Lemmon, Sakina Zaidi, Odile Oberlin, Gaelle Pierron, Xiang Chen, Gang Wu, Erin Hedlund, Thomas Rio-Frio, Stéphanie Reynaud, Michael Rusch, Sandrine Grossetête-Lalami, Eve Lapouble, Zhaojie Zhang, Armita Bahrami, Marie Cécile Le Deley, Matthew Parker, Xiaotu Ma, Didier Surdez, and Franck Tirode
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Supplementary Table 3. Analysis of the statistical significance of mutations.
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- 2023
24. Data from The Clonal Evolution of Metastatic Osteosarcoma as Shaped by Cisplatin Treatment
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Jinghui Zhang, Michael A. Dyer, Benjamin J. Raphael, Alberto S. Pappo, James R. Downing, Richard K. Wilson, Elaine R. Mardis, Xiang Chen, Ludmil B. Alexandrov, John Easton, Michael N. Edmonson, Donald A. Yergeau, Heather L. Mulder, Daniel K. Putnam, Michael Rusch, Scott Newman, Gang Wu, Gryte Satas, Armita Bahrami, Xiaotu Ma, and Samuel W. Brady
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To investigate the genomic evolution of metastatic pediatric osteosarcoma, we performed whole-genome and targeted deep sequencing on 14 osteosarcoma metastases and two primary tumors from four patients (two to eight samples per patient). All four patients harbored ancestral (truncal) somatic variants resulting in TP53 inactivation and cell-cycle aberrations, followed by divergence into relapse-specific lineages exhibiting a cisplatin-induced mutation signature. In three of the four patients, the cisplatin signature accounted for >40% of mutations detected in the metastatic samples. Mutations potentially acquired during cisplatin treatment included NF1 missense mutations of uncertain significance in two patients and a KIT G565R activating mutation in one patient. Three of four patients demonstrated widespread ploidy differences between samples from the sample patient. Single-cell seeding of metastasis was detected in most metastatic samples. Cross-seeding between metastatic sites was observed in one patient, whereas in another patient a minor clone from the primary tumor seeded both metastases analyzed. These results reveal extensive clonal heterogeneity in metastatic osteosarcoma, much of which is likely cisplatin-induced.Implications:The extent and consequences of chemotherapy-induced damage in pediatric cancers is unknown. We found that cisplatin treatment can potentially double the mutational burden in osteosarcoma, which has implications for optimizing therapy for recurrent, chemotherapy-resistant disease.
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- 2023
25. Supplementary Tables S1-S5 from The Clonal Evolution of Metastatic Osteosarcoma as Shaped by Cisplatin Treatment
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Jinghui Zhang, Michael A. Dyer, Benjamin J. Raphael, Alberto S. Pappo, James R. Downing, Richard K. Wilson, Elaine R. Mardis, Xiang Chen, Ludmil B. Alexandrov, John Easton, Michael N. Edmonson, Donald A. Yergeau, Heather L. Mulder, Daniel K. Putnam, Michael Rusch, Scott Newman, Gang Wu, Gryte Satas, Armita Bahrami, Xiaotu Ma, and Samuel W. Brady
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Osteosarcoma clinical history and capture validation sequencing data. Supplementary Table S1. Sample and treatment information for relapsed osteosarcoma patients. Supplementary Table S2. SJOS0011101 SNVs detected by capture validation and tumor purity. Supplementary Table S3. SJOS0011105 SNVs detected by capture validation and tumor purity. Supplementary Table S4. SJOS0011107 SNVs detected by capture validation and tumor purity. Supplementary Table S5. SJOS010 SNVs detected by capture validation and tumor purity.
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- 2023
26. Supplementary Table 2 from Genomic Landscape of Ewing Sarcoma Defines an Aggressive Subtype with Co-Association of STAG2 and TP53 Mutations
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Olivier Delattre, Jinghui Zhang, Michael Dyer, James Downing, Ivo Gut, Perrine Marec-Bérard, Jean Michon, Valérie Laurence, Sheila Shurtleff, Richard K. Wilson, Elaine R. Mardis, Li Ding, Marta Gut, John Easton, Bhavin Vadodaria, Pankaj Gupta, Gordon Lemmon, Sakina Zaidi, Odile Oberlin, Gaelle Pierron, Xiang Chen, Gang Wu, Erin Hedlund, Thomas Rio-Frio, Stéphanie Reynaud, Michael Rusch, Sandrine Grossetête-Lalami, Eve Lapouble, Zhaojie Zhang, Armita Bahrami, Marie Cécile Le Deley, Matthew Parker, Xiaotu Ma, Didier Surdez, and Franck Tirode
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Supplementary Table 2 provides a summary (a), list of structural variants (b), list of copy number alterations (c), list of Tier 1 single nucleotide variants (d), indels (e), and purity analyses (f).
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- 2023
27. Data from Genomic Landscape of Ewing Sarcoma Defines an Aggressive Subtype with Co-Association of STAG2 and TP53 Mutations
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Olivier Delattre, Jinghui Zhang, Michael Dyer, James Downing, Ivo Gut, Perrine Marec-Bérard, Jean Michon, Valérie Laurence, Sheila Shurtleff, Richard K. Wilson, Elaine R. Mardis, Li Ding, Marta Gut, John Easton, Bhavin Vadodaria, Pankaj Gupta, Gordon Lemmon, Sakina Zaidi, Odile Oberlin, Gaelle Pierron, Xiang Chen, Gang Wu, Erin Hedlund, Thomas Rio-Frio, Stéphanie Reynaud, Michael Rusch, Sandrine Grossetête-Lalami, Eve Lapouble, Zhaojie Zhang, Armita Bahrami, Marie Cécile Le Deley, Matthew Parker, Xiaotu Ma, Didier Surdez, and Franck Tirode
- Abstract
Ewing sarcoma is a primary bone tumor initiated by EWSR1–ETS gene fusions. To identify secondary genetic lesions that contribute to tumor progression, we performed whole-genome sequencing of 112 Ewing sarcoma samples and matched germline DNA. Overall, Ewing sarcoma tumors had relatively few single-nucleotide variants, indels, structural variants, and copy-number alterations. Apart from whole chromosome arm copy-number changes, the most common somatic mutations were detected in STAG2 (17%), CDKN2A (12%), TP53 (7%), EZH2, BCOR, and ZMYM3 (2.7% each). Strikingly, STAG2 mutations and CDKN2A deletions were mutually exclusive, as confirmed in Ewing sarcoma cell lines. In an expanded cohort of 299 patients with clinical data, we discovered that STAG2 and TP53 mutations are often concurrent and are associated with poor outcome. Finally, we detected subclonal STAG2 mutations in diagnostic tumors and expansion of STAG2-immunonegative cells in relapsed tumors as compared with matched diagnostic samples.Significance: Whole-genome sequencing reveals that the somatic mutation rate in Ewing sarcoma is low. Tumors that harbor STAG2 and TP53 mutations have a particularly dismal prognosis with current treatments and require alternative therapies. Novel drugs that target epigenetic regulators may constitute viable therapeutic strategies in a subset of patients with mutations in chromatin modifiers. Cancer Discov; 4(11); 1342–53. ©2014 AACR.This article is highlighted in the In This Issue feature, p. 1243
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- 2023
28. Supplementary Table and Figure Legends from Genomic Landscape of Ewing Sarcoma Defines an Aggressive Subtype with Co-Association of STAG2 and TP53 Mutations
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Olivier Delattre, Jinghui Zhang, Michael Dyer, James Downing, Ivo Gut, Perrine Marec-Bérard, Jean Michon, Valérie Laurence, Sheila Shurtleff, Richard K. Wilson, Elaine R. Mardis, Li Ding, Marta Gut, John Easton, Bhavin Vadodaria, Pankaj Gupta, Gordon Lemmon, Sakina Zaidi, Odile Oberlin, Gaelle Pierron, Xiang Chen, Gang Wu, Erin Hedlund, Thomas Rio-Frio, Stéphanie Reynaud, Michael Rusch, Sandrine Grossetête-Lalami, Eve Lapouble, Zhaojie Zhang, Armita Bahrami, Marie Cécile Le Deley, Matthew Parker, Xiaotu Ma, Didier Surdez, and Franck Tirode
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List of supplementary tables and figures.
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- 2023
29. Supplementary Table 5 from Genomic Landscape of Ewing Sarcoma Defines an Aggressive Subtype with Co-Association of STAG2 and TP53 Mutations
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Olivier Delattre, Jinghui Zhang, Michael Dyer, James Downing, Ivo Gut, Perrine Marec-Bérard, Jean Michon, Valérie Laurence, Sheila Shurtleff, Richard K. Wilson, Elaine R. Mardis, Li Ding, Marta Gut, John Easton, Bhavin Vadodaria, Pankaj Gupta, Gordon Lemmon, Sakina Zaidi, Odile Oberlin, Gaelle Pierron, Xiang Chen, Gang Wu, Erin Hedlund, Thomas Rio-Frio, Stéphanie Reynaud, Michael Rusch, Sandrine Grossetête-Lalami, Eve Lapouble, Zhaojie Zhang, Armita Bahrami, Marie Cécile Le Deley, Matthew Parker, Xiaotu Ma, Didier Surdez, and Franck Tirode
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STAG2 mutation in three cases that show a reduction of STAG2-immunopositive cells at disease recurrence.
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- 2023
30. scMINER: a mutual information-based framework for identifying hidden drivers from single-cell omics data
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Jiyang Yu, Liang Ding, Hao Shi, Chenxi Qian, Chad Burdyshaw, Joao Veloso, Alireza Khatamian, Qingfei Pan, Yogesh Dhungana, Zhen Xie, Isabel Risch, Xu Yang, Xin Huang, Lei Yan, Michael Rusch, Michael Brewer, Koon-Kiu Yan, and Hongbo Chi
- Subjects
Article - Abstract
The sparse nature of single-cell omics data makes it challenging to dissect the wiring and rewiring of the transcriptional and signaling drivers that regulate cellular states. Many of the drivers, referred to as “hidden drivers”, are difficult to identify via conventional expression analysis due to low expression and inconsistency between RNA and protein activity caused by post-translational and other modifications. To address this issue, we developed scMINER, a mutual information (MI)-based computational framework for unsupervised clustering analysis and cell-type specific inference of intracellular networks, hidden drivers and network rewiring from single-cell RNA-seq data. We designed scMINER to capture nonlinear cell-cell and gene-gene relationships and infer driver activities. Systematic benchmarking showed that scMINER outperforms popular single-cell clustering algorithms, especially in distinguishing similar cell types. With respect to network inference, scMINER does not rely on the binding motifs which are available for a limited set of transcription factors, therefore scMINER can provide quantitative activity assessment for more than 6,000 transcription and signaling drivers from a scRNA-seq experiment. As demonstrations, we used scMINER to expose hidden transcription and signaling drivers and dissect their regulon rewiring in immune cell heterogeneity, lineage differentiation, and tissue specification. Overall, activity-based scMINER is a widely applicable, highly accurate, reproducible and scalable method for inferring cellular transcriptional and signaling networks in each cell state from scRNA-seq data. The scMINER software is publicly accessible via:https://github.com/jyyulab/scMINER.
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- 2023
31. Integrated Genomic Analysis Identifies UBTF Tandem Duplications as a Recurrent Lesion in Pediatric Acute Myeloid Leukemia
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Masayuki Umeda, Jing Ma, Benjamin J. Huang, Kohei Hagiwara, Tamara Westover, Sherif Abdelhamed, Juan M. Barajas, Melvin E. Thomas, Michael P. Walsh, Guangchun Song, Liqing Tian, Yanling Liu, Xiaolong Chen, Pandurang Kolekar, Quang Tran, Scott G. Foy, Jamie L. Maciaszek, Andrew B. Kleist, Amanda R. Leonti, Bengsheng Ju, John Easton, Huiyun Wu, Virginia Valentine, Marcus B. Valentine, Yen-Chun Liu, Rhonda E. Ries, Jenny L. Smith, Evan Parganas, Ilaria Iacobucci, Ryan Hiltenbrand, Jonathan Miller, Jason R. Myers, Evadnie Rampersaud, Delaram Rahbarinia, Michael Rusch, Gang Wu, Hiroto Inaba, Yi-Cheng Wang, Todd A. Alonzo, James R. Downing, Charles G. Mullighan, Stanley Pounds, M. Madan Babu, Jinghui Zhang, Jeffrey E. Rubnitz, Soheil Meshinchi, Xiaotu Ma, and Jeffery M. Klco
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Myeloid ,Adult ,Pediatric Research Initiative ,Pediatric Cancer ,Childhood Leukemia ,Acute ,In the Spotlight ,Rare Diseases ,Clinical Research ,Recurrence ,hemic and lymphatic diseases ,Genetics ,2.1 Biological and endogenous factors ,Humans ,Aetiology ,Child ,neoplasms ,Cancer ,Pediatric ,Chromosome Aberrations ,Leukemia ,Hematology ,Exons ,Genomics ,General Medicine ,Leukemia, Myeloid, Acute ,Mutation - Abstract
The genetics of relapsed pediatric acute myeloid leukemia (AML) has yet to be comprehensively defined. Here, we present the spectrum of genomic alterations in 136 relapsed pediatric AMLs. We identified recurrent exon 13 tandem duplications (TD) in upstream binding transcription factor (UBTF) in 9% of relapsed AML cases. UBTF-TD AMLs commonly have normal karyotype or trisomy 8 with cooccurring WT1 mutations or FLT3-ITD but not other known oncogenic fusions. These UBTF-TD events are stable during disease progression and are present in the founding clone. In addition, we observed that UBTF-TD AMLs account for approximately 4% of all de novo pediatric AMLs, are less common in adults, and are associated with poor outcomes and MRD positivity. Expression of UBTF-TD in primary hematopoietic cells is sufficient to enhance serial clonogenic activity and to drive a similar transcriptional program to UBTF-TD AMLs. Collectively, these clinical, genomic, and functional data establish UBTF-TD as a new recurrent mutation in AML. Significance: We defined the spectrum of mutations in relapsed pediatric AML and identified UBTF-TDs as a new recurrent genetic alteration. These duplications are more common in children and define a group of AMLs with intermediate-risk cytogenetic abnormalities, FLT3-ITD and WT1 alterations, and are associated with poor outcomes. See related commentary by Hasserjian and Nardi, p. 173. This article is highlighted in the In This Issue feature, p. 171.
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- 2022
32. NetBID2 provides comprehensive hidden driver analysis
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Jiyang Yu, Xinran Dong, Liang Ding, Andrew Thrasher, Xinge Wang, Jingjing Liu, Qingfei Pan, Jordan Rash, Yogesh Dhungana, Xu Yang, Isabel Risch, Yuxin Li, Junmin Peng, Michael Rusch, Clay McLeod, Hongbo Chi, and Jinghui Zhang
- Abstract
We present a comprehensive and versatile toolkit, NetBID2, for integrating multi-omics data and exposing hidden drivers that are not genetically altered or differentially expressed at the RNA/protein level by reverse-engineering context-specific interactomes and inferring protein activity. We deploy NetBID2 Viewer, Runner, and Cloud apps with 145 context-specific gene regulatory and signalling networks across normal tissues and paediatric and adult cancers to facilitate real-time interactive visualization, analysis, end-to-end use, and sharing.
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- 2022
33. St. Jude Cloud: A Pediatric Cancer Genomic Data-Sharing Ecosystem
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Zhaoming Wang, J. Robert Michael, Darrell Gentry, Suzanne J. Baker, Jobin Sunny, S M Ashiqul Islam, Clay McLeod, David W. Ellison, Michael A. Dyer, Mark R. Wilkinson, Jinghui Zhang, Ludmil B. Alexandrov, Chaitanya Bangur, Bob Davidson, Singer Ma, Geralyn Miller, Pamella Tater, Yong Cheng, Arthur Chiao, Alexander M. Gout, Tuan Nguyen, James R. Downing, Edgar Sioson, Gang Wu, Delaram Rahbarinia, Ed Suh, Xiaotu Ma, Shaohua Lei, Yutaka Yasui, Andrew Frantz, Kirby Birch, Scott G. Foy, Nedra Robison, Kim E. Nichols, Aman Patel, Richard Daly, Alberto S. Pappo, Naina Thangaraj, Xin Zhou, Leslie L. Robison, Matthew Lear, Vijay Kandali, Christopher P. Meyer, David Finkelstein, Stephanie Wiggins, Tracy Ard, Irina McGuire, Yu Liu, Samuel W. Brady, Gregory T. Armstrong, Liqing Tian, Charles G. Mullighan, Brent A. Orr, Ti-Cheng Chang, Keith Perry, Michael Macias, Shuoguo Wang, Lance E. Palmer, Soheil Meshinchi, Carmen L. Wilson, James McMurry, Andrew Swistak, Michael Rusch, Scott Newman, Leigh Tanner, Madison Treadway, Xing Tang, Omar Serang, Jian Wang, Andrew Thrasher, Rahul Mudunuri, Mitchell J. Weiss, and Michael N. Edmonson
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0301 basic medicine ,Genomic data ,MEDLINE ,Cloud computing ,Anemia, Sickle Cell ,Article ,03 medical and health sciences ,0302 clinical medicine ,Neoplasms ,Humans ,Medicine ,Child ,Ecosystem ,Information Dissemination ,business.industry ,Cancer ,Genomics ,Cloud Computing ,Hospitals, Pediatric ,medicine.disease ,Pediatric cancer ,Data science ,Treatment efficacy ,Data sharing ,030104 developmental biology ,Workflow ,Oncology ,030220 oncology & carcinogenesis ,business - 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 >10,000 pediatric patients with cancer and long-term survivors, and >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 >1.2 petabytes of raw genomic data from >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
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- 2021
34. Pathogenic Germline Mutations in DNA Repair Genes in Combination With Cancer Treatment Exposures and Risk of Subsequent Neoplasms Among Long-Term Survivors of Childhood Cancer
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Michael N. Edmonson, John Easton, Jinghui Zhang, Qi Liu, Leslie L. Robison, Michael Rusch, Kim E. Nichols, Dennis Kennetz, Kyla Shelton, Carmen L. Wilson, Zhaoming Wang, Na Qin, Yutaka Yasui, Melissa M. Hudson, Nan Song, Heather L. Mulder, James R. Downing, and Matthew J. Ehrhardt
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Adult ,Male ,0301 basic medicine ,Oncology ,Cancer Research ,medicine.medical_specialty ,DNA Repair ,DNA repair ,Childhood cancer ,Cohort Studies ,Young Adult ,03 medical and health sciences ,0302 clinical medicine ,Germline mutation ,Cancer Survivors ,Neoplasms ,Internal medicine ,Exome Sequencing ,medicine ,Humans ,Neoplasm ,Survivors ,Young adult ,Child ,Germ-Line Mutation ,Retrospective Studies ,business.industry ,Retrospective cohort study ,ORIGINAL REPORTS ,medicine.disease ,Cancer treatment ,030104 developmental biology ,Increased risk ,Child, Preschool ,030220 oncology & carcinogenesis ,Female ,business - Abstract
PURPOSE To investigate cancer treatment plus pathogenic germline mutations (PGMs) in DNA repair genes (DRGs) for identification of childhood cancer survivors at increased risk of subsequent neoplasms (SNs). METHODS Whole-genome sequencing was performed on blood-derived DNA from survivors in the St Jude Lifetime Cohort. PGMs were evaluated in 127 genes from 6 major DNA repair pathways. Cumulative doses of chemotherapy and body region–specific radiotherapy (RT) were abstracted from medical records. Relative rates (RRs) and 95% CIs of SNs by mutation status were estimated using multivariable piecewise exponential models. RESULTS Of 4,402 survivors, 495 (11.2%) developed 1,269 SNs. We identified 538 PGMs in 98 DRGs ( POLG, MUTYH, ERCC2, and BRCA2, among others) in 508 (11.5%) survivors. Mutations in homologous recombination (HR) genes were significantly associated with an increased rate of subsequent female breast cancer (RR, 3.7; 95% CI, 1.8 to 7.7), especially among survivors with chest RT ≥ 20 Gy (RR, 4.4; 95% CI, 1.6 to 12.4), or with a cumulative dose of anthracyclines in the second or third tertile (RR, 4.4; 95% CI, 1.7 to 11.4). Mutations in HR genes were also associated with an increased rate of subsequent sarcoma among those who received alkylating agent doses in the third tertile (RR, 14.9; 95% CI, 4.0 to 38.0). Mutations in nucleotide excision repair genes were associated with subsequent thyroid cancer for those treated with neck RT ≥ 30 Gy (RR, 12.9; 95% CI, 1.6 to 46.6) with marginal statistical significance. CONCLUSION Our study provides novel insights regarding the contribution of genetics, in combination with known treatment-related risks, for the development of SNs. These findings have the potential to facilitate identification of high-risk survivors who may benefit from genetic counseling and/or testing of DRGs, which may further inform personalized cancer surveillance and prevention strategies.
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- 2020
35. CICERO: a versatile method for detecting complex and diverse driver fusions using cancer RNA sequencing data
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Andrew Thrasher, Karol Szlachta, Austyn Trull, Liqing Tian, Eric Davis, James R. Downing, Xin Zhou, Clay McLeod, Michael N. Edmonson, Scott Newman, Michael Rusch, Jinghui Zhang, Charles G. Mullighan, David W. Ellison, Bo Tang, J. Robert Michael, Jing Ma, Yongjin Li, Yu Liu, Suzanne J. Baker, and John Easton
- Subjects
Source code ,lcsh:QH426-470 ,media_common.quotation_subject ,Method ,RNA-Seq ,Computational biology ,Biology ,Annotation ,Neoplasms ,medicine ,Humans ,Cloud computing ,lcsh:QH301-705.5 ,media_common ,Sequence Analysis, RNA ,Fusion visualization ,RNA ,Cancer ,Molecular Sequence Annotation ,Precision oncology ,medicine.disease ,Pediatric cancer ,lcsh:Genetics ,lcsh:Biology (General) ,RNA-seq ,human activities ,Algorithms ,Software ,Gene fusion ,Cicero - Abstract
To discover driver fusions beyond canonical exon-to-exon chimeric transcripts, we develop CICERO, a local assembly-based algorithm that integrates RNA-seq read support with extensive annotation for candidate ranking. CICERO outperforms commonly used methods, achieving a 95% detection rate for 184 independently validated driver fusions including internal tandem duplications and other non-canonical events in 170 pediatric cancer transcriptomes. Re-analysis of TCGA glioblastoma RNA-seq unveils previously unreported kinase fusions (KLHL7-BRAF) and a 13% prevalence of EGFR C-terminal truncation. Accessible via standard or cloud-based implementation, CICERO enhances driver fusion detection for research and precision oncology. The CICERO source code is available at https://github.com/stjude/Cicero.
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- 2020
36. Therapy-induced mutations drive the genomic landscape of relapsed acute lymphoblastic leukemia
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Jie Zhao, Ke Xu, Fan Yang, Ludmil B. Alexandrov, Edgar Sioson, Cheng Cheng, Samuel W. Brady, Shuhong Shen, Lele Sun, Liqing Tian, Benshang Li, Heather L. Mulder, Tianyi Wang, Yu Liu, Diane Flasch, James R. Downing, Ting Nien Lin, Xiaofan Zhu, Hui Zhang, Lijuan Du, Ching-Hon Pui, Matthew A. Myers, Yongjin Li, Ningling Wang, Michael Rusch, Karol Szlachta, Xiaotu Ma, Liu Yang, Jingyan Tang, Bin-Bing S. Zhou, Xin Zhou, Benjamin J. Raphael, Jinghui Zhang, Hui Li, Hui Ying Sun, Lixia Ding, Li Dong, Ying Shao, Jiaoyang Cai, Jingliao Zhang, Yingchi Zhang, Hongye Sun, Michael N. Edmonson, Kohei Hagiwara, John Easton, Yanling Liu, and Jun J. Yang
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0301 basic medicine ,Immunology ,Clone (cell biology) ,Drug resistance ,medicine.disease_cause ,Biochemistry ,03 medical and health sciences ,0302 clinical medicine ,Recurrence ,Acute lymphocytic leukemia ,DNA Mutational Analysis ,medicine ,Humans ,Mutation ,Lymphoid Neoplasia ,Thiopurine methyltransferase ,biology ,business.industry ,Cancer ,Genomics ,Cell Biology ,Hematology ,Precursor Cell Lymphoblastic Leukemia-Lymphoma ,medicine.disease ,030104 developmental biology ,MSH2 ,030220 oncology & carcinogenesis ,biology.protein ,Cancer research ,business - Abstract
To study the mechanisms of relapse in acute lymphoblastic leukemia (ALL), we performed whole-genome sequencing of 103 diagnosis-relapse-germline trios and ultra-deep sequencing of 208 serial samples in 16 patients. Relapse-specific somatic alterations were enriched in 12 genes (NR3C1, NR3C2, TP53, NT5C2, FPGS, CREBBP, MSH2, MSH6, PMS2, WHSC1, PRPS1, and PRPS2) involved in drug response. Their prevalence was 17% in very early relapse (36 months) groups. Convergent evolution, in which multiple subclones harbor mutations in the same drug resistance gene, was observed in 6 relapses and confirmed by single-cell sequencing in 1 case. Mathematical modeling and mutational signature analysis indicated that early relapse resistance acquisition was frequently a 2-step process in which a persistent clone survived initial therapy and later acquired bona fide resistance mutations during therapy. In contrast, very early relapses arose from preexisting resistant clone(s). Two novel relapse-specific mutational signatures, one of which was caused by thiopurine treatment based on in vitro drug exposure experiments, were identified in early and late relapses but were absent from 2540 pan-cancer diagnosis samples and 129 non-ALL relapses. The novel signatures were detected in 27% of relapsed ALLs and were responsible for 46% of acquired resistance mutations in NT5C2, PRPS1, NR3C1, and TP53. These results suggest that chemotherapy-induced drug resistance mutations facilitate a subset of pediatric ALL relapses.
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- 2020
37. Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia
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Željko Antić, Xin Zhou, Michael Rusch, Zhaohui Gu, Yiping Fan, Michael N. Edmonson, William E. Evans, Ruben van Boxtel, Ching-Hon Pui, Roland P. Kuiper, John E. Dick, Jian Wang, Francis Blokzijl, Mary V. Relling, Kelly McCastlain, Jiangyan Yu, Debbie Payne-Turner, Ilaria Iacobucci, Charles G. Mullighan, Jinghui Zhang, Jeremy Chase Crawford, Deqing Pei, Ji Wen, Jing Ma, Gang Wu, Xiaotu Ma, Geoffrey Neale, Irina McGuire, Stephanie M. Dobson, Kathryn G. Roberts, Guangchun Song, Cheng Cheng, Kim E. Nichols, Esmé Waanders, Lei Shi, Paul G. Thomas, Ying Shao, John Easton, Scott R. Olsen, Marjolijn C.J. Jongmans, Jun J. Yang, Maartje van der Vorst, and Stanley Pounds
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Genetics ,Mutation ,Lineage (genetic) ,Clone (cell biology) ,Somatic hypermutation ,Genomics ,General Medicine ,Precursor Cell Lymphoblastic Leukemia-Lymphoma ,Biology ,medicine.disease ,medicine.disease_cause ,Somatic evolution in cancer ,Clonal Evolution ,Leukemia ,Recurrence ,medicine ,Tumours of the digestive tract Radboud Institute for Molecular Life Sciences [Radboudumc 14] ,Humans ,Digital polymerase chain reaction ,Child - Abstract
Relapse of acute lymphoblastic leukemia (ALL) remains a leading cause of childhood cancer-related death. Prior studies have shown clonal mutations at relapse often arise from relapse-fated subclones that exist at diagnosis. However, the genomic landscape, evolutionary trajectories, and mutational mechanisms driving relapse are incompletely understood. In an analysis of 92 cases of relapsed childhood ALL incorporating multimodal DNA and RNA sequencing, deep digital mutational tracking, and xenografting to formally define clonal structure, we identified 50 significant targets of mutation with distinct patterns of mutational acquisition or enrichment. CREBBP, NOTCH1, and RAS signaling mutations arose from diagnosis subclones, whereas variants in NCOR2, USH2A, and NT5C2 were exclusively observed at relapse. Evolutionary modeling and xenografting demonstrated that relapse-fated clones were minor (50%), major (27%), or multiclonal (18%) at diagnosis. Putative second leukemias, including those with lineage shift, were shown to most commonly represent relapse from an ancestral clone rather than a truly independent second primary leukemia. A subset of leukemias prone to repeated relapse exhibited hypermutation driven by at least three distinct mutational processes, resulting in heightened neoepitope burden and potential vulnerability to immunotherapy. Finally, relapse-driving sequence mutations were detected prior to relapse using droplet digital PCR at levels comparable with orthogonal approaches to monitor levels of measurable residual disease. These results provide a genomic framework to anticipate and circumvent relapse by earlier detection and targeting of relapse-fated clones. Significance: This study defines the landscape of mutations that preexist and arise after commencement of ALL therapy and shows that relapse may be propagated from ancestral, major, or minor clones at initial diagnosis. A subset of cases exhibits hypermutation that results in expression of neoepitopes that may be substrates for immunotherapeutic intervention. See related video: https://vimeo.com/442838617 See related commentary by Ogawa, p. 21. See related article by S. Dobson et al . This article is highlighted in the In This Issue feature, p. 5
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- 2020
38. Enteropathogen Resource Integration Center (ERIC): bioinformatics support for research on biodefense-relevant enterobacteria.
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Jeremy D. Glasner, Guy Plunkett III, Bradley D. Anderson, David J. Baumler, Bryan S. Biehl, Valerie Burland, Eric L. Cabot, Aaron E. Darling, Bob Mau, Eric C. Neeno-Eckwall, David Pot, Yu Qiu, Anna I. Rissman, Sara Worzella, Sam Zaremba, Joel Fedorko, Thomas Hampton, Paul Liss, Michael Rusch, Matthew Shaker, Lorie Shaull, Panna Shetty, Silpa Thotakura, Jon Whitmore, Frederick R. Blattner, John M. Greene, and Nicole T. Perna
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- 2008
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39. The landscape of coding RNA editing events in pediatric cancer
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Samuel W. Brady, David W. Ellison, Ji Wen, Charles G. Mullighan, Tanja A. Gruber, John Easton, Timothy I. Shaw, Brent B Powers, Michael Rusch, Michael N. Edmonson, Liqing Tian, Jinghui Zhang, and Ying Shao
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Nonsynonymous substitution ,RNA editing ,Cancer Research ,Pediatric cancer ,Genomics ,Computational biology ,Biology ,Open Reading Frames ,Protein sequencing ,Neoplasms ,Genetics ,medicine ,Humans ,Coding region ,RNA, Neoplasm ,Child ,RC254-282 ,Whole Genome Sequencing ,Brain Neoplasms ,Sequence Analysis, RNA ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,Cancer ,DNA, Neoplasm ,Genome project ,medicine.disease ,Oncology ,Organ Specificity ,Immunotherapy ,Research Article - Abstract
Background RNA editing leads to post-transcriptional variation in protein sequences and has important biological implications. We sought to elucidate the landscape of RNA editing events across pediatric cancers. Methods Using RNA-Seq data mapped by a pipeline designed to minimize mapping ambiguity, we investigated RNA editing in 711 pediatric cancers from the St. Jude/Washington University Pediatric Cancer Genome Project focusing on coding variants which can potentially increase protein sequence diversity. We combined de novo detection using paired tumor DNA-RNA data with analysis of known RNA editing sites. Results We identified 722 unique RNA editing sites in coding regions across pediatric cancers, 70% of which were nonsynonymous recoding variants. Nearly all editing sites represented the canonical A-to-I (n = 706) or C-to-U sites (n = 14). RNA editing was enriched in brain tumors compared to other cancers, including editing of glutamate receptors and ion channels involved in neurotransmitter signaling. RNA editing profiles of each pediatric cancer subtype resembled those of the corresponding normal tissue profiled by the Genotype-Tissue Expression (GTEx) project. Conclusions In this first comprehensive analysis of RNA editing events in pediatric cancer, we found that the RNA editing profile of each cancer subtype is similar to its normal tissue of origin. Tumor-specific RNA editing events were not identified indicating that successful immunotherapeutic targeting of RNA-edited peptides in pediatric cancer should rely on increased antigen presentation on tumor cells compared to normal but not on tumor-specific RNA editing per se.
- Published
- 2021
40. ASAP: a resource for annotating, curating, comparing, and disseminating genomic data.
- Author
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Jeremy D. Glasner, Michael Rusch, Paul Liss, Guy Plunkett III, Eric L. Cabot, Aaron E. Darling, Bradley D. Anderson, Paul Infield-Harm, Michael C. Gilson, and Nicole T. Perna
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- 2006
- Full Text
- View/download PDF
41. The genomic landscape of pediatric acute lymphoblastic leukemia
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Samuel W. Brady, Kathryn G. Roberts, Zhaohui Gu, Lei Shi, Stanley Pounds, Deqing Pei, Cheng Cheng, Yunfeng Dai, Meenakshi Devidas, Chunxu Qu, Ashley N. Hill, Debbie Payne-Turner, Xiaotu Ma, Ilaria Iacobucci, Pradyuamna Baviskar, Lei Wei, Sasi Arunachalam, Kohei Hagiwara, Yanling Liu, Diane A. Flasch, Yu Liu, Matthew Parker, Xiaolong Chen, Abdelrahman H. Elsayed, Omkar Pathak, Yongjin Li, Yiping Fan, J. Robert Michael, Michael Rusch, Mark R. Wilkinson, Scott Foy, Dale J. Hedges, Scott Newman, Xin Zhou, Jian Wang, Colleen Reilly, Edgar Sioson, Stephen V. Rice, Victor Pastor Loyola, Gang Wu, Evadnie Rampersaud, Shalini C. Reshmi, Julie Gastier-Foster, Jaime M. Guidry Auvil, Patee Gesuwan, Malcolm A. Smith, Naomi Winick, Andrew J. Carroll, Nyla A. Heerema, Richard C. Harvey, Cheryl L. Willman, Eric Larsen, Elizabeth A. Raetz, Michael J. Borowitz, Brent L. Wood, William L. Carroll, Patrick A. Zweidler-McKay, Karen R. Rabin, Leonard A. Mattano, Kelly W. Maloney, Stuart S. Winter, Michael J. Burke, Wanda Salzer, Kimberly P. Dunsmore, Anne L. Angiolillo, Kristine R. Crews, James R. Downing, Sima Jeha, Ching-Hon Pui, William E. Evans, Jun J. Yang, Mary V. Relling, Daniela S. Gerhard, Mignon L. Loh, Stephen P. Hunger, Jinghui Zhang, and Charles G. Mullighan
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Chromosome Aberrations ,Mutation ,Genetics ,Humans ,Exome ,Genomics ,Precursor Cell Lymphoblastic Leukemia-Lymphoma ,Child ,Article - Abstract
Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Here, using whole-genome, exome and transcriptome sequencing of 2,754 childhood patients with ALL, we find that, despite a generally low mutation burden, ALL cases harbor a median of four putative somatic driver alterations per sample, with 376 putative driver genes identified varying in prevalence across ALL subtypes. Most samples harbor at least one rare gene alteration, including 70 putative cancer driver genes associated with ubiquitination, SUMOylation, noncoding transcripts and other functions. In hyperdiploid B-ALL, chromosomal gains are acquired early and synchronously before ultraviolet-induced mutation. By contrast, ultraviolet-induced mutations precede chromosomal gains in B-ALL cases with intrachromosomal amplification of chromosome 21. We also demonstrate the prognostic significance of genetic alterations within subtypes. Intriguingly, DUX4- and KMT2A-rearranged subtypes separate into CEBPA/FLT3- or NFATC4-expressing subgroups with potential clinical implications. Together, these results deepen understanding of the ALL genomic landscape and associated outcomes.
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- 2021
42. ASAP, a systematic annotation package for community analysis of genomes.
- Author
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Jeremy D. Glasner, Paul Liss, Guy Plunkett III, Aaron E. Darling, Tejasvini Prasad, Michael Rusch, Alexis Byrnes, Michael K. Gilson, Bryan S. Biehl, Frederick R. Blattner, and Nicole T. Perna
- Published
- 2003
- Full Text
- View/download PDF
43. H3.3 K27M depletion increases differentiation and extends latency of diffuse intrinsic pontine glioma growth in vivo
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Brent L. Russell, Celeste Rosencrance, Xiaoyan Zhu, Rachel M. Noyes, Yiping Fan, Donald Yergeau, David Finkelstein, Hongjian Jin, Suzanne J. Baker, Ying Shao, Junyuan Zhang, Jinghui Zhang, Andre B. Silveira, Michael Rusch, Timothy I. Shaw, David W. Ellison, Stanley Pounds, Cynthia Wetmore, Gang Wu, Jon D. Larson, Alberto Broniscer, Liang Ding, Beisi Xu, Lawryn H. Kasper, Kristy Boggs, and John Easton
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0301 basic medicine ,Biology ,Article ,Pathology and Forensic Medicine ,Histones ,Transcriptome ,Mice ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,Histone H3 ,0302 clinical medicine ,Downregulation and upregulation ,Cell Line, Tumor ,Glioma ,medicine ,Animals ,Brain Stem Neoplasms ,Epigenetics ,Gene knockdown ,Diffuse Intrinsic Pontine Glioma ,Cell Differentiation ,Promoter ,Epigenome ,medicine.disease ,Disease Models, Animal ,030104 developmental biology ,Gene Knockdown Techniques ,Mutation ,Cancer research ,Neurology (clinical) ,030217 neurology & neurosurgery - Abstract
Histone H3 K27M mutation is the defining molecular feature of the devastating pediatric brain tumor, diffuse intrinsic pontine glioma (DIPG). The prevalence of histone H3 K27M mutations indicates a critical role in DIPGs, but the contribution of the mutation to disease pathogenesis remains unclear. We show that knockdown of this mutation in DIPG xenografts restores K27M-dependent loss of H3K27me3 and delays tumor growth. Comparisons of matched DIPG xenografts with and without K27M knockdown allowed identification of mutation-specific effects on the transcriptome and epigenome. The resulting transcriptional changes recapitulate expression signatures from K27M primary DIPG tumors, and are strongly enriched for genes associated with nervous system development. Integrated analysis of ChIP-seq and expression data showed that genes upregulated by the mutation are overrepresented in apparently bivalent promoters. Many of these targets are associated with more immature differentiation states. Expression profiles indicate K27M knockdown decreases proliferation and increases differentiation within lineages represented in DIPG. These data suggest that K27M-mediated loss of H3K27me3 directly regulates a subset of genes by releasing poised promoters, and contributes to tumor phenotype and growth by limiting differentiation. The delayed tumor growth associated with knockdown of H3 K27M provides evidence that this highly recurrent mutation is a relevant therapeutic target.
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- 2019
44. Abstract 4092: Fuzzion2: Fast, sensitive detection of known gene fusions by fuzzy pattern matching for clinical testing and large-scale data mining
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Stephen V. Rice, Michael N. Edmonson, Liqing Tian, Michael Rusch, David A. Wheeler, Jennifer L. Neary, Scott Newman, Lu Wang, Patrick R. Blackburn, Michael Macias, Andrew Thrasher, Jian Wang, Mark R. Wilkinson, Xin Zhou, and Jinghui Zhang
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Cancer Research ,Oncology - Abstract
Detection of gene fusions is important for discovery of cancer drivers and clinical oncology testing, but existing software tools for fusion detection usually take hours to run and may fail to find lowly expressed fusions. To overcome these limitations, we developed the Fuzzion2 program, which uses pattern matching to detect known gene fusions in unmapped paired-read RNA-Seq data. Given a set of patterns representing fusion transcript breakpoints, Fuzzion2 finds every read pair matching any of the patterns. Both exact and inexact (fuzzy) matches are detected; the fuzzy matching tolerates variations caused by sequencing errors, SNVs, and indels. By employing a novel index of frequency minimizers, Fuzzion2 needs only minutes to process a sample. We have also developed pipelines to produce patterns for Fuzzion2, from fusion contig sequences, from genomic breakpoints in DNA and RNA, and from fusion protein sequences. To evaluate its applicability in clinical testing, we ran Fuzzion2 on ~2,000 RNA-seq samples profiled by the St. Jude clinical genomics program and confirmed its sensitivity in identifying lowly expressed fusions, such as KIAA1549-BRAF in low-grade glioma, which are frequently missed by commonly used fusion detection programs. Notably, Fuzzion2 detected a subclonal BCR-ABL1 fusion expressed at 1% and 6% of the wild-type BCR and ABL1 transcription level, respectively, in a B-lineage ALL sample that also has an IGH-CRLF fusion. Processing RNA-seq data from BCR-ABL1 cell lines, K562 with p210 fusion and OP1 with p190 fusion, diluted at 1:10, 1:100, and 1:1000 showed that Fuzzion2 can detect the fusion at 1:10-1:100 dilution, achieving a sensitivity 10 times greater than that of other fusion detection programs. We also evaluated the performance of Fuzzion2 for large-scale data mining in a study to compare the prevalence of gene fusions in pediatric versus adult cancers. We assembled a set of 15,474 patterns representing 5,480 fusions identified in the Pediatric Cancer Genome Project, NCI TARGET, clinical sequencing, and the COSMIC database. Fuzzion2 was deployed to the NCI Cancer Genomics Cloud and analyzed 9,464 TCGA RNA-seq samples from adult solid and brain tumors. Processing took an average of 6 minutes at a cost of only US$0.16 per sample. Among the 105 recurrent fusions identified in pediatric cancers, only 11 were also found in adult cancers. These shared fusions can be classified into two categories: 1) gene fusions present in cancers that occur in both children and young adults, e.g., synovial sarcoma, papillary thyroid cancer, and fibrolamellar hepatocellular carcinoma; and 2) kinase fusions involving ABL1, NTRK, and FGFR. Our experience with Fuzzion2 demonstrates that it is a powerful tool for time-critical clinical application and large-scale data mining. It is publicly available at https://github.com/stjude/fuzzion2. Citation Format: Stephen V. Rice, Michael N. Edmonson, Liqing Tian, Michael Rusch, David A. Wheeler, Jennifer L. Neary, Scott Newman, Lu Wang, Patrick R. Blackburn, Michael Macias, Andrew Thrasher, Jian Wang, Mark R. Wilkinson, Xin Zhou, Jinghui Zhang. Fuzzion2: Fast, sensitive detection of known gene fusions by fuzzy pattern matching for clinical testing and large-scale data mining [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4092.
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- 2022
45. A polygenic score for acute vaso-occlusive pain in pediatric sickle cell disease
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Xing Tang, Yu Yao, Ti-Cheng Chang, Martha Barton, Yadav Sapkota, Juan Ding, Evadnie Rampersaud, Jinghui Zhang, Amanda M. Brandow, Heather L. Mulder, Celeste Rosencrance, Lance E. Palmer, Donald Yergeau, Doralina L. Anghelescu, Michael Rusch, Edgar Sioson, Yutaka Yasui, Shawn Levy, Gang Wu, James R. Downing, Russell J. Brooke, Celeste K. Kanne, Yong Cheng, Kirby Birch, Winfred C. Wang, Michael R. DeBaun, John Easton, Wenjian Bi, Nicole M. Alberts, Jason R. Hodges, Ashwin P Patel, Vivien A. Sheehan, Shuoguo Wang, Mitchell J. Weiss, Guolian Kang, Nidal Boulos, Andrew Thrasher, Akshay Sharma, Wenan Chen, Jeremie H. Estepp, Jane S. Hankins, Sara R. Rashkin, and Latika Puri
- Subjects
Anemia ,Thalassemia ,Pain ,Single-nucleotide polymorphism ,Disease ,Anemia, Sickle Cell ,Bioinformatics ,Polymorphism, Single Nucleotide ,03 medical and health sciences ,0302 clinical medicine ,Red Cells, Iron, and Erythropoiesis ,Polymorphism (computer science) ,Fetal hemoglobin ,Genetic variation ,Medicine ,Humans ,Longitudinal Studies ,Child ,Fetal Hemoglobin ,business.industry ,Hematology ,medicine.disease ,IL1A ,030220 oncology & carcinogenesis ,business ,030215 immunology - 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.
- Published
- 2021
46. Genomes for Kids: The Scope of Pathogenic Mutations in Pediatric Cancer Revealed by Comprehensive DNA and RNA Sequencing
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Samuel W. Brady, Brent A. Orr, Jamie L. Maciaszek, Michael N. Edmonson, Michael Rusch, Yu Liu, Andrew Thrasher, Aman Patel, Jessica M. Valdez, Xin Zhou, Scott G. Foy, Jeffery M. Klco, Lu Wang, Stacy Hines-Dowell, Eric Davis, James R. Downing, Jiali Gu, Liza-Marie Johnson, Rose B. McGee, Scott Newman, Roya Mostafavi, Zhaohui Gu, Jian Wang, Armita Bahrami, Sheila A. Shurtleff, Delaram Rahbarinia, Dale Hedges, Lynn W. Harrison, Jay Knight, Ching-Hon Pui, Jared Becksfort, Manish Kubal, Giles W. Robinson, Emily Quinn, Leslie Taylor, Annastasia A. Ouma, Elizabeth M Azzato, Ti-Cheng Chang, Charles G. Mullighan, Yanling Liu, Joy Nakitandwe, Victor B Pastor, Michael R. Clay, Antonina Silkov, Jinghui Zhang, Manjusha Pande, Chimene Kesserwan, Kayla V. Hamilton, Alexander M. Gout, David A. Wheeler, David W. Ellison, Elsie L. Gerhardt, Kim E. Nichols, Zhaojie Zhang, Alberto S. Pappo, Regina Nuccio, and Mark R. Wilkinson
- Subjects
Genetics ,Sequence Analysis, RNA ,Cancer ,RNA ,Disease ,DNA ,Biology ,medicine.disease ,Genome ,Pediatric cancer ,Germline ,Article ,Oncology ,Neoplasms ,Mutation ,Exome Sequencing ,medicine ,Humans ,Child ,Gene ,Exome - Abstract
Genomic studies of pediatric cancer have primarily focused on specific tumor types or high-risk disease. Here, we used a three-platform sequencing approach, including whole-genome sequencing (WGS), whole-exome sequencing (WES), and RNA sequencing (RNA-seq), to examine tumor and germline genomes from 309 prospectively identified children with newly diagnosed (85%) or relapsed/refractory (15%) cancers, unselected for tumor type. Eighty-six percent of patients harbored diagnostic (53%), prognostic (57%), therapeutically relevant (25%), and/or cancer-predisposing (18%) variants. Inclusion of WGS enabled detection of activating gene fusions and enhancer hijacks (36% and 8% of tumors, respectively), small intragenic deletions (15% of tumors), and mutational signatures revealing of pathogenic variant effects. Evaluation of paired tumor–normal data revealed relevance to tumor development for 55% of pathogenic germline variants. This study demonstrates the power of a three-platform approach that incorporates WGS to interrogate and interpret the full range of genomic variants across newly diagnosed as well as relapsed/refractory pediatric cancers. Significance: Pediatric cancers are driven by diverse genomic lesions, and sequencing has proven useful in evaluating high-risk and relapsed/refractory cases. We show that combined WGS, WES, and RNA-seq of tumor and paired normal tissues enables identification and characterization of genetic drivers across the full spectrum of pediatric cancers. This article is highlighted in the In This Issue feature, p. 2945
- Published
- 2020
47. Pan-neuroblastoma analysis reveals age- and signature-associated driver alterations
- Author
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Michael Rusch, Eric Davis, Heather L. Mulder, Samuel W. Brady, Jian Wang, Cheng Cheng, Xiaotu Ma, Michael A. Dyer, Michael Macias, Shaohua Lei, Jinghui Zhang, Xin Zhou, James R. Downing, Yanling Liu, Joy Nakitandwe, Arlene Naranjo, John M. Maris, Michael D. Hogarty, Alexander M. Gout, Kohei Hagiwara, John Easton, Xiao-Long Chen, Lu Wang, and Nai-Kong V. Cheung
- Subjects
Male ,0301 basic medicine ,DNA Mutational Analysis ,Datasets as Topic ,General Physics and Astronomy ,Genome informatics ,medicine.disease_cause ,Cohort Studies ,Mitochondrial Ribosomes ,Transcriptome ,Pathogenesis ,Neuroblastoma ,0302 clinical medicine ,Cancer genomics ,Anaplastic Lymphoma Kinase ,Exome ,Child ,lcsh:Science ,Cancer genetics ,Regulation of gene expression ,Mutation ,Multidisciplinary ,Age Factors ,Gene Expression Regulation, Neoplastic ,Child, Preschool ,030220 oncology & carcinogenesis ,Female ,Adult ,Ribosomal Proteins ,Adolescent ,DNA Copy Number Variations ,Science ,Biology ,Article ,General Biochemistry, Genetics and Molecular Biology ,Electron Transport ,Paediatric cancer ,Young Adult ,03 medical and health sciences ,Biomarkers, Tumor ,medicine ,Humans ,Receptor, Fibroblast Growth Factor, Type 1 ,neoplasms ,ATRX ,Whole Genome Sequencing ,Point mutation ,Infant, Newborn ,Infant ,General Chemistry ,medicine.disease ,030104 developmental biology ,Cancer research ,lcsh:Q - Abstract
Neuroblastoma is a pediatric malignancy with heterogeneous clinical outcomes. To better understand neuroblastoma pathogenesis, here we analyze whole-genome, whole-exome and/or transcriptome data from 702 neuroblastoma samples. Forty percent of samples harbor at least one recurrent driver gene alteration and most aberrations, including MYCN, ATRX, and TERT alterations, differ in frequency by age. MYCN alterations occur at median 2.3 years of age, TERT at 3.8 years, and ATRX at 5.6 years. COSMIC mutational signature 18, previously associated with reactive oxygen species, is the most common cause of driver point mutations in neuroblastoma, including most ALK and Ras-activating variants. Signature 18 appears early and is continuous throughout disease evolution. Signature 18 is enriched in neuroblastomas with MYCN amplification, 17q gain, and increased expression of mitochondrial ribosome and electron transport-associated genes. Recurrent FGFR1 variants in six patients, and ALK N-terminal structural alterations in five samples, identify additional patients potentially amenable to precision therapy., Genomic analysis of neuroblastoma has revealed important disease etiology. In this study, the authors assembled whole genome, exome and transcriptome data from over 700 neuroblastomas and identified molecular signatures correlated with age, and rare, potentially targetable variants overlooked in smaller cohorts.
- Published
- 2020
48. St. Jude Cloud—a Pediatric Cancer Genomic Data Sharing Ecosystem
- Author
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Michael Rusch, Pamella Tater, Aman Patel, Michael N. Edmonson, Bob Davidson, Ti-Cheng Chang, Andrew Frantz, Alexander M. Gout, Xin Zhou, Yu Liu, Michael A. Dyer, Samuel W. Brady, Yong Cheng, Brent A. Orr, Vijay Kandali, Kim E. Nichols, Michael Macias, Shaohua Lei, Richard Daly, Rahul Mudunuri, Jian Wang, Leslie L. Robison, Matthew Lear, David Finkelstein, Chitanya Bangur, Andrew Thrasher, Mitch Weiss, Scott Newman, Charles G. Mullighan, Christopher P. Meyer, Shuoguo Wang, Keith Perry, Tracy Ard, Mark R. Wilkinson, Delaram Rahbarinia, Gregory T. Armstrong, David W. Ellison, Kirby Birch, Geralyn Miller, J. Robert Michael, James R. Downing, James McMurry, Madison Treadway, Jinghui Zhang, Carmen L. Wilson, Singer Ma, Clay McLeod, Yutaka Yasui, Naina Thangaraj, Gang Wu, Ed Suh, Tuan Nguyen, Xiaotu Ma, Zhaoming Wang, Scott G. Foy, Nedra Robison, Darrell Gentry, Suzanne J. Baker, Jobin Sunny, Liqing Tian, Lance E. Palmer, Leigh Tanner, Xing Tang, Omar Serang, Edgar Sioson, Stephanie Wiggins, Irina McGuire, and Andrew Swistak
- Subjects
Public access ,Data sharing ,Clinical genomics ,medicine.medical_specialty ,business.industry ,Genomic data ,Medicine ,Medical physics ,Cloud computing ,business ,Pediatric cancer - Abstract
Effective data sharing is key to accelerating research that will improve the precision of diagnoses, efficacy of treatments and long-term survival of pediatric cancer and other childhood catastrophic diseases. We present St. Jude Cloud (https://www.stjude.cloud), a cloud-based data sharing ecosystem developed via collaboration between St. Jude Children’s Research Hospital, DNAnexus, and Microsoft, for accessing, analyzing and visualizing genomic data from >10,000 pediatric cancer patients, long-term survivors of pediatric cancer and >800 pediatric sickle cell patients. Harmonized genomic data totaling 1.25 petabyes on St. Jude Cloud include 12,104 whole genomes, 7,697 whole exomes and 2,202 transcriptomes, which are freely available to researchers worldwide. The resource is expanding rapidly with regular data uploads from St. Jude’s prospective clinical genomics programs, providing public access as soon as possible rather than holding data back until publication. Three interconnected apps within the St. Jude Cloud ecosystem—Genomics Platform, Pediatric Cancer Knowledgebase (PeCan) and Visualization Community—provide a unique experience for simultaneously performing advanced data analysis in the cloud and enhancing the pediatric cancer knowledgebase. We demonstrate the value of the St. Jude Cloud ecosystem through use cases that classify 48 pediatric cancer subtypes by gene expression profiling and map mutational signatures across 35 subtypes of pediatric cancer.
- Published
- 2020
49. Germline Elongator mutations in sonic hedgehog medulloblastoma
- Author
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Michael Rusch, Aksana Vasilyeva, Marc Remke, Paul A. Northcott, Tanvi Sharma, Finn Wesenberg, Andrey Korshunov, Peter Lichter, Kristian W. Pajtler, Natalie Jäger, Sonia Partap, Till Milde, John R. Crawford, Amar Gajjar, Stefan Rutkowski, Nicholas G. Gottardo, Kyle S. Smith, Daniel C. Bowers, Christoffer Johansen, Sebastian M. Waszak, Tobias Rausch, Christelle Dufour, Damarys Loew, David T.W. Jones, Geoffrey Neale, Olaf Witt, Tone Eggen, Ivo Buchhalter, Olivier Ayrault, Dominik Sturm, Maria Feychting, Jesus Garcia-Lopez, Michael A. Grotzer, Claudia E. Kuehni, Emilie Indersie, Brandon J. Wainwright, Stéphanie Puget, Joy Nakitandwe, Marcel Kool, David W. Ellison, Marina Ryzhova, Jules Kerssemakers, Birgitta Lannering, Amy A Smith, Brent A. Orr, Joachim Schüz, Tina Veje Andersen, Murali Chintagumpala, Brian Gudenas, Bérangère Lombard, Antoine Forget, Laurence Brugières, Marija Kojic, Kim E. Nichols, Jennifer Hadley, Martin Röösli, Kristina Kjærheim, Anne Bendel, Stefan M. Pfister, Kayla V. Hamilton, Ruth G. Tatevossian, Giles W. Robinson, Jan O. Korbel, Institut Curie, PSL Research University, CNRS UMR, INSERM, Orsay, France. Université Paris Sud, Université Paris- Saclay, CNRS UMR 3347, INSERM U1021, Orsay, France., and Institut Curie [Paris]
- Subjects
0301 basic medicine ,Male ,[SDV]Life Sciences [q-bio] ,Germline ,Article ,03 medical and health sciences ,0302 clinical medicine ,Germline mutation ,RNA, Transfer ,Genetic predisposition ,medicine ,Humans ,Sonic hedgehog ,Cerebellar Neoplasms ,Child ,ComputingMilieux_MISCELLANEOUS ,Germ-Line Mutation ,Genetics ,Medulloblastoma ,Multidisciplinary ,biology ,Cancer ,medicine.disease ,3. Good health ,Pedigree ,030104 developmental biology ,PTCH1 ,030220 oncology & carcinogenesis ,biology.protein ,Female ,Translational elongation ,Transcriptional Elongation Factors - Abstract
Cancer genomics has illuminated a wide spectrum of genes and core molecular processes contributing to human malignancy. Still, the genetic and molecular basis of many cancers remains only partially explained. Genetic predisposition accounts for 5-10% of cancer diagnoses(1,2) and genetic events cooperating with known somatic driver events are poorly understood. Analyzing established cancer predisposition genes in medulloblastoma (MB), a malignant childhood brain tumor, we recently identified pathogenic germline variants that account for 5% of all MB patients(3). Here, by extending our previous analysis to include all protein-coding genes, we discovered and replicated rare germline loss-of-function (LoF) variants across Elongator Complex Protein 1 (ELP1) on 9q31.3 in 15% of pediatric MB(SHH) cases, thus implicating ELP1 as the most common MB predisposition gene and increasing genetic predisposition to 40% for pediatric MB(SHH). Inheritance was verified based on parent-offspring and pedigree analysis, which identified two families with a history of pediatric MB. ELP1-associated MBs were restricted to the molecular SHHα subtype(4) and were characterized by universal biallelic inactivation of ELP1 due to somatic loss of chromosome 9q. The majority of ELP1-associated MBs exhibited co-occurring somatic PTCH1 (9q22.32) alterations, suggesting that ELP1-deficiency predisposes to tumor development in combination with constitutive activation of SHH signaling. ELP1 is an essential subunit of the evolutionary conserved Elongator complex, whose primary function is to enable efficient translational elongation through tRNA modifications at the wobble (U(34)) position(5,6). Biochemical, transcriptional, and proteomic analyses revealed that ELP1-associated MB(SHH) are characterized by a destabilized core Elongator complex, loss of Elongator-dependent tRNA wobble modifications, codon-dependent translational reprogramming, and induction of the unfolded protein response (UPR), consistent with deregulation of protein homeostasis due to Elongator-deficiency in model systems(7–9). Our findings suggest that genetic predisposition to proteome instability is a previously underappreciated determinant in the pathogenesis of pediatric brain cancer. These results provide a strong rationale for further investigating the role of protein homeostasis in other cancer types and potential opportunities for novel therapeutic interference.
- Published
- 2020
50. Clinical cancer genomic profiling by three-platform sequencing of whole genome, whole exome and transcriptome
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Andrew Thrasher, Michael Rusch, Ruth G. Tatevossian, Yanling Liu, Joy Nakitandwe, Xiang Chen, Tanja A. Gruber, Jeffery M. Klco, Dale Hedges, Matthew Parker, Bhavin Vadodaria, Xiaotu Ma, Michael N. Edmonson, Susana C. Raimondi, Rose B. McGee, Scott Newman, Donald Yergeau, Sheila A. Shurtleff, Erin Hedlund, John Easton, Kohei Hagiwara, Aman Patel, James R. Downing, Michael Walsh, James McMurry, Jiali Gu, Giles W. Robinson, David W. Ellison, Jinghui Zhang, Yongjin Li, Zhaojie Zhang, Jared Becksfort, and Yuannian Jiao
- Subjects
0301 basic medicine ,Science ,General Physics and Astronomy ,Genomics ,Computational biology ,Biology ,Genome ,Article ,General Biochemistry, Genetics and Molecular Biology ,Transcriptome ,03 medical and health sciences ,Germline mutation ,Neoplasms ,Humans ,Exome ,Child ,Indel ,lcsh:Science ,Multidisciplinary ,Genome, Human ,Genetic Variation ,Sequence Analysis, DNA ,General Chemistry ,Pediatric cancer ,3. Good health ,030104 developmental biology ,Human genome ,lcsh:Q - Abstract
To evaluate the potential of an integrated clinical test to detect diverse classes of somatic and germline mutations relevant to pediatric oncology, we performed three-platform whole-genome (WGS), whole exome (WES) and transcriptome (RNA-Seq) sequencing of tumors and normal tissue from 78 pediatric cancer patients in a CLIA-certified, CAP-accredited laboratory. Our analysis pipeline achieves high accuracy by cross-validating variants between sequencing types, thereby removing the need for confirmatory testing, and facilitates comprehensive reporting in a clinically-relevant timeframe. Three-platform sequencing has a positive predictive value of 97–99, 99, and 91% for somatic SNVs, indels and structural variations, respectively, based on independent experimental verification of 15,225 variants. We report 240 pathogenic variants across all cases, including 84 of 86 known from previous diagnostic testing (98% sensitivity). Combined WES and RNA-Seq, the current standard for precision oncology, achieved only 78% sensitivity. These results emphasize the critical need for incorporating WGS in pediatric oncology testing., Clinical oncology is rapidly adopting next-generation sequencing technology for nucleotide variant and indel detection. Here the authors present a three-platform approach (whole-genome, whole-exome, and whole-transcriptome) in pediatric patients for the detection of diverse types of germline and somatic variants.
- Published
- 2018
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