Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway.
NMR Biomed. 2010 May;23(4):424-31. doi: 10.1002/nbm.1478. Epub 2010 Jan 25.
Absolute quantitative measures of breast cancer tissue metabolites can increase our understanding of biological processes. Electronic REference To access In vivo Concentrations (ERETIC) was applied to high resolution magic angle spinning MR spectroscopy (HR MAS MRS) to quantify metabolites in intact breast cancer samples. The ERETIC signal was calibrated using solutions of creatine and TSP. The largest relative errors of the ERETIC method were 8.4%, compared to 4.4% for the HR MAS MRS method using TSP as a standard. The same MR experimental procedure was applied to intact tissue samples from breast cancer patients with clinically defined good (n = 13) and poor (n = 16) prognosis. All samples were examined by histopathology for relative content of different tissue types and proliferation index (MIB-1) after MR analysis. The resulting spectra were analyzed by quantification of tissue metabolites (β-glucose, lactate, glycine, myo-inositol, taurine, glycerophosphocholine, phosphocholine, choline and creatine), by peak area ratios and by principal component analysis. We found a trend toward lower concentrations of glycine in patients with good prognosis (1.1 µmol/g) compared to patients with poor prognosis (1.9 µmol/g, p = 0.067). Tissue metabolite concentrations (except for β-glucose) were also found to correlate to the fraction of tumor, connective, fat or glandular tissue by Pearson correlation analysis. Tissue concentrations of β-glucose correlated to proliferation index (MIB-1) with a negative correlation factor (-0.45, p = 0.015), consistent with increased energy demand in proliferating tumor cells. By analyzing several metabolites simultaneously, either in ratios or by metabolic profiles analyzed by PCA, we found that tissue metabolites correlate to patients' prognoses and health status five years after surgery. This study shows that the diagnostic and prognostic potential in MR metabolite analysis of breast cancer tissue is greater when combining multiple metabolites (MR Metabolomics).
绝对定量测量乳腺癌组织代谢物可以增加我们对生物学过程的理解。电子参考物活体浓度(ERETIC)被应用于高分辨率魔角旋转磁共振波谱(HR MAS MRS),以定量分析完整乳腺癌样本中的代谢物。通过使用肌酸和 TSP 溶液对 ERETIC 信号进行校准。与使用 TSP 作为标准的 HR MAS MRS 方法相比,ERETIC 方法的最大相对误差为 8.4%,而相对误差为 4.4%。相同的磁共振实验程序应用于来自临床定义良好(n = 13)和不良(n = 16)预后的乳腺癌患者的完整组织样本。所有样本在磁共振分析后均通过组织学检查评估不同组织类型的相对含量和增殖指数(MIB-1)。对所得光谱进行分析,通过定量分析组织代谢物(β-葡萄糖、乳酸、甘氨酸、肌醇、牛磺酸、甘油磷酸胆碱、磷酸胆碱、胆碱和肌酸)、峰面积比和主成分分析进行分析。我们发现,与预后不良的患者(1.9μmol/g)相比,预后良好的患者(1.1μmol/g)中甘氨酸的浓度呈下降趋势(p = 0.067)。通过皮尔逊相关分析,还发现组织代谢物浓度(除β-葡萄糖外)与肿瘤、结缔组织、脂肪或腺组织的比例也相关。β-葡萄糖的组织浓度与增殖指数(MIB-1)呈负相关(-0.45,p = 0.015),这与增殖肿瘤细胞中能量需求的增加一致。通过同时分析几种代谢物,无论是通过比值还是通过 PCA 分析的代谢谱,我们发现组织代谢物与患者手术后五年的预后和健康状况相关。这项研究表明,在分析乳腺癌组织的磁共振代谢物时,结合多种代谢物(磁共振代谢组学)可以提高诊断和预后的潜力。