高通量代谢组学鉴定出宫颈癌的新生物标志物。
High-throughput metabolomics identifies new biomarkers for cervical cancer.
作者信息
Li Xue, Zhang Liyi, Huang Xuan, Peng Qi, Zhang Shoutao, Tang Jiangming, Wang Jing, Gui Dingqing, Zeng Fanxin
机构信息
Department of Clinical Research Center, Dazhou Central Hospital, Dazhou, 635000, Sichuan, China.
Department of Gynaecology and Obstetrics, Dazhou Central Hospital, Dazhou, Sichuan, China.
出版信息
Discov Oncol. 2024 Mar 29;15(1):90. doi: 10.1007/s12672-024-00948-8.
BACKGROUND
Cervical cancer (CC) is a danger to women's health, especially in many developing countries. Metabolomics can make the connection between genotypes and phenotypes. It provides a wide spectrum profile of biological processes under pathological or physiological conditions.
METHOD
In this study, we conducted plasma metabolomics of healthy volunteers and CC patients and integratively analyzed them with public CC tissue transcriptomics from Gene Expression Omnibus (GEO).
RESULT
Here, we screened out a panel of 5 metabolites to precisely distinguish CC patients from healthy volunteers. Furthermore, we utilized multi-omics approaches to explore patients with stage I-IIA1 and IIA2-IV4 CC and comprehensively analyzed the dysregulation of genes and metabolites in CC progression. We identified that plasma levels of trimethylamine N-oxide (TMAO) were associated with tumor size and regarded as a risk factor for CC. Moreover, we demonstrated that TMAO could promote HeLa cell proliferation in vitro. In this study, we delineated metabolic profiling in healthy volunteers and CC patients and revealed that TMAO was a potential biomarker to discriminate between I-IIA1 and IIA2-IV patients to indicate CC deterioration.
CONCLUSION
Our study identified a diagnostic model consisting of five metabolites in plasma that can effectively distinguish CC from healthy volunteers. Furthermore, we proposed that TMAO was associated with CC progression and might serve as a potential non-invasive biomarker to predict CC substage.
IMPACT
These findings provided evidence of the important role of metabolic molecules in the progression of cervical cancer disease, as well as their ability as potential biomarkers.
背景
宫颈癌(CC)对女性健康构成威胁,在许多发展中国家尤为如此。代谢组学能够建立基因型与表型之间的联系。它提供了病理或生理条件下生物过程的广泛图谱。
方法
在本研究中,我们对健康志愿者和CC患者进行了血浆代谢组学分析,并与来自基因表达综合数据库(GEO)的公开CC组织转录组学数据进行综合分析。
结果
在此,我们筛选出一组5种代谢物,以精确区分CC患者和健康志愿者。此外,我们利用多组学方法研究I-IIA1期和IIA2-IV4期CC患者,并全面分析CC进展过程中基因和代谢物的失调情况。我们发现氧化三甲胺(TMAO)的血浆水平与肿瘤大小相关,并被视为CC的一个危险因素。此外,我们证明TMAO在体外可促进HeLa细胞增殖。在本研究中,我们描绘了健康志愿者和CC患者的代谢谱,并揭示TMAO是区分I-IIA1期和IIA2-IV期患者以指示CC病情恶化的潜在生物标志物。
结论
我们的研究确定了一种由血浆中5种代谢物组成的诊断模型,可有效区分CC患者和健康志愿者。此外,我们提出TMAO与CC进展相关,可能作为预测CC分期的潜在非侵入性生物标志物。
影响
这些发现提供了代谢分子在宫颈癌疾病进展中的重要作用及其作为潜在生物标志物能力的证据。