Abstract Introduction Anti–programmed cell death protein 1 (PD-1) or programmed death-ligand 1 (PD-L1) antibody therapy is a standard treatment for advanced NSCLC, and PD-L1 immunohistochemistry is used as a predictive… Click to show full abstract
Abstract Introduction Anti–programmed cell death protein 1 (PD-1) or programmed death-ligand 1 (PD-L1) antibody therapy is a standard treatment for advanced NSCLC, and PD-L1 immunohistochemistry is used as a predictive biomarker for therapeutic response. However, because not all patients with NSCLC with high PD-L1 respond, and some patients with low PD-L1 expression exhibit durable benefit, more accurate predictive biomarkers are needed. Circulating microRNA (miRNA) and miRNA packaged in extracellular vesicles (EVs) are believed to play a role in intercellular communication among immune cells and between immune cells and tumor cells and may represent a good source of mechanism-related biomarkers. Methods Pretreatment plasma of patients with advanced NSCLC treated with single-agent anti–PD-1 or anti–PD-L1 antibody was used in this study. Plasma EVs were isolated using size-exclusion chromatography. Whole plasma and EV-containing RNAs were extracted. The miRNA profile was analyzed with a next-generation sequencing platform. Results Samples from 14 responders (patients who exhibited partial response or stable disease ≥6 mo) and 15 nonresponders (patients who exhibited progressive disease as per Response Evaluation Criteria in Solid Tumors) were analyzed. In total, 32 miRNAs (p = 0.0030–0.0495) from whole plasma and seven EV-associated miRNAs (p = 0.041–0.0457) exhibited significant concentration differences between responders and nonresponders. The results of some of these circulating miRNAs were validated in a separate cohort with eight responders and 13 nonresponders. The tumor PD-L1 level was also assessed using immunohistochemistry for patients involved in both cohorts. Conclusions Specific circulating miRNAs in whole plasma and plasma EVs are differentially expressed between responders and nonresponders and have potential as predictive biomarkers for anti–PD-1/PD-L1 treatment response.
               
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