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Anti-PD-1 Therapy Response Predicted by the Combination of Exosomal PD-L1 and CD28

Chaoxu Zhang, Yibo Fan, Xiaofang Che, Min Zhang, Zhi Li, Ce Li, Shuo Wang, Ti Wen, Kezuo Hou, Xinye Shao, Yunpeng Liu, Xiujuan Qu

2020Frontiers in Oncology69 citationsDOIOpen Access PDF

Abstract

Anti-PD-1 therapy has been approved for cancer treatment. However, the response rate is unsatisfactory. The expression of PD-L1 in tumor tissues is unreliable to predict the treatment response. Recent studies suggested that exosomal PD-L1 not only exerts immunosuppressive effects but also plays a significant role in the development of tumor microenvironment. Thus, the present study aimed to investigate exosomal PD-L1 in improving its predictive value and efficacy. A total of 44 patients with several types of advanced tumors, treated by anti-PD-1 therapy, were enrolled. Exosomes were collected and purified from plasma. The exosomal PD-L1 was detected by ELISA. The cytokines were measured by the MILLIPLEX magnetic bead assay. Compared to the responders, exosomal PD-L1 of the non-responders were significantly higher than those of the responders (P=0.010) before the treatment. Concurrently, exosomal PD-L1 and tumor burden decreased when the therapy was effective. Also, the baseline expression of CD28 was higher in the responders than non-responders (P=0.005). Univariate and multivariate analysis validated with 1000 times bootstrapping suggested that high exosomal PD-L1 and low CD28 expression were negative factors for progression-free survival (PFS) in patients who underwent anti-PD-1 treatment. The combination of exosomal PD-L1 and CD28 obtained more area under the curve (AUC) of receiver operating characteristic (ROC) (AUC 0.850 vs. 0.784 vs. 0.678) and showed a higher probability without progression via nomograph. These findings suggested that the expression of exosomal PD-L1 and CD28 could serve as the predictive biomarkers for clinical responses to anti-PD-1 treatment.

Topics & Concepts

MedicineInternal medicineOncologyMicrovesiclesPD-L1Receiver operating characteristicCombination therapyMultivariate analysisUnivariate analysisTumor progressionCancerImmunotherapymicroRNABiologyBiochemistryGeneCancer Immunotherapy and BiomarkersExtracellular vesicles in diseaseImmunotherapy and Immune Responses