Impact of intratumoral heterogeneity of breast cancer tissue on quantitative metabolomics using high‐resolution magic angle spinning 1 H NMR spectroscopy

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EarlyView Article

  • Published: Dec 5, 2017
  • Author: Mikheil Gogiashvili, Salome Horsch, Rosemarie Marchan, Kathrin Gianmoena, Cristina Cadenas, Berno Tanner, Sabrina Naumann, Diana Ersova, Frank Lippek, Jörg Rahnenführer, Jan T. Andersson, Roland Hergenröder, Jörg Lambert, Jan G. Hengstler, Karolina Edlund
  • Journal: NMR in Biomedicine

High‐resolution magic angle spinning (HR MAS) nuclear magnetic resonance (NMR) spectroscopy is increasingly being used to study metabolite levels in human breast cancer tissue, assessing, for instance, correlations with prognostic factors, survival outcome or therapeutic response. However, the impact of intratumoral heterogeneity on metabolite levels in breast tumor tissue has not been studied comprehensively. More specifically, when biopsy material is analyzed, it remains questionable whether one biopsy is representative of the entire tumor. Therefore, multi‐core sampling (n = 6) of tumor tissue from three patients with breast cancer, followed by lipid (0.9‐ and 1.3‐ppm signals) and metabolite quantification using HR MAS 1H NMR, was performed, resulting in the quantification of 32 metabolites. The mean relative standard deviation across all metabolites for the six tumor cores sampled from each of the three tumors ranged from 0.48 to 0.74. This was considerably higher when compared with a morphologically more homogeneous tissue type, here represented by murine liver (0.16–0.20). Despite the seemingly high variability observed within the tumor tissue, a random forest classifier trained on the original sample set (training set) was, with one exception, able to correctly predict the tumor identity of an independent series of cores (test set) that were additionally sampled from the same three tumors and analyzed blindly. Moreover, significant differences between the tumors were identified using one‐way analysis of variance (ANOVA), indicating that the intertumoral differences for many metabolites were larger than the intratumoral differences for these three tumors. That intertumoral differences, on average, were larger than intratumoral differences was further supported by the analysis of duplicate tissue cores from 15 additional breast tumors. In summary, despite the observed intratumoral variability, the results of the present study suggest that the analysis of one, or a few, replicates per tumor may be acceptable, and supports the feasibility of performing reliable analyses of patient tissue.

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