Song Nie

Glycoprotein biomarker panel for pancreatic cancer discovered by quantitative proteomics analysis.

Pancreatic cancer is a lethal disease where specific early detection biomarkers would be very valuable to improve outcomes in patients. Many previous studies have compared biosamples from pancreatic cancer patients with healthy controls to find potential biomarkers. However, a range of related disease conditions can influence the performance of these putative biomarkers, including pancreatitis and diabetes. In this study, quantitative proteomics methods were applied to discover potential serum glycoprotein biomarkers that distinguish pancreatic cancer from other pancreas related conditions (diabetes, cyst, chronic pancreatitis, obstructive jaundice) and healthy controls. Aleuria aurantia lectin (AAL) was used to extract fucosylated glycoproteins and then both TMT protein-level labeling and label-free quantitative analysis were performed to analyze glycoprotein differences from 179 serum samples across the six different conditions. A total of 243 and 354 serum proteins were identified and quantified by label-free and TMT protein-level quantitative strategies, respectively. Nineteen and 25 proteins were found to show significant differences in samples between the pancreatic cancer and other conditions using the label-free and TMT strategies, respectively, with 7 proteins considered significant in both methods. Significantly different glycoproteins were further validated by lectin-ELISA and ELISA assays. Four candidates were identified as potential markers with profiles found to be highly complementary with CA 19–9 (p < 0.001). Obstructive jaundice (OJ) was found to have a significant impact on the performance of every marker protein, including CA 19–9. The combination of α-1-antichymotrypsin (AACT), thrombospondin-1 (THBS1), and haptoglobin (HPT) outperformed CA 19–9 in distinguishing pancreatic cancer from normal controls (AUC = 0.95), diabetes (AUC = 0.89), cyst (AUC = 0.82), and chronic pancreatitis (AUC = 0.90). A marker panel of AACT, THBS1, HPT, and CA 19–9 showed a high diagnostic potential in distinguishing pancreatic cancer from other conditions with OJ (AUC = 0.92) or without OJ (AUC = 0.95).

Altered expression of sialylated glycoproteins in ovarian cancer sera using lectin-based ELISA assay and quantitative glycoproteomics analysis.

Herein, we identify and confirm differentially expressed sialoglycoproteins in the serum of patients with ovarian cancer. On the basis of Sambucus nigra (SNA) lectin enrichment and on an isobaric chemical labeling quantitative strategy, clusterin (CLUS), leucine-rich alpha-2-glycoprotein (LRG1), hemopexin (HEMO), vitamin D-binding protein (VDB), and complement factor H (CFH) were found to be differentially expressed in the serum of patients with ovarian cancer compared to benign diseases. The abnormal sialylation levels of CLUS, CFH, and HEMO in serum of ovarian cancer patients were verified by a lectin-based ELISA assay. ELISA assays were further applied to measure total protein level changes of these glycoproteins. Protein levels of CLUS were found to be down-regulated in the serum of ovarian cancer patients, while protein levels of LRG1 were increased. The combination of CLUS and LRG1 (AUC = 0.837) showed improved performance for distinguishing stage III ovarian cancer from benign diseases compared to CA125 alone (AUC = 0.811). In differentiating early stage ovarian cancer from benign diseases or healthy controls, LRG1 showed comparable performance to CA125. An independent sample set was further used to confirm the ability of these candidate markers to detect patients with ovarian cancer. Our study provides a comprehensive strategy for the identification of candidate biomarkers that show the potential for diagnosis of ovarian cancer. Further studies using a large number of samples are necessary to validate the utility of this panel of proteins.

Large-Scale Identification of Core-Fucosylated Glycopeptide Sites in Pancreatic Cancer Serum Using Mass Spectrometry

Glycosylation has significant effects on protein function and cell metastasis, which are important in cancer progression. It is of great interest to identify site-specific glycosylation in search of potential cancer biomarkers. However, the abundance of glycopeptides is low compared to that of nonglycopeptides after trypsin digestion of serum samples, and the mass spectrometric signals of glycopeptides are often masked by coeluting nonglycopeptides due to low ionization efficiency. Selective enrichment of glycopeptides from complex serum samples is essential for mass spectrometry (MS)-based analysis. Herein, a strategy has been optimized using LCA enrichment to improve the identification of core-fucosylation (CF) sites in serum of pancreatic cancer patients. The optimized strategy was then applied to analyze CF glycopeptide sites in 13 sets of serum samples from pancreatic cancer, chronic pancreatitis, healthy controls, and a standard reference. In total, 630 core-fucosylation sites were identified from 322 CF proteins in pancreatic cancer patient serum using an Orbitrap Elite mass spectrometer. Further data analysis revealed that 8 CF peptides exhibited a significant difference between pancreatic cancer and other controls, which may be potential diagnostic biomarkers for pancreatic cancer.

Target Proteomic Profiling of Frozen Pancreatic CD24+ Adenocarcinoma Tissues by Immuno-Laser Capture Microdissection and Nano-LC-MS/MS

Cellular heterogeneity of solid tumors represents a common problem in mass spectrometry (MS)-based analysis of tissue specimens. Combining immuno-laser capture microdissection (iLCM) and mass spectrometry (MS) provides a means to study proteins that are specific for pure cell subpopulations in complex tissues. CD24, as a cell surface marker for detecting pancreatic cancer stem cells (CSCs), is directly correlated with the development and metastasis of pancreatic cancer. Herein, we describe an in-depth proteomic profiling of frozen pancreatic CD24(+) adenocarcinoma cells from early stage tumors using iLCM and LC-MS/MS and a comparison with CD24(-) cells dissected from patient-matched adjacent normal tissues. Approximately 40 nL of tissue was procured from each specimen and subjected to tandem MS analysis in triplicate. A total of 2665 proteins were identified, with 375 proteins in common that were significantly differentially expressed in CD24(+) versus CD24(-) cells by at least a 2-fold change. The major groups of the differentially overexpressed proteins are involved in promoting tumor cell migration and invasion, immune escape, and tumor progression. Three selected candidates relevant to mediating immune escape, CD59, CD70, and CD74, and a tumor promoter, TGFBI, were further validated by immunohistochemistry analysis on tissue microarrays. These proteins showed significantly increased expression in a large group of clinical pancreatic adenocarcinomas but were negative in all normal pancreas samples. The significant coexpression of these proteins with CD24 suggests that they may play important roles in the progression of pancreatic cancer and could serve as promising prognosis markers and novel therapeutic targets for this deadly disease.

Mass-selected site-specific core-fucosylation of ceruloplasmin in alcohol-related hepatocellular carcinoma.

A mass spectrometry-based methodology has been developed to study changes in core-fucosylation of serum ceruloplasmin that are site-specific between cirrhosis and hepatocellular carcinoma (HCC). The serum samples studied for these changes were from patients affected by cirrhosis or HCC with different etiologies, including alcohol, hepatitis B virus, or hepatitis C virus. The methods involved trypsin digestion of ceruloplasmin into peptides followed by Endo F3 digestion, which removed most of the glycan structure while retaining the innermost N-acetylglucosamine (GlcNAc) and/or core-fucose bound to the peptide. This procedure simplified the structures for further analysis by mass spectrometry, where four core-fucosylated sites (sites 138, 358, 397, and 762) were detected in ceruloplasmin. The core-fucosylation ratio of three of these sites increased significantly in alcohol-related HCC samples (sample size = 24) compared to that in alcohol-related cirrhosis samples (sample size = 18), with the highest AUC value of 0.838 at site 138. When combining the core-fucosylation ratio of site 138 in ceruloplasmin and the alpha-fetoprotein (AFP) value, the AUC value increased to 0.954 (ORsite138 = 12.26, p = 0.017; ORAFP = 3.64, p = 0.022), which was markedly improved compared to that of AFP (AUC = 0.867) (LR test p = 0.0002) alone. However, in HBV- or HCV-related liver diseases, no significant site-specific change in core-fucosylation of ceruloplasmin was observed between HCC and cirrhosis.

Tenascin-C: a novel candidate marker for cancer stem cells in glioblastoma identified by tissue microarrays.

Glioblastoma multiforme (GBM) is a highly aggressive brain tumor, with dismal survival outcomes. Recently, cancer stem cells (CSCs) have been demonstrated to play a role in therapeutic resistance and are considered to be the most likely cause of cancer relapse. The identification of CSCs is an important step toward finding new and effective ways to treat GBM. Tenascin-C (TNC) protein has been identified as a potential marker for CSCs in gliomas based on previous work. Here, we have investigated the expression of TNC in tissue microarrays including 17 GBMs, 18 WHO grade III astrocytomas, 15 WHO grade II astrocytomas, 4 WHO grade I astrocytomas, and 7 normal brain tissue samples by immunohistochemical staining. TNC expression was found to be highly associated with the grade of astrocytoma. It has a high expression level in most of the grade III astrocytomas and GBMs analyzed and a very low expression in most grade II astrocytomas, whereas it is undetectable in grade I astrocytomas and normal brain tissues. Double-immunofluorescence staining for TNC and CD133 in GBM tissues revealed that there was a high overlap between theses two positive populations. The results were further confirmed by flow cytometry analysis of TNC and CD133 in GBM-derived stem-like neurospheres in vitro. A limiting dilution assay demonstrated that the sphere formation ability of CD133+/TNC+ and CD133–/TNC+ cell populations is much higher than that of the CD133+/TNC– and CD133–/TNC– populations. These results suggest that TNC is not only a potential prognostic marker for GBM but also a potential marker for glioma CSCs, where the TNC+ population is identified as a CSC population overlapping with part of the CD133– cell population.

Isobaric Protein-Level Labeling Strategy for Serum Glycoprotein Quantification Analysis by Liquid Chromatography–Tandem Mass Spectrometry

While peptide-level labeling using isobaric tag reagents has been widely applied for quantitative proteomics experiments, there are comparatively few reports of protein-level labeling. Intact protein labeling could be broadly applied to quantification experiments utilizing protein-level separations or enrichment schemes. Here, protein-level isobaric labeling was explored as an alternative strategy to peptide-level labeling for serum glycoprotein quantification. Labeling and digestion conditions were optimized by comparing different organic solvents and enzymes. Digestions with Asp-N and trypsin were found highly complementary; combining the results enabled quantification of 30% more proteins than either enzyme alone. Three commercial reagents were compared for protein-level labeling. Protein identification rates were highest with iTRAQ 4-plex when compared to TMT 6-plex and iTRAQ 8-plex using higher-energy collisional dissociation on an Orbitrap Elite mass spectrometer. The compatibility of isobaric protein-level labeling with lectin-based glycoprotein enrichment was also investigated. More than 74% of lectin-bound labeled proteins were known glycoproteins, which was similar to results from unlabeled and peptide-level labeled serum samples. Finally, protein-level and peptide-level labeling strategies were compared for serum glycoprotein quantification. Isobaric protein-level labeling gave comparable identification levels and quantitative precision to peptide-level labeling.

Quantitative Analysis of Single Amino Acid Variant Peptides Associated with Pancreatic Cancer in Serum by an Isobaric Labeling Quantitative Method

Single amino acid variations are highly associated with many human diseases. The direct detection of peptides containing single amino acid variants (SAAVs) derived from nonsynonymous single nucleotide polymorphisms (SNPs) in serum can provide unique opportunities for SAAV associated biomarker discovery. In the present study, an isobaric labeling quantitative strategy was applied to identify and quantify variant peptides in serum samples of pancreatic cancer patients and other benign controls. The largest number of SAAV peptides to date in serum including 96 unique variant peptides were quantified in this quantitative analysis, of which five variant peptides showed a statistically significant difference between pancreatic cancer and other controls (p-value < 0.05). Significant differences in the variant peptide SDNCEDTPEAGYFAVAVVK from serotransferrin were detected between pancreatic cancer and controls, which was further validated by selected reaction monitoring (SRM) analysis. The novel biomarker panel obtained by combining α-1-antichymotrypsin (AACT), Thrombospondin-1 (THBS1) and this variant peptide showed an excellent diagnostic performance in discriminating pancreatic cancer from healthy controls (AUC = 0.98) and chronic pancreatitis (AUC = 0.90). These results suggest that large-scale analysis of SAAV peptides in serum may provide a new direction for biomarker discovery research.

A quantitative proteomics analysis of MCF7 breast cancer stem and progenitor cell populations

Accumulating evidence has demonstrated that breast cancers are initiated and develop from a small population of stem‐like cells termed cancer stem cells (CSCs). These cells are hypothesized to mediate tumor metastasis and contribute to therapeutic resistance. However, the molecular regulatory networks responsible for maintaining CSCs in an undifferentiated state have yet to be elucidated. In this study, we used CSC markers to isolate pure breast CSCs fractions (ALDH+ and CD44+CD24‐ cell populations) and the mature luminal cells (CD49f‐EpCAM+) from the MCF7 cell line. Proteomic analysis was performed on these samples and a total of 3304 proteins were identified. A label‐free quantitative method was applied to analyze differentially expressed proteins. Using the criteria of greater than twofold changes and p value <0.05, 305, 322 and 98 proteins were identified as significantly different in three pairwise comparisons of ALDH+ versus CD44+CD24‐, ALDH+ versus CD49f‐EpCAM+ and CD44+CD24‐ versus CD49f‐EpCAM+, respectively. Pathway analysis of differentially expressed proteins by Ingenuity Pathway Analysis (IPA) revealed potential molecular regulatory networks that may regulate CSCs. Selected differential proteins were validated by Western blot assay and immunohistochemical staining. The use of proteomics analysis may increase our understanding of the underlying molecular mechanisms of breast CSCs. This may be of importance in the future development of anti‐CSC therapeutics.

Serum Metabolomic Analysis of Pancreatic Cancer—Letter

In their recent article, Kobayashi and colleagues ([1][1]) sought to construct and validate a diagnostic model for pancreatic cancer using gas chromatography-mass spectrometry-based human serum metabolomics approach. The study included a training set ( n = 85) and a validation set ( n = 106). Using