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; College of Chemistry and Materials Science, Fujian Provincial Key Laboratory of advanced Oriented Chemical Engineer, Fujian Key Laboratory of Polymer Materials, Fujian Normal University, Fuzhou, Fujian 350117, China; School of Mechanical & Electrical Engineering, PuTian University, PuTian, Fujian 351100, China.
College of Chemistry and Materials Science, Fujian Provincial Key Laboratory of advanced Oriented Chemical Engineer, Fujian Key Laboratory of Polymer Materials, Fujian Normal University, Fuzhou, Fujian 350117, China.
Colloids Surf B Biointerfaces. 2024 Apr;236:113824. doi: 10.1016/j.colsurfb.2024.113824. Epub 2024 Feb 24.
Exosomes, extracellular vesicles released by cells, hold potential as diagnostic markers for the early detection of lung cancer. Despite their clinical promise, current technologies lack rapid and effective means to discriminate between exosomes derived from adenocarcinoma in situ (AIS) and early-stage invasive adenocarcinoma (IAC). This challenge arises from the intrinsic structural heterogeneity of exosomes, necessitating the development of advanced methodologies for precise differentiation. Here, we demonstrate a novel approach for plasma exosome detection utilizing multi-receptor surface-enhanced Raman spectroscopy (SERS) technology to differentiate between AIS and early-stage IAC. To accomplish this, we synthesized a stable and uniform two-dimensional SERS substrate (BC/Au NPs film) by fabricating gold nanoparticles onto bacterial cellulose. We then enhanced its capabilities by introducing multi-receptor SERS functionality via modifying the substrate with both low-specificity and physicochemical-selective molecules. Furthermore, by strategically combining all capturer-exosome SERS spectra, comprehensive "combined-SERS spectra" are reconstructed to enhance spectral variations of the exosome. Combining these features with partial least squares regression-discriminant analysis (PLS-DA) modeling significantly improved discriminatory accuracy, achieving 90% sensitivity and 95% specificity in distinguishing AIS from early-stage IAC. Our developed SERS sensor provides an effective method for early detection of lung cancer, thereby paving a new way for innovative advancements in diagnosing lung cancer.
细胞外囊泡（exosomes）是一种由细胞释放的细胞外囊泡，具有作为肺癌早期检测的诊断标志物的潜力。尽管具有临床应用前景，但目前的技术缺乏快速有效的手段来区分原位腺癌（adenocarcinoma in situ，AIS）和早期浸润性腺癌（invasive adenocarcinoma，IAC）来源的外泌体。这一挑战源于外泌体的内在结构异质性，需要开发先进的方法来进行精确区分。在这里，我们展示了一种利用多受体表面增强拉曼光谱（surface-enhanced Raman spectroscopy，SERS）技术检测血浆外泌体的新方法，以区分 AIS 和早期 IAC。为了实现这一目标，我们通过在细菌纤维素上制造金纳米颗粒来合成一种稳定且均匀的二维 SERS 基底（BC/Au NPs 膜）。然后，我们通过用低特异性和物理化学选择性分子修饰基底来引入多受体 SERS 功能，从而增强其功能。此外，通过策略性地组合所有捕获器-外泌体 SERS 光谱，重建全面的“组合-SERS 光谱”以增强外泌体的光谱变化。将这些特征与偏最小二乘回归判别分析（partial least squares regression-discriminant analysis，PLS-DA）建模相结合，显著提高了区分准确性，在区分 AIS 和早期 IAC 时达到了 90%的灵敏度和 95%的特异性。我们开发的 SERS 传感器为肺癌的早期检测提供了一种有效的方法，为诊断肺癌的创新进展开辟了新途径。
