Abstract
BackgroundThe integration of large-scale drug sensitivity screens and genome-wide experiments is changing the field of pharmacogenomics, revealing molecular determinants of drug response without the need for previous knowledge about drug action. In particular, transcriptional signatures of drug sensitivity may guide drug repositioning, prioritize drug combinations, and point to new therapeutic biomarkers. However, the inherent complexity of transcriptional signatures, with thousands of differentially expressed genes, makes them hard to interpret, thus giving poor mechanistic insights and hampering translation to clinics.MethodsTo simplify drug signatures, we have developed a network-based methodology to identify functionally coherent gene modules. Our strategy starts with the calculation of drug-gene correlations and is followed by a pathway-oriented filtering and a network-diffusion analysis across the interactome.ResultsWe apply our approach to 189 drugs tested in 671 cancer cell lines and observe a connection between gene expression levels of the modules and mechanisms of action of the drugs. Further, we characterize multiple aspects of the modules, including their functional categories, tissue-specificity, and prevalence in clinics. Finally, we prove the predictive capability of the modules and demonstrate how they can be used as gene sets in conventional enrichment analyses.ConclusionsNetwork biology strategies like module detection are able to digest the outcome of large-scale pharmacogenomic initiatives, thereby contributing to their interpretability and improving the characterization of the drugs screened.
Highlights
The integration of large-scale drug sensitivity screens and genome-wide experiments is changing the field of pharmacogenomics, revealing molecular determinants of drug response without the need for previous knowledge about drug action
We found that cancer cell line (CCL) derived from neuroblastoma, hematopoietic, bone, and small cell lung cancers may confound global studies of drug-gene correlations due to their unspecific sensitivity to drugs (Additional file 1: Figure S2A)
Going back to the targeting of EGFR, we show in Fig. 1e that the “global” correlation can be partly attributed to non-small cell lung cancer (NSCLC) cells
Summary
The integration of large-scale drug sensitivity screens and genome-wide experiments is changing the field of pharmacogenomics, revealing molecular determinants of drug response without the need for previous knowledge about drug action. The inherent complexity of transcriptional signatures, with thousands of differentially expressed genes, makes them hard to interpret, giving poor mechanistic insights and hampering translation to clinics. The largest cell panels available today are derived from cancerous tissues, since a crucial step towards personalized cancer medicine is the identification of transcriptional signatures that can guide drug prescription. Current signatures are composed of several hundred genes, thereby making them difficult to interpret, harmonize across platforms, and translate to clinical practice [14,15,16]. The length of the signatures largely exceeds the number of sensitive cell lines available for each drug, which often yields inconsistent results between cell panels from different laboratories [14]. The current challenge is to filter and characterize transcriptional signatures so that they become robust, informative, and more homogeneous, while still retaining the complexity ( the predictive power) of the original profiles [17]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
