Inconsistency in large pharmacogenomic studies

By Benjamin Haibe-Kains, N. El-Hachem, Nicolai J. Birkbak, Andrew C. Jin, Andrew H. Beck, Hugo J. W. L. Aerts, John Quackenbush. Nature, 2013

486 citations recorded by the source corpus.

Two large-scale pharmacogenomic studies were published recently in this journal. Genomic data are well correlated between studies; however, the measured drug response data are highly discordant. Although the source of inconsistencies remains uncertain, it has potential implications for using these outcome measures to assess gene–drug associations or select potential anticancer drugs on the basis of their reported results.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/eb9b5eda01c33051acc7ba3898782d71702f27dd

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Citations in the corpus

• Reproducibility in Science: Improving the Standard for Basic and Preclinical Research (2015, unknown): “standardization of the experimental assays and methods of analysis.(29)”
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• pRRophetic: An R Package for Prediction of Clinical Chemotherapeutic Response from Tumor Gene Expression Levels (2014, result): “These represent similar correlations to those observed when drug sensitivity was compared for cell lines that overlap both CGP and CCLE [4].”
• Large-scale integration of small molecule-induced genome-wide transcriptional responses, Kinome-wide binding affinities and cell-growth inhibition profiles reveal global trends characterizing systems-level drug action (2014, result): “It may therefore be the case that such results are in fact more robust in terms of reproducibility as oppose to comparing just two different assay methods or assay conditions, which can sometimes give considerably different outcomes (Haibe-Kains et al., 2013).”
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