| Title |
Dynamics of clonal evolution in myelodysplastic syndromes
|
|---|---|
| Published in |
Nature Genetics, December 2016
|
| DOI | 10.1038/ng.3742 |
| Pubmed ID | |
| Authors |
Hideki Makishima, Tetsuichi Yoshizato, Kenichi Yoshida, Mikkael A Sekeres, Tomas Radivoyevitch, Hiromichi Suzuki, Bartlomiej Przychodzen, Yasunobu Nagata, Manja Meggendorfer, Masashi Sanada, Yusuke Okuno, Cassandra Hirsch, Teodora Kuzmanovic, Yusuke Sato, Aiko Sato-Otsubo, Thomas LaFramboise, Naoko Hosono, Yuichi Shiraishi, Kenichi Chiba, Claudia Haferlach, Wolfgang Kern, Hiroko Tanaka, Yusuke Shiozawa, Inés Gómez-Seguí, Holleh D Husseinzadeh, Swapna Thota, Kathryn M Guinta, Brittney Dienes, Tsuyoshi Nakamaki, Shuichi Miyawaki, Yogen Saunthararajah, Shigeru Chiba, Satoru Miyano, Lee-Yung Shih, Torsten Haferlach, Seishi Ogawa, Jaroslaw P Maciejewski |
| Abstract |
To elucidate differential roles of mutations in myelodysplastic syndromes (MDS), we investigated clonal dynamics using whole-exome and/or targeted sequencing of 699 patients, of whom 122 were analyzed longitudinally. Including the results from previous reports, we assessed a total of 2,250 patients for mutational enrichment patterns. During progression, the number of mutations, their diversity and clone sizes increased, with alterations frequently present in dominant clones with or without their sweeping previous clones. Enriched in secondary acute myeloid leukemia (sAML; in comparison to high-risk MDS), FLT3, PTPN11, WT1, IDH1, NPM1, IDH2 and NRAS mutations (type 1) tended to be newly acquired, and were associated with faster sAML progression and a shorter overall survival time. Significantly enriched in high-risk MDS (in comparison to low-risk MDS), TP53, GATA2, KRAS, RUNX1, STAG2, ASXL1, ZRSR2 and TET2 mutations (type 2) had a weaker impact on sAML progression and overall survival than type-1 mutations. The distinct roles of type-1 and type-2 mutations suggest their potential utility in disease monitoring. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 19 | 48% |
| Japan | 5 | 13% |
| Belgium | 2 | 5% |
| United Kingdom | 2 | 5% |
| Romania | 1 | 3% |
| Australia | 1 | 3% |
| Mexico | 1 | 3% |
| United Arab Emirates | 1 | 3% |
| Montenegro | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 7 | 18% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 19 | 48% |
| Scientists | 17 | 43% |
| Practitioners (doctors, other healthcare professionals) | 3 | 8% |
| Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | <1% |
| Peru | 1 | <1% |
| Netherlands | 1 | <1% |
| Japan | 1 | <1% |
| France | 1 | <1% |
| Unknown | 369 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 66 | 18% |
| Researcher | 60 | 16% |
| Student > Master | 28 | 7% |
| Other | 27 | 7% |
| Student > Bachelor | 26 | 7% |
| Other | 66 | 18% |
| Unknown | 102 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 96 | 26% |
| Biochemistry, Genetics and Molecular Biology | 91 | 24% |
| Agricultural and Biological Sciences | 43 | 11% |
| Engineering | 8 | 2% |
| Immunology and Microbiology | 4 | 1% |
| Other | 26 | 7% |
| Unknown | 107 | 29% |