Abstract
New therapeutics targeting immune checkpoint proteins have significantly advanced treatment of non-small cell lung cancer (NSCLC), but protein level quantitation of drug targets presents a critical problem. We used multiplexed, targeted mass spectrometry (MS) to quantify immunotherapy target proteins PD-1, PD-L1, PD-L2, IDO1, LAG3, TIM3, ICOSLG, VISTA, GITR, and CD40 in formalin-fixed, paraffin-embedded (FFPE) NSCLC specimens. Immunohistochemistry (IHC) and MS measurements for PD-L1 were weakly correlated, but IHC did not distinguish protein abundance differences detected by MS. PD-L2 abundance exceeded PD-L1 in over half the specimens and the drug target proteins all displayed different abundance patterns. mRNA correlated with protein abundance only for PD-1, PD-L1, and IDO1 and tumor mutation burden did not predict abundance of any protein targets. Global proteome analyses identified distinct proteotypes associated with high PD-L1-expressing and high IDO1-expressing NSCLC. MS quantification of multiple drug targets and tissue proteotypes can improve clinical evaluation of immunotherapies for NSCLC.
Highlights
The large number of validated drug targets and the complexity of their interactions presents a substantial challenge in systematic development of new therapeutics and therapeutic combinations
PD-1 protein was detected by mass spectrometry (MS) in 27 of the 46 tumors analyzed and mRNA was measured in 43 tumors
PD-L1 protein was detected in 40 tumors and was correlated with mRNA abundance (r2 = 0.7040; p < 0.0001) (Fig. 1B)
Summary
The large number of validated drug targets and the complexity of their interactions presents a substantial challenge in systematic development of new therapeutics and therapeutic combinations. In NSCLC, clinical trials are evaluating drugs targeting multiple immune checkpoint proteins PD-1, PD-L1, LAG3, TIM3 (HAVCR2), VISTA (VSIR), CD40, and GITR (TNFRSF18), as well as combinations of immune checkpoint inhibitors and other targets. The success of combination therapies will depend in large part on understanding the relationships between drug target protein abundances and tumor phenotypes. Analysis of drug protein targets in tissues has been done largely by immunochemical methods, immunohistochemistry (IHC)[10]. A key limitation of MS methods for drug target quantitation is that sample processing does not preserve protein localization in tissue components. We combined targeted MS of immune checkpoint proteins and global MS to analyze FFPE specimens from a set of 46 NSCLCs, which we analyzed by RNA-Seq, DNA sequencing to analyze tumor mutation burden (TMB) and IHC. Comparison of the datasets demonstrates the unique value of MS measurements for protein level analysis of drug targets and their associated proteotypes
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