Defining molecular interfaces of glyco-immune checkpoint ligands using tandem mass spectrometry and ion-ion reactions

The Siglec ( s ialic acid-binding i mmuno g lobulin-like lec tin) family of glycan-binding immune receptors are emerging as attractive targets for cancer immunotherapy. Siglecs recognize cell surface glycoproteins through complex interactions with various glycans containing sialic acid residues, which are upregulated in numerous malignancies. Engagement of Siglecs by their sialoglyco-ligands elicits an inhibitory signaling cascade using the same immunoreceptor tyrosine-based inhibitory motif (ITIM) signaling domains shared by established immune checkpoint receptors (e.g., PD-1, CTLA-4, and SIRPalpha). Our understanding of the mechanisms behind Siglec-mediated immune evasion has been rapidly improving, largely due to efforts to define transcriptional and metabolic programs that promote Siglec ligand expression. Even so, unknown combinations of glycan and protein epitopes (i.e., the glycocode) that guide Siglec ligand recognition are a major hurdle for exploiting Siglecs as therapeutic targets. Molecular details of specific glycocode patterns that contribute to Siglec ligand recognition are needed to target immune modulatory glycoforms in tumor-specific microenvironments while minimizing off-target effects, but these heterogenous modifications states challenge traditional analytical approaches. Here, we describe our efforts to develop cutting-edge mass spectrometry (MS) data acquisition technologies that incorporate electron transfer dissociation (ETD) and proton transfer charge reduction (PTCR) ion-ion reactions to profile highly complex Siglec ligand glycoproteins. We use online and offline MS workflows in combination with bottom-up glycoproteomics to profile highly heterogeneous intact glycoproteoforms of Siglec ligands that have emerged as attractive targets for next-generation glyco-immunotherapies. PTCR readily isolated and charge-reduced proteoforms of interest, generating pseudo-native spectra. PTCR scans of interest were identified, and spectra were cleaned using in-house software, PTCRcleaner. Analysis of both intact approaches was supported by bottom-up mass spectrometry data collected using a sceHCD-pd-EThcD approach. We also applied this workflow to characterize other glycosylated immune checkpoint ligands, e.g., PD-L1. Altogether, our novel tandem MS approaches that uniquely leverage ion-ion reactions enable the characterization of highly heterogeneous glycoproteoform repertoires, contributing to a deeper understanding of the complexity of the glycocode and how these proteins contribute to heterogeneity in the tumor-immune synapse.