Consensus-Phenotype Integration of Transcriptomic and Metabolomic Data Implies a Role for Metabolism in the Chemosensitivity of Tumour Cells

Using transcriptomic and metabolomic measurements from the NCI60 cell line panel, together with a novel approach to integration of molecular profile data, we show that the biochemical pathways associated with tumour cell chemosensitivity to platinum-based drugs are highly coincident, i.e. they describe a consensus phenotype. Direct integration of metabolome and transcriptome data at the point of pathway analysis improved the detection of consensus pathways by 76%, and revealed associations between platinum sensitivity and several metabolic pathways that were not visible from transcriptome analysis alone. These pathways included the TCA cycle and pyruvate metabolism, lipoprotein uptake and nucleotide synthesis by both salvage and de novo pathways. Extending the approach across a wide panel of chemotherapeutics, we confirmed the specificity of the metabolic pathway associations to platinum sensitivity. We conclude that metabolic phenotyping could play a role in predicting response to platinum chemotherapy and that consensus-phenotype integration of molecular profiling data is a powerful and versatile tool for both biomarker discovery and for exploring the complex relationships between biological pathways and drug response

Longitudinal pharmacometabonomics for predicting patient responses to therapy: drug metabolism, toxicity and efficacy

Pharmacometabonomics describes the use of metabolic profiling of biofluids, tissues and tissue extracts to predict, prior to dosing, the beneficial and adverse effects of an intervention such as drug administration. The approach not only is analogous to pharmacogenomics but also is sensitive to environmental factors such as the gut microbiome. Recent applications of pharmacometabonomics are presented and the extension to the use of longitudinal sampling is introduced. Clinical and other human applications of pharmacometabonomics are highlighted and possible future clinical applications of pharmacometabonomics and longitudinal pharmacometabonomics are discussed. These include clinical trials of new drugs either at the first-into-man stage or later in Phase II and III trials, and assessment of individual patients or groups of patients for particular therapies (personalised and stratified medicine approaches). Since metabonomics approaches are sensitive to both the host genome effects and the gut microbiome, pharmacometabonomics has particular utility for studying the host–microbiome interactions and for assessing new therapies that target the gut bacteria. Since the microbiome also has implications for nutrition and drug pharmacokinetics, such metabolic profiling approaches are likely to of use in such studies. It is anticipated that as metabonomics analytical and statistical technologies continue to develop, more applications will be realised and these should find use in real clinical situations, even monitoring patients in real time