Wang Xiaowei, Xu Xuefeng, Jia Ran, Xu Yuanhong, Hu Ping
Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Department of Hepatobiliary surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Front Mol Biosci. 2025 Apr 7;12:1549223. doi: 10.3389/fmolb.2025.1549223. eCollection 2025.
Cholangiocarcinoma (CCA) is a highly aggressive malignancy, and early diagnosis remains challenging. Metabolic biomarkers are increasingly recognized as promising tools for the early detection of cancer. However, a comprehensive exploration of metabolic alterations in CCA, especially from a global metabolic perspective, has yet to be fully realized. To identify reliable metabolic markers for the early diagnosis of CCA and to explore its potential pathogenesis through an in-depth analysis of global metabolism.
Serum samples from 30 CCA patients and 31 healthy individuals were analyzed using an unbiased UPLC-Q-TOF-MS based metabolomics approach. Principal component analysis (PCA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA) were applied to identify potential biomarkers. High-resolution MS/MS and available standards were used to further confirm the identified metabolites. A systematic metabolic pathway analysis was conducted to interpret the biological roles of these biomarkers and explore their relevance to CCA progression.
A total of 25 marker metabolites were identified, including lysophosphatidylcholines (LysoPCs), phosphatidylcholines (PCs), organic acids, sphinganine, and ketoleucine. These metabolites effectively distinguished CCA patients from healthy controls, with an AUC of 0.995 for increased biomarkers and 0.992 for decreased biomarkers in positive mode. In negative mode, the AUC for increased and decreased biomarkers was 0.899 and 0.976, respectively. The metabolic pathway analysis revealed critical biological functions linked to these biomarkers, offering insights into the molecular mechanisms underlying CCA initiation and progression.
This study identifies novel metabolic biomarkers for the early diagnosis of CCA and provides a deeper understanding of the metabolic alterations associated with the disease. These findings could contribute to the development of diagnostic strategies and therapeutic interventions for CCA.
胆管癌（CCA）是一种侵袭性很强的恶性肿瘤，早期诊断仍然具有挑战性。代谢生物标志物越来越被认为是癌症早期检测的有前景的工具。然而，对CCA代谢改变的全面探索，尤其是从整体代谢角度，尚未完全实现。旨在识别用于CCA早期诊断的可靠代谢标志物，并通过深入分析整体代谢来探索其潜在发病机制。
使用基于超高效液相色谱-四极杆飞行时间质谱（UPLC-Q-TOF-MS）的非靶向代谢组学方法分析30例CCA患者和31名健康个体的血清样本。应用主成分分析（PCA）和正交投影到潜在结构判别分析（OPLS-DA）来识别潜在生物标志物。使用高分辨率串联质谱（MS/MS）和可用标准品进一步确认所鉴定的代谢物。进行系统的代谢途径分析以解释这些生物标志物的生物学作用，并探索它们与CCA进展的相关性。
共鉴定出25种标志物代谢物，包括溶血磷脂酰胆碱（LysoPCs）、磷脂酰胆碱（PCs）、有机酸、鞘氨醇和酮亮氨酸。这些代谢物能有效区分CCA患者和健康对照，在正模式下生物标志物升高的曲线下面积（AUC）为0.995，生物标志物降低的AUC为0.992。在负模式下，生物标志物升高和降低的AUC分别为0.899和0.976。代谢途径分析揭示了与这些生物标志物相关的关键生物学功能，为CCA发生和进展的分子机制提供了见解。
本研究鉴定出用于CCA早期诊断的新型代谢生物标志物，并对与该疾病相关的代谢改变有了更深入的了解。这些发现可能有助于开发CCA的诊断策略和治疗干预措施。
