Impact of intratumoral heterogeneity on the metabolic profiling of breast cancer tissue using high-resolution magic angle spinning magnetic resonance spectroscopy.

Abstract

High-resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) is a useful metabolic profiling technique for human tissue. However, the impact of intratumoral heterogeneity on the metabolite levels of breast cancers is not yet established. The purpose of this prospective study was to investigate whether the tumor cell fraction of core needle biopsy (CNB) specimens of breast cancers affect metabolic profiles assessed with HR-MAS MRS. From June 2015 to December 2016, 46 patients with 47 breast cancers were enrolled. HR-MAS MRS was used for the metabolic profiling of 285 CNB specimens from the 47 cancers. Multiple CNB samples (range 2-8) for the HR-MAS MRS experiment were obtained from surgical specimens under ultrasound guidance following surgical removal of the tumor. Tumor cell fraction was expressed as a percentage of the tumor cell volume relative to the total tumor volume contained in each CNB sample. Metabolite quantification levels were compared according to primary tumor characteristics using the t-test. Multivariate analyses were performed including primary tumor characteristics and tumor cell percentages as variables. Correlations between tumor cell percentage and metabolite levels in the CNB specimens were assessed according to the immunohistochemical status of the primary tumor. In univariate analysis, levels of choline-containing compounds, glutamate, glutamine, glycine, serine, and taurine were correlated with primary tumor characteristics. In multivariate analysis, most metabolite levels were not affected by tumor cell percentage. Tumor cell percentage showed poor correlation with metabolite levels in hormone receptor-positive cancer and triple-negative cancer, and poor to fair correlation with metabolite levels in HER2-positive cancer. This study showed that differences in the tumor cell fraction of CNB samples do not affect predictions on the primary cancer from which the samples are obtained.