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The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data
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...
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Published in: | BMC cancer 2019-10, Vol.19 (1), p.1005-1005, Article 1005 |
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creator | 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 |
description | 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.
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.
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.
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. |
doi_str_mv | 10.1186/s12885-019-6209-9 |
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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.
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.
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.</description><identifier>ISSN: 1471-2407</identifier><identifier>EISSN: 1471-2407</identifier><identifier>DOI: 10.1186/s12885-019-6209-9</identifier><identifier>PMID: 31655559</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Adolescent ; Alternative Splicing - genetics ; Antineoplastic agents ; Antineoplastic Agents - therapeutic use ; Cancer ; Care and treatment ; Computational biology ; Diagnosis ; DNA ; Drugs ; Exome - genetics ; Exome sequencing ; Gene Fusion - genetics ; Genes ; Genome, Human - genetics ; Genomes ; Genomics ; Genomics - methods ; High-Throughput Nucleotide Sequencing ; Humans ; Leukemia ; Lymphocytic leukemia ; Male ; Mutation - genetics ; Next-generation sequencing technologies ; PanDrugs ; Personalized precision medicine ; Precision medicine ; Precision Medicine - methods ; Precision oncology ; Precursor T-Cell Lymphoblastic Leukemia-Lymphoma - drug therapy ; RNA ; RNA sequencing ; RNA-Seq ; Spain ; T cells ; T-ALL ; Technology ; Toxicity ; Transcriptome - genetics ; Translational bioinformatics ; Tumors</subject><ispartof>BMC cancer, 2019-10, Vol.19 (1), p.1005-1005, Article 1005</ispartof><rights>COPYRIGHT 2019 BioMed Central Ltd.</rights><rights>The Author(s). 2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c597t-5c26a3759db9e7c868215e914b1512ca864dfbac6345c2659521e22b0039bd433</citedby><cites>FETCH-LOGICAL-c597t-5c26a3759db9e7c868215e914b1512ca864dfbac6345c2659521e22b0039bd433</cites><orcidid>0000-0002-9570-5542 ; 0000-0003-4520-6785 ; 0000-0003-2373-769X ; 0000-0001-6369-2444 ; 0000-0001-9427-2581 ; 0000-0003-2773-2343</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6815385/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6815385/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,37013,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31655559$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Fernández-Navarro, Pablo</creatorcontrib><creatorcontrib>López-Nieva, Pilar</creatorcontrib><creatorcontrib>Piñeiro-Yañez, Elena</creatorcontrib><creatorcontrib>Carreño-Tarragona, Gonzalo</creatorcontrib><creatorcontrib>Martinez-López, Joaquín</creatorcontrib><creatorcontrib>Sánchez Pérez, Raúl</creatorcontrib><creatorcontrib>Aroca, Ángel</creatorcontrib><creatorcontrib>Al-Shahrour, Fátima</creatorcontrib><creatorcontrib>Cobos-Fernández, María Ángeles</creatorcontrib><creatorcontrib>Fernández-Piqueras, José</creatorcontrib><title>The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data</title><title>BMC cancer</title><addtitle>BMC Cancer</addtitle><description>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.
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.
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.
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.</description><subject>Adolescent</subject><subject>Alternative Splicing - genetics</subject><subject>Antineoplastic agents</subject><subject>Antineoplastic Agents - therapeutic use</subject><subject>Cancer</subject><subject>Care and treatment</subject><subject>Computational biology</subject><subject>Diagnosis</subject><subject>DNA</subject><subject>Drugs</subject><subject>Exome - genetics</subject><subject>Exome sequencing</subject><subject>Gene Fusion - genetics</subject><subject>Genes</subject><subject>Genome, Human - genetics</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Genomics - methods</subject><subject>High-Throughput Nucleotide Sequencing</subject><subject>Humans</subject><subject>Leukemia</subject><subject>Lymphocytic leukemia</subject><subject>Male</subject><subject>Mutation - genetics</subject><subject>Next-generation sequencing technologies</subject><subject>PanDrugs</subject><subject>Personalized precision medicine</subject><subject>Precision medicine</subject><subject>Precision Medicine - methods</subject><subject>Precision oncology</subject><subject>Precursor T-Cell Lymphoblastic Leukemia-Lymphoma - drug therapy</subject><subject>RNA</subject><subject>RNA sequencing</subject><subject>RNA-Seq</subject><subject>Spain</subject><subject>T cells</subject><subject>T-ALL</subject><subject>Technology</subject><subject>Toxicity</subject><subject>Transcriptome - genetics</subject><subject>Translational bioinformatics</subject><subject>Tumors</subject><issn>1471-2407</issn><issn>1471-2407</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNptkl2P1CAUhhujcdfVH-CNITExetEVKFC4MZmsX5NMotHxmlCgHTYdGIFu1F8vs10300S44OM85w3n8FbVcwQvEeLsbUKYc1pDJGqGoajFg-ockRbVmMD24cn-rHqS0jWEqOWQP67OGsRoGeK8Omx3FkzJgtCDr8q_j9OQQA7gEF2ILrs_FiifnVZe2whMCYMcrcp763MCzgMFtJrTt_VqswFdORkQfIkZd-PMpEYwWB_2TgOjsnpaPerVmOyzu_Wi-vHxw_bqc7358ml9tdrUmoo211RjppqWCtMJ22rOOEbUCkQ6RBHWijNi-k5p1pAjSgXFyGLcQdiIzpCmuajWs64J6lqWcvYq_pZBOXl7EeIgVSyFjVYSTohgjeZdz0lrO9EKI4ziAmGE6a3Wu1nrMHV7a3SpPapxIbqMeLeTQ7iRjCPacFoEXt8JxPBzsinLvUvajqPyNkxJ4gaK8jMMi4K-nNFBlac534eiqI-4XDFIKBGEwUJd_ocq09jS6OBt78r9IuHNIqEw2f7Kg5pSkuvv35bsqxN2Z9WYdymMU3bBpyWIZlDHkFK0_X1LEJRHh8rZobI4VB4dKo_1vTjt5X3GP0s2fwG-Ct13</recordid><startdate>20191026</startdate><enddate>20191026</enddate><creator>Fernández-Navarro, Pablo</creator><creator>López-Nieva, Pilar</creator><creator>Piñeiro-Yañez, Elena</creator><creator>Carreño-Tarragona, Gonzalo</creator><creator>Martinez-López, Joaquín</creator><creator>Sánchez Pérez, Raúl</creator><creator>Aroca, Ángel</creator><creator>Al-Shahrour, Fátima</creator><creator>Cobos-Fernández, María Ángeles</creator><creator>Fernández-Piqueras, José</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-9570-5542</orcidid><orcidid>https://orcid.org/0000-0003-4520-6785</orcidid><orcidid>https://orcid.org/0000-0003-2373-769X</orcidid><orcidid>https://orcid.org/0000-0001-6369-2444</orcidid><orcidid>https://orcid.org/0000-0001-9427-2581</orcidid><orcidid>https://orcid.org/0000-0003-2773-2343</orcidid></search><sort><creationdate>20191026</creationdate><title>The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data</title><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></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c597t-5c26a3759db9e7c868215e914b1512ca864dfbac6345c2659521e22b0039bd433</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Adolescent</topic><topic>Alternative Splicing - genetics</topic><topic>Antineoplastic agents</topic><topic>Antineoplastic Agents - therapeutic use</topic><topic>Cancer</topic><topic>Care and treatment</topic><topic>Computational biology</topic><topic>Diagnosis</topic><topic>DNA</topic><topic>Drugs</topic><topic>Exome - genetics</topic><topic>Exome sequencing</topic><topic>Gene Fusion - genetics</topic><topic>Genes</topic><topic>Genome, Human - genetics</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Genomics - methods</topic><topic>High-Throughput Nucleotide Sequencing</topic><topic>Humans</topic><topic>Leukemia</topic><topic>Lymphocytic leukemia</topic><topic>Male</topic><topic>Mutation - genetics</topic><topic>Next-generation sequencing technologies</topic><topic>PanDrugs</topic><topic>Personalized precision medicine</topic><topic>Precision medicine</topic><topic>Precision Medicine - methods</topic><topic>Precision oncology</topic><topic>Precursor T-Cell Lymphoblastic Leukemia-Lymphoma - drug therapy</topic><topic>RNA</topic><topic>RNA sequencing</topic><topic>RNA-Seq</topic><topic>Spain</topic><topic>T cells</topic><topic>T-ALL</topic><topic>Technology</topic><topic>Toxicity</topic><topic>Transcriptome - genetics</topic><topic>Translational bioinformatics</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fernández-Navarro, Pablo</creatorcontrib><creatorcontrib>López-Nieva, Pilar</creatorcontrib><creatorcontrib>Piñeiro-Yañez, Elena</creatorcontrib><creatorcontrib>Carreño-Tarragona, Gonzalo</creatorcontrib><creatorcontrib>Martinez-López, Joaquín</creatorcontrib><creatorcontrib>Sánchez Pérez, Raúl</creatorcontrib><creatorcontrib>Aroca, Ángel</creatorcontrib><creatorcontrib>Al-Shahrour, Fátima</creatorcontrib><creatorcontrib>Cobos-Fernández, María Ángeles</creatorcontrib><creatorcontrib>Fernández-Piqueras, José</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>BMC cancer</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fernández-Navarro, Pablo</au><au>López-Nieva, Pilar</au><au>Piñeiro-Yañez, Elena</au><au>Carreño-Tarragona, Gonzalo</au><au>Martinez-López, Joaquín</au><au>Sánchez Pérez, Raúl</au><au>Aroca, Ángel</au><au>Al-Shahrour, Fátima</au><au>Cobos-Fernández, María Ángeles</au><au>Fernández-Piqueras, José</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data</atitle><jtitle>BMC cancer</jtitle><addtitle>BMC Cancer</addtitle><date>2019-10-26</date><risdate>2019</risdate><volume>19</volume><issue>1</issue><spage>1005</spage><epage>1005</epage><pages>1005-1005</pages><artnum>1005</artnum><issn>1471-2407</issn><eissn>1471-2407</eissn><abstract>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.
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.
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.
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.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>31655559</pmid><doi>10.1186/s12885-019-6209-9</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-9570-5542</orcidid><orcidid>https://orcid.org/0000-0003-4520-6785</orcidid><orcidid>https://orcid.org/0000-0003-2373-769X</orcidid><orcidid>https://orcid.org/0000-0001-6369-2444</orcidid><orcidid>https://orcid.org/0000-0001-9427-2581</orcidid><orcidid>https://orcid.org/0000-0003-2773-2343</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adolescent Alternative Splicing - genetics Antineoplastic agents Antineoplastic Agents - therapeutic use Cancer Care and treatment Computational biology Diagnosis DNA Drugs Exome - genetics Exome sequencing Gene Fusion - genetics Genes Genome, Human - genetics Genomes Genomics Genomics - methods High-Throughput Nucleotide Sequencing Humans Leukemia Lymphocytic leukemia Male Mutation - genetics Next-generation sequencing technologies PanDrugs Personalized precision medicine Precision medicine Precision Medicine - methods Precision oncology Precursor T-Cell Lymphoblastic Leukemia-Lymphoma - drug therapy RNA RNA sequencing RNA-Seq Spain T cells T-ALL Technology Toxicity Transcriptome - genetics Translational bioinformatics Tumors |
title | The use of PanDrugs to prioritize anticancer drug treatments in a case of T-ALL based on individual genomic data |
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