Cargando…

FUNGI: FUsioN Gene Integration toolset

MOTIVATION: Fusion genes are both useful cancer biomarkers and important drug targets. Finding relevant fusion genes is challenging due to genomic instability resulting in a high number of passenger events. To reveal and prioritize relevant gene fusion events we have developed FUsionN Gene Identific...

Descripción completa

Detalles Bibliográficos
Autores principales: Cervera, Alejandra, Rausio, Heidi, Kähkönen, Tiia, Andersson, Noora, Partel, Gabriele, Rantanen, Ville, Paciello, Giulia, Ficarra, Elisa, Hynninen, Johanna, Hietanen, Sakari, Carpén, Olli, Lehtonen, Rainer, Hautaniemi, Sampsa, Huhtinen, Kaisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504624/
https://www.ncbi.nlm.nih.gov/pubmed/33772596
http://dx.doi.org/10.1093/bioinformatics/btab206
_version_ 1784581357655031808
author Cervera, Alejandra
Rausio, Heidi
Kähkönen, Tiia
Andersson, Noora
Partel, Gabriele
Rantanen, Ville
Paciello, Giulia
Ficarra, Elisa
Hynninen, Johanna
Hietanen, Sakari
Carpén, Olli
Lehtonen, Rainer
Hautaniemi, Sampsa
Huhtinen, Kaisa
author_facet Cervera, Alejandra
Rausio, Heidi
Kähkönen, Tiia
Andersson, Noora
Partel, Gabriele
Rantanen, Ville
Paciello, Giulia
Ficarra, Elisa
Hynninen, Johanna
Hietanen, Sakari
Carpén, Olli
Lehtonen, Rainer
Hautaniemi, Sampsa
Huhtinen, Kaisa
author_sort Cervera, Alejandra
collection PubMed
description MOTIVATION: Fusion genes are both useful cancer biomarkers and important drug targets. Finding relevant fusion genes is challenging due to genomic instability resulting in a high number of passenger events. To reveal and prioritize relevant gene fusion events we have developed FUsionN Gene Identification toolset (FUNGI) that uses an ensemble of fusion detection algorithms with prioritization and visualization modules. RESULTS: We applied FUNGI to an ovarian cancer dataset of 107 tumor samples from 36 patients. Ten out of 11 detected and prioritized fusion genes were validated. Many of detected fusion genes affect the PI3K-AKT pathway with potential role in treatment resistance. AVAILABILITYAND IMPLEMENTATION: FUNGI and its documentation are available at https://bitbucket.org/alejandra_cervera/fungi as standalone or from Anduril at https://www.anduril.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
format Online
Article
Text
id pubmed-8504624
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-85046242021-10-13 FUNGI: FUsioN Gene Integration toolset Cervera, Alejandra Rausio, Heidi Kähkönen, Tiia Andersson, Noora Partel, Gabriele Rantanen, Ville Paciello, Giulia Ficarra, Elisa Hynninen, Johanna Hietanen, Sakari Carpén, Olli Lehtonen, Rainer Hautaniemi, Sampsa Huhtinen, Kaisa Bioinformatics Applications Notes MOTIVATION: Fusion genes are both useful cancer biomarkers and important drug targets. Finding relevant fusion genes is challenging due to genomic instability resulting in a high number of passenger events. To reveal and prioritize relevant gene fusion events we have developed FUsionN Gene Identification toolset (FUNGI) that uses an ensemble of fusion detection algorithms with prioritization and visualization modules. RESULTS: We applied FUNGI to an ovarian cancer dataset of 107 tumor samples from 36 patients. Ten out of 11 detected and prioritized fusion genes were validated. Many of detected fusion genes affect the PI3K-AKT pathway with potential role in treatment resistance. AVAILABILITYAND IMPLEMENTATION: FUNGI and its documentation are available at https://bitbucket.org/alejandra_cervera/fungi as standalone or from Anduril at https://www.anduril.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-03-27 /pmc/articles/PMC8504624/ /pubmed/33772596 http://dx.doi.org/10.1093/bioinformatics/btab206 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Cervera, Alejandra
Rausio, Heidi
Kähkönen, Tiia
Andersson, Noora
Partel, Gabriele
Rantanen, Ville
Paciello, Giulia
Ficarra, Elisa
Hynninen, Johanna
Hietanen, Sakari
Carpén, Olli
Lehtonen, Rainer
Hautaniemi, Sampsa
Huhtinen, Kaisa
FUNGI: FUsioN Gene Integration toolset
title FUNGI: FUsioN Gene Integration toolset
title_full FUNGI: FUsioN Gene Integration toolset
title_fullStr FUNGI: FUsioN Gene Integration toolset
title_full_unstemmed FUNGI: FUsioN Gene Integration toolset
title_short FUNGI: FUsioN Gene Integration toolset
title_sort fungi: fusion gene integration toolset
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504624/
https://www.ncbi.nlm.nih.gov/pubmed/33772596
http://dx.doi.org/10.1093/bioinformatics/btab206
work_keys_str_mv AT cerveraalejandra fungifusiongeneintegrationtoolset
AT rausioheidi fungifusiongeneintegrationtoolset
AT kahkonentiia fungifusiongeneintegrationtoolset
AT anderssonnoora fungifusiongeneintegrationtoolset
AT partelgabriele fungifusiongeneintegrationtoolset
AT rantanenville fungifusiongeneintegrationtoolset
AT paciellogiulia fungifusiongeneintegrationtoolset
AT ficarraelisa fungifusiongeneintegrationtoolset
AT hynninenjohanna fungifusiongeneintegrationtoolset
AT hietanensakari fungifusiongeneintegrationtoolset
AT carpenolli fungifusiongeneintegrationtoolset
AT lehtonenrainer fungifusiongeneintegrationtoolset
AT hautaniemisampsa fungifusiongeneintegrationtoolset
AT huhtinenkaisa fungifusiongeneintegrationtoolset