Abstract
Epithelial ovarian cancer (EOC) is an often-fatal malignancy marked by the development of resistance to platinum-based chemotherapy. Thus, accurate prediction of platinum drug efficacy is crucial for strategically selecting postoperative interventions to mitigate the risks associated with suboptimal therapeutic outcomes and adverse effects. Tissue-derived extracellular vesicles (tsEVs), in contrast to their plasma counterparts, have emerged as a powerful tool for examining distinctive attributes of EOC tissues. In this study, 4D data-independent acquisition (DIA) proteomic sequencing was performed on tsEVs obtained from 58 platinum-sensitive and 30 platinum-resistant patients with EOC. The analysis revealed a notable enrichment of differentially expressed proteins that were predominantly associated with immune-related pathways. Moreover, pivotal immune-related proteins (IRPs) were identified by LASSO regression. These factors, combined with clinical parameters selected through univariate logistic regression, were used for the construction of a model employing multivariate logistic regression. This model integrated three tsEV IRPs, CCR1, IGHV_35 and CD72, with one clinical parameter, the presence of postoperative residual lesions. Thus, this model could predict the efficacy of initial platinum-based chemotherapy in patients with EOC post-surgery, providing prognostic insights even before the initiation of chemotherapy.