Differential expression of N-glycopeptides derived from serum glycoproteins in mild cognitive impairment (MCI) patients.

Mild cognitive impairment (MCI) is an early stage of memory loss that affects cognitive abilities with the aging of individuals, such as language or visual/spatial comprehension. MCI is considered a prodromal phase of more complicated neurodegenerative diseases such as Alzheimer's. Therefore, accurate diagnosis and better understanding of the disease prognosis will facilitate prevention of neurodegeneration. However, the existing diagnostic methods fail to provide precise and well-timed diagnoses, and the pathophysiology of MCI is not fully understood. Alterations of the serum N-glycoproteome expression could represent an essential contributor to the overall pathophysiology of neurodegenerative diseases and be used as a potential marker to assess MCI diagnosis using less invasive procedures. In this approach, we identified N-glycopeptides with different expressions between healthy and MCI patients from serum glycoproteins. Seven of the N-glycopeptides showed outstanding AUC values, among them the antithrombin-III Asn224 + 4-5-0-2 with an AUC value of 1.00 and a p value of 0.0004. According to proteomics and ingenuity pathway analysis (IPA), our data is in line with recent publications, and the glycoproteins carrying the identified N-sites play an important role in neurodegeneration.

In-Depth Proteome Profiling of Small Extracellular Vesicles Isolated from Cancer Cell Lines and Patient Serum.

Extracellular vesicle (EV) secretion has been observed in many types of both normal and tumor cells. EVs contain a variety of distinctive cargoes, allowing tumor-derived serum proteins in EVs to act as a minimally invasive method for clinical monitoring. We have undertaken a comprehensive study of the protein content of the EVs from several cancer cell lines using direct data-independent analysis. Several thousand proteins were detected, including many classic EV markers such as CD9, CD81, CD63, TSG101, and Syndecan-1, among others. We detected many distinctive cancer-specific proteins, including several known markers used in cancer detection and monitoring. We further studied the protein content of EVs from patient serum for both normal controls and pancreatic cancer and hepatocellular carcinoma. The EVs for these studies have been isolated by various methods for comparison, including ultracentrifugation and CD9 immunoaffinity column. Typically, 500-1000 proteins were identified, where most of them overlapped with the EV proteins identified from the cell lines studied. We were able to identify many of the cell-line EV protein markers in the serum EVs, in addition to the large numbers of proteins specific to pancreatic and HCC cancers.

A guide to mass spectrometric analysis of extracellular vesicle proteins for biomarker discovery.

Exosomes (small extracellular vesicles) in living organisms play an important role in processes such as cell proliferation or intercellular communication. Recently, exosomes have been extensively investigated for biomarker discoveries for various diseases. An important aspect of exosome analysis involves the development of enrichment methods that have been introduced for successful isolation of exosomes. These methods include ultracentrifugation, size exclusion chromatography, polyethylene glycol-based precipitation, immunoaffinity-based enrichment, ultrafiltration, and asymmetric flow field-flow fractionation among others. To confirm the presence of exosomes, various characterization methods have been utilized such as Western blot analysis, atomic force microscopy, electron microscopy, optical methods, zeta potential, visual inspection, and mass spectrometry. Recent advances in high-resolution separations, high-performance mass spectrometry and comprehensive proteome databases have all contributed to the successful analysis of exosomes from patient samples. Herein we review various exosome enrichment methods, characterization methods, and recent trends of exosome investigations using mass spectrometry-based approaches for biomarker discovery.

GlycoSLASH: Concurrent Glycopeptide Identification from Multiple Related LC-MS/MS Data Sets by Using Spectral Clustering and Library Searching.

Liquid chromatography coupled with tandem mass spectrometry is commonly adopted in large-scale glycoproteomic studies involving hundreds of disease and control samples. The software for glycopeptide identification in such data (e.g., the commercial software Byonic) analyzes the individual data set and does not exploit the redundant spectra of glycopeptides presented in the related data sets. Herein, we present a novel concurrent approach for glycopeptide identification in multiple related glycoproteomic data sets by using spectral clustering and spectral library searching. The evaluation on two large-scale glycoproteomic data sets showed that the concurrent approach can identify 105%-224% more spectra as glycopeptides compared to the glycopeptide identification on individual data sets using Byonic alone. The improvement of glycopeptide identification also enabled the discovery of several potential biomarkers of protein glycosylations in hepatocellular carcinoma patients.

Matrix-assisted laser desorption/ionization-Fourier-transform ion cyclotron resonance-mass spectrometry analysis of exosomal lipids from human serum.

RATIONALE: Exosomes contain biomarkers such as proteins and lipids that help in understanding normal physiology and diseases. Lipids, in particular, are infrequently studied using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) for biomarker discovery. In this study, MALDI was equipped with a high-resolution MS to investigate exosomal lipids from human serum. METHODS: Exosomal lipids were profiled using MALDI with Fourier-transform ion cyclotron resonance (FTICR)-MS. Four matrices (i.e., α-cyano-4-hydroxycinnamic acid [CHCA], 2,5-dihydroxybenzoic acid, sinapinic acid, and graphene oxide [GO]) and three sample preparation methods (i.e., dried droplet, thin layer, and two layer) were compared for the number of lipid species detected and the relative abundance of each lipid from human serum and human serum exosomes. RESULTS: In sum, 172 and 89 lipid species were identified from human serum and human serum exosomes, respectively, using all the methods. The highest number of exosome lipid species, 69, was detected using the CHCA matrix, whereas only 8 exosome lipid species were identified using the GO matrix. Among the identified lipid species, phosphatidylcholine was identified most frequently, probably due to the use of a positive ion mode. CONCLUSIONS: Exosomes and human serum showed comparable lipid profiles as determined using MALDI-FTICR-MS. These findings provide a new perspective on exosomal lipidomics analysis and may serve as a foundation for future lipidomics-based biomarker research using MALDI-FTICR-MS.

GlycoHybridSeq: Automated Identification of N-Linked Glycopeptides Using Electron Transfer/High-Energy Collision Dissociation (EThcD).

Glycosylation is one of the most common post-translational modifications (PTM) occurring in a large variety of proteins with important biological functions in human and other higher organisms. Liquid chromatography tandem mass spectrometry (LC-MS/MS) has been routinely used to characterize site-specific protein glycosylation at high throughput in complex glycoproteomic samples. Recently, electron transfer/high-energy collision dissociation (EThcD) was introduced for glycopeptide identification, which offers rich structural information on glycopepides with the fragment ions from the cleavages of both the glycan and the peptide backbone. Herein, we present the software GlycoHybridSeq for automated interpretation of EThcD-MS/MS spectra from glycoproteomic data using a customized scoring function, which enables the functionalities of identifying glycopeptides, characterizing glycosylation sites, and distinguishing some isomeric glycans. We evaluate GlycoHybridSeq on glycoproteomic data collected for cancer biomarker discovery. The results showed that it achieved comparable or better performance than that of Byonic and MSFragger. GlycoHybridSeq is released as an open source software and is ready to be used in large-scale glycoproteomic data analyses.

Column-based Technology for CD9-HPLC Immunoaffinity Isolation of Serum Extracellular Vesicles.

Serum-derived extracellular vesicles (EVs) are a promising source of biomarkers; however, major challenges in EV separation and proteomic profiling remain for isolating EVs from a small amount, that is, on the microliter scale, of human serum while minimizing the contamination of blood proteins and lipoprotein particles coeluting in EV preparations. Herein we have developed a column-based CD9-antibody-immobilized high-performance liquid chromatography immunoaffinity chromatography(CD9-HPLC-IAC) technology for EV isolation from a microliter scale of serum for downstream proteomic analysis. The CD9-HPLC-IAC method achieved EV isolation from 40 µL of serum in 30 min with a yield of 8.0 × 109 EVs, where EVs were further processed with a postcolumn cleaning step using the 50 kDa molecular weight cut-off filter for the buffer exchange, concentration, and reduction of potentially coeluting serum proteins. In total, 482 proteins were identified in EVs by using liquid chromatography tandem mass spectrometry, including the common exosomal markers such as CD63, CD81, CD82, Alix, and TSG101. The statistical analysis of EV protein content showed that the top 10 serum proteins in EVs were significantly decreased by using the CD9-HPLC-IAC method compared with the use of ultracentrifugation (p = 0.001) and size exclusion chromatography (p = 0.009), and apolipoproteins were significantly reduced 4.8-fold compared with the SEC method (p < 0.001). The result demonstrates the potential of the CD9-HPLC-IAC method for the efficient isolation and proteomic characterization of EVs from a microscale volume of serum.

A Panel of Glycopeptides as Candidate Biomarkers for Early Diagnosis of NASH Hepatocellular Carcinoma Using a Stepped HCD Method and PRM Evaluation.

Changes in N-glycosylation on specific peptide sites of serum proteins have been investigated as potential markers for diagnosis of nonalcoholic steatohepatitis (NASH)-related HCC. To accomplish this work, a novel workflow involving broad-scale marker discovery in serum followed by targeted marker evaluation of these glycopeptides were combined. The workflow involved an LC-Stepped HCD-DDA-MS/MS method coupled with offline peptide fractionation for large-scale identification of N-glycopeptides directly from pooled serum samples (each n = 10) as well as differential determination of N-glycosylation changes between disease states. We then evaluated several potentially diagnostic N-glycopeptides among 78 individual patient samples (40 cirrhosis, 28 early stage NASH HCC, and 10 late-stage NASH HCC) by LC-Stepped HCD-PRM-MS/MS to quantitatively analyze 65 targeted glycopeptides from 7 glycoproteins. Of these targets, we found site-specific N-glycopeptides n169GSLFAFR_HexNAc(4)Hex(5)NeuAc(2) and n242ISDGFDGIPDNVDAALALPAHSYSGR_HexNAc(5)Hex(6)Fuc(1)NeuAc(3) from VTNC were significantly increased comparing samples from patients with NASH cirrhosis and NASH HCC (p < 0.05). When combining results of these 2 glycopeptides with AFP, the ROC curve analysis demonstrated the AUC value increased to 0.834 (95% CI, 0.748-0.921) and 0.847 (95% CI, 0.766-0.932), respectively, as compared to that of AFP alone (AUC = 0.791, 95% CI, 0.690-0.892). These 2 glycopeptides may serve as potential biomarkers for early HCC diagnosis in patients with NASH related cirrhosis.

Intestinal extracellular vesicles are altered by vertical sleeve gastrectomy.

Bariatric surgery is the most effective treatment for obesity and its comorbidities. However, our understanding of the molecular mechanisms behind its beneficial effects is limited. Extracellular vesicles (EVs) comprise an important mode of intercellular communication. They carry nucleic acids, hormones, and signaling molecules and regulate multiple processes. Our aim was to test the role of EVs in the effects of vertical sleeve gastrectomy (VSG) using a mouse model. Small intestinal EVs were obtained from the mice that underwent VSG or control surgery and were on chow or high-fat diet or diet-restricted, and then they were subjected to the proteomic analysis. Enteroid and bacterial cultures were treated with EVs to evaluate their survival effect. A mouse cohort received intraduodenal administration of EVs from VSG or Sham mice for 10 days. Body weight, glucose metabolism, and intestinal morphology were evaluated. EVs were enriched in the intestinal lumen and mucus of VSG compared with Sham mice. Protein composition of VSG and Sham-derived EVs was highly distinct. When introduced into culture, VSG EVs decreased survival of intestinal enteroids and, conversely, promoted proliferation of bacteria. Mice administered with EVs obtained from VSG and Sham groups did not show differences in body weight, food intake, or glucose metabolism. Intestinal morphology was altered, as VSG EVs caused reduction of ileal villi length and decreased epithelial proliferation in the jejunum and ileum. VSG causes remodeling of intestinal EVs, which results in unique protein composition. VSG-derived EVs exhibit cytotoxic effects on epithelial cells and reduce proliferation of intestinal progenitor cells in mice.NEW & NOTEWORTHY This is the first study that investigates the impact of bariatric surgery on protein composition of intestinal extracellular vesicles. Extracellular vesicle composition is greatly altered after vertical sleeve gastrectomy and may potentially modulate various signaling pathways. In our study, extracellular vesicles from vertical sleeve gastrectomy-treated mice promote bacterial proliferation but exhibit cytotoxic effect on epithelial cells and reduce proliferation of intestinal progenitor cells in mice.

A novel method of high-purity extracellular vesicle enrichment from microliter-scale human serum for proteomic analysis.

We have developed a rapid, low-cost, and simple separation strategy to separate extracellular vesicles (EVs) from a small amount of serum (i.e.,<100 µL) with minimal contamination by serum proteins and lipoprotein particles to meet the high purity requirement for EV proteome analysis. EVs were separated by a novel polyester capillary channel polymer (PET C-CP) fiber phase/hydrophobic interaction chromatography (HIC) method which is rapid and can process small size samples. The collected EV fractions were subjected to a post-column cleanup protocol using a centrifugal filter to perform buffer exchange and eliminate potential coeluting non-EV proteins while minimizing EV sample loss. Downstream characterization demonstrated that our current strategy can separate EVs with the anticipated exosome-like particle size distribution and high yield (∼1 × 1011 EV particles per mL of serum) in approximately 15 min. Proteome profiling of the EVs reveals that a group of genuine EV components were identified that have significantly less high-abundance blood proteins and lipoprotein particle contamination in comparison to traditional separation methods. The use of this methodology appears to address the major challenges facing EV separation for proteomics analysis. In addition, the EV post-column cleanup protocol proposed in the current work has the potential to be combined with other separation methods, such as ultracentrifugation (UC), to further purify the separated EV samples.

Glycopeptide Biomarkers in Serum Haptoglobin for Hepatocellular Carcinoma Detection in Patients with Nonalcoholic Steatohepatitis.

Nonalcoholic steatohepatitis (NASH) is rising in prevalence in the United States and is a growing cause of hepatocellular carcinomas (HCCs). Site-specific glycan heterogeneity on glycoproteins has been shown as a potential diagnostic biomarker for HCC. Herein, we have performed a comprehensive screening of site-specific N-glycopeptides in serum haptoglobin (Hp), a reporter molecule for aberrant glycosylation in HCC, to characterize glycopeptide markers for NASH-related HCCs. In total, 70 NASH patients (22 early HCC, 15 advanced HCC, and 33 cirrhosis cases) were analyzed, with Hp purified from 20 µL of serum in each patient, and 140 sets of mass spectrometry (MS) data were collected using liquid chromatography coupled with electron-transfer high-energy collisional dissociation tandem MS (LC-EThcD-MS/MS) for quantitative analysis on a novel software platform, Byos. Differential quantitation analysis revealed that five N-glycopeptides at sites N184 and N241 were significantly elevated during the progression from NASH cirrhosis to HCC (p < 0.05). Receiver operating characteristic (ROC) curve analysis demonstrated that the N-glycopeptides at sites N184 and N241 bearing a monofucosylated triantennary glycan A3G3F1S3 had the best diagnostic performance in detection of early NASH HCC, area under the curve (AUC) = 0.733 and 0.775, respectively, whereas α-fetoprotein (AFP) had an AUC of 0.692. When combined with AFP, the two panels improved the sensitivity for early NASH HCC from 59% (AFP alone) to 73% while maintaining a specificity of 70%, based on the optimal cutoff. Two-dimensional (2-D) scatter plots of the AFP value and N-glycopeptides showed that these N-glycopeptide markers detected 58% of AFP-negative HCC patients as distinct from cirrhosis. These site-specific N-glycopeptides could serve as potential markers for early detection of HCC in patients with NASH-related cirrhosis.

Comprehensive Detection of Single Amino Acid Variants and Evaluation of Their Deleterious Potential in a PANC-1 Cell Line.

Identifying single amino acid variants (SAAVs) in cancer is critical for precision oncology. Several advanced algorithms are now available to identify SAAVs, but attempts to combine different algorithms and optimize them on large data sets to achieve a more comprehensive coverage of SAAVs have not been implemented. Herein, we report an expanded detection of SAAVs in the PANC-1 cell line using three different strategies, which results in the identification of 540 SAAVs in the mass spectrometry data. Among the set of 540 SAAVs, 79 are evaluated as deleterious SAAVs based on analysis using the novel AssVar software in which one of the driver mutations found in each protein of KRAS, TP53, and SLC37A4 is further validated using independent selected reaction monitoring (SRM) analysis. Our study represents the most comprehensive discovery of SAAVs to date and the first large-scale detection of deleterious SAAVs in the PANC-1 cell line. This work may serve as the basis for future research in pancreatic cancer and personal immunotherapy and treatment.

Quantitative Analysis of α-1-Antitrypsin Glycosylation Isoforms in HCC Patients Using LC-HCD-PRM-MS.

The change in glycosylation of serum proteins is often associated with the development of various diseases and thus can be used for diagnosis. In this study, a liquid chromatography-tandem mass spectrometry-based method is used for accurate structural analysis and quantification of site-specific glycoforms of serum α-1-antitrypsin (A1AT) in early-stage HCC and cirrhosis patients. Serum protein A1AT was purified from patient sera by immunoprecipitation with anti-A1AT antibody conjugated agarose beads, and the isolated A1AT protein was digested and analyzed by LC-MS/MS. Two tandem mass spectrometry strategies are integrated in this study: a nontargeted stepped HCD strategy for structural analysis of A1AT glycopeptides and a targeted parallel reaction monitoring (PRM) strategy for quantification of site-specific glycoforms of A1AT in HCC and cirrhosis patient sera. Accordingly, pGlyco2.0 software was used for glycopeptide identification, and Skyline software was used for glycoform quantification using the Y1 ion (peptide+GlcNAc) in MS/MS spectra. Ten site-specific glycopeptides of A1AT were identified with stepped HCD-MS/MS in patient samples, 7 of which were further quantified using HCD-PRM-MS among patient samples. We found that our strategy was able to distinguish isomers of glycopeptides where several isomers showed distinctly different patterns between cirrhosis and HCC patients. We also found that the ratio of different charge states (2+/3+) of one glycopeptide of A1AT can significantly discriminate early-stage HCC from cirrhosis with the area under the receiver operating characteristic curve AUC of 0.9. Further analysis showed that the difference may be related to the sialic acid/galactose linkage of the glycan motif.

Glycoproteomic markers of hepatocellular carcinoma-mass spectrometry based approaches.

Hepatocellular carcinoma (HCC) is the third most-common cause of cancer-related death worldwide. Most cases of HCC develop in patients that already have liver cirrhosis and have been recommended for surveillance for an early onset of HCC. Cirrhosis is the final common pathway for several etiologies of liver disease, including hepatitis B and C, alcohol, and increasingly non-alcoholic fatty liver disease. Only 20-30% of patients with HCC are eligible for curative therapy due primarily to inadequate early-detection strategies. Reliable, accurate biomarkers for HCC early detection provide the highest likelihood of curative therapy and survival; however, current early-detection methods that use abdominal ultrasound and serum alpha fetoprotein are inadequate due to poor adherence and limited sensitivity and specificity. There is an urgent need for convenient and highly accurate validated biomarkers for HCC early detection. The theme of this review is the development of new methods to discover glycoprotein-based markers for detection of HCC with mass spectrometry approaches. We outline the non-mass spectrometry based methods that have been used to discover HCC markers including immunoassays, capillary electrophoresis, 2-D gel electrophoresis, and lectin-FLISA assays. We describe the development and results of mass spectrometry-based assays for glycan screening based on either MALDI-MS or ESI analysis. These analyses might be based on the glycan content of serum or on glycan screening for target molecules from serum. We describe some of the specific markers that have been developed as a result, including for proteins such as Haptoglobin, Hemopexin, Kininogen, and others. We discuss the potential role for other technologies, including PGC chromatography and ion mobility, to separate isoforms of glycan markers. Analyses of glycopeptides based on new technologies and innovative softwares are described and also their potential role in discovery of markers of HCC. These technologies include new fragmentation methods such as EThcD and stepped HCD, which can identify large numbers of glycopeptide structures from serum. The key role of lectin extraction in various assays for intact glycopeptides or their truncated versions is also described, where various core-fucosylated and hyperfucosylated glycopeptides have been identified as potential markers of HCC. Finally, we describe the role of LC-MRMs or lectin-FLISA MRMs as a means to validate these glycoprotein markers from patient samples. These technological advancements in mass spectrometry have the potential to lead to novel biomarkers to improve the early detection of HCC.

Single Amino Acid Variant Discovery in Small Numbers of Cells.

We have performed deep proteomic profiling down to as few as 9 Panc-1 cells using sample fractionation, TMT multiplexing, and a carrier/reference strategy. Off line fractionation of the TMT-labeled sample pooled with TMT-labeled carrier Panc-1 whole cell proteome was achieved using alkaline reversed phase spin columns. The fractionation in conjunction with the carrier/reference (C/R) proteome allowed us to detect 47 414 unique peptides derived from 6261 proteins, which provided a sufficient coverage to search for single amino acid variants (SAAVs) related to cancer. This high sample coverage is essential in order to detect a significant number of SAAVs. In order to verify genuine SAAVs versus false SAAVs, we used the SAVControl pipeline and found a total of 79 SAAVs from the 9-cell Panc-1 sample and 174 SAAVs from the 5000-cell Panc-1 C/R proteome. The SAAVs as sorted into high confidence and low confidence SAAVs were checked manually. All the high confidence SAAVs were found to be genuine SAAVs, while half of the low confidence SAAVs were found to be false SAAVs mainly related to PTMs. We identified several cancer-related SAAVs including KRAS, which is an important oncoprotein in pancreatic cancer. In addition, we were able to detect sites involved in loss or gain of glycosylation due to the enhanced coverage available in these experiments where we can detect both sites of loss and gain of glycosylation.

Differential Quantitative Determination of Site-Specific Intact N-Glycopeptides in Serum Haptoglobin between Hepatocellular Carcinoma and Cirrhosis Using LC-EThcD-MS/MS.

Intact N-glycopeptide analysis remains challenging due to the complexity of glycopeptide structures, low abundance of glycopeptides in protein digests, and difficulties in data interpretation/quantitation. Herein, we developed a workflow that involved advanced methodologies, the EThcD-MS/MS fragmentation method and data interpretation software, for differential analysis of the microheterogeneity of site-specific intact N-glycopeptides of serum haptoglobin between early hepatocellular carcinoma (HCC) and liver cirrhosis. Haptoglobin was immunopurified from 20 µL of serum in patients with early HCC, liver cirrhosis, and healthy controls, respectively, followed by trypsin/GluC digestion, glycopeptide enrichment, and LC-EThcD-MS/MS analysis. Identification and differential quantitation of site-specific N-glycopeptides were performed using a combination of Byonic and Byologic software. In total, 93, 87, and 68 site-specific N-glycopeptides were identified in early HCC, liver cirrhosis, and healthy controls, respectively, with high confidence. The increased variety of N-glycopeptides in liver diseases compared to healthy controls was due to increased branching with hyper-fucosylation and sialylation. Differential quantitation analysis showed that 5 site-specific N-glycopeptides on sites N184 and N241 were significantly elevated in early HCC compared to cirrhosis ( p < 0.05) and normal controls ( p ≤ 0.001). The result demonstrates that the workflow provides a strategy for detailed profiles of N-glycopeptides of patient samples as well as for relative quantitation to determine the level changes in site-specific N-glycopeptides between disease states.

Platelet Factor 4 as a Novel Exosome Marker in MALDI-MS Analysis of Exosomes from Human Serum.

Exosomes are nanosized vesicles commonly found in biological fluids as a result of a secretion process involving endosomes and multivesicular bodies. The isolation and analysis of exosomes can be useful for noninvasive clinical diagnosis of a variety of human diseases. We investigated the utility of analyzing exosomal proteins, using matrix-assisted laser desorption/ionization combined with Fourier-transform ion cyclotron resonance mass spectrometry (MALDI-FTICR-MS), as a means of determining the presence of exosomes. MALDI-FTICR-MS analyses of exosomes enriched from human serum via centrifugation in a mass range of m/z 1000-20 000 yielded a distinctive protein around m/z 7766. The high mass accuracy and resolution of MALDI-FTICR-MS allowed for reliable comparisons against a protein database, through which the protein was identified as platelet factor 4 (PLF4), whose singly charged protein peak has an elemental composition of C341H577N96O101S4+, with a theoretical most abundant isotopic peak at m/z 7765.194 and a theoretical average peak at m/z 7766. The MALDI-TOF MS analysis of exosomes from the serum of 27 patients with different states of liver diseases provided the most abundant PLF4 peak for each mass spectrum, along with several additional minor peaks. In conclusion, MALDI-MS is suitable as an alternative exosome detection method, serving as a valuable confirmation tool, greatly decreasing the time and workload associated with exosome identification.

Serum Protein Biomarkers of Fibrosis Aid in Risk Stratification of Future Stricturing Complications in Pediatric Crohn's Disease.

OBJECTIVES: Avoiding fibrostenotic complications is of paramount concern in the management of Crohn's disease (CD). We sought to investigate the association of candidate biomarkers of fibrosis collected at diagnosis with the future development of fibrostenotic CD. METHODS: Using the Risk Stratification and Identification of Immunogenetic and Microbial Markers of Rapid Disease Progression in Children with Crohn's Disease cohort, a multicenter prospective observational pediatric inception cohort, subjects with an inflammatory phenotype (B1) at diagnosis who later converted to a stricturing phenotype (B2) within 3 years were compared with those who remained B1. Serum collected at diagnosis underwent both parallel reaction monitoring-targeted proteomic analysis and conventional enzyme-linked immunosorbent assay for 10 candidate biomarkers of intestinal fibrosis. Cox proportional hazard regression was used for multivariable analysis of time-dependent outcomes. RESULTS: In 116 subjects 58 subjects with verified B1 phenotype at diagnosis who later converted to B2 disease were compared with 58 subjects who remained B1 over 3 years of follow-up. Extracellular matrix protein 1 (ECM1) levels in the upper quartile (hazard ratio [HR] 3.43, 95% confidence limit [CL] 1.33, 8.42) were associated with future fibrostenotic disease. ASCA IgA (HR 4.99, 95% CL 1.50, 16.68) and CBir levels (HR 5.19, 95% CL 1.83, 14.74) were also associated with future intestinal fibrostenosis, although ECM1 continued to demonstrate independent association with conversion to B2 even with adjustment for serologies in multivariable analysis (HR 5.33, 95% CL 1.29, 22.13). CONCLUSIONS: ECM1 and other biomarkers of fibrosis may aid in determining the risk of uncomplicated inflammatory disease converting to B2 stricturing phenotypes in children with CD. Prospective validation studies to verify test performance and optimize clinical utilization are needed before clinical implementation.

Aberrant glycosylation and cancer biomarker discovery: a promising and thorny journey.

Glycosylation is among the most important post-translational modifications for proteins and is of intrinsic complex character compared with DNAs and naked proteins. Indeed, over 50%-70% of proteins in circulation are glycosylated, and the "sweet attachments" have versatile structural and functional implications. Both the configuration and composition of the attached glycans affect the biological activities of consensus proteins significantly. Glycosylation is generated by complex biosynthetic pathways comprising hundreds of glycosyltransferases, glycosidases, transcriptional factors, transporters and the protein backbone. In addition, lack of direct genetic templates and glyco-specific antibodies such as those commonly used in DNA amplification and protein capture makes research on glycans and glycoproteins even more difficult, thus resulting in sparse knowledge on the pathophysiological implications of glycosylation. Fortunately, cutting-edge technologies have afforded new opportunities and approaches for investigating cancer-related glycosylation. Thus, glycans as well as aberrantly glycosylated protein-based cancer biomarkers have been increasingly recognized. This mini-review highlights the most recent developments in glyco-biomarker studies in an effort to discover clinically relevant cancer biomarkers using advanced analytical methodologies such as mass spectrometry, high-performance liquid chromatographic/ultra-performance liquid chromatography, capillary electrophoresis, and lectin-based technologies. Recent clinical-centered glycobiological studies focused on determining the regulatory mechanisms and the relation with diagnostics, prognostics and even therapeutics are also summarized. These studies indicate that glycomics is a treasure waiting to be mined where the growth of cancer-related glycomics and glycoproteomics is the next great challenge after genomics and proteomics.