Gogiashvili Mikheil, Horsch Salome, Marchan Rosemarie, Gianmoena Kathrin, Cadenas Cristina, Tanner Berno, Naumann Sabrina, Ersova Diana, Lippek Frank, Rahnenführer Jörg, Andersson Jan T, Hergenröder Roland, Lambert Jörg, Hengstler Jan G, Edlund Karolina
Leibniz Institut für Analytische Wissenschaften - ISAS e.V, Dortmund, Germany.
Department of Statistics, TU Dortmund University, Dortmund, Germany.
NMR Biomed. 2018 Feb;31(2). doi: 10.1002/nbm.3862. Epub 2017 Dec 5.
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 H 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.
高分辨率魔角旋转(HR MAS)核磁共振(NMR)光谱越来越多地用于研究人类乳腺癌组织中的代谢物水平,例如评估其与预后因素、生存结果或治疗反应的相关性。然而,肿瘤内异质性对乳腺肿瘤组织中代谢物水平的影响尚未得到全面研究。更具体地说,在分析活检材料时,一次活检是否代表整个肿瘤仍存在疑问。因此,对三名乳腺癌患者的肿瘤组织进行了多核采样(n = 6),然后使用HR MAS ¹H NMR对脂质(0.9 ppm和1.3 ppm信号)和代谢物进行定量,共定量了32种代谢物。从三个肿瘤中的每个肿瘤采集的六个肿瘤核心中,所有代谢物的平均相对标准偏差范围为0.48至0.74。与形态上更均匀的组织类型(此处以小鼠肝脏为代表,相对标准偏差为0.16 - 0.20)相比,这一数值要高得多。尽管在肿瘤组织中观察到了看似较高的变异性,但在原始样本集(训练集)上训练的随机森林分类器,除了一个例外,能够正确预测从相同的三个肿瘤中额外采样并进行盲法分析的独立核心系列(测试集)的肿瘤身份。此外,使用单因素方差分析(ANOVA)确定了肿瘤之间的显著差异,表明许多代谢物的肿瘤间差异大于这三个肿瘤的肿瘤内差异。对另外15个乳腺肿瘤的重复组织核心进行分析进一步支持了肿瘤间差异平均大于肿瘤内差异这一结论。总之,尽管观察到肿瘤内存在变异性,但本研究结果表明每个肿瘤分析一个或几个重复样本可能是可以接受的,并支持对患者组织进行可靠分析的可行性。