Abstract
Adaptive metabolic switches are proposed to underlie conversions between cellular states during normal development as well as in cancer evolution, where they represent important therapeutic targets. However, the full spectrum, characteristics and regulation of existing metabolic switches are unknown. We propose that metabolic switches can be recognised by locating large alternating gene expression patterns and associate them with specific metabolic states. We developed a method to identify interspersed genesets by massive correlated biclustering (MCbiclust) and to predict their metabolic wiring. Testing the method on major breast cancer transcriptome datasets we discovered a series of gene sets with switch-like behaviour, predicting mitochondrial content, activity and central carbon fluxes in tumours associated with different switch positions. The predictions were experimentally validated by bioenergetic profiling and metabolic flux analysis of 13C-labelled substrates and were ultimately extended by geneset analysis to link metabolic alterations to cellular states, thus predicting tumour pathology, prognosis and chemosensitivity. The method is applicable to any large and heterogeneous transcriptome dataset to discover metabolic and associated pathophysiological states.
Statement of significance We present a novel method to identify the transcriptomic signatures of metabolic switches underlying divergent routes of cellular transformation. We illustrate the power of the method by stratifying breast cancer into metabolic subtypes, predicting their biology, architecture and clinical outcome.
Competing Interest Statement
The authors declare no competing interests. RCS is the Chief Investigator of the OPTIMA Trial (ISRCTN42400492) which uses the Prosigna test to make therapeutic decisions in breast cancer treatment. He has no personal financial links with the vendors, NanoString Inc. and Veracyte Inc.
Footnotes
Additional information:
↵* shared first authorship
↵# shared senior authorship
Conflict of interest statement: The authors declare no competing interests. RCS is the Chief Investigator of the OPTIMA Trial (ISRCTN42400492) which uses the Prosigna test to make therapeutic decisions in breast cancer treatment. He has no personal financial links with the vendors, NanoString Inc. and Veracyte Inc.
Introduction and discussion has been extensively rewritten to reflect and explain better the aims of the analysis. Figures and data remained essentially the same.