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 Pathology, Clinical Oncology School of Fujian Medical University and Fujian Cancer Hospital, Fuzhou, Fujian, 350014, China.
Biosens Bioelectron. 2023 Sep 1;235:115235. doi: 10.1016/j.bios.2023.115235. Epub 2023 Mar 15.
DNA methylation plays a critical role in the development of human tumors. However, routine characterization of DNA methylation can be time-consuming and labor-intensive. We herein describe a sensitive, simple surface-enhanced Raman spectroscopy (SERS) approach for identifying the DNA methylation pattern in early-stage lung cancer (LC) patients. By comparing SERS spectra of methylated DNA bases or sequences with their counterparts, we identified a reliable spectral marker of cytosine methylation. To move toward clinical applications, we applied our SERS strategy to detect the methylation patterns of genomic DNA (gDNA) extracted from cell line models as well as formalin-fixed paraffin-embedded tissues of early-stage LC and benign lung diseases (BLD) patients. In a clinical cohort of 106 individuals, our results showed distinct methylation patterns in gDNA between early-stage LC (n = 65) and BLD patients (n = 41), suggesting cancer-induced DNA methylation alterations. Combined with partial least square discriminant analysis, early-stage LC and BLD patients were differentiated with an area under the curve (AUC) value of 0.85. We believe that the SERS profiling of DNA methylation alterations, together with machine learning could potentially offer a promising new route toward the early detection of LC.
DNA 甲基化在人类肿瘤的发展中起着关键作用。然而，常规的 DNA 甲基化特征分析既耗时又费力。在此，我们描述了一种用于鉴定早期肺癌（LC）患者 DNA 甲基化模式的灵敏、简单的表面增强拉曼光谱（SERS）方法。通过比较甲基化 DNA 碱基或序列的 SERS 光谱与其对应物，我们确定了一种可靠的胞嘧啶甲基化的光谱标记物。为了向临床应用推进，我们应用我们的 SERS 策略来检测来自细胞系模型以及早期 LC 和良性肺部疾病（BLD）患者的福尔马林固定石蜡包埋组织中基因组 DNA（gDNA）的甲基化模式。在 106 名个体的临床队列中，我们的结果显示，早期 LC（n=65）和 BLD 患者（n=41）之间 gDNA 存在明显的甲基化模式，表明癌症诱导的 DNA 甲基化改变。结合偏最小二乘判别分析，早期 LC 和 BLD 患者得到了 0.85 的曲线下面积（AUC）值。我们相信，DNA 甲基化改变的 SERS 分析，加上机器学习，可能为 LC 的早期检测提供一种有前途的新途径。
