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循环代谢物作为胃肠道癌早期检测和预后监测的潜在生物标志物。

Circulating metabolites as potential biomarkers for the early detection and prognosis surveillance of gastrointestinal cancers.

机构信息

The Second Hospital of Tianjin Medical University, No 23. Pingjiang Road, Hexi District, 300211, Tianjin, China.

Metanotitia Inc, No 59. Gaoxin South 9Th Road, Yuehai Street, Nanshan District, Shenzhen, 518056, Guangdong, China.

出版信息

Metabolomics. 2023 Apr 4;19(4):36. doi: 10.1007/s11306-023-02002-0.

Abstract

BACKGROUND AND AIMS

Two of the most lethal gastrointestinal (GI) cancers, gastric cancer (GC) and colon cancer (CC), are ranked in the top five cancers that cause deaths worldwide. Most GI cancer deaths can be reduced by earlier detection and more appropriate medical treatment. Unlike the current "gold standard" techniques, non-invasive and highly sensitive screening tests are required for GI cancer diagnosis. Here, we explored the potential of metabolomics for GI cancer detection and the classification of tissue-of-origin, and even the prognosis management.

METHODS

Plasma samples from 37 gastric cancer (GC), 17 colon cancer (CC), and 27 non-cancer (NC) patients were prepared for metabolomics and lipidomics analysis by three MS-based platforms. Univariate, multivariate, and clustering analyses were used for selecting significant metabolic features. ROC curve analysis was based on a series of different binary classifications as well as the true-positive rate (sensitivity) and the false-positive rate (1-specificity).

RESULTS

GI cancers exhibited obvious metabolic perturbation compared with benign diseases. The differentiated metabolites of gastric cancer (GC) and colon cancer (CC) were targeted to same pathways but with different degrees of cellular metabolism reprogramming. The cancer-specific metabolites distinguished the malignant and benign, and classified the cancer types. We also applied this test to before- and after-surgery samples, wherein surgical resection significantly altered the blood-metabolic patterns. There were 15 metabolites significantly altered in GC and CC patients who underwent surgical treatment, and partly returned to normal conditions.

CONCLUSION

Blood-based metabolomics analysis is an efficient strategy for GI cancer screening, especially for malignant and benign diagnoses. The cancer-specific metabolic patterns process the potential for classifying tissue-of-origin in multi-cancer screening. Besides, the circulating metabolites for prognosis management of GI cancer is a promising area of research.

摘要

背景与目的

胃癌(GC)和结肠癌(CC)是两种最致命的胃肠道(GI)癌症,在全球导致死亡的癌症中排名前五。通过早期发现和更适当的治疗,可以降低大多数 GI 癌症的死亡率。与当前的“金标准”技术不同,需要用于 GI 癌症诊断的非侵入性和高度敏感的筛选测试。在这里,我们探索了代谢组学在 GI 癌症检测和组织起源分类中的潜力,甚至在预后管理方面。

方法

通过三种基于 MS 的平台,对来自 37 例胃癌(GC)、17 例结肠癌(CC)和 27 例非癌症(NC)患者的血浆样本进行代谢组学和脂质组学分析。使用单变量、多变量和聚类分析来选择有意义的代谢特征。ROC 曲线分析基于一系列不同的二分类以及真阳性率(敏感性)和假阳性率(1 特异性)。

结果

GI 癌症与良性疾病相比表现出明显的代谢紊乱。胃癌(GC)和结肠癌(CC)的分化代谢物靶向相同的途径,但细胞代谢重编程的程度不同。癌症特异性代谢物可区分恶性和良性,并对癌症类型进行分类。我们还将该测试应用于手术前后的样本中,其中手术切除显著改变了血液代谢模式。在接受手术治疗的 GC 和 CC 患者中,有 15 种代谢物发生了显著变化,部分恢复正常。

结论

基于血液的代谢组学分析是 GI 癌症筛查的有效策略,特别是用于恶性和良性诊断。癌症特异性代谢模式有可能在多癌筛查中进行组织起源分类。此外,用于 GI 癌症预后管理的循环代谢物是一个很有前途的研究领域。

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