PUBLICATION
Combining genomic and network characteristics for extended capability in predicting synergistic drugs for cancer
- Authors
- Sun, Y., Sheng, Z., Ma, C., Tang, K., Zhu, R., Wu, Z., Shen, R., Feng, J., Wu, D., Huang, D., Huang, D., Fei, J., Liu, Q., Cao, Z.
- ID
- ZDB-PUB-150929-8
- Date
- 2015
- Source
- Nature communications 6: 8481 (Journal)
- Registered Authors
- Sun, Yi
- Keywords
- Bioinformatics, Cancer, Combination drug therapy
- MeSH Terms
-
- Animals
- Antineoplastic Agents/pharmacology*
- Antineoplastic Agents/therapeutic use
- Drug Synergism*
- Genomics
- Humans
- MCF-7 Cells
- Models, Theoretical*
- Neoplasms/drug therapy*
- Xenograft Model Antitumor Assays
- Zebrafish
- PubMed
- 26412466 Full text @ Nat. Commun.
Citation
Sun, Y., Sheng, Z., Ma, C., Tang, K., Zhu, R., Wu, Z., Shen, R., Feng, J., Wu, D., Huang, D., Huang, D., Fei, J., Liu, Q., Cao, Z. (2015) Combining genomic and network characteristics for extended capability in predicting synergistic drugs for cancer. Nature communications. 6:8481.
Abstract
The identification of synergistic chemotherapeutic agents from a large pool of candidates is highly challenging. Here, we present a Ranking-system of Anti-Cancer Synergy (RACS) that combines features of targeting networks and transcriptomic profiles, and validate it on three types of cancer. Using data on human β-cell lymphoma from the Dialogue for Reverse Engineering Assessments and Methods consortium we show a probability concordance of 0.78 compared with 0.61 obtained with the previous best algorithm. We confirm 63.6% of our breast cancer predictions through experiment and literature, including four strong synergistic pairs. Further in vivo screening in a zebrafish MCF7 xenograft model confirms one prediction with strong synergy and low toxicity. Validation using A549 lung cancer cells shows similar results. Thus, RACS can significantly improve drug synergy prediction and markedly reduce the experimental prescreening of existing drugs for repurposing to cancer treatment, although the molecular mechanism underlying particular interactions remains unknown.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping