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Status |
Public on May 06, 2024 |
Title |
A network-based trans-omics approach for predicting synergistic drug combinations |
Organism |
Homo sapiens |
Experiment type |
Expression profiling by array
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Summary |
We examined the mode-of-action of synergistic drug combinations by microarray analysis. We focused on the drug combination of capsaicin and mitoxantrone, which were the top predicted drug pair identified by SyndrumNET. Combination 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. The 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), and it outperformed the previous methods in terms of high accuracy. We performed in vitro cell survival assays to validate our prediction for CML. Of the top 17 predicted drug pairs, 14 drug pairs successfully exhibited synergistic anticancer effects. Our mode-of-action analysis also revealed that the drug synergy of the top predicted combination of capsaicin and mitoxantrone was due to the complementary regulation of 12 pathways, including the Rap1 signaling pathway. The proposed method is expected to be useful for various complex diseases.
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Overall design |
Gene expression was measured when capsaicin 50 μM, mitoxantrone 30 nM, and capsaicin 50 μM + mitoxantrone 30 nM were exposed to K562 human CML cells for 24 hours.
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Contributor(s) |
Iida M, Kuniki Y, Yagi K, Goda M, Namba S, Takeshita J, Sawada R, Iwata M, Zamami Y, Ishizawa K, Yamanishi Y |
Citation missing |
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Submission date |
Jan 24, 2024 |
Last update date |
May 07, 2024 |
Contact name |
Midori Iida |
E-mail(s) |
redgreen@bio.kyutech.ac.jp
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Organization name |
Kyushu Institute of Technology
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Street address |
Kawazu 680-4
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City |
Iizuka |
ZIP/Postal code |
820-0067 |
Country |
Japan |
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Platforms (1) |
GPL21185 |
Agilent-072363 SurePrint G3 Human GE v3 8x60K Microarray 039494 [Probe Name Version] |
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Samples (4)
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Relations |
BioProject |
PRJNA1068432 |
Supplementary file |
Size |
Download |
File type/resource |
GSE254052_RAW.tar |
24.8 Mb |
(http)(custom) |
TAR (of TXT) |
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