Examination of Carbohydrate Products in Feces Reveals Potential Biomarkers Distinguishing Exclusive and Nonexclusive Breastfeeding Practices in Infants.

BACKGROUND: The stable isotope deuterium dose-to-mother (DTM) technique to estimate nonbreast milk water intake demonstrates that maternal self-report methods of infant feeding overestimate the true prevalence of exclusively breastfeeding practices. OBJECTIVE: We aimed to determine potential monosaccharide and oligosaccharide markers that distinguish between exclusively breastfed (EBF) versus nonexclusively breastfed (non-EBF) infants utilizing LC-MS-based methods. METHODS: Data for the analysis were collected as part of a larger, longitudinal study of 192 breastfed Indonesian infants aged 2 mo and followed up at 5 mo. Feces samples were collected from infants aged 2 mo (n = 188) and 5 mo (n = 184). EBF and non-EBF strata at each time point were determined via the DTM technique. Feces samples were analyzed to determine monosaccharide content using ultra-high-performance LC-triple quadrupole MS (UHPLC-QqQ MS). Relative abundances of fecal oligosaccharides were determined using nano-LC-Chip-quadrupole time-of-flight MS (nano-LC-Chip-Q-ToF MS). RESULTS: At age 2 mo, monosaccharide analysis showed the abundance of fructose and mannose were significantly higher (+377% and +388%, respectively) in non-EBF compared with EBF infants (P <0.0001). Fructose and mannose also showed good discrimination with areas under the curve (AUC) of 0.86 and 0.82, respectively. Oligosaccharide analysis showed that a 6-hexose (Hex6) isomer had good discrimination (AUC = 0.80) between EBF and non-EBF groups at 5 mo. CONCLUSION: Carbohydrate products, particularly fecal mono- and oligosaccharides, differed between EBF and non-EBF infants aged under 6 mo and can be used as potential biomarkers to distinguish EBF versus non-EBF feeding practices.

Multiple Reaction Monitoring for the Quantitation of Serum Protein Glycosylation Profiles: Application to Ovarian Cancer.

Protein glycosylation fingerprints are widely recognized as potential markers for disease states, and indeed differential glycosylation has been identified in multiple types of autoimmune diseases and several types of cancer. However, releasing the glycans leave the glycoproteins unknown; therefore, there exists a need for high-throughput methods that allow quantification of site- and protein-specific glycosylation patterns from complex biological mixtures. In this study, a targeted multiple reaction monitoring (MRM)-based method for the protein- and site-specific quantitation involving serum proteins immunoglobulins A, G and M, alpha-1-antitrypsin, transferrin, alpha-2-macroglobulin, haptoglobin, alpha-1-acid glycoprotein and complement C3 was developed. The method is based on tryptic digestion of serum glycoproteins, followed by immediate reverse phase UPLC-QQQ-MS analysis of glycopeptides. To quantitate protein glycosylation independent of the protein serum concentration, a nonglycosylated peptide was also monitored. Using this strategy, 178 glycopeptides and 18 peptides from serum glycoproteins are analyzed with good repeatability (interday CVs of 3.65-21-92%) in a single 17 min run. To assess the potential of the method, protein glycosylation was analyzed in serum samples from ovarian cancer patients and controls. A training set consisting of 40 cases and 40 controls was analyzed, and differential analyses were performed to identify aberrant glycopeptide levels. All findings were validated in an independent test set (n = 44 cases and n = 44 controls). In addition to the differential glycosylation on the immunoglobulins, which was reported previously, aberrant glycosylation was also observed on each of the glycoproteins, which could be corroborated in the test set. This report shows the development of a method for targeted protein- and site-specific glycosylation analysis and the potential of such methods in biomarker development.

Serum glycosylation characterization of osteonecrosis of the femoral head by mass spectrometry.

Osteonecrosis of the femoral head is a recalcitrant and paralyzing disease often discovered in the end stage at the time of diagnosis, which is often performed by physical examination and diagnostic imaging. Osteonecrosis of the femoral head is typically caused by trauma or long-term steroid use. There are over 30 million patients in the US taking steroids, and roughly 40% will develop osteonecrosis of the femoral head. However, the exact pathophysiological process is not well understood. This study aims to examine the alteration in serum glycosylation of osteonecrosis of the femoral head using the state-of-the-art analytical tools to provide more chemical data for pathophysiology research and possibly biomarker discovery. A training set containing 27 serum samples from steroid-induced osteonecrosis of the femoral head patients and 25 from gender- and age-matched controls was collected and analyzed. Glycosylation of whole serum and site-specific glycosylation of immunoglobulins are characterized using electrospray ionization-Q-time of flight and electrospray ionization-Triple-Quadruple via multiple reaction monitoring, respectively. The whole serum glycosylation analysis yielded 14 N-glycan compositions and multiple reaction monitoring yielded eight glycopeptides that were altered between cases and controls with statistical significance. The increase of nonsialylated, nonfucosylated N-glycans and decrease of fucosylated N-glycans are associated with the development of osteonecrosis of the femoral head. Glycosylation is a posttranslational protein modification and is apparently affected by osteonecrosis of the femoral head. Future studies with a larger cohort and patients from earlier stage will be performed to assess these potential markers' value in disease onset.

Proteomic profiling of lung adenocarcinoma indicates heightened DNA repair, antioxidant mechanisms and identifies LASP1 as a potential negative predictor of survival.

BACKGROUND: Lung cancer is the leading cause of cancer mortality in the United States. Non-small cell lung cancer accounts for 85% of all lung cancers for which adenocarcinoma is the most common histological type. Management of lung cancer is hindered by high false-positive rates due to difficulty resolving between benign and malignant tumors. Better molecular analysis comparing malignant and non-malignant tissues will provide important evidence of the underlying biology contributing to tumorigenesis. METHODS: We utilized a proteomics approach to analyze 38 malignant and non-malignant paired tissue samples obtained from current or former smokers with early stage (Stage IA/IB) lung adenocarcinoma. Statistical mixed effects modeling and orthogonal partial least squares discriminant analysis were used to identify key cancer-associated perturbations in the adenocarcinoma proteome. Identified proteins were subsequently assessed against clinicopathological variables. RESULTS: Top cancer-associated protein alterations were characterized by: (1) elevations in APEX1, HYOU1 and PDIA4, indicative of increased DNA repair machinery and heightened anti-oxidant defense mechanisms; (2) increased LRPPRC, STOML2, COPG1 and EPRS, suggesting altered tumor metabolism and inflammation; (3) reductions in SPTB, SPTA1 and ANK1 implying dysregulation of membrane integrity; and (4) decreased SLCA41 suggesting altered pH regulation. Increased protein levels of HYOU1, EPRS and LASP1 in NSCLC adenocarcinoma was independently validated by tissue microarray immunohistochemistry. Immunohistochemistry for HYOU1 and EPRS indicated AUCs of 0.952 and 0.841, respectively, for classifying tissue as malignant. Increased LASP1 correlated with poor overall survival (HR 3.66 per unit increase; CI 1.37-9.78; p = 0.01). CONCLUSION: These results reveal distinct proteomic changes associated with early stage lung adenocarcinoma that may be useful prognostic indicators and therapeutic targets.

Glycoproteomic Analysis of Malignant Ovarian Cancer Ascites Fluid Identifies Unusual Glycopeptides.

Ovarian cancer is a major cause of cancer mortality among women, largely due to late diagnosis of advanced metastatic disease. More extensive molecular analysis of metastatic ovarian cancer is needed to identify post-translational modifications of proteins, especially glycosylation that is particularly associated with metastatic disease to better understand the metastatic process and identify potential therapeutic targets. Glycoproteins in ascites fluid were enriched by affinity binding to lectins (ConA or WGA) and other affinity matrices. Separate glycomic, proteomic, and glycopeptide analyses were performed. Relative abundances of different N-glycan groups and proteins were identified from ascites fluids and a serum control. Levels of biomarkers CA125, MUC1, and fibronectin were also monitored in OC ascites samples by Western blot analysis. N-Glycan analysis of ascites fluids showed the presence of large, highly fucosylated and sialylated complex and hybrid glycans, some of which were not observed in normal serum. OC ascites glycoproteins, haptoglobin, fibronectin, lumican, fibulin, hemopexin, ceruloplasmin, alpha-1-antitrypsin, and alpha-1-antichymotrypsin were more abundant in OC ascites or not present in serum control samples. Further glycopeptide analysis of OC ascites identified N- and O-glycans in clusterin, hemopexin, and fibulin glycopeptides, some of which are unusual and may be important in OC metastasis.

Protein-Specific Differential Glycosylation of Immunoglobulins in Serum of Ovarian Cancer Patients.

Previous studies indicated that glycans in serum may serve as biomarkers for diagnosis of ovarian cancer; however, it was unclear to which proteins these glycans belong. We hypothesize that protein-specific glycosylation profiles of the glycans may be more informative of ovarian cancer and can provide insight into biological mechanisms underlying glycan aberration in serum of diseased individuals. Serum samples from women diagnosed with epithelial ovarian cancer (EOC, n = 84) and matched healthy controls (n = 84) were obtained from the Gynecologic Oncology Group. Immunoglobulin (IgG, IgA, and IgM) concentrations and glycosylation profiles were quantified using multiple reaction monitoring mass spectrometry. Differential and classification analyses were performed to identify aberrant protein-specific glycopeptides using a training set. All findings were validated in an independent test set. Multiple glycopeptides from immunoglubins IgA, IgG, and IgM were found to be differentially expressed in serum of EOC patients compared with controls. The protein-specific glycosylation profiles showed their potential in the diagnosis of EOC. In particular, IgG-specific glycosylation profiles are the most powerful in discriminating between EOC case and controls. Additional studies of protein- and site-specific glycosylation profiles of immunoglobulins and other proteins will allow further elaboration on the characteristics of biological functionality and causality of the differential glycosylation in ovarian cancer and thus ultimately lead to increased sensitivity and specificity of diagnosis.

Serum Glycans as Risk Markers for Non-Small Cell Lung Cancer.

Previous studies have suggested occurrence of altered serum glycan profiles in patients with lung cancer. Here, we aimed to determine the predictive value of serum glycans to distinguish non-small cell lung cancer (NSCLC) cases from controls in prediagnostic samples using a previously validated predictive protein marker pro-SFTPB, as anchor. Blinded prediagnostic serum samples were obtained from the Carotene and Retinol Efficacy Trial (CARET), and included a discovery set of 100 NSCLC cases and 199 healthy controls. A second test set consisted of 108 cases and 216 controls. Cases and controls were matched for age at baseline (5-year groups), sex, smoking status (current vs. former), study enrollment cohort, and date of blood draw. Serum glycan profiles were determined by mass spectrometry. Twelve glycan variables were identified to have significant discriminatory power between cases and controls in the discovery set (AUC > 0.6). Of these, four were confirmed in the independent validation set. A combination marker yielded AUCs of 0.74 and 0.64 in the discovery and test set, respectively. Four glycan variables exhibited significant incremental value when combined with pro-SFTPB compared with pro-SFTPB alone with AUCs of 0.73, 0.72, 0.72, and 0.72 in the test set, indicating that serum glycan signatures have relevance to risk assessment for NSCLC.

A Method for Comprehensive Glycosite-Mapping and Direct Quantitation of Serum Glycoproteins.

A comprehensive glycan map was constructed for the top eight abundant glycoproteins in plasma using both specific and nonspecific enzyme digestions followed by nano liquid chromatography (LC)-chip/quadrupole time-of-flight mass spectrometry (MS) analysis. Glycopeptides were identified using an in-house software tool, GPFinder. A sensitive and reproducible multiple reaction monitoring (MRM) technique on a triple quadrupole MS was developed and applied to quantify immunoglobulins G, A, M, and their site-specific glycans simultaneously and directly from human serum/plasma without protein enrichments. A total of 64 glycopeptides and 15 peptides were monitored for IgG, IgA, and IgM in a 20 min ultra high performance (UP)LC gradient. The absolute protein contents were quantified using peptide calibration curves. The glycopeptide ion abundances were normalized to the respective protein abundances to separate protein glycosylation from protein expression. This technique yields higher method reproducibility and less sample loss when compared with the quantitation method that involves protein enrichments. The absolute protein quantitation has a wide linear range (3-4 orders of magnitude) and low limit of quantitation (femtomole level). This rapid and robust quantitation technique, which provides quantitative information for both proteins and glycosylation, will further facilitate disease biomarker discoveries.

Differential N-Glycosylation Patterns in Lung Adenocarcinoma Tissue.

To decrease the mortality of lung cancer, better screening and diagnostic tools as well as treatment options are needed. Protein glycosylation is one of the major post-translational modifications that is altered in cancer, but it is not exactly clear which glycan structures are affected. A better understanding of the glycan structures that are differentially regulated in lung tumor tissue is highly desirable and will allow us to gain greater insight into the underlying biological mechanisms of aberrant glycosylation in lung cancer. Here, we assess differential glycosylation patterns of lung tumor tissue and nonmalignant tissue at the level of individual glycan structures using nLC-chip-TOF-MS. Using tissue samples from 42 lung adenocarcinoma patients, 29 differentially expressed (FDR < 0.05) glycan structures were identified. The levels of several oligomannose type glycans were upregulated in tumor tissue. Furthermore, levels of fully galactosylated glycans, some of which were of the hybrid type and mostly without fucose, were decreased in cancerous tissue, whereas levels of non- or low-galactosylated glycans mostly with fucose were increased. To further assess the regulation of the altered glycosylation, the glycomics data was compared to publicly available gene expression data from lung adenocarcinoma tissue compared to nonmalignant lung tissue. The results are consistent with the possibility that the observed N-glycan changes have their origin in differentially expressed glycosyltransferases. These results will be used as a starting point for the further development of clinical glycan applications in the fields of imaging, drug targeting, and biomarkers for lung cancer.

The Serum Immunoglobulin G Glycosylation Signature of Gastric Cancer.

Biomarkers may facilitate detection of gastric cancer at an earlier stage and reduce mortality. Here we sought to determine if the glycosylation profile of serum immunoglobulin G (IgG) could distinguish patients with non-atrophic gastritis (NAG), duodenal ulcer (DU) and gastric cancer (GC). Serum IgG was released and analyzed using nano-LC-TOF mass spectrometry. Statistically significant false discovery rate (FDR)-adjusted p-values were observed for 18 glycans, eight that differed significantly between NAG and GC, three that distinguished NAG from DU, and eight that differed between DU and GC. The IgG glycosylation signature may be useful as a predictive marker for gastric cancer.

Rapid-throughput glycomics applied to human milk oligosaccharide profiling for large human studies.

Glycomic analysis is the comprehensive determination of glycan (oligosaccharide) structures with quantitative information in a biological sample. Rapid-throughput glycomics is complicated due to the lack of a template, which has greatly facilitated analysis in the field of proteomics. Furthermore, the large similarities in structures make fragmentation spectra (as obtained in electron impact ionization and tandem mass spectrometry) less definitive for identification as it has been in metabolomics. In this study, we develop a concept of rapid-throughput glycomics on human milk oligosaccharides, which have proven to be an important bioactive component of breast milk, providing the infant with protection against pathogenic infection and supporting the establishment of a healthy microbiota. To better understand the relationship between diverse oligosaccharides structures and their biological function as anti-pathogenic and prebiotic compounds, large human studies are needed, which necessitate rapid- to high-throughput analytical platforms. Herein, a complete glycomics methodology is presented, evaluating the most effective human milk oligosaccharide (HMO) extraction protocols, the linearity and reproducibility of the nano-liquid chromatography chip time-of-flight mass spectrometry (nano-LC chip-TOF MS) method, and the efficacy of newly developed, in-house software for chromatographic peak alignment that allows for rapid data analysis. High instrument stability and retention time reproducibility, together with the successful automated alignment of hundreds of features in hundreds of milk samples, allow for the use of an HMO library for rapid assignment of fully annotated structures.

Detection of milk oligosaccharides in plasma of infants.

Human milk oligosaccharides (HMO) are one of the major components of human milk. HMO are non-digestible by the human gut, where they are known to play important functions as prebiotics and decoys for binding pathogens. Moreover, it has been proposed that HMO may provide sialic acids to the infant that are important in brain development, however this would require absorption of HMO into the bloodstream. HMO have consistently been found in the urine of humans and other mammals, suggesting systemic absorption. Here, we present a procedure for the profiling of milk oligosaccharides (MO) in plasma samples obtained from 13 term infants hospitalized for surgery for congenital heart disease. The method comprises protein denaturation, oligosaccharide reduction, and porous graphitized carbon solid phase extraction for purification followed by analysis using nHPLC-PGC-chip-TOF-MS. Approximately 15 free MO were typically observed in the plasma of human infants, including LNT, LDFP, LNFT, 3'SL, 6'SL, 3'SLN, and 6'SLN, of which the presence was confirmed using fragmentation studies. A novel third isomer of SLN, not found in human or bovine milk was also consistently detected. Differences in the free MO profiles were observed between infants that were totally formula-fed and infants that received at least some part breast milk. Our results indicate that free MO similar in structure to those found in human milk and urine are present in the blood of infants. The method and results presented here will facilitate further research toward the possible roles of free MO in the development of the infant.

Evaluation of glycomic profiling as a diagnostic biomarker for epithelial ovarian cancer.

BACKGROUND: Prior studies suggested that glycans were differentially expressed in patients with ovarian cancer and controls. We hypothesized that glycan-based biomarkers might serve as a diagnostic test for ovarian cancer and evaluated the ability of glycans to distinguish ovarian cancer cases from matched controls. METHODS: Serum samples were obtained from the tissue-banking repository of the Gynecologic Oncology Group, and included healthy female controls (n = 100), women diagnosed with low malignant potential (LMP) tumors (n = 52), and epithelial ovarian cancers (EOC) cases (n = 147). Cases and controls were matched on age at enrollment within ±5 years. Serum samples were analyzed by glycomics analysis to detect abundance differences in glycan expression levels. A two-stage procedure was carried out for biomarker discovery and validation. Candidate classifiers of glycans that separated cases from controls were developed using a training set in the discovery phase and the classification performance of the candidate classifiers was assessed using independent test samples that were not used in discovery. RESULTS: The patterns of glycans showed discriminatory power for distinguishing EOC and LMP cases from controls. Candidate glycan-based biomarkers developed on a training set (sensitivity, 86% and specificity, 95.8% for distinguishing EOC from controls through leave-one-out cross-validation) confirmed their potential use as a detection test using an independent test set (sensitivity, 70% and specificity, 86.5%). CONCLUSION: Formal investigations of glycan biomarkers that distinguish cases and controls show great promise for an ovarian cancer diagnostic test. Further validation of a glycan-based test for detection of ovarian cancer is warranted. IMPACT: An emerging diagnostic test based on the knowledge gained from understanding the glycobiology should lead to an assay that improves sensitivity and specificity and allows for early detection of ovarian cancer.

Enrichment strategies in glycomics-based lung cancer biomarker development.

PURPOSE: There is a need to identify better glycan biomarkers for diagnosis, early detection, and treatment monitoring in lung cancer using biofluids such as blood. Biofluids are complex mixtures of proteins dominated by a few high abundance proteins that may not have specificity for lung cancer. Therefore, two methods for protein enrichment were evaluated; affinity capturing of IgG and enrichment of medium abundance proteins, thus allowing us to determine which method yields the best candidate glycan biomarkers for lung cancer. EXPERIMENTAL DESIGN: N-glycans isolated from plasma samples from 20 cases of lung adenocarcinoma and 20 matched controls were analyzed using nLC-PGC-chip-TOF-MS (where PGC is porous-graphitized carbon). N-glycan profiles were obtained for five different fractions: total plasma, isolated IgG, IgG-depleted plasma, and the bound and flow-through fractions of protein enrichment. RESULTS: Four glycans differed significantly (false discovery rate, FDR < 0.05) between cases and controls in whole unfractionated plasma, while four other glycans differed significantly by cancer status in the IgG fraction. No significant glycan differences were observed in the other fractions. CONCLUSIONS AND CLINICAL RELEVANCE: These results confirm that the N-glycan profile in plasma of lung cancer patients is different from healthy controls and appears to be dominated by alterations in relatively abundant proteins.