Metabotypes of breast cancer cell lines revealed by non-targeted metabolomics

Abstract

We present an analysis of intracellular metabolism by non-targeted, high-throughput metabolomics profiling of 18 breast cell lines. We profiled >900 putatively annotated metabolite ions for >100 samples collected under both normoxic and hypoxic conditions and revealed extensive heterogeneity across all metabolic pathways and cell lines. Cell line-specific metabolome profiles dominated over patterns associated with malignancy or with the clinical nomenclature of breast cancer cells. Such characteristic metabolome profiles were reproducible across different laboratories and experiments and exhibited mild to robust changes with change in experimental conditions. To extract a functional overview of cell line heterogeneity, we devised an unsupervised metabotyping procedure that for each pathway automatically recognized metabolic types from metabolome data and assigned cell lines. Our procedure provided a condensed yet global representation of cell line metabolism, revealing the fine structure of metabolic heterogeneity across all tested pathways and cell lines. In follow-up experiments on selected pathways, we confirmed that different metabolic types correlated to differences in the underlying fluxes and difference sensitivity to gene knockdown or pharmacological inhibition. Thus, the identified metabotypes recapitulated functional differences at the pathway level. Metabotyping provides a powerful compression of multi-dimensional data that preserves functional information and serves as a resource for reconciling or understanding heterogeneous metabolic phenotypes or response to inhibition of metabolic pathways.

Keywords: Breast cancer; Cell line; Metabolism; Metabolomics; Modeling; Typing.