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Synthetic lethal combinations of low-toxicity drugs for breast cancer identified in silico by genetic screens in yeast

In recent years, the concept of synthetic lethality, describing a cellular state where loss of two genes leads to a non-viable phenotype while loss of one gene can be compensated, has emerged as a novel strategy for cancer therapy. Various compounds targeting synthetic lethal pathways are either und...

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Autores principales: Marhold, Maximilian, Tomasich, Erwin, Schwarz, Michael, Udovica, Simon, Heinzel, Andreas, Mayer, Paul, Horak, Peter, Perco, Paul, Krainer, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6284748/
https://www.ncbi.nlm.nih.gov/pubmed/30555636
http://dx.doi.org/10.18632/oncotarget.26372
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author Marhold, Maximilian
Tomasich, Erwin
Schwarz, Michael
Udovica, Simon
Heinzel, Andreas
Mayer, Paul
Horak, Peter
Perco, Paul
Krainer, Michael
author_facet Marhold, Maximilian
Tomasich, Erwin
Schwarz, Michael
Udovica, Simon
Heinzel, Andreas
Mayer, Paul
Horak, Peter
Perco, Paul
Krainer, Michael
author_sort Marhold, Maximilian
collection PubMed
description In recent years, the concept of synthetic lethality, describing a cellular state where loss of two genes leads to a non-viable phenotype while loss of one gene can be compensated, has emerged as a novel strategy for cancer therapy. Various compounds targeting synthetic lethal pathways are either under clinical investigation or are already routinely used in multiple cancer entities such as breast cancer. Most of them target the well-described synthetic lethal interplay between PARP1 and BRCA1/2. In our study, we investigated, using an in silico methodological approach, clinically utilized drug combinations for breast cancer treatment, by correlating their known molecular targets with known homologous interaction partners that cause synthetic lethality in yeast. Further, by creating a machine-learning algorithm, we were able to suggest novel synthetic lethal drug combinations of low-toxicity drugs in breast cancer and showed their negative effects on cancer cell viability in vitro. Our findings foster the understanding of evolutionarily conserved synthetic lethality in breast cancer cells and might lead to new drug combinations with favorable toxicity profile in this entity.
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spelling pubmed-62847482018-12-14 Synthetic lethal combinations of low-toxicity drugs for breast cancer identified in silico by genetic screens in yeast Marhold, Maximilian Tomasich, Erwin Schwarz, Michael Udovica, Simon Heinzel, Andreas Mayer, Paul Horak, Peter Perco, Paul Krainer, Michael Oncotarget Research Paper In recent years, the concept of synthetic lethality, describing a cellular state where loss of two genes leads to a non-viable phenotype while loss of one gene can be compensated, has emerged as a novel strategy for cancer therapy. Various compounds targeting synthetic lethal pathways are either under clinical investigation or are already routinely used in multiple cancer entities such as breast cancer. Most of them target the well-described synthetic lethal interplay between PARP1 and BRCA1/2. In our study, we investigated, using an in silico methodological approach, clinically utilized drug combinations for breast cancer treatment, by correlating their known molecular targets with known homologous interaction partners that cause synthetic lethality in yeast. Further, by creating a machine-learning algorithm, we were able to suggest novel synthetic lethal drug combinations of low-toxicity drugs in breast cancer and showed their negative effects on cancer cell viability in vitro. Our findings foster the understanding of evolutionarily conserved synthetic lethality in breast cancer cells and might lead to new drug combinations with favorable toxicity profile in this entity. Impact Journals LLC 2018-11-20 /pmc/articles/PMC6284748/ /pubmed/30555636 http://dx.doi.org/10.18632/oncotarget.26372 Text en Copyright: © 2018 Marhold et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Marhold, Maximilian
Tomasich, Erwin
Schwarz, Michael
Udovica, Simon
Heinzel, Andreas
Mayer, Paul
Horak, Peter
Perco, Paul
Krainer, Michael
Synthetic lethal combinations of low-toxicity drugs for breast cancer identified in silico by genetic screens in yeast
title Synthetic lethal combinations of low-toxicity drugs for breast cancer identified in silico by genetic screens in yeast
title_full Synthetic lethal combinations of low-toxicity drugs for breast cancer identified in silico by genetic screens in yeast
title_fullStr Synthetic lethal combinations of low-toxicity drugs for breast cancer identified in silico by genetic screens in yeast
title_full_unstemmed Synthetic lethal combinations of low-toxicity drugs for breast cancer identified in silico by genetic screens in yeast
title_short Synthetic lethal combinations of low-toxicity drugs for breast cancer identified in silico by genetic screens in yeast
title_sort synthetic lethal combinations of low-toxicity drugs for breast cancer identified in silico by genetic screens in yeast
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6284748/
https://www.ncbi.nlm.nih.gov/pubmed/30555636
http://dx.doi.org/10.18632/oncotarget.26372
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