Khan Imran, Nam Miso, Kwon Minji, Seo Sang-Soo, Jung Sunhee, Han Ji Soo, Hwang Geum-Sook, Kim Mi Kyung
Division of Cancer Epidemiology and Prevention, National Cancer Center, Madu-dong, Ilsandong-gu, Goyang-si, Gyeonggi-do 10408, Korea.
Integrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seoul 03759, Korea.
Cancers (Basel). 2019 Apr 10;11(4):511. doi: 10.3390/cancers11040511.
Cervical cancer remains one of the most prevalent cancers among females worldwide. Therefore, it is important to discover new biomarkers for early diagnosis of cervical intraepithelial neoplasia (CIN) and cervical cancer, preferably non-invasive ones. In the present study, we aimed to identify unique metabolic signatures for CINs and cervical cancers using global and targeted metabolomic profiling. Plasma samples (69 normal, 55 CIN1, 42 CIN2/3, and 60 cervical cancer) were examined by ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UPLC-QTOF-MS) coupled with multivariate statistical analysis. Metabolic pathways were analyzed using the integrated web-based tool MetaboAnalyst. A multivariate logistic regression analysis was conducted to evaluate the combined association of metabolites and human papillomavirus (HPV) status with the risk of cervical carcinogenesis. A total of 28 metabolites exhibiting discriminating levels among normal, CIN, and cervical cancer patients (Kruskal-Wallis test < 0.05) were identified in the global profiling analysis. The pathway analysis showed significantly altered alanine, aspartate, and glutamate metabolic pathways (FDR -value < 0.05) in both the discovery and validation phases. Seven metabolites (AMP, aspartate, glutamate, hypoxanthine, lactate, proline, and pyroglutamate) were discriminated between CINs and cervical cancer versus normal (area under the curve (AUC) value > 0.8). The levels of these metabolites were significantly high in patients versus normal ( < 0.0001) and were associated with increased risk of developing CIN2/3 and cervical cancer. Additionally, elevated levels of the seven metabolites combined with positive HPV status were correlated with substantial risk of cancer progression. These results demonstrated that metabolomics profiling is capable of distinguishing CINs and cervical cancers from normal and highlighted potential biomarkers for the early detection of cervical carcinogenesis.
宫颈癌仍然是全球女性中最常见的癌症之一。因此，发现用于早期诊断宫颈上皮内瘤变（CIN）和宫颈癌的新生物标志物非常重要，最好是无创的生物标志物。在本研究中，我们旨在通过全局和靶向代谢组学分析来识别CIN和宫颈癌的独特代谢特征。通过超高效液相色谱-四极杆-飞行时间质谱（UPLC-QTOF-MS）结合多变量统计分析对血浆样本（69例正常、55例CIN1、42例CIN2/3和60例宫颈癌）进行检测。使用基于网络的综合工具MetaboAnalyst分析代谢途径。进行多变量逻辑回归分析以评估代谢物和人乳头瘤病毒（HPV）状态与宫颈癌发生风险的联合关联。在全局分析中，共鉴定出28种在正常、CIN和宫颈癌患者中表现出有差异水平的代谢物（Kruskal-Wallis检验<0.05）。通路分析显示，在发现和验证阶段，丙氨酸、天冬氨酸和谷氨酸代谢途径均有显著改变（FDR值<0.05）。在CIN和宫颈癌与正常样本之间，有7种代谢物（AMP、天冬氨酸、谷氨酸、次黄嘌呤、乳酸、脯氨酸和焦谷氨酸）具有区分能力（曲线下面积（AUC）值>0.8）。与正常样本相比，这些代谢物在患者中的水平显著升高（<0.0001），并且与发生CIN2/3和宫颈癌的风险增加相关。此外，这7种代谢物水平升高与HPV阳性状态相结合，与癌症进展的高风险相关。这些结果表明，代谢组学分析能够将CIN和宫颈癌与正常样本区分开来，并突出了用于早期检测宫颈癌发生的潜在生物标志物。
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