Covalent attachment of carbohydrates to proteins is one of the most common post-translational modifications. At the cell surface, sugar moieties of glycoproteins contribute to molecular recognition events involved in cancer metastasis. We have combined glycan metabolic labeling with mass spectrometry analysis to identify and characterize metastasis-associated cell surface sialoglycoproteins. Our model system used syngeneic prostate cancer cell lines derived from PC3 (N2, nonmetastatic, and ML2, highly metastatic). The metabolic incorporation of AC(4)ManNAz and subsequent specific labeling of cell surface sialylation was confirmed by flow cytometry and confocal microscopy. Affinity isolation of the modified sialic-acid containing cell surface proteins via click chemistry was followed by SDS-PAGE separation and liquid chromatography-tandem MS analysis. We identified 324 proteins from N2 and 372 proteins of ML2. Using conservative annotation, 64 proteins (26%) from N2 and 72 proteins (29%) from ML2 were classified as extracellular or membrane-associated glycoproteins. A selective enrichment of sialoglycoproteins was confirmed. When compared with global proteomic analysis of the same cells, the proportion of identified glycoprotein and cell-surface proteins were on average threefold higher using the selective capture approach. Functional clustering of differentially expressed proteins by Ingenuity Pathway Analysis revealed that the vast majority of glycoproteins overexpressed in the metastatic ML2 subline were involved in cell motility, migration, and invasion. Our approach effectively targeted surface sialoglycoproteins and efficiently identified proteins that underlie the metastatic potential of the ML2 cells.

As man has moved rapidly from the hunter-gatherer environment to the living conditions of the industrialized countries, the incidences of some cancers have increased alarmingly. Recent increases are usually attributed to dietary changes or to altered exposures to putative carcinogens associated with the modern lifestyle. However, the changes in cancer incidence parallel similar increases in non-neoplastic chronic inflammatory disorders (inflammatory bowel disease, allergies, and autoimmunity), and the epidemiology is often strikingly similar. This parallel is worth exploring, because the increases in chronic inflammatory disorders are at least partly explained by immunoregulatory defects resulting from diminished exposure to microorganisms that co-evolved with mammals and developed a role in driving immunoregulatory circuits (the hygiene hypothesis). Dysregulated chronic inflammation can drive oncogenesis and also provides growth and angiogenic factors that enhance the subsequent proliferation and spread of tumor cells. Thus, a modern failure to downregulate inappropriate inflammation could underlie increases in some cancers in parallel with the increases in chronic inflammatory disorders. This possibility is supported by recent work showing that in some circumstances regulatory T cells protect against cancer, rather than aggravating it, as previously assumed. A greater understanding of these interactions might pave the way to improved microbe-based immunotherapies.

The classification of colorectal cancers (CRC) is currently based largely on histologically determined tumour characteristics, such as differentiation status and tumour stage, i.e., depth of tumour invasion, involvement of regional lymph nodes and the occurrence of metastatic spread to other organs. These are the conventional prognostic factors for patient survival and often determine the requirement for adjuvant therapy after surgical resection of the primary tumour. However, patients with the same CRC stage can have very different disease-related outcomes. For some, surgical removal of early-stage tumours leads to full recovery, while for others, disease recurrence and metastasis may occur regardless of adjuvant therapy. It is therefore important to understand the molecular processes that lead to disease progression and metastasis and to find more reliable prognostic markers and novel targets for therapy. This review focuses on cell surface proteins that correlate with tumour progression, metastasis and patient outcome, and discusses some of the challenges in finding prognostic protein markers in CRC.

A common phenotypic change in cancer is a dramatic transformation of cellular glycosylation. Functional studies of particular tumour-associated oligosaccharides are difficult to interpret conclusively, but carbohydrate-binding proteins are likely to contribute to progression of the tumour. This review discusses the potential role of CLRs (C-type lectin receptors), expressed by antigen-presenting cells of the immune system, in tumour recognition and immune modulation. Studies in recent years have provided significant insight into the immunomodulatory function of CLR during infections, but their role in cancer remains elusive; some strongly bind tumour cells and antigens, indicating participation in malignancy. The potential to use recombinant CLR as diagnostic tools will also be discussed.

Although melanoma is one of the most studied malignancies, it still remains challenging for biomedicine. Since aberrant glycosylation has been considered as an important hallmark of cancer for many years, melanoma glycomic studies give a chance of better understanding the biology of the disease. The multistage nature of melanoma development, which is accompanied by changes in the expression of adhesion receptors from the integrin family, provides a chance for searching for neoglycoforms of proteins that can be considered as future sensitive melanoma biomarkers. The β1,6-branching, sialylation and fucosylation seem to be important modifications of integrin N-glycans in the case of malignant melanoma progression.

Melanoma, which is one of the most aggressive human tumours, originates from melanin-producing melanocytes. As no effective systemic therapy exists for advanced-stage melanoma, the best chance of recovery remains surgical removal of thin early-stage melanoma. Aberrant glycosylation is a hallmark of malignancy and a well-studied class of β1,6-branched oligosaccharides is associated with malignant transformation of rodent and human cells, and poor prognosis in cancer patients. It is evident that increased β1,6 branching significantly contributes to the phenotype of melanoma cells, influencing the adhesion to extracellular matrix components and motility as well as invasive and metastatic potential. Despite the considerable success in establishing the role of β1,6-branched N-linked oligosaccharides in melanoma biology, there is virtually no progress in using these glycans as a screening tool for the early diagnosis of the disease, or a target-specific therapeutic agent.

Glycans are cell-type-specific, posttranslational protein modifications that are modulated during developmental and disease processes. As such, glycoproteins are attractive biomarker candidates. Here, we describe a mass spectrometry-based workflow that incorporates lectin affinity chromatography to enrich for proteins that carry specific glycan structures. As increases in sialylation and fucosylation are prominent among cancer-associated modifications, we focused on Sambucus nigra agglutinin (SNA) and Aleuria aurantia lectin (AAL), lectins which bind sialic acid- and fucose-containing structures, respectively. Fucosylated and sialylated glycopeptides from human lactoferrin served as positive controls, and high-mannose structures from yeast invertase served as negative controls. The standards were spiked into Multiple Affinity Removal System (MARS) 14-depleted, trypsin-digested human plasma from healthy donors. Samples were loaded onto lectin columns, separated by HPLC into flow-through and bound fractions, and treated with peptide: N-glycosidase F to remove N-linked glycans. The deglycosylated peptide fractions were interrogated by ESI HPLC-MS/MS. We identified a total of 122 human plasma glycoproteins containing 247 unique glycosites. Importantly, several of the observed glycoproteins (e.g., cadherin 5 and neutrophil gelatinase-associated lipocalin) typically circulate in plasma at low nanogram per milliliter levels. Together, these results provide mass spectrometry-based evidence of the utility of incorporating lectin-separation platforms into cancer biomarker discovery pipelines.

One of the most urgent requirements in breast cancer is the development of a blood-based test for early detection and prognosis. Previously published results found a significant difference between specific glycan levels in patients with advanced breast cancer and healthy controls. The aim of this investigation was to address a more clinically relevant problem, i.e., whether the measurement of specific glycans could identify women with aggressive disease at an early stage. In order to reduce potential bias in this study, blood samples from patients were collected, stored and analyzed in a similar manner. Agalactosyl biantennary glycans (FA2) and glycans containing the sialyl Lewis x epitope (A3F1G1 and A2F1G1) were measured using high throughput normal-phase high-performance liquid chromatography in combination with exoglycosidase digestions in sera from 52 patients with early breast cancer (21 with lymph node-negative and 20 with lymph node-positive disease) and 134 women with benign breast disease. The combined levels of the glycans were significantly higher in patients with lymph node metastases compared to women without these metastases. Lymph node status is the single most important determinant of survival in early stage breast cancer. As high levels of these glycans were associated with nodal metastases, their measurement may provide a new non-invasive approach to determining prognosis in women with newly diagnosed breast cancer.

Systems biology is an approach to the science that views biology as an information science, studies biological systems as a whole and their interactions with the environment. This approach, for the reasons described here, has particular power in the search for informative diagnostic biomarkers of diseases because it focuses on the fundamental causes and keys on the identification and understanding of disease- perturbed molecular networks. In this review, we describe some recent developments that have used systems biology to address complex diseases - prion disease and drug induced liver injury- and use these as examples to illustrate the importance of understanding network structure and dynamics. The knowledge of network dynamics through in vitro experimental perturbation and modeling allows us to determine the state of the networks, to identify molecular correlates, and to derive new disease treatment approaches to reverse the pathology or prevent its progress into a more severe state through the manipulation of network states. This general approach, including diagnostics and therapeutics, is becoming known as systems medicine.

We used a lectin chromatography/MS-based approach to screen conditioned medium from a panel of luminal (less aggressive) and triple negative (more aggressive) breast cancer cell lines (n = 5/subtype). The samples were fractionated using the lectins Aleuria aurantia (AAL) and Sambucus nigra agglutinin (SNA), which recognize fucose and sialic acid, respectively. The bound fractions were enzymatically N-deglycosylated and analyzed by LC-MS/MS. In total, we identified 533 glycoproteins, ∼90% of which were components of the cell surface or extracellular matrix. We observed 1011 glycosites, 100 of which were solely detected in ≥3 triple negative lines. Statistical analyses suggested that a number of these glycosites were triple negative-specific and thus potential biomarkers for this tumor subtype. An analysis of RNaseq data revealed that approximately half of the mRNAs encoding the protein scaffolds that carried potential biomarker glycosites were up-regulated in triple negative vs luminal cell lines, and that a number of genes encoding fucosyl- or sialyltransferases were differentially expressed between the two subtypes, suggesting that alterations in glycosylation may also drive candidate identification. Notably, the glycoproteins from which these putative biomarker candidates were derived are involved in cancer-related processes. Thus, they may represent novel therapeutic targets for this aggressive tumor subtype.

Glycans are cell-type-specific, posttranslational protein modifications that are modulated during developmental and disease processes. As such, glycoproteins are attractive biomarker candidates. Here, we describe a mass spectrometry-based workflow that incorporates lectin affinity chromatography to enrich for proteins that carry specific glycan structures. As increases in sialylation and fucosylation are prominent among cancer-associated modifications, we focused on Sambucus nigra agglutinin (SNA) and Aleuria aurantia lectin (AAL), lectins which bind sialic acid- and fucose-containing structures, respectively. Fucosylated and sialylated glycopeptides from human lactoferrin served as positive controls, and high-mannose structures from yeast invertase served as negative controls. The standards were spiked into Multiple Affinity Removal System (MARS) 14-depleted, trypsin-digested human plasma from healthy donors. Samples were loaded onto lectin columns, separated by HPLC into flow-through and bound fractions, and treated with peptide: N-glycosidase F to remove N-linked glycans. The deglycosylated peptide fractions were interrogated by ESI HPLC-MS/MS. We identified a total of 122 human plasma glycoproteins containing 247 unique glycosites. Importantly, several of the observed glycoproteins (e.g., cadherin 5 and neutrophil gelatinase-associated lipocalin) typically circulate in plasma at low nanogram per milliliter levels. Together, these results provide mass spectrometry-based evidence of the utility of incorporating lectin-separation platforms into cancer biomarker discovery pipelines.

Glycans are an important class of post-translational modifications. Typically found on secreted and extracellular molecules, glycan structures signal the internal status of the cell. Glycans on tumor cells tend to have abundant sialic acid and fucose moieties. We propose that these cancer-associated glycan variants be exploited for biomarker development aimed at diagnosing early-stage disease. Accordingly, we developed a mass spectrometry-based workflow that incorporates chromatography on affinity matrices formed from lectins, proteins that bind specific glycan structures. The lectins Sambucus nigra (SNA) and Aleuria aurantia (AAL), which bind sialic acid and fucose, respectively, were covalently coupled to POROS beads (Applied Biosystems) and packed into PEEK columns for high pressure liquid chromatography (HPLC). Briefly, plasma was depleted of the fourteen most abundant proteins using a multiple affinity removal system (MARS-14; Agilent). Depleted plasma was trypsin-digested and separated into flow-through and bound fractions by SNA or AAL HPLC. The fractions were treated with PNGaseF to remove N-linked glycans, and analyzed by LC-MS/MS on a QStar Elite. Data were analyzed using Mascot software. The experimental design included positive controls-fucosylated and sialylated human lactoferrin glycopeptides-and negative controls-high mannose glycopeptides from Saccharomyces cerevisiae-that were used to monitor the specificity of lectin capture. Key features of this workflow include the reproducibility derived from the HPLC format, the positive identification of the captured and PNGaseF-treated glycopeptides from their deamidated Asn-Xxx-Ser/Thr motifs, and quality assessment using glycoprotein standards. Protocol optimization also included determining the appropriate ratio of starting material to column capacity, identifying the most efficient capture and elution buffers, and monitoring the PNGaseF-treatment to ensure full deglycosylation. Future directions include using this workflow to perform mass spectrometry-based discovery experiments on plasma from breast cancer patients and control individuals.

Verification of candidate biomarkers relies upon specific, quantitative assays optimized for selective detection of target proteins, and is increasingly viewed as a critical step in the discovery pipeline that bridges unbiased biomarker discovery to preclinical validation. Although individual laboratories have demonstrated that multiple reaction monitoring (MRM) coupled with isotope dilution mass spectrometry can quantify candidate protein biomarkers in plasma, reproducibility and transferability of these assays between laboratories have not been demonstrated. We describe a multilaboratory study to assess reproducibility, recovery, linear dynamic range and limits of detection and quantification of multiplexed, MRM-based assays, conducted by NCI-CPTAC. Using common materials and standardized protocols, we demonstrate that these assays can be highly reproducible within and across laboratories and instrument platforms, and are sensitive to low mug/ml protein concentrations in unfractionated plasma. We provide data and benchmarks against which individual laboratories can compare their performance and evaluate new technologies for biomarker verification in plasma.

Clinical proteomics has the potential to enable the early detection of cancer through the development of multiplex assays that can inform clinical decisions. However, there has been some uncertainty among translational researchers and developers as to the specific analytical measurement criteria needed to validate protein-based multiplex assays. To begin to address the causes of this uncertainty, a day-long workshop titled "Interagency Oncology Task Force Molecular Diagnostics Workshop" was held in which members of the proteomics and regulatory communities discussed many of the analytical evaluation issues that the field should address in development of protein-based multiplex assays for clinical use. This meeting report explores the issues raised at the workshop and details the recommendations that came out of the day's discussions, such as a workshop summary discussing the analytical evaluation issues that specific proteomic technologies should address when seeking US Food and Drug Administration approval.

As a part of ongoing efforts of the NCI-FDA Interagency Oncology Task Force subcommittee on molecular diagnostics, members of the Clinical Proteomics Technology Assessment for Cancer program of the National Cancer Institute have submitted 2 protein-based multiplex assay descriptions to the Office of In Vitro Diagnostic Device Evaluation and Safety, US Food and Drug Administration. The objective was to evaluate the analytical measurement criteria and studies needed to validate protein-based multiplex assays. Each submission described a different protein-based platform: a multiplex immunoaffinity mass spectrometry platform for protein quantification, and an immunological array platform quantifying glycoprotein isoforms. Submissions provided a mutually beneficial way for members of the proteomics and regulatory communities to identify the analytical issues that the field should address when developing protein-based multiplex clinical assays.

A major unmet need in liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomic analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS and peptide identification. Applied to datasets from replicate LC-MS/MS analyses, these metrics display consistent, reasonable responses to controlled perturbations. The metrics typically display variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications.

Huntingtons disease (HD) is a dominantly inherited neurodegenerative disease caused by a polyglutamine expansion in the protein huntingtin (Htt). Striatal and cortical neuronal loss are prominent features of this disease. No disease modifying treatments have been discovered for HD. To identify new therapeutic targets in HD, we screened a kinase inhibitor library for molecules that block mutant Htt cellular toxicity in a mouse HD striatal cell model. We found that diacylglycerol kinase (DGK) inhibitor II (R59949) decreased caspase-3/7 activity after serum withdrawal in striatal Hdh111Q/111Q cells. In addition, R59949 decreased the level of cleaved caspase-3, the accumulation of the 513 amino acid N-terminal Htt fragment processed by caspase-3, and blocked alterations in lipid metabolism during serum withdrawal. To identify the diacylglyercol kinase mediating this effect, we knocked down all four DGK isoforms expressed in the brain using siRNA (beta, gamma, epsilon and zeta). Only the knockdown of the family member, DGK-epsilon (DGKε), blocked striatal Hdh111Q/111Q-mediated toxicity. We also investigated the significance of these findings in vivo. First, we found that reduced function of the Drosophila DGKε homolog significantly improves Htt-induced motor dysfunction in a fly model of HD. In addition, we find that the levels of DGKε are increased in the striatum of R6/2 HD transgenic mice when compared to controls. Together these findings indicate that increased levels of kinase DGKε contribute to HD pathogenesis, and suggest that reducing its levels or activity is a potential therapy for HD.

3-nitrotyrosine (3NT) is an oxidative posttranslational modification associated with many diseases. Determining the specific sites of this modification remains a challenge due to the low stoichiometry of 3NT modifications in biological samples. Mass spectrometry-based proteomics is a powerful tool for identifying 3NT modifications, however several reports identifying 3NT sites were later demonstrated to be incorrect, highlighting that both the accuracy and efficiency of these workflows need improvement. To advance our understanding of the chromatographic and spectral properties of 3NT-containing peptides we have adapted a straightforward, reproducible procedure to generate a large set of 3NT peptides by chemical nitration of a defined, commercially available 48 protein mixture. Using two complementary LC-MS/MS platforms, a QTOF (QSTAR Elite) and dual pressure ion trap mass spectrometer (LTQ Velos), we detected over 200 validated 3NT-containing peptides with significant overlap in the peptides detected by both systems. We investigated the LC-MS/MS properties for each peptide manually using defined criteria and then assessed their utility to confirm that the peptide was 3NT modified. This broad set of validated 3NT-containing peptides can be utilized to optimize mass spectrometric instrumentation and data mining strategies or further develop 3NT peptide enrichment strategies for this biologically important, oxidative posttranslational modification.