Nutritional and Clinical Glycomics Research

Tag: glycans

Glycomic Profiling and IgG Quantification of HIV-Infected Plasma

 Cynthia Williams
Cynthia Williams; Anne Fenton; Lauren Nagy; Qiuting Hong; L.Renee Ruhaak; Satya Dadenkar; Carlito Lebrilla
UC Davis, Davis, CA
NOVEL ASPECT: Plasma and IgG glycan profiles, but not IgG protein abundances are altered in HIV infection.
INTRODUCTION:
Human immunodeficiency virus (HIV) is a retrovirus that infects and weakens the immune system and can progress to AIDS, which can be fatal. Extensive HIV studies have shown that immunoglobulin expressions are abnormal and display altered glycosylation patterns. However, compositional glycomic profiling of human plasma and quantitation of specific protein glycosylation in HIV samples has not been widely explored. In this study, we profile the plasma glycans to determine glycan biomarkers for HIV infection. In addition, we have developed a method for quantification of glycosylated proteins, specifically immunoglobulin G (IgG) to examine whether IgG-specific glycosylation varies in HIV infection.
METHODS:
Plasma samples from 26 male patients as well as 11 controls were collected; HIV infected patients were divided into 3 groups: no therapy (n=11), therapy (n=11), and long term no therapy (n=4). For the glycomic analysis, the glycoproteins were denatured and glycans were enzymatically released by PNGase F. The N-glycans were purified using graphitized carbon SPE and analyzed on an Agilent 6520 HPLC-Chip/QTOF MS. Accurate mass, retention time, and a retrosynthetic library was used for glycan identification. For IgG quantification, plasma samples were treated with DTT and IAA followed by an overnight tryptic digestion at 37˚C. Quantification was performed using an Agilent 6490 QqQ MS coupled with an Agilent 1290 UPLC system.
ABSTRACT:
Total plasma N-glycan profiles were generated for all 37 samples using our high-throughput nano-LC separation method. Namely, N-glycans were chromatographically separated on a PGC chip. Over 300 glycan features were resolved and identified which corresponded to over 100 glycan compositions. Statistical differences were found in neutral, fucosylated and sialylated, as well as high mannose glycans. Specifically, Hex9HexNAc2 or Man 9 was found to be decreased in HIV patients but increased in those with little to no therapy, with therapy treatment, and in control cases. With Man 9, t-tests revealed a p= 7.46*10-4 between healthy and no therapy samples. Conversely, Hex3HexNAc5Fuc1 was found to decrease with therapy treatment versus healthy controls (p=8.9*10-3). Previous studies in our lab have shown that Man 9 and Hex3HexNAc5Fuc1 are both associated with immunoglobulins, specifically IgM, and IgM, IgG, and IgA, respectively. Quantification of IgG glycosylation was examined to determine whether the observed differences originated from glycan or protein expression. A method for IgG quantitation using QqQ-MS was developed for quantitating peptides and applied to the 37 HIV sample set.  Quantitation of the peptide that is common to IgG 1, 2, 3, and 4, using MRM, revealed no statistical differences in the IgG levels between the different HIV sample groups. However, after normalizing the protein glycosylation to the total protein content, many glycopeptides revealed significant statistical differences. Galactose-deficient glycopeptides were observed at much higher intensities in HIV patients compared to healthy cases, which is a trend that has already been reported in literature. These results suggest that glycosylation undergoes specific changes during infection but not necessarily protein expression.

Gastric cancer detection by serum glycan signatures

Sureyya Ozcan
Sureyya Ozcan1; Cara Cooke2; Donald Barkauskas3; Hyun Joo An4; Serenus Hua4; Cynthia Williams1; Lauren Dimapasoc1; L. Renee Ruhaak1; Jae Han Kim4; David Rocke5; Javier Torres6; Carlito B Lebrilla1; Jay V Solnick2
1UC Davis Chemistry Department, Davis, CA; 2UC Davis, Center for Comparative Medicine, Davis, CA; 3University of Southern California, Los Angeles, CA; 4Chungnam National University, Daejeon, Korea; 5University of California Davis, Davis, CA; 6Instituto Mexicano del Seguro Social, Mexico, Mexico
NOVEL ASPECT: Novel glycan markers for gastric cancer under different diagnosis categories.
INTRODUCTION:
Gastric cancer (GC) is the second most common cause of cancer-related death, with nearly around 1 million cases per year. The progression of gastric cancer differs through a series of histologic stages that begins with gastritis and evolves over decades to atrophy (loss of glands), intestinal metaplasia, dysplasia, and finally adenocarcinoma. Thus, finding disease markers has become more crucial in identifying disease pathways.  Due to the complexity of the proteome, glycosylation, a common post-translational modification of protein, has received increasing interest in the cancer community. In this study we aimed to evaluate the utility of native N-glycans in serum as biomarkers for the identification of GC progression pathways with respect to different diagnosis categories.
METHODS:
For the case-cohort study, we collected a subset of 72 serum samples from Mexico City. The sample set included four diagnostic categories: non-atrophic gastritis (NAG) (n = 18), duodenal ulcer (DU) (n = 18), intestinal-type gastric cancer (n = 18), and diffuse-type gastric cancer (DGC) (n = 18). N-glycans were released from serum samples using the generic method with PNGase F and were analyzed by MALDI FT-ICR MS. The corresponding glycan compositions were calculated based on accurate mass. ANOVA based statistical analysis was performed to identify potential markers for each sub-groups.
ABSTRACT:
Candidate glycan markers isolated from serum were monitored in different disease stages including non-atrophic gastritis, duodenal ulcer, diffuse cancer and intestinal cancer. Around twenty N-glycan markers were significantly different in at least one way. Generally, fucosylated complex/hybrid type and high mannose type N-glycans showed stronger significance to differentiate gastric cancer, while NeuAc containing complex/hybrid type N-glycans were more significant in duodenal ulcer. Those glycans are usually correlated to IgG based serum protein. Our result will lead further studies to identify disease pathways from a glycomics point of view. Specificity and sensitivity of predicted values show promising results to distinguish gastric cancer from non-atrophic gastritis. In this study, we characterized potential glycan markers to differentiate gastric cancer and to identify disease progression pathways.

Validation of a glycan biomarker set for the detection of ovarian cancer using mass spectrometry

Renee
L. Renee Ruhaak1; Sandra Taylor1; Cynthia Williams1; UyenThao Nguyen1; Lauren Dimapasoc1; Sureyya Ozcan1; Carol Stroble1, 2; Suzanne Miyamoto2; Kyoungmi Kim1; Gary Leiserowitz2; Carlito B. Lebrilla1
1University of California, Davis, Davis, CA; 2UC Davis Comprehensive Cancer Center, Sacramento, CA
NOVEL ASPECT: Altered serum glycan profiles were validated as discriminating OC cases from controls, showing its great potential as a diagnostic tool.
INTRODUCTION:
Protein glycosylation plays important roles in cancer; aberrant glycosylation has been observed with malignant transformation, and altered glycosylation profiles were observed in serum and plasma of cancer patients compared to healthy controls. The survival rates of ovarian cancer (OC) are lower than most other cancers that affect women, but if tests with better accuracy than the test for CA125 were available for early detection then more lives could be saved. While the literature reports altered serum glycosylation profiles with ovarian cancer, the predictive values of such candidate biomarkers have not been determined and results have not been validated in independent test sets. We now report the potential of serum glycomics analysis using nLC-PGC-chip-TOF-MS as a diagnostic test for ovarian cancer.
METHODS:
Pre-operative sera of OC cases and healthy controls consisting of 43 stage III-IV OC cases and 49 age-matched controls were used as a training set for biomarker detection. Independently a set of patient sera was collected from 52 stage I-II cases, 52 stage III-IV cases, 52 cases with low malignant potential and 52 age-matched controls as a test set for validation. A high-throughput 96-well based nLC-PGC-chip-TOF-MS strategy, which was previously validated for its stability and repeatability, was employed to evaluate serum N-glycan profiles in each of the samples. N-glycan peak integrals were used for biostatistical analysis to evaluate the OC differential potential for the glycan features in the training set. These results were then validated in the independent test set.
ABSTRACT:
Within the training set, 330 glycan compositions were detected in at least one of the samples analyzed. Of the glycan compositions that were consistently detected in the samples, levels of 36 compositions were shown to alter significantly (either over- or under-expressed) with OC at a false discovery rate of <0.05. Among the most significant glycan compositions were Hex5HexNAc4Fuc1, Hex4HexNAc4, Hex5HexNAc5Fuc2NeuAc1, Hex5HexNAc3, Hex6HexNAc3 and Hex5HexNAc6Fuc1NeuAc2. The most informative glycan (Hex6HexNAc3) singly yielded an AUC value of 0.896 with 93% sensitivity and 75% specificity. Multiplex classifiers combining one or more glycans together were developed with the highest accuracy of 91.2% (sensitivity 86.0%, specificity 95.8%) when combining nine glycans.Using the test set, we were also able to observe 330 glycan compositions, and levels of 33 compositions were significantly altered with OC. Twenty glycan compositions were significantly altered with OC stage III-IV in the same direction in both the training and the test set. The glycan composition with the highest classification accuracy in the stage III-IV samples of the training set continued to perform well in the independent test set. When testing the multiplex classifiers developed in the training set in samples of the independent testing set, an accuracy of 78% was achieved. Independent of the training set, which only contained stage III-IV samples, good separation was also obtained between the healthy controls and the stage I-II OC cases, with a classification rate of 83%. These results indicate that glycan profiles are promising new tools which could lead to improvement in the detection of ovarian cancer.

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