Yang Shengli, Li Peixian, Zhang Xiaowen, Liu Zhipeng, Zhou Dan, Chen Yihao, Chen Zhuxing, Xiong Yaming
Pulmonary Nodule Surgical Department, The First People's Hospital of Foshan, Foshan 528000, China.
The Institution of Translational Medicine, The First People's Hospital of Foshan, Foshan 528000, China.
ACS Omega. 2025 May 12;10(21):21857-21866. doi: 10.1021/acsomega.5c01737. eCollection 2025 Jun 3.
Proteins are pivotal in life processes; however, the constraints of current detection technologies limit our comprehensive understanding of their mechanisms. Disease progression, particularly in complex, multifactorial conditions, such as lung cancer, involves the dysregulation of numerous proteins. While protein array technology has been at the forefront in proteomic analysis, its challenges in detection throughput, sensitivity, specificity, and cost-effectiveness have impeded its broader clinical application. The enzymatic cleavage of proteins in the bloodstream into peptides of diverse sizes presents an opportunity for peptide array technology, providing both a theoretical basis and practical utility. We have developed a high-throughput peptide array specifically designed for the diagnosis and treatment of lung adenocarcinoma, encompassing peptides from 5 to 16 amino acids in length. This array provides comprehensive coverage of peptides derived from proteins with high mutation frequencies in lung adenocarcinoma as well as those that are differentially expressed in association with the disease. The array's potential for thorough lung cancer surveillance is demonstrated through the concurrent detection and classification of five distinct sample types: healthy controls, benign nodules, stage I lung adenocarcinoma, and both pre- and postoperative samples.
蛋白质在生命过程中起着关键作用；然而，当前检测技术的局限性限制了我们对其机制的全面理解。疾病进展，尤其是在复杂的多因素疾病中，如肺癌，涉及众多蛋白质的失调。虽然蛋白质阵列技术在蛋白质组学分析中处于前沿地位，但其在检测通量、灵敏度、特异性和成本效益方面的挑战阻碍了其更广泛的临床应用。血液中蛋白质酶解为不同大小的肽为肽阵列技术提供了机会，具有理论基础和实际应用价值。我们开发了一种高通量肽阵列，专门用于肺腺癌的诊断和治疗，包含长度为5至16个氨基酸的肽。该阵列全面覆盖了源自肺腺癌中高突变频率蛋白质以及与疾病相关差异表达的肽。通过同时检测和分类五种不同的样本类型：健康对照、良性结节、I期肺腺癌以及术前和术后样本，证明了该阵列在全面监测肺癌方面的潜力。
