Phenotyping multiple subsets in Sjögren’s syndrome: a salivary proteomic SWATH-MS approach towards precision medicine

Abstract

Background This proof of concept study was aimed at characterizing novel salivary biomarkers specific for different subsets in primary Sjögren’s syndrome (pSS) in order to improve patients’ profiling. Methods pSS patients were stratified in three subgroups according to both (a) focus score in the minor salivary gland biopsies (i.e. intensity of immune cell infiltration in the tissue) and (b) unstimulated salivary flow rate. Healthy volunteers were included as controls. A nano-HPLC-SWATH-MS approach was used for the analysis of saliva proteome of different subsets. Results We found 203 differentially expressed proteins in pSS patients with respect to controls with evident differences in the expression of normal constituents of the human salivary proteome (i.e. prolactin-inducible protein, proline-rich proteins, cystatins) and several mediators of inflammatory processes. The comparative analysis of the pSS phenotypes unrevealed 63 proteins that were shared and specifically modulated in the three subsets of pSS patients converging on several inflammatory pathways. Among them S100A protein appeared of particular interest merging on IL-12 signaling and being significantly influenced by either salivary flow impairment or intensity of immune cell infiltration in the tissue. Conclusions Constellations of proteins, including S100A proteins, characterize different pSS subsets reflecting either salivary gland dysfunction or inflammation. Salivary proteomics may foster future research projects ultimately aimed at developing personalized treatments for pSS patients. Electronic supplementary material The online version of this article (10.1186/s12014-019-9245-1) contains supplementary material, which is available to authorized users.

Characterization of Extracellular Vesicle Cargo in Sjögren’s Syndrome through a SWATH-MS Proteomics Approach

“…Proteins commonly identified/quantified in both EVs and WS included groups of proteins previously found in saliva like cystatins family (B, D, S, SA, and SN), BPI fold-containing family A and B members, mucins 5AC and CB and mucin 7, some members of S100 proteins (A8 and A9) and prolactin-inducible protein that was previously shown as potential salivary biomarker of pSS by our group [ 9 ]. Proteins exclusively quantified in WS mainly included a class of proteins that are major components of parotid and submandibular gland tissue in humans which are the basic salivary proline-rich protein 2, small proline-rich proteins 2A, 2B, 2D, 2E, 2G, and 2F.…”

“…During the last decade, salivary proteomics has appeared as a promising tool for identifying specific biomarkers able to mirror no-invasively pSS-related salivary gland inflammation and dysfunction [ 8 ]. Indeed, existing literature has described a number of qualitative and quantitative protein abnormalities in pSS saliva composition potentially correlated with the oral inflammation and salivary rheological alterations observed during the disease course suggesting that salivary proteomic biomarkers and salivary cytokines may be able to reflect not only the local but also the systemic activity of the disease [ 9 , 10 , 11 , 12 , 13 , 14 , 15 ]. However, despite the advantages recognized in studying whole saliva (WS), several potential limitations have been gradually come to light.…”

A mouse SWATH-MS reference spectral library enables deconvolution of species-specific proteomic alterations in human tumour xenografts

“…The ability to capture all peptide precursor ions dramatically improves reproducibility in protein identification across multiple samples. These quantitative digital proteome maps have been shown to have wide applications in medical research, such as the discovery of potential biomarkers and therapeutic targets ( Cecchettini et al, 2019 ; Gao et al, 2017 ; Miyauchi et al, 2018 ; Hou et al, 2016 ; Xu et al, 2018 ), as well as tumour proteotyping for cancer stratification and classification ( Bouchal et al, 2019 ; Zhu et al, 2019 ).…”

A mouse SWATH-MS reference spectral library enables deconvolution of species-specific proteomic alterations in human tumour xenografts

“…In this manner, all precursor ions generated from the sample under investigation are fragmented and their fragmentation spectra acquired for subsequent in silico analysis. These quantitative digital proteome maps have been shown to have wide applications in medical research such as the discovery of potential biomarkers and therapeutic targets [6–10] as well as tumour proteotyping for cancer stratification and classification [11, 12].…”