¹H NMR 衍生血清代谢组学在口腔白斑病和鳞状细胞癌中的应用。

¹H NMR-derived serum metabolomics of leukoplakia and squamous cell carcinoma.

机构信息

Department of Metabolomics, Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India.

Department of Oral Pathology and Microbiology, King George's Medical University, Lucknow, India.

出版信息

Clin Chim Acta. 2015 Feb 20;441:47-55. doi: 10.1016/j.cca.2014.12.003. Epub 2014 Dec 9.

DOI:10.1016/j.cca.2014.12.003

PMID:25499120

Abstract

BACKGROUND

Oral cancer (OC) is the sixth commonest cancer worldwide with alarming mortality. If identified at an early stage, the survival rate would be improved.

METHODS

We appraised the feasibility of using (1)H nuclear magnetic resonance ((1)H NMR) based metabolomics in the identification of signature metabolites in serum from patients suffering with oral leukoplakia (OLK, n=100), oral squamous cell carcinoma (OSCC, n=100), and healthy control (HC, n=75). (1)H NMR derived data were processed by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) to reveal discriminating metabolites among these groups. Receiver operating characteristic (ROC) curve evaluation was also executed.

RESULTS

NMR-derived serum metabolomics reveals eight differentially expressed biomarkers. Among them four biomarkers (glutamine, propionate, acetone, and choline) were able to accurately (ROC; 0.97) segregate 93.5% of OC cases equated to HC with substantial sensitivity and specificity. Similarly, four biomarkers (glutamine, acetone, acetate, and choline) were able to precisely (ROC; 0.96) discriminate, 92.4% of OLK cases from OSCC with considerable sensitivity and specificity. (1)H NMR-based metabolic fingerprint obtained for oral cancer is remarkable, even for OLK stage.

CONCLUSION

There is a systemic metabolic response to initial stage of cancer, which carries immense possibility for early appraisal.

摘要

背景

口腔癌（OC）是全球第六大常见癌症，死亡率令人震惊。如果能在早期发现，生存率将会提高。

方法

我们评估了（1）H 核磁共振（1H NMR）基于代谢组学在识别口腔白斑（OLK，n=100）、口腔鳞状细胞癌（OSCC，n=100）和健康对照组（HC，n=75）患者血清中特征代谢物的可行性。（1）H NMR 衍生数据通过主成分分析（PCA）和正交偏最小二乘判别分析（OPLS-DA）进行处理，以揭示这些组之间的差异代谢物。还执行了接收器操作特征（ROC）曲线评估。

结果

NMR 衍生的血清代谢组学揭示了 8 个差异表达的生物标志物。其中四个生物标志物（谷氨酰胺、丙酸盐、丙酮和胆碱）能够准确（ROC；0.97）将 93.5%的 OC 病例与 HC 区分开来，具有很高的敏感性和特异性。同样，四个生物标志物（谷氨酰胺、丙酮、醋酸盐和胆碱）能够准确（ROC；0.96）区分 92.4%的 OLK 病例与 OSCC，具有相当高的敏感性和特异性。（1）H NMR 基于代谢指纹图谱对口腔癌的识别非常显著，即使在 OLK 阶段也是如此。