多矩阵代谢组学分析用于结直肠癌和腺瘤的特异性检测。
Multiple-matrix metabolomics analysis for the distinct detection of colorectal cancer and adenoma.
机构信息
Department of Oncology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
The First Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, China.
出版信息
Metabolomics. 2024 Apr 20;20(3):47. doi: 10.1007/s11306-024-02114-1.
OBJECTIVES
Although colorectal cancer (CRC) is the leading cause of cancer-related morbidity and mortality, current diagnostic tests for early-stage CRC and colorectal adenoma (CRA) are suboptimal. Therefore, there is an urgent need to explore less invasive screening procedures for CRC and CRA diagnosis.
METHODS
Untargeted gas chromatography-mass spectrometry (GC-MS) metabolic profiling approach was applied to identify candidate metabolites. We performed metabolomics profiling on plasma samples from 412 subjects including 200 CRC patients, 160 CRA patients and 52 normal controls (NC). Among these patients, 45 CRC patients, 152 CRA patients and 50 normal controls had their fecal samples tested simultaneously.
RESULTS
Differential metabolites were screened in the adenoma-carcinoma sequence. Three diagnostic models were further developed to identify cancer group, cancer stage, and cancer microsatellite status using those significant metabolites. The three-metabolite-only classifiers used to distinguish the cancer group always keeps the area under the receiver operating characteristic curve (AUC) greater than 0.7. The AUC performance of the classifiers applied to discriminate CRC stage is generally greater than 0.8, and the classifiers used to distinguish microsatellite status of CRC is greater than 0.9.
CONCLUSION
This finding highlights potential early-driver metabolites in CRA and early-stage CRC. We also find potential metabolic markers for discriminating the microsatellite state of CRC. Our study and diagnostic model have potential applications for non-invasive CRC and CRA detection.
目的
尽管结直肠癌(CRC)是导致癌症相关发病率和死亡率的主要原因,但目前用于早期 CRC 和结直肠腺瘤(CRA)的诊断测试并不理想。因此,迫切需要探索用于 CRC 和 CRA 诊断的非侵入性筛查程序。
方法
应用非靶向气相色谱-质谱(GC-MS)代谢组学分析方法来鉴定候选代谢物。我们对 412 名受试者的血浆样本进行了代谢组学分析,其中包括 200 名 CRC 患者、160 名 CRA 患者和 52 名正常对照(NC)。在这些患者中,45 名 CRC 患者、152 名 CRA 患者和 50 名正常对照者同时进行了粪便样本检测。
结果
在腺瘤-癌序列中筛选出差异代谢物。使用这些显著代谢物进一步开发了三种诊断模型,以识别癌症组、癌症分期和癌症微卫星状态。用于区分癌症组的三个仅代谢物分类器始终保持接收者操作特征曲线(AUC)大于 0.7。应用于区分 CRC 分期的分类器的 AUC 性能通常大于 0.8,用于区分 CRC 微卫星状态的分类器大于 0.9。
结论
这一发现强调了 CRA 和早期 CRC 中潜在的早期驱动代谢物。我们还发现了用于区分 CRC 微卫星状态的潜在代谢标志物。我们的研究和诊断模型具有用于非侵入性 CRC 和 CRA 检测的潜在应用。