Title |
Influence of UGT1A1 polymorphisms on the outcome of acute myeloid leukemia patients treated with cytarabine-base regimens
|
---|---|
Published in |
Journal of Translational Medicine, July 2018
|
DOI | 10.1186/s12967-018-1579-3 |
Pubmed ID | |
Authors |
Peng Chen, Ke-Wei Zhu, Dao-Yu Zhang, Han Yan, Han Liu, Yan-Ling Liu, Shan Cao, Gan Zhou, Hui Zeng, Shu-Ping Chen, Xie-Lan Zhao, Jing Yang, Xiao-Ping Chen |
Abstract |
UDP-glucuronosyltransferase 1A subfamily (UGT1A) enzymes can inactivate cytarabine (Ara-C) by glucuronidation, and thus serves as candidate genes for interindividual difference in Ara-C response. UGT1A1 is a major UGT1A isoform expressed in human liver. UGT1A1*6 and *28 polymorphisms resulting in reduced UGT1A1 activity were genotyped in 726 adult acute myeloid leukemia (AML) patients treated with Ara-C based regimens. Influences of both polymorphisms on chemosensitivity and disease prognosis of the patients were evaluated. After one or two courses of Ara-C based induction chemotherapy, the complete remission (CR) rate was significantly higher in patients carrying the UGT1A1*6 (77.0%) or the UGT1A1*28 (76.4%) alleles as compared with corresponding wild-type homozygotes (66.9 and 68.5%, respectively). Carriers of the UGT1A1*6 or *28 alleles showed significantly decreased risk of non-CR (OR = 0.528, 95% CI 0.379-0.737, P = 1.7 × 10-4) and better overall survival (HR = 0.787, 95% CI 0.627-0.990, P = 0.040) as compared with homozygotes for both polymorphisms. Our results suggest that UGT1A1*28 and UGT1A1*6 are associated with improved clinical outcomes in Chinese AML patients treated with Ara-C. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 14 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Other | 2 | 14% |
Student > Master | 2 | 14% |
Lecturer | 1 | 7% |
Student > Bachelor | 1 | 7% |
Student > Doctoral Student | 1 | 7% |
Other | 2 | 14% |
Unknown | 5 | 36% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 3 | 21% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 7% |
Biochemistry, Genetics and Molecular Biology | 1 | 7% |
Computer Science | 1 | 7% |
Agricultural and Biological Sciences | 1 | 7% |
Other | 2 | 14% |
Unknown | 5 | 36% |