Multiplex Immuno-Liquid Chromatography–Mass Spectrometry–Parallel Reaction Monitoring (LC–MS–PRM) Quantitation of CD8A, CD4, LAG3, PD1, PD-L1, and PD-L2 in Frozen Human Tissues

The immune status of tumors critically influences their responsiveness to PD1 blockades and other immune-based therapies. Programmed death ligand 1 (PD-L1) immunohistochemistry (IHC) is a clinically validated predictive biomarker of response to checkpoint-inhibitor therapy in a limited number of clinical settings but is poorly predictive in most. With emerging evidence that multiple pathways and immune-checkpoint proteins may coordinately contribute to the adaptive immune resistance, the identification and quantitation of multiple immune markers in tumor tissue could help identify the controlling pathways in a given patient, guide the selection of optimal therapy, and monitor response to treatment. We developed and validated a sensitive and robust immuno-liquid chromatography–parallel reaction monitoring assay to simultaneously quantify the expression levels of six immune markers (CD8A, CD4, LAG3, PD1, PD-L1, and PD-L2) using as little as 1–2 mg of fresh frozen tissue. The lower limit of quantitation ranged from 0.07 ng/mg protein for PD1 to 1.0 ng/mg protein for CD4. The intrabatch accuracy was within −16.6% to 15.0% for all proteins at all concentrations, and the variation ranged from 0.8% to 14.7%, while interbatch accuracy was within −6.3% to 8.6%, and the variation ranged from 1.3% to 12.8%. The validated assay was then applied to quantify all six biomarkers in different tissues and was confirmed to have sufficient sensitivity (0.07–1.00 ng/mg protein) and reproducibility (variation ranged from 4.3 to 12.0%). In an analysis of 26 cervical tumors, CD8A and CD4 were detected in all tumors, followed by PD-L1 in 85%, LAG-3 in 65%, PD1 in 50%, and PD-L2 in 35%. The strongest correlations were observed between CD8A and CD4 (r = 0.88) and CD8A and LAG-3 (r = 0.86). PD1 was not significantly correlated with any of the other proteins tested. This method can be applied to survey the immune signatures across tumor types and tailored to incorporate additional markers as needed.