Dai Ze, Li Tong, Lai Kecong, Wang Xiaomei, Zhou Peng, Hu Kefeng, Zhou Yuping
Department of Gastroenterology, The First Affiliated Hospital of Ningbo University, Ningbo, 315020, Zhejiang, China.
Institute of Digestive Disease of Ningbo University, Ningbo University, Ningbo, 315020, Zhejiang, China.
Sci Rep. 2025 Feb 26;15(1):6845. doi: 10.1038/s41598-025-91444-8.
Colorectal cancer (CRC) can evolve from colorectal adenomas, which can be further classified into non-advanced adenomas (NAAs) and advanced adenomas (AAs) based on their clinical characteristics. Their prognoses are vastly different, with patients with NAAs having significantly lower recurrence and CRC-related mortality rates than those with AA or CRC. Although serum metabolomics has shown promise for the early diagnosis of CRC, the differences in serum metabolite composition between NAA and AA still need to be further elucidated. This study aimed to explore the mechanism of CRC occurrence and development based on the unique serum metabolic fingerprints of different stages of CRC and to discover a new non-invasive diagnostic method based on serum metabolomics. A clinical CRC progression cohort containing healthy control (NC; n = 40), NAA (n = 40), AA (n = 40), and CRC (n = 22) groups was constructed, and untargeted metabolomic analysis based on liquid chromatography/mass spectrometry was performed to analyze the serum metabolite characteristics of each group. A semi-quantitative analysis of intergroup metabolite differences was conducted, focusing on specific metabolites that differed in the NAA and AA groups. Finally, variable metabolites were selected based on least absolute shrinkage and selection operator (LASSO) regression analysis, and receiver operating characteristic curves were plotted to evaluate the efficacy of the serum metabolite-based diagnostic model in distinguishing NC/NAA populations from AA/CRC populations. Metabolomic analysis revealed significant differences in the composition of metabolites in the NC and NAA groups compared to the CRC group, whereas the serum metabolites of the AA group were similar to those of the CRC group. The levels of 33 metabolites were significantly different in the serum of AA/CRC patients compared to that of NAA patients, and their functions included glycerophospholipid, sphingolipid, and caffeine metabolism. LASSO regression analysis identified 57 differential metabolite variables between the NC/NAA and AA/CRC groups. The diagnostic model constructed using the random forest algorithm had the best discrimination effect, with areas under the curve of 1.000 (95% confidence interval [CI] 1.000-1.000) and 0.685 (95% CI 0.540-0.830) for the training and testing sets, respectively. The composition of serum metabolites is specific to the different stages of CRC development. The serum metabolite composition of patients with AAs was similar to that of patients with CRC. Auxiliary diagnostic measures based on serum metabolites have the potential to guide the follow-up and treatment of patients with adenoma.
结直肠癌（CRC）可由结直肠腺瘤演变而来，根据其临床特征，结直肠腺瘤可进一步分为非进展性腺瘤（NAAs）和进展性腺瘤（AAs）。它们的预后差异很大，NAAs患者的复发率和CRC相关死亡率明显低于AA或CRC患者。尽管血清代谢组学在CRC的早期诊断中显示出前景，但NAA和AA之间血清代谢物组成的差异仍需进一步阐明。本研究旨在基于CRC不同阶段独特的血清代谢指纹图谱探索CRC发生发展的机制，并发现一种基于血清代谢组学的新型非侵入性诊断方法。构建了一个包含健康对照（NC；n = 40）、NAA（n = 40）、AA（n = 40）和CRC（n = 22）组的临床CRC进展队列，并基于液相色谱/质谱进行非靶向代谢组学分析，以分析每组的血清代谢物特征。对组间代谢物差异进行半定量分析，重点关注NAA和AA组中不同的特定代谢物。最后，基于最小绝对收缩和选择算子（LASSO）回归分析选择可变代谢物，并绘制受试者工作特征曲线，以评估基于血清代谢物的诊断模型区分NC/NAA人群与AA/CRC人群的效能。代谢组学分析显示，与CRC组相比，NC和NAA组代谢物组成存在显著差异，而AA组的血清代谢物与CRC组相似。与NAA患者相比，AA/CRC患者血清中33种代谢物的水平存在显著差异，其功能包括甘油磷脂、鞘脂和咖啡因代谢。LASSO回归分析确定了NC/NAA和AA/CRC组之间的57个差异代谢物变量。使用随机森林算法构建的诊断模型具有最佳的区分效果，训练集和测试集的曲线下面积分别为1.000（95%置信区间[CI]1.000 - 1.000）和0.685（95%CI 0.540 - 0.830）。血清代谢物的组成在CRC发展的不同阶段具有特异性。AA患者的血清代谢物组成与CRC患者相似。基于血清代谢物的辅助诊断措施有可能指导腺瘤患者的随访和治疗。
