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      Cancer Driver Drug Interaction Explorer

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            Abstract

            Cancer is a heterogeneous disease characterized by unregulated cell growth and promoted by mutations in cancerdriver genes some of which encode suitable drug targets. Since the distinct set of cancer driver genes can varybetween and within cancer types, evidence-based selection of drugs is crucial for targeted therapy following theprecision medicine paradigm. However, many putative cancer driver genes cannot be targeted directly, suggestingan indirect approach that considers alternative functionally related targets in the gene interaction network [1]. Oncepotential drug targets have been identified, it is essential to consider all available drugs. Since tools that offer supportfor systematic discovery of drug repurposing candidates in oncology are lacking, we developed CADDIE, a webapplication integrating six human gene-gene and four drug-gene interaction databases, information regardingcancer driver genes, cancer-type specific mutation frequencies, gene expression information, genetically relateddiseases, and anticancer drugs. CADDIE offers access to various network algorithms for identifying drug targetsand drug repurposing candidates. It guides users from the selection of seed genes to the identification of therapeutictargets or drug candidates, making network medicine algorithms accessible for clinical research. CADDIE isavailable at https://exbio.wzw.tum.de/caddie/ and programmatically via a python package athttps://pypi.org/project/caddiepy/.

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            Author and article information

            Conference
            ScienceOpen
            20 July 2022
            Affiliations
            [1 ] Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany ( https://ror.org/00g30e956)
            [2 ] School of Computing, Newcastle University, Newcastle upon Tyne, UK ( https://ror.org/01kj2bm70)
            [3 ] Department of Pharmacology and Personalised Medicine, Maastricht University, Maastricht, Netherlands; Department of Pharmacology and Toxicology, Faculty of Pharmacy, Zagazig University, Zagazig, Egypt ( https://ror.org/02jz4aj89)
            [4 ] Department of Pharmacology and Personalised Medicine, Maastricht University, Maastricht, Netherlands ( https://ror.org/02jz4aj89)
            [5 ] Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany; Computational Biomedicine Lab, Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark;
            [6 ] Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany ( https://ror.org/02kkvpp62)
            Author notes
            Author information
            https://orcid.org/0000-0002-3992-0125
            Article
            10.14293/S2199-1006.1.SOR-.PPPPRSWM.v1
            8e85bd4a-7748-4213-8fa9-c21d2d5d55aa

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

            RExPO22
            Maastricht, Netherlands
            2-3 September, 2022
            History
            : 20 July 2022
            Product

            ScienceOpen

            Funding
            Funded by: funder-id http://dx.doi.org/10.13039/100010661, Horizon 2020 Framework Programme;
            Award ID: 777111

            The datasets generated during and/or analysed during the current study are available in the repository: https://github.com/biomedbigdata/CADDIE-backend
            drug repurposing,drug prioritization,network analysis,cancer,network medicine

            References

            1. Hartung Michael, Anastasi Elisa, Mamdouh Zeinab M, Nogales Cristian, Schmidt Harald H H W, Baumbach Jan, Zolotareva Olga, List Markus. Cancer driver drug interaction explorer. Nucleic Acids Research. Vol. 50(W1)2022. Oxford University Press (OUP). [Cross Ref]

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