Abstract

Abstract Introduction/Objective Lung cancer is the leading cause of cancer-related deaths worldwide, with a majority of cases detected at a non-resectable advanced stage. Current anti PD-1/-L1 therapy has reformed cancer treatment strategies with remarkable clinical outcomes in non-small cell lung cancer (NSCLC). However, the overall response rate is still marginal, demonstrating the need for biomarkers predictive of response. The objective of this study is to develop a serum based panel to prognosticate clinical response in advanced NSCLC patients receiving anti PD-1/-L1 therapy. Methods Pooled sera from two response groups (Poor response, n=20, overall survival < 12 months; Good response, n=20, overall survival > 12 months) were evaluated via the HuProt™ Human Proteome Microarray (CDI laboratories, Baltimore, MD) to identify expressed neoantigens. Recombinant proteins representative to identified neoantigens along with their corresponding antibodies, were commercially acquired to develop a robust 13-plex bead- based immunoassay to evaluate the autoantibodies in pretreatment sera from 125 advanced-stage NSCLC patients. Finally, levels of autoantibodies were correlated to clinical outcome, including progression free survival (PFS), overall survival (OS) and grade III adverse events. Results Low baseline levels of ZNF695, MCM4, PRMT2, FGD3, GTF2A1, GLUL, CDCA3, ZNF277, GARS, GBP2, UBL7, and ASNA1 autoantibodies were found to be associated with a longer PFS (all p-values < 0.01), whereas increased levels were associated with a poor PFS outcome (0.06, HR=0.66, 95% CI). Low levels of ZNF695, MCM4, PRMT2, FGD3, GARS, GBP2, and UBL7 autoantibodies were associated with favorable OS (all p-values < 0.01). Conclusion In this study we demonstrated that serum autoantibodies have great promise to serve as a prognostic tool for immunotherapy response. We successfully developed a high performance multiplexed serum based assay to evaluate autoantibodies in an advanced NSCLC patients receiving anti PD-1/-L1 therapy.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call