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Oxford University Press, Bioinformatics, 21(38), p. 4975-4977, 2022

DOI: 10.1093/bioinformatics/btac611

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DRviaSPCN: a software package for drug repurposing in cancer via a subpathway crosstalk network

Journal article published in 2022 by Jiashuo Wu ORCID, Xiangmei Li, Qian Wang, Junwei Han ORCID
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Abstract Summary Drug repurposing is an approach used to discover new indications for existing drugs. Recently, several computational approaches have been developed for drug repurposing in cancer. Nevertheless, no approaches have reported a systematic analysis of pathway crosstalk. Pathway crosstalk, which refers to the phenomenon of interaction or cooperation between pathways, is a critical aspect of tumor pathways that allows cancer cells to survive and acquire resistance to drug therapy. Here, we innovatively developed a system biology R-based software package, DRviaSPCN, to repurpose drugs for cancer via a subpathway (SP) crosstalk network. This package provides a novel approach to prioritize cancer candidate drugs by considering drug-induced SPs and their crosstalk effects. The operation modes mainly include construction of the SP network and calculation of the centrality scores of SPs to reflect the influence of SP crosstalk, calculation of enrichment scores of drug- and disease-induced dysfunctional SPs and weighted them by the centrality scores of SPs, evaluation of the drug–disease reverse association at the weighted SP level, identification of cancer candidate drugs and visualization of the results. Its capabilities enable DRviaSPCN to find cancer candidate drugs, which will complement the recent tools which did not consider crosstalk among pathways/SPs. DRviaSPCN may help to facilitate the development of drug discovery. Availability and implementation The package is implemented in R and available under GPL-2 license from the CRAN website (https://CRAN.R-project.org/package=DRviaSPCN). Supplementary information Supplementary data are available at Bioinformatics online.