The sensitive and specific detection of glycans via mass spectrometry (MS) remains a significant challenge due to their low abundance in complex biological mixtures, inherent lack of hydrophobicity, and suppression by other, more abundant biological molecules (proteins/peptides) or contaminants. A new strategy for the sensitive and selective MS analysis of glycans based on fluorous chemistry is reported. Glycan reducing ends were derivatized with a hydrophobic fluorinated carbon tag, increasing glycan ionization efficiency during MS by more than an order of magnitude. More importantly, the fluorinated carbon tag enabled efficient fluorous solid-phase extraction (FSPE) to specifically enrich the glycans from contaminated solutions and protein mixtures. Finally, we successfully analyzed the N-glycome in human serum using this new method.

Glycosylation is estimated to be found in over 50% of human proteins. Aberrant protein glycosylation and alteration of glycans are closely related to many diseases. More than half of the cancer biomarkers are glycosylated-proteins, and specific glycoforms of glycosylated-proteins may serve as biomarkers for either the early detection of disease or the evaluation of therapeutic efficacy for treatment of diseases. Glycoproteomics, therefore, becomes an emerging field that can make unique contributions to the discovery of biomarkers of cancers. The recent advances in mass spectrometry (MS)-based glycoproteomics, which can analyze thousands of glycosylated-proteins in a single experiment, have shown great promise for this purpose. Herein, we described the MS-based strategies that are available for glycoproteomics, and discussed the sensitivity and high throughput in both qualitative and quantitative manners. The discovery of glycosylated-proteins as biomarkers in some representative diseases by employing glycoproteomics was also summarized.

Due to severe presence of speckle noise, poor image contrast and irregular lesion shape, it is challenging to build a fully automatic detection and classification system for breast ultrasonic images. In this paper, a novel and effective computer-aided method including generation of a region of interest (ROI), segmentation and classification of breast tumor is proposed without any manual intervention. By incorporating local features of texture and position, a ROI is firstly detected using a self-organizing map neural network. Then a modified Normalized Cut approach considering the weighted neighborhood gray values is proposed to partition the ROI into clusters and get the initial boundary. In addition, a regional-fitting active contour model is used to adjust the few inaccurate initial boundaries for the final segmentation. Finally, three textures and five morphologic features are extracted from each breast tumor; whereby a highly efficient Affinity Propagation clustering is used to fulfill the malignancy and benign classification for an existing database without any training process. The proposed system is validated by 132 cases (67 benignancies and 65 malignancies) with its performance compared to traditional methods such as level set segmentation, artificial neural network classifiers, and so forth. Experiment results show that the proposed system, which needs no training procedure or manual interference, performs best in detection and classification of ultrasonic breast tumors, while having the lowest computation complexity.

A general and simple labeling method, termed glycan reductive isotope-coded amino acid labeling (GRIAL), was developed for mass spectrometry-based quantitative N-glycomics.

A novel implementation of in situ protein digestion supported by a graphene oxide-immobilized enzyme reactor (GO-IMER) in the MALDI imaging mass spectrometry (IMS) workflow is reported, which enables the simultaneous diagnostic identity and distribution attributes of the proteome on tissue.

N-glycosylation plays an important role in chief biological and pathological processes. Quantifying the N-glycan is important since glycan alterations are related to many diseases. In this study, we developed a novel N-glycan quantitation approach using metallic element chelated tag labeling (MeCTL) through reductive amination. The MeCTL strategy is of high labeling efficiency and accurate in quantitation with high reproducibility (CV < 17.03%) and good linearity (R > 0.99) within 2 orders of magnitude of dynamic range. Additionally, it provides significant cross-ring fragmentation to distinguish N-glycan isomers. Furthermore, multiplex quantitation by chelation with several different rare earth elements can be achieved. At last, this strategy has been successfully used for evaluation of N-glycan changes in human serum associated with CRC, indicating its potential in clinical applications including disease N-glycome profiling and relative quantitation.

Analysis of oligosaccharides with matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) remains challenging due to their low ionization efficiency. The sensitivity achieved by MS for oligosaccharides lags far behind that for proteins/peptides. Here, hydrazinonicotinic acid (HYNIC) is proposed as a new matrix to realize highly sensitive and selective analysis of oligosaccharides in MALDI-MS. The detection limit of maltoheptaose provided by HYNIC is as low as 1 amol, which is five orders of magnitude lower than that provided by the traditional matrix 2,5-dihydroxybenzoic acid (DHB). Interestingly, HYNIC displayed remarkable selectivity for ionization of oligosaccharides, making glycans from glycoproteins become more accessible to be detected even without pre-purification, as demonstrated by the direct detection of the oligosaccharides from human serum without pre-separation of the proteins/peptides. The HYNIC matrix also possessed the virtue of higher homogeneity of crystallization and better salt tolerance (up to 200 mM NaCl, 140 mM urea and 40 mM sulfocarbamide et al.) compared with the traditional matrix DHB. Furthermore, the HYNIC matrix afforded adequate fragmentation, thus providing rich information for the structural elucidation of the oligosaccharide. Therefore, using HYNIC as the matrix to directly analyze oligosaccharides is inherently simple and straightforward.

Programmed cell death 1 (PD-1) monoclonal antibodies have been approved by regulatory agencies for the treatment of various types of cancer, and the mechanism involves the restoration of T cell functions. We report herein the X-ray crystal structure of a fully human monoclonal antibody mAb059c fragment antigen-binding (Fab) in complex with the PD-1 extracellular domain (ECD) at a resolution of 1.70 Å. Structural analysis indicates 1) an epitope, comprising fragments from the C’D, BC and FG loops of PD-1, contributes to mAb059c interaction, 2) an unique conformation of the C’D loop and a different orientation of R86 enabling the capture of PD-1 by the antibody complementarity determining region (CDR) and the formation of one salt-bridge contact – ASP101(HCDR3):ARG86(PD-1), and 3) the contact of FG with light chain (LC) CDR3 is maintained by a second salt-bridge and two backbone hydrogen bonds. Interface analysis reveals that N-glycosylation sites 49, 74 and 116 on PD-1 do not contact mAb059c; while N58 in the BC loop is recognized by mAb059c heavy chain CDR1 and CDR2. Mutation of N58 attenuated mAb059c binding to PD-1. These findings and the novel anti-PD-1 antibody will facilitate better understanding of the mechanisms of the molecular recognition of PD-1 receptor by anti-PD-1 mAb and, thereby, enable the development of new therapeutics with an expanded spectrum of efficacy for unmet medical needs.