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PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data
BACKGROUND: Large-sequencing cancer genome projects have shown that tumors have thousands of molecular alterations and their frequency is highly heterogeneous. In such scenarios, physicians and oncologists routinely face lists of cancer genomic alterations where only a minority of them are relevant...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977747/ https://www.ncbi.nlm.nih.gov/pubmed/29848362 http://dx.doi.org/10.1186/s13073-018-0546-1 |
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author | Piñeiro-Yáñez, Elena Reboiro-Jato, Miguel Gómez-López, Gonzalo Perales-Patón, Javier Troulé, Kevin Rodríguez, José Manuel Tejero, Héctor Shimamura, Takeshi López-Casas, Pedro Pablo Carretero, Julián Valencia, Alfonso Hidalgo, Manuel Glez-Peña, Daniel Al-Shahrour, Fátima |
author_facet | Piñeiro-Yáñez, Elena Reboiro-Jato, Miguel Gómez-López, Gonzalo Perales-Patón, Javier Troulé, Kevin Rodríguez, José Manuel Tejero, Héctor Shimamura, Takeshi López-Casas, Pedro Pablo Carretero, Julián Valencia, Alfonso Hidalgo, Manuel Glez-Peña, Daniel Al-Shahrour, Fátima |
author_sort | Piñeiro-Yáñez, Elena |
collection | PubMed |
description | BACKGROUND: Large-sequencing cancer genome projects have shown that tumors have thousands of molecular alterations and their frequency is highly heterogeneous. In such scenarios, physicians and oncologists routinely face lists of cancer genomic alterations where only a minority of them are relevant biomarkers to drive clinical decision-making. For this reason, the medical community agrees on the urgent need of methodologies to establish the relevance of tumor alterations, assisting in genomic profile interpretation, and, more importantly, to prioritize those that could be clinically actionable for cancer therapy. RESULTS: We present PanDrugs, a new computational methodology to guide the selection of personalized treatments in cancer patients using the variant lists provided by genome-wide sequencing analyses. PanDrugs offers the largest database of drug-target associations available from well-known targeted therapies to preclinical drugs. Scoring data-driven gene cancer relevance and drug feasibility PanDrugs interprets genomic alterations and provides a prioritized evidence-based list of anticancer therapies. Our tool represents the first drug prescription strategy applying a rational based on pathway context, multi-gene markers impact and information provided by functional experiments. Our approach has been systematically applied to TCGA patients and successfully validated in a cancer case study with a xenograft mouse model demonstrating its utility. CONCLUSIONS: PanDrugs is a feasible method to identify potentially druggable molecular alterations and prioritize drugs to facilitate the interpretation of genomic landscape and clinical decision-making in cancer patients. Our approach expands the search of druggable genomic alterations from the concept of cancer driver genes to the druggable pathway context extending anticancer therapeutic options beyond already known cancer genes. The methodology is public and easily integratable with custom pipelines through its programmatic API or its docker image. The PanDrugs webtool is freely accessible at http://www.pandrugs.org. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13073-018-0546-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5977747 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-59777472018-06-06 PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data Piñeiro-Yáñez, Elena Reboiro-Jato, Miguel Gómez-López, Gonzalo Perales-Patón, Javier Troulé, Kevin Rodríguez, José Manuel Tejero, Héctor Shimamura, Takeshi López-Casas, Pedro Pablo Carretero, Julián Valencia, Alfonso Hidalgo, Manuel Glez-Peña, Daniel Al-Shahrour, Fátima Genome Med Software BACKGROUND: Large-sequencing cancer genome projects have shown that tumors have thousands of molecular alterations and their frequency is highly heterogeneous. In such scenarios, physicians and oncologists routinely face lists of cancer genomic alterations where only a minority of them are relevant biomarkers to drive clinical decision-making. For this reason, the medical community agrees on the urgent need of methodologies to establish the relevance of tumor alterations, assisting in genomic profile interpretation, and, more importantly, to prioritize those that could be clinically actionable for cancer therapy. RESULTS: We present PanDrugs, a new computational methodology to guide the selection of personalized treatments in cancer patients using the variant lists provided by genome-wide sequencing analyses. PanDrugs offers the largest database of drug-target associations available from well-known targeted therapies to preclinical drugs. Scoring data-driven gene cancer relevance and drug feasibility PanDrugs interprets genomic alterations and provides a prioritized evidence-based list of anticancer therapies. Our tool represents the first drug prescription strategy applying a rational based on pathway context, multi-gene markers impact and information provided by functional experiments. Our approach has been systematically applied to TCGA patients and successfully validated in a cancer case study with a xenograft mouse model demonstrating its utility. CONCLUSIONS: PanDrugs is a feasible method to identify potentially druggable molecular alterations and prioritize drugs to facilitate the interpretation of genomic landscape and clinical decision-making in cancer patients. Our approach expands the search of druggable genomic alterations from the concept of cancer driver genes to the druggable pathway context extending anticancer therapeutic options beyond already known cancer genes. The methodology is public and easily integratable with custom pipelines through its programmatic API or its docker image. The PanDrugs webtool is freely accessible at http://www.pandrugs.org. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13073-018-0546-1) contains supplementary material, which is available to authorized users. BioMed Central 2018-05-31 /pmc/articles/PMC5977747/ /pubmed/29848362 http://dx.doi.org/10.1186/s13073-018-0546-1 Text en © The Author(s). 2018 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 | Software Piñeiro-Yáñez, Elena Reboiro-Jato, Miguel Gómez-López, Gonzalo Perales-Patón, Javier Troulé, Kevin Rodríguez, José Manuel Tejero, Héctor Shimamura, Takeshi López-Casas, Pedro Pablo Carretero, Julián Valencia, Alfonso Hidalgo, Manuel Glez-Peña, Daniel Al-Shahrour, Fátima PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data |
title | PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data |
title_full | PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data |
title_fullStr | PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data |
title_full_unstemmed | PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data |
title_short | PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data |
title_sort | pandrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977747/ https://www.ncbi.nlm.nih.gov/pubmed/29848362 http://dx.doi.org/10.1186/s13073-018-0546-1 |
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