背景：当前呼吸生物标志物的敏感性和特异性往往不足以有效进行癌症筛查，特别是结直肠癌（CRC）。虽然 CRC 中的一些呼出生物标志物表现出高特异性，但它们缺乏早期检测所需的敏感性，从而限制了患者生存率的提高。方法：在这项研究中，我们开发了一种先进的基于质谱的挥发组学平台，并辅以增强型呼吸采样器。该平台集成了人工智能（AI）辅助算法，可检测人类呼吸中的多种挥发性有机化合物（VOC）生物标志物。随后，我们应用该平台分析了364份临床CRC和正常呼出气样本。结果：该平台生成的诊断特征（包括 2-甲基、辛烷和丁酸）可有效区分 CRC 患者与正常对照，具有高灵敏度 (89.7%)、特异度 (86.8%) 和准确性 (AUC = 0.91)。此外，转移特征正确识别了超过 50% 的癌胚抗原 (CEA) 检测呈阴性的转移患者。粪便验证表明，呼吸生物标志物升高与结直肠癌中脆弱拟杆菌引导的炎症反应相关。结论：本研究引入了一个复杂的人工智能辅助质谱平台，能够识别用于早期 CRC 检测的新颖且可行的呼吸生物标志物。这些有希望的结果使该平台成为临床应用的有效无创筛查测试，为早期检测和提高 CRC 患者的生存率提供了潜在的进步。© 作者。

Background: The sensitivity and specificity of current breath biomarkers are often inadequate for effective cancer screening, particularly in colorectal cancer (CRC). While a few exhaled biomarkers in CRC exhibit high specificity, they lack the requisite sensitivity for early-stage detection, thereby limiting improvements in patient survival rates. Methods: In this study, we developed an advanced Mass Spectrometry-based volatilomics platform, complemented by an enhanced breath sampler. The platform integrates artificial intelligence (AI)-assisted algorithms to detect multiple volatile organic compounds (VOCs) biomarkers in human breath. Subsequently, we applied this platform to analyze 364 clinical CRC and normal exhaled samples. Results: The diagnostic signatures, including 2-methyl, octane, and butyric acid, generated by the platform effectively discriminated CRC patients from normal controls with high sensitivity (89.7%), specificity (86.8%), and accuracy (AUC = 0.91). Furthermore, the metastatic signature correctly identified over 50% of metastatic patients who tested negative for carcinoembryonic antigen (CEA). Fecal validation indicated that elevated breath biomarkers correlated with an inflammatory response guided by Bacteroides fragilis in CRC. Conclusion: This study introduces a sophisticated AI-aided Mass Spectrometry-based platform capable of identifying novel and feasible breath biomarkers for early-stage CRC detection. The promising results position the platform as an efficient noninvasive screening test for clinical applications, offering potential advancements in early detection and improved survival rates for CRC patients.© The author(s).