Early increment of soluble triggering receptor expressed on myeloid cells 2 in plasma might be a predictor of poor outcome after ischemic stroke.

Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) is derived from cleavage of TREM2, which is expressed on the cell surface of microlgia and other tissue-specific macrophages. In the present study, the changes in the sTREM2 levels after ischemic stroke (IS) and their association with clinical outcomes were evaluated. A total of 43 patients diagnosed with non-cardioembolic IS between June 2011 and May 2014 were consecutively included in this study. Patients treated with intravenous thrombolysis or intra-arterial thrombectomy were excluded. Plasma samples were collected three times (days 1, 7, and 90) after ictus. The sTREM2 level was measured in the samples using the highly sensitive solid-phase proximity ligation assay (SP-PLA). Among the 43 subjects, higher initial NIH stroke scale (NIHSS) score (P = 0.005), early increment of sTREM2 (P < 0.001), and late decrement of sTREM2 (P = 0.002), were more common in patients with poor outcome. Based on multivariate analysis, initial NIHSS score (P = 0.015) and early increment of sTREM2 (P = 0.032) were independently associated with poor outcome. The results from the present study indicate that increment of sTREM2 level at the early phase was a predictor of poor outcome. Serial follow-up of sTREM2 may aid prognosis after stroke.

A targeted proteomics approach reveals a serum protein signature as diagnostic biomarker for resectable gastric cancer.

BACKGROUND: Gastric cancer (GC) is the third leading cause of cancer death. Early detection is a key factor to reduce its mortality. METHODS: We retrospectively collected pre- and postoperative serum samples as well as tumour tissues and adjacent normal tissues from 100 GC patients. Serum samples from non-cancerous patients were served as controls (n = 50). A high-throughput protein detection technology, multiplex proximity extension assays (PEA), was applied to measure levels of over 300 proteins. Alteration of each protein was analysed by univariate analysis. Elastic-net logistic regression was performed to select serum proteins into the diagnostic model. FINDINGS: We identified 19 serum proteins (CEACAM5, CA9, MSLN, CCL20, SCF, TGF-alpha, MMP-1, MMP-10, IGF-1, CDCP1, PPIA, DDAH-1, HMOX-1, FLI1, IL-7, ZBTB-17, APBB1IP, KAZALD-1, and ADAMTS-15) that together distinguish GC cases from controls with a diagnostic sensitivity of 93%, specificity of 100%, and area under receiver operating characteristic curve (AUC) of 0·99 (95% CI: 0·98-1). Moreover, the 19-serum protein signature provided an increased diagnostic capacity in patients at TNM I-II stage (sensitivity 89%, specificity 100%, AUC 0·99) and in patients with high microsatellite instability (MSI) (91%, 98%, and 0·99) compared to individual proteins. These promising results will inspire a large-scale independent cohort study to be pursued for validating the proposed protein signature. INTERPRETATION: Based on targeted proteomics and elastic-net logistic regression, we identified a 19-serum protein signature which could contribute to clinical GC diagnosis, especially for patients at early stage and those with high MSI. FUND: This study was supported by a European H2020-Marie Sklodowska-Curie Innovative Training Networks grant (316,929, GastricGlycoExplorer). Funder had no influence on trial design, data evaluation, and interpretation.

Protein measurements in venous plasma, earlobe capillary plasma and in plasma stored on filter paper.

In this study, levels of inflammatory protein biomarkers in venous plasma, plasma derived from capillary blood from the earlobe, and capillary plasma stored as dried plasma spots (DPS) were compared. Samples from 12 male individuals were assessed with a panel of 92 inflammation-related proteins using multiplex proximity extension assay. Correlations between sample types varied greatly between analytes. A high correlation of ρ > 0.8 was observed between capillary plasma and DPS for 32 analytes. At this level of correlation, 13 analytes correlated between venous and capillary plasma and 5 analytes in the comparison of venous blood with DPS.