Straightforward and Highly Efficient Strategy for Hepatocellular Carcinoma Glycoprotein Biomarker Discovery Using a Nonglycopeptide-Based Mass Spectrometry Pipeline.

Efficient detection of aberrant glycoproteins in serum is particularly important for biomarker discovery. However, direct quantitation of glycoproteins in serum remains technically challenging because of the extraordinary complexity of the serum proteome. In the current work, we proposed a straightforward and highly efficient strategy by using the nonglycopeptides releasing from the specifically enriched glycoproteins for targeted glycoprotein quantification. With this so-called nonglycopeptide-based mass spectrometry (NGP-MS) strategy, a powerful and nondiscriminatory pipeline for hepatocellular carcinoma (HCC) glycoprotein biomarker discovery, verification, and validation has been developed. First, a data set of 234 NGPs was strictly established for multiple-reaction monitoring (MRM) quantification in serum. Second, the NGPs enriched from 20 HCC serum mixtures and 20 normal serum mixtures were labeled with mTRAQ reagents (Δ0 and Δ8, respectively) to find the differentially expressed glycoproteins in HCC. A total of 97 glycoprotein candidates were preliminarily screened and submitted for absolute quantitation with NGP-based stable-isotope-labeled (SID)-MRM in the individual samples of 38 HCC serum and 24 normal controls. Finally, 21 glycoproteins were absolutely quantified with high quality. The diagnostic sensitivity results showed that three glycoproteins, ß-2-glycoprotein 1 (APOH), α-1-acid glycoprotein 2 (ORM2), and complement C3 (C3), could be used for the discrimination between HCC patients and healthy people. A novel glycoprotein biomarker panel [APOH, ORM2, C3, and α-fetoprotein (AFP)] has proven to outperform AFP, the known HCC serum biomarker, alone, in this study. We believe that this strategy and the panel of glycoproteins might hold great clinical value for HCC detection in the future.

pGlyco 2.0 enables precision N-glycoproteomics with comprehensive quality control and one-step mass spectrometry for intact glycopeptide identification.

The precise and large-scale identification of intact glycopeptides is a critical step in glycoproteomics. Owing to the complexity of glycosylation, the current overall throughput, data quality and accessibility of intact glycopeptide identification lack behind those in routine proteomic analyses. Here, we propose a workflow for the precise high-throughput identification of intact N-glycopeptides at the proteome scale using stepped-energy fragmentation and a dedicated search engine. pGlyco 2.0 conducts comprehensive quality control including false discovery rate evaluation at all three levels of matches to glycans, peptides and glycopeptides, improving the current level of accuracy of intact glycopeptide identification. The N-glycoproteome of samples metabolically labeled with 15N/13C were analyzed quantitatively and utilized to validate the glycopeptide identification, which could be used as a novel benchmark pipeline to compare different search engines. Finally, we report a large-scale glycoproteome dataset consisting of 10,009 distinct site-specific N-glycans on 1988 glycosylation sites from 955 glycoproteins in five mouse tissues.Protein glycosylation is a heterogeneous post-translational modification that generates greater proteomic diversity that is difficult to analyze. Here the authors describe pGlyco 2.0, a workflow for the precise one step identification of intact N-glycopeptides at the proteome scale.

[Preliminary study of apoptotic inhibition and its molecular mechanism of dexamethasone on cisplatin-induced human lung adenocarcinoma cell line SPCA/I].

OBJECTIVE: To study the apoptotic inhibition and its molecular mechanism of dexamethasone (Dex) on cisplatin (CDDP)-induced human lung adenocarcinoma cells. METHODS: The human lung adenocarcinoma cell The human lung adenocarcinoma cell line, SPCA/I, was pre-cultured in vitro for 24 hours with Dex in different concentration and then different concentration of CDDP was added. The cells were cultured for another 48 hours. The survival rate of the cells was determined by MTT colorimetry. The appototic rate of SPCA/I cells measured by flow cytometer. Using 1 micromol/ L Dex to stimulate the SPCA/I cells RNAs of the cells at different time points (1 h, 2 h, 4 h, 6 h, 12 h) were extracted respectively. Semi-quantitative RT-PCR technology was used to detect the expression of the serum and glucocorticoid-induced kinase (SGK-1) and mitogen-activated protein kinase phosphatase-1(MKP-1) in SPCA/I cells. Simultaneously the glucocorticoid receptor (GR) of the SPCA/I cell line cells were measured by using biotin-labeled anti-glucocorticoid receptor antibody with immunohistochemistry assay. RESULTS: SPCA/I cells showed resistance to CDDP-induced apoptosis while pre-cultured with Dex and the resistance intensity was Dex concentration-dependent. After Dex stimulating the SPCA/I cells, SGK-1 expressed increased and reached the peak at 12 h. But the expression of MKP-1 was not detected. Immunohistochemistry results showed that upregulated GR in SPCA/I cells after stimulation with Dex. The number of intracellular GR was significantly higher than that of control group. CONCLUSION: The experimental results in vitro demonstrated that Dex inhibits apoptosis on CDDP-induced human lung adenocarcinoma cell line, SPCA/I. This anti-apoptosis effect might due to Dex increasing the expression of SGK-1, an anti-apoptotic protein, in its downstream signal pathway through the increasement of intracellular GR of SPCA/I cells.