Data from Integrated Metabolic Profiling and Transcriptional Analysis Reveals Therapeutic Modalities for Targeting Rapidly Proliferating Breast Cancers

Abstract

<div>Abstract<p>Metabolic dysregulation is a prominent feature in breast cancer, but it remains poorly characterized in patient tumors. In this study, untargeted metabolomics analysis of triple-negative breast cancer (TNBC) and patient with estrogen receptor (ER)–positive breast cancer samples, as well as TNBC patient-derived xenografts (PDX), revealed two major metabolic groups independent of breast cancer histologic subtypes: a “Nucleotide/Carbohydrate-Enriched” group and a “Lipid/Fatty Acid-Enriched” group. Cell lines grown <i>in vivo</i> more faithfully recapitulated the metabolic profiles of patient tumors compared with those grown <i>in vitro</i>. Integrated metabolic and gene expression analyses identified genes that strongly correlate with metabolic dysregulation and predict patient prognosis. As a proof of principle, targeting Nucleotide/Carbohydrate-Enriched TNBC cell lines or PDX xenografts with a pyrimidine biosynthesis inhibitor or a glutaminase inhibitor led to therapeutic efficacy. In multiple <i>in vivo</i> models of TNBC, treatment with the pyrimidine biosynthesis inhibitor conferred better therapeutic outcomes than chemotherapeutic agents. This study provides a metabolic stratification of breast tumor samples that can guide the selection of effective therapeutic strategies targeting breast cancer subsets. In addition, we have developed a public, interactive data visualization portal (<a href="http://brcametab.org" target="_blank">http://brcametab.org</a>) based on the data generated from this study to facilitate future research.</p>Significance:<p>A multiomics strategy that integrates metabolic and gene expression profiling in patient tumor samples and animal models identifies effective pharmacologic approaches to target rapidly proliferating breast tumor subtypes.</p></div>