Computational discovery of transcription factors associated with drug response

Pharmacogenomics J. 2016 Nov;16(6):573-582. doi: 10.1038/tpj.2015.74. Epub 2015 Oct 27.


This study integrates gene expression, genotype and drug response data in lymphoblastoid cell lines with transcription factor (TF)-binding sites from ENCODE (Encyclopedia of Genomic Elements) in a novel methodology that elucidates regulatory contexts associated with cytotoxicity. The method, GENMi (Gene Expression iN the Middle), postulates that single-nucleotide polymorphisms within TF-binding sites putatively modulate its regulatory activity, and the resulting variation in gene expression leads to variation in drug response. Analysis of 161 TFs and 24 treatments revealed 334 significantly associated TF-treatment pairs. Investigation of 20 selected pairs yielded literature support for 13 of these associations, often from studies where perturbation of the TF expression changes drug response. Experimental validation of significant GENMi associations in taxanes and anthracyclines across two triple-negative breast cancer cell lines corroborates our findings. The method is shown to be more sensitive than an alternative, genome-wide association study-based approach that does not use gene expression. These results demonstrate the utility of GENMi in identifying TFs that influence drug response and provide a number of candidates for further testing.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Anthracyclines / adverse effects
  • Anthracyclines / therapeutic use*
  • Antibiotics, Antineoplastic / adverse effects
  • Antibiotics, Antineoplastic / therapeutic use*
  • Binding Sites
  • Cell Line, Tumor
  • Cell Survival / drug effects
  • Computational Biology*
  • Databases, Genetic
  • Dose-Response Relationship, Drug
  • Gene Expression Profiling
  • Gene Expression Regulation
  • Humans
  • Inhibitory Concentration 50
  • Male
  • Patient Selection
  • Pharmacogenetics / methods*
  • Pharmacogenomic Variants*
  • Phenotype
  • Polymorphism, Single Nucleotide*
  • RNA Interference
  • Taxoids / adverse effects
  • Taxoids / therapeutic use*
  • Transcription Factors / genetics*
  • Transcription Factors / metabolism
  • Transfection
  • Triple Negative Breast Neoplasms / drug therapy*
  • Triple Negative Breast Neoplasms / genetics
  • Triple Negative Breast Neoplasms / metabolism
  • Triple Negative Breast Neoplasms / pathology


  • Anthracyclines
  • Antibiotics, Antineoplastic
  • Taxoids
  • Transcription Factors