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The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data

BACKGROUND: Acute T-cell lymphoblastic leukaemia (T-ALL) is an aggressive disorder derived from immature thymocytes. The variability observed in clinical responses on this type of tumours to treatments, the high toxicity of current protocols and the poor prognosis of patients with relapse or refract...

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Autores principales: Fernández-Navarro, Pablo, López-Nieva, Pilar, Piñeiro-Yañez, Elena, Carreño-Tarragona, Gonzalo, Martinez-López, Joaquín, Sánchez Pérez, Raúl, Aroca, Ángel, Al-Shahrour, Fátima, Cobos-Fernández, María Ángeles, Fernández-Piqueras, José
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6815385/
https://www.ncbi.nlm.nih.gov/pubmed/31655559
http://dx.doi.org/10.1186/s12885-019-6209-9
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author Fernández-Navarro, Pablo
López-Nieva, Pilar
Piñeiro-Yañez, Elena
Carreño-Tarragona, Gonzalo
Martinez-López, Joaquín
Sánchez Pérez, Raúl
Aroca, Ángel
Al-Shahrour, Fátima
Cobos-Fernández, María Ángeles
Fernández-Piqueras, José
author_facet Fernández-Navarro, Pablo
López-Nieva, Pilar
Piñeiro-Yañez, Elena
Carreño-Tarragona, Gonzalo
Martinez-López, Joaquín
Sánchez Pérez, Raúl
Aroca, Ángel
Al-Shahrour, Fátima
Cobos-Fernández, María Ángeles
Fernández-Piqueras, José
author_sort Fernández-Navarro, Pablo
collection PubMed
description BACKGROUND: Acute T-cell lymphoblastic leukaemia (T-ALL) is an aggressive disorder derived from immature thymocytes. The variability observed in clinical responses on this type of tumours to treatments, the high toxicity of current protocols and the poor prognosis of patients with relapse or refractory make it urgent to find less toxic and more effective therapies in the context of a personalized medicine of precision. METHODS: Whole exome sequencing and RNAseq were performed on DNA and RNA respectively, extracted of a bone marrow sample from a patient diagnosed with tumour primary T-ALL and double negative thymocytes from thymus control samples. We used PanDrugs, a computational resource to propose pharmacological therapies based on our experimental results, including lists of variants and genes. We extend the possible therapeutic options for the patient by taking into account multiple genomic events potentially sensitive to a treatment, the context of the pathway and the pharmacological evidence already known by large-scale experiments. RESULTS: As a proof-of-principle we used next-generation-sequencing technologies (Whole Exome Sequencing and RNA-Sequencing) in a case of diagnosed Pro-T acute lymphoblastic leukaemia. We identified 689 disease-causing mutations involving 308 genes, as well as multiple fusion transcript variants, alternative splicing, and 6652 genes with at least one principal isoform significantly deregulated. Only 12 genes, with 27 pathogenic gene variants, were among the most frequently mutated ones in this type of lymphoproliferative disorder. Among them, 5 variants detected in CTCF, FBXW7, JAK1, NOTCH1 and WT1 genes have not yet been reported in T-ALL pathogenesis. CONCLUSIONS: Personalized genomic medicine is a therapeutic approach involving the use of an individual’s information data to tailor drug therapy. Implementing bioinformatics platform PanDrugs enables us to propose a prioritized list of anticancer drugs as the best theoretical therapeutic candidates to treat this patient has been the goal of this article. Of note, most of the proposed drugs are not being yet considered in the clinical practice of this type of cancer opening up the approach of new treatment possibilities.
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spelling pubmed-68153852019-10-31 The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data Fernández-Navarro, Pablo López-Nieva, Pilar Piñeiro-Yañez, Elena Carreño-Tarragona, Gonzalo Martinez-López, Joaquín Sánchez Pérez, Raúl Aroca, Ángel Al-Shahrour, Fátima Cobos-Fernández, María Ángeles Fernández-Piqueras, José BMC Cancer Research Article BACKGROUND: Acute T-cell lymphoblastic leukaemia (T-ALL) is an aggressive disorder derived from immature thymocytes. The variability observed in clinical responses on this type of tumours to treatments, the high toxicity of current protocols and the poor prognosis of patients with relapse or refractory make it urgent to find less toxic and more effective therapies in the context of a personalized medicine of precision. METHODS: Whole exome sequencing and RNAseq were performed on DNA and RNA respectively, extracted of a bone marrow sample from a patient diagnosed with tumour primary T-ALL and double negative thymocytes from thymus control samples. We used PanDrugs, a computational resource to propose pharmacological therapies based on our experimental results, including lists of variants and genes. We extend the possible therapeutic options for the patient by taking into account multiple genomic events potentially sensitive to a treatment, the context of the pathway and the pharmacological evidence already known by large-scale experiments. RESULTS: As a proof-of-principle we used next-generation-sequencing technologies (Whole Exome Sequencing and RNA-Sequencing) in a case of diagnosed Pro-T acute lymphoblastic leukaemia. We identified 689 disease-causing mutations involving 308 genes, as well as multiple fusion transcript variants, alternative splicing, and 6652 genes with at least one principal isoform significantly deregulated. Only 12 genes, with 27 pathogenic gene variants, were among the most frequently mutated ones in this type of lymphoproliferative disorder. Among them, 5 variants detected in CTCF, FBXW7, JAK1, NOTCH1 and WT1 genes have not yet been reported in T-ALL pathogenesis. CONCLUSIONS: Personalized genomic medicine is a therapeutic approach involving the use of an individual’s information data to tailor drug therapy. Implementing bioinformatics platform PanDrugs enables us to propose a prioritized list of anticancer drugs as the best theoretical therapeutic candidates to treat this patient has been the goal of this article. Of note, most of the proposed drugs are not being yet considered in the clinical practice of this type of cancer opening up the approach of new treatment possibilities. BioMed Central 2019-10-26 /pmc/articles/PMC6815385/ /pubmed/31655559 http://dx.doi.org/10.1186/s12885-019-6209-9 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Fernández-Navarro, Pablo
López-Nieva, Pilar
Piñeiro-Yañez, Elena
Carreño-Tarragona, Gonzalo
Martinez-López, Joaquín
Sánchez Pérez, Raúl
Aroca, Ángel
Al-Shahrour, Fátima
Cobos-Fernández, María Ángeles
Fernández-Piqueras, José
The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data
title The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data
title_full The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data
title_fullStr The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data
title_full_unstemmed The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data
title_short The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data
title_sort use of pandrugs to prioritize anticancer drug treatments in a case of t-all based on individual genomic data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6815385/
https://www.ncbi.nlm.nih.gov/pubmed/31655559
http://dx.doi.org/10.1186/s12885-019-6209-9
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