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Updated: Aug 29, 2025

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
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Published on: December 11, 2016

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

Jiashuo Wu1, Xiangmei Li1, Qian Wang1

  • 1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

Bioinformatics (Oxford, England)
|September 6, 2022
PubMed
Abstract

Insights

This study introduces DRviaSPCN, an R package for cancer drug repurposing by analyzing subpathway crosstalk networks. It prioritizes candidate drugs by integrating drug-induced subpathways and their crosstalk effects, aiding drug discovery.

Area of Science:

  • Computational biology
  • Systems biology
  • Pharmacology

Background:

  • Drug repurposing accelerates the discovery of new cancer treatments.
  • Existing computational methods often overlook pathway crosstalk, a key factor in cancer cell survival and drug resistance.

Purpose of the Study:

  • To develop a novel computational approach for cancer drug repurposing.
  • To systematically analyze pathway crosstalk for identifying new drug indications.

Main Methods:

  • Developed DRviaSPCN, an R-based software package utilizing a subpathway (SP) crosstalk network.
  • Calculated SP centrality scores to quantify crosstalk influence.
  • Assessed drug-disease associations by integrating drug- and disease-induced SPs, weighted by centrality scores.

Main Results:

  • DRviaSPCN prioritizes cancer candidate drugs by considering drug-induced SPs and their crosstalk effects.
  • The software provides a novel method for evaluating drug-disease reverse association at the weighted SP level.
  • Identified potential cancer drugs by analyzing subpathway crosstalk networks.

Conclusions:

  • DRviaSPCN offers a unique approach to cancer drug repurposing by incorporating pathway crosstalk analysis.
  • This tool complements existing methods by addressing the critical aspect of pathway interactions.
  • DRviaSPCN has the potential to facilitate and accelerate cancer drug discovery efforts.

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