Tissue Metabonomic Phenotyping for Diagnosis and Prognosis of Human Colorectal Cancer.
Tissue Metabonomic Phenotyping for Diagnosis and Prognosis of Human Colorectal Cancer.
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用于人类结直肠癌诊断和预后的组织代谢表型分析。
DOI：
10.1038/srep20790
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发表时间：
2016-02-15
影响因子：
4.6
通讯作者：
Tang H
中科院分区：
文献类型：
--
作者：
Tian Y;Xu T;Huang J;Zhang L;Xu S;Xiong B;Wang Y;Tang H
结直肠癌(CRC)是世界范围内与癌症相关的死亡的主要原因之一，根据传统的组织学分级方法，结直肠癌的预后仍然很差。为了改善这种情况，我们用高分辨率魔角旋转(HRMAS)~1H核磁共振波谱分析了50例人结直肠癌组织及其邻近非受累组织(ANIT)的代谢组学特征，并用GC-FID/MS分析了这些组织的脂肪酸组成。结果表明，组织代谢表型不仅能区分结直肠癌组织和ANIT组织，而且还能区分低级别肿瘤组织(I-II期)和高级别肿瘤组织(III-IV期)，具有很高的敏感性和特异性。结直肠癌组织的代谢表型在能量代谢、膜生物合成和降解、渗透调节以及蛋白质和核苷酸的代谢等方面与ANIT组织有显著差异。在所有的结直肠癌组织中，I期肿瘤与ANIT的分化最大。这些分化代谢物的组合在区分肿瘤和鼻咽癌以及区分不同阶段的结直肠癌组织方面显示出突出的集体能力。这些发现揭示了与结直肠癌组织相关的典型代谢组学表型的细节，并表明组织代谢组学表型是诊断和预测癌性实体瘤预后的重要分子病理学工具。
Colorectal cancer (CRC) is one of the leading causes of cancer-related death worldwide and prognosis based on the conventional histological grading method for CRC remains poor. To better the situation, we analyzed the metabonomic signatures of 50 human CRC tissues and their adjacent non-involved tissues (ANIT) using high-resolution magic-angle spinning (HRMAS) 1H NMR spectroscopy together with the fatty acid compositions of these tissues using GC-FID/MS. We showed that tissue metabolic phenotypes not only discriminated CRC tissues from ANIT, but also distinguished low-grade tumor tissues (stages I-II) from the high-grade ones (stages III-IV) with high sensitivity and specificity in both cases. Metabonomic phenotypes of CRC tissues differed significantly from that of ANIT in energy metabolism, membrane biosynthesis and degradations, osmotic regulations together with the metabolism of proteins and nucleotides. Amongst all CRC tissues, the stage I tumors exhibited largest differentiations from ANIT. The combination of the differentiating metabolites showed outstanding collective power for differentiating cancer from ANIT and for distinguishing CRC tissues at different stages. These findings revealed details in the typical metabonomic phenotypes associated with CRC tissues nondestructively and demonstrated tissue metabonomic phenotyping as an important molecular pathology tool for diagnosis and prognosis of cancerous solid tumors.