ArticleCommunications medicine2024
A network-based trans-omics approach for predicting synergistic drug combinations.
Article in Communications medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Multi-omics-driven precision medicine.iMeta · 2026Review
- Unifying Phytochemistry, Analytics, and Target Prediction to AdvanceLife (Basel, Switzerland) · 2026Review
- Robustness Analyses Substantially Narrow in silico Network-Toxicology Signals Linking Selected Pharmaceuticals and Caffeine to Vitiligo.Clinical, cosmetic and investigational dermatology · 2026Article
- A directed weighted network-based method for drug combinations identification using drug-target and inter-target regulation.BMC bioinformatics · 2025Article
- The role for artificial intelligence in identifying combination therapies for Alzheimer's disease.The journal of prevention of Alzheimer's disease · 2025Review
- A network-based trans-omics approach for predicting synergistic drug combinations.Communications medicine · 2024Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundCombination therapy can offer greater efficacy on medical treatments. However, the discovery of synergistic drug combinations is challenging. We propose a novel computational method, SyndrumNET, to predict synergistic drug combinations by network propagation with trans-omics analyses.
methodsThe prediction is based on the topological relationship, network-based proximity, and transcriptional correlation between diseases and drugs. SyndrumNET was applied to analyzing six diseases including asthma, diabetes, hypertension, colorectal cancer, acute myeloid leukemia (AML), and chronic myeloid leukemia (CML).
resultsHere we show that SyndrumNET outperforms the previous methods in terms of high accuracy. We perform in vitro cell survival assays to validate our prediction for CML. Of the top 17 predicted drug pairs, 14 drug pairs successfully exhibits synergistic anticancer effects. Our mode-of-action analysis also reveals that the drug synergy of the top predicted combination of capsaicin and mitoxantrone is due to the complementary regulation of 12 pathways, including the Rap1 signaling pathway.
conclusionsThe proposed method is expected to be useful for discovering synergistic drug combinations for various complex diseases.
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Registered trials
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