Depletion-dependent activity-based protein profiling SWATH/DIA mass spectrometry discriminates aggressive lung adenocarcinomas through molecular abundances and catalytic action of serine hydrolases

Background: Aberrant molecular mechanisms at the origin of pathologies depend on the activity and regulation of molecules, primarily proteins and their interactions. Abundance measurements of proteins or transcripts, widely used in molecular medicine, are generally blind to functional protein status. Determining the functional state of proteins, in particular the catalytic state of enzymes and their regulation by genetic variation, compartmentalisation, post-translational modifications, ligands or molecular interactions, is a prerequisite for understanding cancer progression and therapy resistance. Activity-based proteome profiling (ABPP) is the tool of functional MS-based proteomics for the quantification of catalytically active enzymes1. Here, we describe a novel variant of ABPP, depletion-dependent ABPP (dd-ABPP) combined with an automated SWATH/DIA-MS workflow, which simultaneously determines three molecular layers of data: i) the fractions of catalytically active enzymes; ii) the relative abundances of enzymes and background proteins; and iii) context-dependent protein-protein interactions involving enzymes. Methods: To demonstrate the capabilities of the platform, 32 lung biopsies from a cohort of patients with long and short survival type IIIA lung adenocarcinoma (LUAD) and their normal tissue counterparts embedded in OCT were retrospectively analysed. We monitored the activities of the serine hydrolase (SH) family of enzymes known to be involved in cancer1 and abundances of approximately 4000 contextual tissue proteins using the dd-ABPP-SWATH/DIA-MS workflow, which integrates bespoke software tools for automation2,3. Commercial assays and subsequent lipidomic, metallomic and genomic analyses were used for data validation. Results: A discriminative signature of the activity profiles of 23 SHs and 59 tissue proteins associated with the active enzymes identified accelerated de-palmitoylation of lipoproteins, which were enriched sevenfold with dysregulated hydrolases within the discriminative signature compared to standard proteomes (Fig 1). In aggressive tumours, subsequent lipidomics confirmed an increase in monounsaturated metabolites of palmitic acid in line with increased expression of stearoyl-CoA desaturase, a rate-limiting enzyme of palmitate desaturation. Further results showed that dysregulated catalytic fractions of palmitoyl-(protein) hydrolases are not compensated by biological levels of enzymes, but are most likely related to the specificity of enzyme-protein sequences or molecular tissue heterogeneity (e.g. somatic mutations of SH genes, tissue content of "tobacco" metals). Conclusions: Taken together, the ensemble of our proteomic data, integrated via computational modelling tools, has the ability to provide new insights into the functional regulation of enzymes in tumours.

1.Jessani, N., et al., Nat Methods, 2005. 2(9): p. 691-7.
2.Rost, H.L., et al., Nat Biotechnol, 2014. 32(3): p. 219-23.
3.Rost, H.L., et al., Nat Methods, 2016. 13(9): p. 777-83.