Title |
Recurrent Somatic Structural Variations Contribute to Tumorigenesis in Pediatric Osteosarcoma
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Published in |
Cell Reports, April 2014
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DOI | 10.1016/j.celrep.2014.03.003 |
Pubmed ID | |
Authors |
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, Michael A. Dyer, St. Jude Children’s Research Hospital–Washington University Pediatric Cancer Genome Project |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
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France | 1 | 50% |
United States | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 50% |
Science communicators (journalists, bloggers, editors) | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | <1% |
Germany | 2 | <1% |
Netherlands | 1 | <1% |
Korea, Republic of | 1 | <1% |
Italy | 1 | <1% |
Switzerland | 1 | <1% |
Singapore | 1 | <1% |
Canada | 1 | <1% |
Spain | 1 | <1% |
Other | 1 | <1% |
Unknown | 376 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 78 | 20% |
Researcher | 67 | 17% |
Student > Master | 41 | 11% |
Student > Bachelor | 35 | 9% |
Other | 18 | 5% |
Other | 46 | 12% |
Unknown | 104 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 96 | 25% |
Medicine and Dentistry | 72 | 19% |
Agricultural and Biological Sciences | 56 | 14% |
Immunology and Microbiology | 10 | 3% |
Pharmacology, Toxicology and Pharmaceutical Science | 7 | 2% |
Other | 36 | 9% |
Unknown | 112 | 29% |