State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China.
Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, P.R. China.
Cell Rep Med. 2024 Jun 18;5(6):101579. doi: 10.1016/j.xcrm.2024.101579. Epub 2024 May 21.
Molecular phenotypic variations in metabolites offer the promise of rapid profiling of physiological and pathological states for diagnosis, monitoring, and prognosis. Since present methods are expensive, time-consuming, and still not sensitive enough, there is an urgent need for approaches that can interrogate complex biological fluids at a system-wide level. Here, we introduce hyperspectral surface-enhanced Raman spectroscopy (SERS) to profile microliters of biofluidic metabolite extraction in 15 min with a spectral set, SERSome, that can be used to describe the structures and functions of various molecules produced in the biofluid at a specific time via SERS characteristics. The metabolite differences of various biofluids, including cell culture medium and human serum, are successfully profiled, showing a diagnosis accuracy of 80.8% on the internal test set and 73% on the external validation set for prostate cancer, discovering potential biomarkers, and predicting the tissue-level pathological aggressiveness. SERSomes offer a promising methodology for metabolic phenotyping.
分子表型变化在代谢物中提供了快速分析生理和病理状态的可能性,可用于诊断、监测和预后。由于目前的方法昂贵、耗时,而且仍然不够敏感,因此迫切需要能够在系统水平上检测复杂生物流体的方法。在这里,我们介绍了超高光谱表面增强拉曼光谱 (SERS),它可以在 15 分钟内对微升生物流体代谢物提取进行分析,使用 SERSome 光谱集,可以通过 SERS 特征来描述特定时间在生物流体中产生的各种分子的结构和功能。成功地对各种生物流体(包括细胞培养基和人血清)进行了代谢物差异分析,在内部测试集中的诊断准确率为 80.8%,在外部验证集中的准确率为 73%,用于前列腺癌的诊断,发现了潜在的生物标志物,并预测了组织级别的病理侵袭性。SERSomes 为代谢表型分析提供了一种很有前途的方法。