Chen Dayu, Wang Yingfei, Wei Ying, Lu Zhenda, Ju Huangxian, Yan Feng, Liu Ying
The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu cancer hospital, Jiangsu Institute of cancer research, Nanjing 210009, China.
State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
Nano Lett. 2025 Jan 8;25(1):453-460. doi: 10.1021/acs.nanolett.4c05233. Epub 2024 Dec 16.
Classifying lung cancer subtypes, which are characterized by multi-microRNAs (miRNAs) upregulation, is important for therapy and prognosis evaluation. Liquid biopsy is a promising approach, but the pretreatment of RNA extraction is labor-intensive and impairs accuracy. Here we develop size-coded hydrogel microbeads for extraction-free quantification of miR-21, miR-205, and miR-375 directly from serum. The hydrogel microbead is immobilized with an miRNA capture probe, which well retains target miRNA and provides good nonfouling capability for nonspecific biomolecules in serum. The porous structure of microbeads allows efficient DNA cascade amplification reaction and generates a fluorescence signal. The microbeads are clustered into three groups according to size via flow cytometry sorting, and the group fluorescence is integrated for the corresponding miRNA quantification. With machine-learning-assisted data analysis, it achieves good lung cancer diagnosis accuracy and 80% accuracy for subtype classification for 108 serum samples, including lung cancer patients and healthy controls.
对以多种微小RNA（miRNA）上调为特征的肺癌亚型进行分类，对于治疗和预后评估至关重要。液体活检是一种很有前景的方法，但RNA提取的预处理工作强度大且会影响准确性。在此，我们开发了尺寸编码水凝胶微珠，用于直接从血清中对miR-21、miR-205和miR-375进行无需提取的定量分析。水凝胶微珠固定有miRNA捕获探针，该探针能很好地保留靶miRNA，并为血清中的非特异性生物分子提供良好的抗污染能力。微珠的多孔结构允许高效的DNA级联扩增反应并产生荧光信号。通过流式细胞术分选，微珠根据尺寸被聚集成三组，并且对组荧光进行积分以进行相应的miRNA定量分析。借助机器学习辅助数据分析，对于108份血清样本（包括肺癌患者和健康对照），它实现了良好的肺癌诊断准确性以及80%的亚型分类准确率。
