Centre of Biomedical Research, Formerly Centre of Biomedical Magnetic Resonance (CBMR), Sanjay Gandhi Postgraduate Institute of Medical Sciences Campus, Rae Bareli Road, Lucknow, 226014, India.
Department of Chemistry, University of Lucknow, University Road, Babuganj, Hasanganj, Lucknow, 226007, India.
Metabolomics. 2018 Sep 3;14(9):119. doi: 10.1007/s11306-018-1411-3.
Breast cancer is the most frequent diagnosed cancer among women with a mortality rate of 15% of all cancer related deaths in women. Breast cancer is heterogeneous in nature and produces plethora of metabolites allowing its early detection using molecular diagnostic techniques like magnetic resonance spectroscopy.
To evaluate the variation in metabolic profile of breast cancer focusing on lipids as triglycerides (TG) and free fatty acids (FFA) that may alter in malignant breast tissues and lymph nodes from adjacent benign breast tissues by HRMAS H NMR spectroscopy.
The H NMR spectra recorded on 173 tissue specimens comprising of breast tumor tissues, adjacent tissues, few lymph nodes and overlying skin tissues obtained from 67 patients suffering from breast cancer. Multivariate statistical analysis was employed to identify metabolites acting as major confounders for differentiation of malignancy.
Reduction in lipid content were observed in malignant breast tissues along with a higher fraction of FFA. Four small molecule metabolites e.g., choline containing compounds (Chocc), taurine, glycine, and glutamate were also identified as major confounders. The test set for prediction provided sensitivity and specificity of more than 90% excluding the lymph nodes and skin tissues.
Fatty acids composition in breast cancer using in vivo magnetic resonance spectroscopy (MRS) is gaining its importance in clinical settings (Coum et al. in Magn Reson Mater Phys Biol Med 29:1-4, 2016). The present study may help in future for precise evaluation of lipid classification including small molecules as a source of early diagnosis of invasive ductal carcinoma by employing in vivo magnetic resonance spectroscopic methods.
乳腺癌是女性中最常见的癌症诊断，其死亡率占女性所有癌症相关死亡的 15%。乳腺癌在性质上具有异质性，并产生大量代谢物，允许使用磁共振波谱等分子诊断技术进行早期检测。
通过高分辨率磁共振波谱（HRMAS H NMR）光谱评估乳腺癌代谢谱的变化，重点关注甘油三酯（TG）和游离脂肪酸（FFA）等脂质，这些脂质可能在恶性乳腺组织和淋巴结中发生变化，而在相邻良性乳腺组织中则不会发生变化。
对 67 名乳腺癌患者的 173 个组织标本（包括乳腺肿瘤组织、相邻组织、少数淋巴结和覆盖皮肤组织）进行 H NMR 谱记录。采用多变量统计分析方法，确定作为区分恶性肿瘤主要混杂因素的代谢物。
恶性乳腺组织中的脂质含量降低，同时 FFA 的比例更高。还确定了四种小分子代谢物，如含有胆碱的化合物（Chocc）、牛磺酸、甘氨酸和谷氨酸，它们也是主要的混杂因素。预测的测试集排除了淋巴结和皮肤组织后，敏感性和特异性均超过 90%。
使用体内磁共振波谱（MRS）检测乳腺癌中的脂肪酸组成在临床环境中越来越重要（Coum 等人，Magn Reson Mater Phys Biol Med 29:1-4, 2016）。本研究将来可能有助于通过体内磁共振波谱方法对包括小分子在内的脂质分类进行精确评估，作为早期诊断浸润性导管癌的一种来源。
