Extracellular vesicles (EVs) play critical roles in intercellular communications, which contain valuable biomarkers for the detection of cancers. Phosphoproteomics analysis of human saliva EVs (sEVs) can help to discover lung cancer-related candidates. Due to the low abundance of phosphoproteins in sEVs, an efficient, reproducible, and cost-effective strategy is required for their enrichment. Here, we compared the latest phosphopeptide techniques, including TiO, ZrO, CaTiO, and Ti-IMAC (immobilized metal affinity chromatography) methods, for phosphopeptide isolation. Our data demonstrated that Ti-IMAC was the superior one. By using the optimized Ti-IMAC approach, we identified more than 500 sEV phosphopeptides. Quantitative proteomics was employed to comprehensively decipher the sEV phosphoproteome of the normal group (n = 6) and lung cancer group (n = 6). Accordingly, 524 and 333 phosphopeptides were enriched, respectively, which corresponded to 439 and 282 phosphoproteins. In total, 857 unique sEV phosphopeptides corresponding to 721 phosphoproteins were revealed. Among 493 identified phosphosites, 37 were upregulated (> 1.5) and 217 were downregulated (< 0.66) in the cancer group. Our data collectively demonstrated that Ti-IMAC is an efficient and reproducible technology for comprehensive analysis of sEV phosphoproteome. Differentially expressed sEV phosphoproteins and phosphosites might be used for the detection of lung cancer non-invasively.
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http://dx.doi.org/10.1007/s00216-022-04013-7 | DOI Listing |
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