Chinese scientists have developed a novel surface-enhanced Raman spectroscopy (SERS) array sensor that transforms nanoproteomics data into multidimensional Raman spectromics, enabling facile and cost-effective ovarian cancer (OC) diagnosis. The study bridges the gap between deep proteomic analysis and clinical-scale screening, offering a powerful new tool for tackling one of the deadliest gynecologic cancers.
This research was led by Prof. LIU Yuan from Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences and Prof. TAO Wei from Brigham and Women’s Hospital Harvard Medical School. The findings has been published in Cell Biomaterials.
The team have discovered that blood proteomics based on nanoparticle-protein corona (NPC) achieve significant progress in deep proteomics for cancer biomarker discovery and diagnosis. However, laborious, time-consuming, and high-cost liquid chromatography-tandem mass spectrometry (LC-MS/MS) hinders its clinical application in rapid and high-throughput cancer screening. The team set out to bridge NPC nanoproteomics with SERS to create a diagnostic tool that preserves proteomic specificity while overcoming the limitations of MS-based approaches.
The SiO2@Au NPC array sensor modified with DNA-Cy3 and three distinct Raman dyes (3,4-difluorothiophenol [DFTP], 4-nitrothiophenol [NTP], and 4-bromothiophenol [BTP]) generated a robust spectral fingerprint comprising 26 resolvable peaks, effectively mitigating spectral overlap inherent to complex serum samples.
Clinical validation using 137 serum samples (90 healthy controls and 47 OC patients) showed that the full three-dye SERS array achieved an AUC of 97.31% and an accuracy of 92.73%, outperforming standard OC biomarkers (CA125 and HE4, which only had an AUC of 78%). Notably, the sensor also successfully distinguished untreated OC patients from those who had undergone chemotherapy, demonstrating its ability to detect dynamic proteomic changes associated with treatment response.
This approach bridges nanoproteomics and optical biosensing, offering a scalable alternative to traditional mass spectrometry for cancer screening. The technology’s high diagnostic accuracy and capacity to detect treatment-related changes underscore its potential for precision oncology applications.
