DeSigN: Connecting gene expression with therapeutics for drug repurposing and development

Bernard Kok Bang Lee, Kai Hung Tiong, Jit Kang Chang, Chee Sun Liew, Zainal Ariff Abdul Rahman, Aik-Choon Tan, Tsung Fei Khang, Sok Ching Cheong

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

Background: The drug discovery and development pipeline is a long and arduous process that inevitably hampers rapid drug development. Therefore, strategies to improve the efficiency of drug development are urgently needed to enable effective drugs to enter the clinic. Precision medicine has demonstrated that genetic features of cancer cells can be used for predicting drug response, and emerging evidence suggest that gene-drug connections could be predicted more accurately by exploring the cumulative effects of many genes simultaneously. Results: We developed DeSigN, a web-based tool for predicting drug efficacy against cancer cell lines using gene expression patterns. The algorithm correlates phenotype-specific gene signatures derived from differentially expressed genes with pre-defined gene expression profiles associated with drug response data (IC50) from 140 drugs. DeSigN successfully predicted the right drug sensitivity outcome in four published GEO studies. Additionally, it predicted bosutinib, a Src/Abl kinase inhibitor, as a sensitive inhibitor for oral squamous cell carcinoma (OSCC) cell lines. In vitro validation of bosutinib in OSCC cell lines demonstrated that indeed, these cell lines were sensitive to bosutinib with IC50 of 0.8-1.2 μM. As further confirmation, we demonstrated experimentally that bosutinib has anti-proliferative activity in OSCC cell lines, demonstrating that DeSigN was able to robustly predict drug that could be beneficial for tumour control. Conclusions: DeSigN is a robust method that is useful for the identification of candidate drugs using an input gene signature obtained from gene expression analysis. This user-friendly platform could be used to identify drugs with unanticipated efficacy against cancer cell lines of interest, and therefore could be used for the repurposing of drugs, thus improving the efficiency of drug development.

Original languageEnglish
Article number934
JournalBMC Genomics
Volume18
DOIs
Publication statusPublished - 2017 Jan 25
Externally publishedYes

Fingerprint

Drug Repositioning
Gene Expression
Pharmaceutical Preparations
Cell Line
Therapeutics
Squamous Cell Carcinoma
Genes
Transcriptome
Inhibitory Concentration 50
Neoplasms
Precision Medicine
src-Family Kinases
Drug Discovery

Keywords

  • Cancer
  • Cell line
  • DeSigN
  • Drug repurposing
  • Gene expression

ASJC Scopus subject areas

  • Biotechnology
  • Genetics

Cite this

Lee, B. K. B., Tiong, K. H., Chang, J. K., Liew, C. S., Abdul Rahman, Z. A., Tan, A-C., ... Cheong, S. C. (2017). DeSigN: Connecting gene expression with therapeutics for drug repurposing and development. BMC Genomics, 18, [934]. https://doi.org/10.1186/s12864-016-3260-7

DeSigN : Connecting gene expression with therapeutics for drug repurposing and development. / Lee, Bernard Kok Bang; Tiong, Kai Hung; Chang, Jit Kang; Liew, Chee Sun; Abdul Rahman, Zainal Ariff; Tan, Aik-Choon; Khang, Tsung Fei; Cheong, Sok Ching.

In: BMC Genomics, Vol. 18, 934, 25.01.2017.

Research output: Contribution to journalArticle

Lee, BKB, Tiong, KH, Chang, JK, Liew, CS, Abdul Rahman, ZA, Tan, A-C, Khang, TF & Cheong, SC 2017, 'DeSigN: Connecting gene expression with therapeutics for drug repurposing and development', BMC Genomics, vol. 18, 934. https://doi.org/10.1186/s12864-016-3260-7
Lee BKB, Tiong KH, Chang JK, Liew CS, Abdul Rahman ZA, Tan A-C et al. DeSigN: Connecting gene expression with therapeutics for drug repurposing and development. BMC Genomics. 2017 Jan 25;18. 934. https://doi.org/10.1186/s12864-016-3260-7
Lee, Bernard Kok Bang ; Tiong, Kai Hung ; Chang, Jit Kang ; Liew, Chee Sun ; Abdul Rahman, Zainal Ariff ; Tan, Aik-Choon ; Khang, Tsung Fei ; Cheong, Sok Ching. / DeSigN : Connecting gene expression with therapeutics for drug repurposing and development. In: BMC Genomics. 2017 ; Vol. 18.
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