DriveWays: a method for identifying possibly overlapping driver pathways in cancer

Abstract The majority of the previous methods for identifying cancer driver modules output nonoverlapping modules. This assumption is biologically inaccurate as genes can participate in multiple molecular pathways. This is particularly true for cancer-associated genes as many of them are network hub...

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Autores principales:	Ilyes Baali, Cesim Erten, Hilal Kazan
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/5bdc5c1867664b96acee24c58817f5d4
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id	oai:doaj.org-article:5bdc5c1867664b96acee24c58817f5d4
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spelling	oai:doaj.org-article:5bdc5c1867664b96acee24c58817f5d42021-12-02T12:40:40ZDriveWays: a method for identifying possibly overlapping driver pathways in cancer10.1038/s41598-020-78852-82045-2322https://doaj.org/article/5bdc5c1867664b96acee24c58817f5d42020-12-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-78852-8https://doaj.org/toc/2045-2322Abstract The majority of the previous methods for identifying cancer driver modules output nonoverlapping modules. This assumption is biologically inaccurate as genes can participate in multiple molecular pathways. This is particularly true for cancer-associated genes as many of them are network hubs connecting functionally distinct set of genes. It is important to provide combinatorial optimization problem definitions modeling this biological phenomenon and to suggest efficient algorithms for its solution. We provide a formal definition of the Overlapping Driver Module Identification in Cancer (ODMIC) problem. We show that the problem is NP-hard. We propose a seed-and-extend based heuristic named DriveWays that identifies overlapping cancer driver modules from the graph built from the IntAct PPI network. DriveWays incorporates mutual exclusivity, coverage, and the network connectivity information of the genes. We show that DriveWays outperforms the state-of-the-art methods in recovering well-known cancer driver genes performed on TCGA pan-cancer data. Additionally, DriveWay’s output modules show a stronger enrichment for the reference pathways in almost all cases. Overall, we show that enabling modules to overlap improves the recovery of functional pathways filtered with known cancer drivers, which essentially constitute the reference set of cancer-related pathways.Ilyes BaaliCesim ErtenHilal KazanNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-14 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ilyes Baali Cesim Erten Hilal Kazan DriveWays: a method for identifying possibly overlapping driver pathways in cancer
description	Abstract The majority of the previous methods for identifying cancer driver modules output nonoverlapping modules. This assumption is biologically inaccurate as genes can participate in multiple molecular pathways. This is particularly true for cancer-associated genes as many of them are network hubs connecting functionally distinct set of genes. It is important to provide combinatorial optimization problem definitions modeling this biological phenomenon and to suggest efficient algorithms for its solution. We provide a formal definition of the Overlapping Driver Module Identification in Cancer (ODMIC) problem. We show that the problem is NP-hard. We propose a seed-and-extend based heuristic named DriveWays that identifies overlapping cancer driver modules from the graph built from the IntAct PPI network. DriveWays incorporates mutual exclusivity, coverage, and the network connectivity information of the genes. We show that DriveWays outperforms the state-of-the-art methods in recovering well-known cancer driver genes performed on TCGA pan-cancer data. Additionally, DriveWay’s output modules show a stronger enrichment for the reference pathways in almost all cases. Overall, we show that enabling modules to overlap improves the recovery of functional pathways filtered with known cancer drivers, which essentially constitute the reference set of cancer-related pathways.
format	article
author	Ilyes Baali Cesim Erten Hilal Kazan
author_facet	Ilyes Baali Cesim Erten Hilal Kazan
author_sort	Ilyes Baali
title	DriveWays: a method for identifying possibly overlapping driver pathways in cancer
title_short	DriveWays: a method for identifying possibly overlapping driver pathways in cancer
title_full	DriveWays: a method for identifying possibly overlapping driver pathways in cancer
title_fullStr	DriveWays: a method for identifying possibly overlapping driver pathways in cancer
title_full_unstemmed	DriveWays: a method for identifying possibly overlapping driver pathways in cancer
title_sort	driveways: a method for identifying possibly overlapping driver pathways in cancer
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/5bdc5c1867664b96acee24c58817f5d4
work_keys_str_mv	AT ilyesbaali drivewaysamethodforidentifyingpossiblyoverlappingdriverpathwaysincancer AT cesimerten drivewaysamethodforidentifyingpossiblyoverlappingdriverpathwaysincancer AT hilalkazan drivewaysamethodforidentifyingpossiblyoverlappingdriverpathwaysincancer
_version_	1718393739105271808

DriveWays: a method for identifying possibly overlapping driver pathways in cancer

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