mRNA and microRNA expression profiles of the NCI-60 integrated with drug activities

Hongfang Liu1, Petula D'Andrade, Stephanie Fulmer-Smentek

  • 1Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.

Insights

New molecular profiling of National Cancer Institute-60 (NCI-60) cell lines reveals correlations between gene and microRNA expression and anticancer drug activity. These findings aid in identifying potential drug-target interactions.

Area of Science:

  • Cancer research
  • Molecular biology
  • Pharmacogenomics

Background:

  • The National Cancer Institute's Developmental Therapeutics program (NCI DTP) drug screen utilizes the NCI-60 cell line panel for anticancer drug discovery.
  • Understanding molecular profiles of these cell lines is crucial for interpreting drug activity and identifying mechanisms of action.

Purpose of the Study:

  • To perform comprehensive mRNA and microRNA expression profiling of the NCI-60 cell lines.
  • To integrate these molecular profiles with existing anticancer drug activity data.
  • To identify correlations between gene/microRNA expression and drug responses.

Main Methods:

  • Utilized Agilent Whole Human Genome Oligo Microarray (41,000 probes) for mRNA expression profiling.
  • Employed Agilent Human microRNA Microarray V2 (15,000 features) for microRNA expression profiling.
  • Integrated expression data with a database of 1,429 anticancer compounds and their activities from NCI DTP screens.

Main Results:

  • Measured expression levels for approximately 21,000 genes and 723 human microRNAs across NCI-60 cell lines.
  • Demonstrated high reproducibility for both mRNA and microRNA profiling platforms.
  • Identified significant correlations between blocks of mRNAs/microRNAs and approximately 1,300 drugs, including 121 with known mechanisms.

Conclusions:

  • The generated mRNA and microRNA expression datasets are publicly available via the CellMiner database.
  • These comprehensive datasets facilitate the discovery of novel drug-target interactions and biomarkers.
  • The study provides a valuable resource for understanding cellular responses to anticancer agents.