| Title |
Copy number abnormality of acute lymphoblastic leukemia cell lines based on their genetic subtypes
|
|---|---|
| Published in |
International Journal of Hematology, May 2018
|
| DOI | 10.1007/s12185-018-2474-7 |
| Pubmed ID | |
| Authors |
Chihiro Tomoyasu, Toshihiko Imamura, Toshihiro Tomii, Mio Yano, Daisuke Asai, Hiroaki Goto, Akira Shimada, Masashi Sanada, Shotaro Iwamoto, Junko Takita, Masayoshi Minegishi, Takeshi Inukai, Kanji Sugita, Hajime Hosoi |
| Abstract |
In this study, we performed genetic analysis of 83 B cell precursor acute lymphoblastic leukemia (B-ALL) cell lines. First, we performed multiplex ligation-dependent probe amplification analysis to identify copy number abnormalities (CNAs) in eight genes associated with B-ALL according to genetic subtype. In Ph+ B-ALL cell lines, the frequencies of IKZF1, CDKN2A/2B, BTG1, and PAX5 deletion were significantly higher than those in Ph- B-ALL cell lines. The frequency of CDKN2A/2B deletion in KMT2A rearranged cell lines was significantly lower than that in non-KMT2A rearranged cell lines. These findings suggest that CNAs are correlated with genetic subtype in B-ALL cell lines. In addition, we determined that three B-other ALL cell lines had IKZF1 deletions (YCUB-5, KOPN49, and KOPN75); we therefore performed comprehensive genetic analysis of these cell lines. YCUB-5, KOPN49, and KOPN75 had P2RY8-CRLF2, IgH-CRLF2, and PAX5-ETV6 fusions, respectively. Moreover, targeted capture sequencing revealed that YCUB-5 had JAK2 R683I and KRAS G12D, and KOPN49 had JAK2 R683G and KRAS G13D mutations. These data may contribute to progress in the field of leukemia research. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 31% |
| Student > Master | 2 | 15% |
| Student > Doctoral Student | 1 | 8% |
| Student > Bachelor | 1 | 8% |
| Other | 1 | 8% |
| Other | 3 | 23% |
| Unknown | 1 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 6 | 46% |
| Biochemistry, Genetics and Molecular Biology | 4 | 31% |
| Immunology and Microbiology | 1 | 8% |
| Nursing and Health Professions | 1 | 8% |
| Unknown | 1 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 November 2018.
All research outputs
#18,623,070
of 23,070,218 outputs
Outputs from International Journal of Hematology
#930
of 1,415 outputs
Outputs of similar age
#255,247
of 330,209 outputs
Outputs of similar age from International Journal of Hematology
#10
of 23 outputs
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