Zhang Dechun, Peng Kaiming, Xu Hui, Chen Yanping, Wang Jing
Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, Fujian, 350117, China.
Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, 350001, China.
Adv Sci (Weinh). 2025 Jul;12(25):e2501336. doi: 10.1002/advs.202501336. Epub 2025 May 3.
The presence of a micropapillary (MPP) component is a crucial determinant of surgical strategies for lung adenocarcinoma (LUAD), yet reliable blood biomarkers for predicting MPP⁺ LUAD remain elusive. Here, we integrate 4D label-free quantitative proteomics, a nanomixing-enhanced microfluidic surface-enhanced Raman spectroscopy (SERS) platform, and machine learning to sensitively identify and validate blood protein biomarkers associated with MPP⁺ LUAD. Comparative proteomics reveal 44 differentially expressed proteins (DEPs) between MPP⁺ and MPP⁻ LUADs, with bioinformatics uncovering their roles in MPP⁺ LUAD formation. To enable sensitive, multiplex detection of 4 upregulated DEPs, the nanomixing effect is leveraged to enhance target protein-SERS barcode interactions while minimizing nonspecific binding to antibody-functionalized gold electrodes. The SERS barcode cocktail allows simultaneous detection of the 4 selected DEPs. Machine learning models based on SERS detection effectively distinguish MPP⁺ from MPP⁻ LUAD patients, as well as LUAD patients from healthy donors. This approach demonstrates strong diagnostic potential for early, non-invasive MPP detection in LUAD, advancing nanotechnology-driven disease diagnosis and monitoring.
微乳头（MPP）成分的存在是肺腺癌（LUAD）手术策略的关键决定因素，但用于预测MPP⁺LUAD的可靠血液生物标志物仍然难以捉摸。在此，我们整合了无标记4D定量蛋白质组学、纳米混合增强微流控表面增强拉曼光谱（SERS）平台和机器学习，以灵敏地识别和验证与MPP⁺LUAD相关的血液蛋白质生物标志物。比较蛋白质组学揭示了MPP⁺和MPP⁻LUAD之间44种差异表达蛋白（DEP），生物信息学揭示了它们在MPP⁺LUAD形成中的作用。为了实现对4种上调DEP的灵敏、多重检测，利用纳米混合效应增强靶蛋白-SERS条形码相互作用，同时将与抗体功能化金电极的非特异性结合降至最低。SERS条形码混合物可同时检测4种选定的DEP。基于SERS检测的机器学习模型能够有效区分MPP⁺和MPP⁻LUAD患者，以及LUAD患者和健康供体。这种方法在LUAD早期非侵入性MPP检测中显示出强大的诊断潜力，推动了纳米技术驱动的疾病诊断和监测。
