Iron Oxide-based SERS Bioprobe for Detecting Tumor Cells in Serous Effusion

We developed an iron oxide-based surface-enhanced Raman spectroscopy (SERS) bioprobe for detecting tumor cells in serous effusions. First, we characterized the bioprobe. Second, we validated its targeting ability and specificity. We first incubated the bioprobe with its target tumor cells for varying durations to determine the optimal incubation time. Then, we incubated it with different tumor cells to observe its specific targeting capability. Next, we evaluated its performance in detecting lung cancer cells in simulated pleural effusion and ovarian cancer cells in ascites. We incubated the IGR bioprobe with pleural effusion containing lung cancer cells and with pleural effusion without lung cancer cells, respectively; additionally, we incubated the IGR bioprobe (without antibodies) with pleural effusion containing lung cancer cells. We then compared the SERS signals among the three groups. We prepared simulated samples with tumor cells at varying concentrations and measured their average Raman signals. Subsequently, we established a classification model to differentiate tumor cells based on their concentrations. Finally, we validated the model using 105 clinical samples and employed machine learning to enhance the accuracy of the SERS bioprobe in classifying tumor cells according to their concentration.