Abstract
Cancer cell metabolism has received increasing attention. Despite a boost in the application of clinical metabolic profiling (CMP) in cancer patients, a meta‐analysis has not been performed. The primary goal of this study was to assess whether public accessibility of metabolomics data and identification and reporting of metabolites were sufficient to assess which metabolites were consistently altered in cancer patients. We therefore retrospectively curated data from CMP studies in cancer patients published during 5 recent years and used an established vote‐counting method to perform a semiquantitative meta‐analysis of metabolites in tumor tissue and blood. This analysis confirmed well‐known increases in glycolytic metabolites, but also unveiled unprecedented changes in other metabolites such as ketone bodies and amino acids (histidine, tryptophan). However, this study also highlighted that insufficient public accessibility of metabolomics data, and inadequate metabolite identification and reporting hamper the discovery potential of meta‐analyses of CMP studies, calling for improved standardization of metabolomics studies.
Highlights
Clinical metabolomics investigates how metabolite levels are altered in variousphysiological conditions, often with the objective to find new roles of metabolism in disease, to discover novel metabolic drug targets, or to identify biomarkers (Fernie et al, 2004)
Since deposition of metabolomics data in publicly available repositories is generally not required by scientific journals to date, comprehensive datasets for meta-analysis have to be created by alternative approaches, for instance, by retrospective manual curation
Despite incomplete reporting of clinical metabolic profiling (CMP) data, the semiquantitative meta-analysis approach used in this study was capable of identifying distinct metabolite signatures in cancer and type 2 diabetes mellitus (T2DM)
Summary
Clinical metabolomics investigates how metabolite levels are altered in various (patho)physiological conditions, often with the objective to find new roles of metabolism in disease, to discover novel metabolic drug targets, or to identify biomarkers (Fernie et al, 2004). Apart from a few high-profile discoveries (Dang et al, 2009; Wang et al, 2011), these expectations have not been fully met and the impact of CMP studies has remained relatively modest (Sevin et al, 2015) This has raised concerns about the robustness, consistency, and translational potential of CMP studies (Gika et al, 2014). The aggregation of information from multiple studies in a meta-analysis leads in many cases to higher statistical (discovery) power and higher impact of individual studies (Green, 2005) It remains undetermined whether a meta-analysis of cancer CMP studies would offer novel insight, since cancer is a heterogeneous disease, and CMP studies greatly vary in (i) how and how many metabolites are measured, identified, and reported; (ii) how such studies are designed; and (iii) whether and how they are validated (Dunn et al, 2012). This meta-analysis was performed only on a subset of prospective CMP studies in diabetic patients and even though this study associated elevated plasma levels of branched-chain amino acids with the risk of developing type 2 diabetes (T2DM), it did not attempt to aggregate and analyze the data of all the metabolites reported in all individual studies (Guasch-Ferre et al, 2016)
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