Pharmacogenomic and Pharmacotranscriptomic Profiling of Childhood Acute Lymphoblastic Leukemia: Paving the Way to Personalized Treatment

被引:27
作者
Pavlovic, Sonja [1 ]
Kotur, Nikola [1 ]
Stankovic, Biljana [1 ]
Zukic, Branka [1 ]
Gasic, Vladimir [1 ]
Dokmanovic, Lidija [2 ,3 ]
机构
[1] Univ Belgrade, Inst Mol Genet & Genet Engn, Lab Mol Biomed, Belgrade 11000, Serbia
[2] Univ Childrens Hosp, Belgrade 11000, Serbia
[3] Univ Belgrade, Fac Med, Belgrade 11000, Serbia
来源
GENES | 2019年 / 10卷 / 03期
关键词
pharmacogenomics; pharmacotranscriptomics; high-throughput analysis; childhood acute lymphoblastic leukemia; ANTHRACYCLINE-INDUCED CARDIOTOXICITY; METHOTREXATE-RELATED TOXICITY; GLUCOCORTICOID-RECEPTOR GENE; REDUCED FOLATE CARRIER; THIOPURINE METHYLTRANSFERASE ACTIVITY; DIHYDROFOLATE-REDUCTASE EXPRESSION; ACUTE LYMPHOCYTIC-LEUKEMIA; PROMOTER VARIABLE NUMBER; S-TRANSFERASE GENES; SRC-FAMILY KINASES;
D O I
10.3390/genes10030191
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Personalized medicine is focused on research disciplines which contribute to the individualization of therapy, like pharmacogenomics and pharmacotranscriptomics. Acute lymphoblastic leukemia (ALL) is the most common malignancy of childhood. It is one of the pediatric malignancies with the highest cure rate, but still a lethal outcome due to therapy accounts for 1-3% of deaths. Further improvement of treatment protocols is needed through the implementation of pharmacogenomics and pharmacotranscriptomics. Emerging high-throughput technologies, including microarrays and next-generation sequencing, have provided an enormous amount of molecular data with the potential to be implemented in childhood ALL treatment protocols. In the current review, we summarized the contribution of these novel technologies to the pharmacogenomics and pharmacotranscriptomics of childhood ALL. We have presented data on molecular markers responsible for the efficacy, side effects, and toxicity of the drugs commonly used for childhood ALL treatment, i.e., glucocorticoids, vincristine, asparaginase, anthracyclines, thiopurines, and methotrexate. Big data was generated using high-throughput technologies, but their implementation in clinical practice is poor. Research efforts should be focused on data analysis and designing prediction models using machine learning algorithms. Bioinformatics tools and the implementation of artificial i Lack of association of the CEP72 rs924607 TT genotype with intelligence are expected to open the door wide for personalized medicine in the clinical practice of childhood ALL.
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页数:31
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