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

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 cu...

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Autores principales: Pavlovic, Sonja, Kotur, Nikola, Stankovic, Biljana, Zukic, Branka, Gasic, Vladimir, Dokmanovic, Lidija
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471971/
https://www.ncbi.nlm.nih.gov/pubmed/30832275
http://dx.doi.org/10.3390/genes10030191
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author Pavlovic, Sonja
Kotur, Nikola
Stankovic, Biljana
Zukic, Branka
Gasic, Vladimir
Dokmanovic, Lidija
author_facet Pavlovic, Sonja
Kotur, Nikola
Stankovic, Biljana
Zukic, Branka
Gasic, Vladimir
Dokmanovic, Lidija
author_sort Pavlovic, Sonja
collection PubMed
description 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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spelling pubmed-64719712019-04-27 Pharmacogenomic and Pharmacotranscriptomic Profiling of Childhood Acute Lymphoblastic Leukemia: Paving the Way to Personalized Treatment Pavlovic, Sonja Kotur, Nikola Stankovic, Biljana Zukic, Branka Gasic, Vladimir Dokmanovic, Lidija Genes (Basel) Review 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. MDPI 2019-03-01 /pmc/articles/PMC6471971/ /pubmed/30832275 http://dx.doi.org/10.3390/genes10030191 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Pavlovic, Sonja
Kotur, Nikola
Stankovic, Biljana
Zukic, Branka
Gasic, Vladimir
Dokmanovic, Lidija
Pharmacogenomic and Pharmacotranscriptomic Profiling of Childhood Acute Lymphoblastic Leukemia: Paving the Way to Personalized Treatment
title Pharmacogenomic and Pharmacotranscriptomic Profiling of Childhood Acute Lymphoblastic Leukemia: Paving the Way to Personalized Treatment
title_full Pharmacogenomic and Pharmacotranscriptomic Profiling of Childhood Acute Lymphoblastic Leukemia: Paving the Way to Personalized Treatment
title_fullStr Pharmacogenomic and Pharmacotranscriptomic Profiling of Childhood Acute Lymphoblastic Leukemia: Paving the Way to Personalized Treatment
title_full_unstemmed Pharmacogenomic and Pharmacotranscriptomic Profiling of Childhood Acute Lymphoblastic Leukemia: Paving the Way to Personalized Treatment
title_short Pharmacogenomic and Pharmacotranscriptomic Profiling of Childhood Acute Lymphoblastic Leukemia: Paving the Way to Personalized Treatment
title_sort pharmacogenomic and pharmacotranscriptomic profiling of childhood acute lymphoblastic leukemia: paving the way to personalized treatment
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471971/
https://www.ncbi.nlm.nih.gov/pubmed/30832275
http://dx.doi.org/10.3390/genes10030191
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