A Proteomic Analysis of the Plasma Glycoproteins of a MCF-7 Mouse Xenograft: A Model System for the Detection of Tumor Markers

Use of Lectin-based Affinity Techniques in Breast Cancer Glycoproteomics: A Review

Changes in glycoprotein content, altered glycosylations, and aberrant glycan structures are increasingly recognized as cancer hallmarks. Because breast cancer is one of the most common causes of cancer deaths in the world, it is highly urgent to find other reliable biomarkers for its initial diagnosis and to learn as much as possible about this disease. In this Review, the applications of lectins to a screening of potential breast cancer biomarkers published during recent years are overviewed. These data provide a deeper insight into the use of modern strategies, technologies, and scientific knowledge in glycoproteomic breast cancer research. Particular attention is concentrated on the use of lectin-based affinity techniques, applied independently or most frequently in combination with mass spectrometry, as an effective tool for the targeting, separation, and reliable identification of glycoprotein molecules. Individual procedures and lectins used in published glycoproteomic studies of breast-cancer-related glycoproteins are discussed. The summarized approaches have the potential for use in diagnostic and predictive applications. Finally, the use of lectins is briefly discussed from the view of their future applications in the analysis of glycoproteins in cancer.

Quantification, 2DE analysis and identification of enriched glycosylated proteins from mouse muscles: Difficulties and alternatives

One of the problems with 2DE is that proteins present in low amounts in a sample are usually not detected, since their signals are masked by the predominant proteins. The elimination of these abundant proteins is not a guaranteed solution to achieve the desired results. The main objective of this study was the comparison of common and simple methodologies employed for 2DE analysis followed by MS identification, focusing on a pre-purified sample using a wheat germ agglutinin (WGA) column. Adult male C57Black/Crj6 (C57BL/6) mice were chosen as the model animal in this study; the gastrocnemius muscles were collected and processed for the experiments. The initial fractionation with succinylated WGA was successful for the elimination of the most abundant proteins. Two quantification methods were employed for the purified samples, and bicinchoninic acid (BCA) was proven to be most reliable for the quantification of glycoproteins. The gel staining method, however, was found to be decisive for the detection of specific proteins, since their structures affect the interaction of the dye with the peptide backbone. The Coomassie Blue R-250 dye very weakly stained the gel with the WGA purified sample. When the same gel was stained with silver nitrate, however, MS could positively assign 12 new spots. The structure of the referred proteins was not found to be prone to interaction with Coomassie blue.

IRAK4 and TLR3 Sequence Variants may Alter Breast Cancer Risk among African-American Women

Mounting evidence suggests that imbalances in immune regulation contribute to cell transformation. Women of African descent are an understudied group at high risk for developing aggressive breast cancer (BrCa). Therefore, we examined the role of 16 innate immune single nucleotide polymorphisms (SNPs) in relation to BrCa susceptibility among 174 African-American women in Atlanta, GA, USA. SNPs were examined in germ-line DNA collected from 102 BrCa patients and 72 women with benign nodules using SNPstream methodology. Inheritance of the TLR3 rs10025405 GG genotype was associated with an 82% decrease in BrCa risk. In contrast, individuals who possessed at least one IRAK4 rs4251545 T allele had a 1.68- to 4.99-fold increase in the risk of developing BrCa relative to those with the referent genotype (OR = 4.99; 95% CI = 1.00, 25.00; p = 0.0605). However, the IRAK4 rs4251545 locus was only significant under the additive genetic model (p trend = 0.0406). In silico predictions suggest IRAK4 rs4251545 SNP falls within a transcription enhancer/silencer region of the gene and codes for an Ala428Thr amino acid change. This missense mutation introduces a potential phosphorylation site in the extreme carboxy terminus (XCT) of the IRAK4 kinase domain. Preliminary molecular modeling predicts that this SNP stabilizes two alpha helices within the XCT on the surface of the IRAK4 kinase domain and increases the size of the groove between them. Our in silico results, combined with previous reports noting the presence of IRAK4 and XCT fragments in mouse and human serum, suggest the possibility that the XCT subdomain of IRAK4 possesses biological function. These findings require further evaluation and validation in larger populations, additional molecular modeling as well as functional studies to explore the role of IRAK4 and its XCT in cell transformation and innate immunity.

Quantitative proteomic analysis of human lung tumor xenografts treated with the ectopic ATP synthase inhibitor citreoviridin

ATP synthase is present on the plasma membrane of several types of cancer cells. Citreoviridin, an ATP synthase inhibitor, selectively suppresses the proliferation and growth of lung cancer without affecting normal cells. However, the global effects of targeting ectopic ATP synthase in vivo have not been well defined. In this study, we performed quantitative proteomic analysis using isobaric tags for relative and absolute quantitation (iTRAQ) and provided a comprehensive insight into the complicated regulation by citreoviridin in a lung cancer xenograft model. With high reproducibility of the quantitation, we obtained quantitative proteomic profiling with 2,659 proteins identified. Bioinformatics analysis of the 141 differentially expressed proteins selected by their relative abundance revealed that citreoviridin induces alterations in the expression of glucose metabolism-related enzymes in lung cancer. The up-regulation of enzymes involved in gluconeogenesis and storage of glucose indicated that citreoviridin may reduce the glycolytic intermediates for macromolecule synthesis and inhibit cell proliferation. Using comprehensive proteomics, the results identify metabolic aspects that help explain the antitumorigenic effect of citreoviridin in lung cancer, which may lead to a better understanding of the links between metabolism and tumorigenesis in cancer therapy.

Genome wide proteomics of ERBB2 and EGFR and other oncogenic pathways in inflammatory breast cancer

In this study we selected three breast cancer cell lines (SKBR3, SUM149 and SUM190) with different oncogene expression levels involved in ERBB2 and EGFR signaling pathways as a model system for the evaluation of selective integration of subsets of transcriptomic and proteomic data. We assessed the oncogene status with reads per kilobase per million mapped reads (RPKM) values for ERBB2 (14.4, 400, and 300 for SUM149, SUM190, and SKBR3, respectively) and for EGFR (60.1, not detected, and 1.4 for the same 3 cell lines). We then used RNA-Seq data to identify those oncogenes with significant transcript levels in these cell lines (total 31) and interrogated the corresponding proteomics data sets for proteins with significant interaction values with these oncogenes. The number of observed interactors for each oncogene showed a significant range, e.g., 4.2% (JAK1) to 27.3% (MYC). The percentage is measured as a fraction of the total protein interactions in a given data set vs total interactors for that oncogene in STRING (Search Tool for the Retrieval of Interacting Genes/Proteins, version 9.0) and I2D (Interologous Interaction Database, version 1.95). This approach allowed us to focus on 4 main oncogenes, ERBB2, EGFR, MYC, and GRB2, for pathway analysis. We used bioinformatics sites GeneGo, PathwayCommons and NCI receptor signaling networks to identify pathways that contained the four main oncogenes and had good coverage in the transcriptomic and proteomic data sets as well as a significant number of oncogene interactors. The four pathways identified were ERBB signaling, EGFR1 signaling, integrin outside-in signaling, and validated targets of C-MYC transcriptional activation. The greater dynamic range of the RNA-Seq values allowed the use of transcript ratios to correlate observed protein values with the relative levels of the ERBB2 and EGFR transcripts in each of the four pathways. This provided us with potential proteomic signatures for the SUM149 and 190 cell lines, growth factor receptor-bound protein 7 (GRB7), Crk-like protein (CRKL) and Catenin delta-1 (CTNND1) for ERBB signaling; caveolin 1 (CAV1), plectin (PLEC) for EGFR signaling; filamin A (FLNA) and actinin alpha1 (ACTN1) (associated with high levels of EGFR transcript) for integrin signalings; branched chain amino-acid transaminase 1 (BCAT1), carbamoyl-phosphate synthetase (CAD), nucleolin (NCL) (high levels of EGFR transcript); transferrin receptor (TFRC), metadherin (MTDH) (high levels of ERBB2 transcript) for MYC signaling; S100-A2 protein (S100A2), caveolin 1 (CAV1), Serpin B5 (SERPINB5), stratifin (SFN), PYD and CARD domain containing (PYCARD), and EPH receptor A2 (EPHA2) for PI3K signaling, p53 subpathway. Future studies of inflammatory breast cancer (IBC), from which the cell lines were derived, will be used to explore the significance of these observations.

Tumor-derived secretory clusterin induces epithelial-mesenchymal transition and facilitates hepatocellular carcinoma metastasis

Hepatocellular carcinoma (HCC) is the third most common cause of cancer mortality. Metastasis is the major concern that causes death in HCC. The goal of this study was to identify tumor-derived proteins in serum during HCC metastasis using an orthotopic xenograft tumor model and explore the role of key protein in HCC metastasis. Serum samples collected from HCCLM3-R metastatic HCC tumor model at specific stages of metastasis (1 wk, 3 wks and 6 wks) were subjected to iTRAQ labeling followed by 2DLC-ESI-MS/MS analysis. Twenty tumor-derived proteins were identified through human specific peptides. Secretory clusterin (sCLU), which was significantly upregulated during cancer progression and metastasis, was chosen for further study. The expression of sCLU was significantly higher in metastatic HCC cell lines and samples from metastatic HCC patients. ShRNA-mediated down-regulation of sCLU resulted in a reduced migratory capacity in HCC cell lines, as well as a reduction in pulmonary metastasis in vivo. Overexpression of sCLU in HepG2 cell line showed increased cell migratory ability. Further study found that sCLU contributed to HCC migration and epithelial-mesenchymal transition (EMT) in vitro, and metastasis in vivo. In addition, sCLU also plays an important role in the regulation of TGF-β1-smad3 signaling. These findings suggest that sCLU may promote HCC metastasis via the induction of EMT process and may be a candidate target for HCC therapy.

Sparc-like protein 1 is a new marker of human glioma progression

High-grade gliomas (glioblastomas) are the most common and deadly brain tumors in adults, currently with no satisfactory treatment available. Apart from de novo glioblastoma, it is currently accepted that these malignancies mainly progress from lower grade glial tumors. However, the molecular entities governing the progression of gliomas are poorly understood. Extracellular and membrane proteins are key biomolecules found at the cell-to-cell communication interface and hence are a promising proteome subpopulation that could help understand the development of glioma. Accordingly, the current study aims at identifying new protein markers of human glioma progression. For this purpose, we used glial tumors generated orthotopically with T98G and U373 human glioma cells in nude mice. This setup allowed also to discriminate the protein origin, namely, human (tumor) or mouse (host). Extracellular and membrane proteins were selectively purified using biotinylation followed by streptavidin affinity chromatography. Isolated proteins were digested and then identified and quantified employing 2D-nano-HPLC-MS/MS analysis. A total of 23 and 27 up-regulated extracellular and membrane proteins were identified in the T98G and U373 models, respectively. Approximately two-thirds of these were predominantly produced by the tumor, whereas the remaining proteins appeared to be mainly overexpressed by the host tissue. Following extensive validation, we have focused our attention on sparc-like protein 1. This protein was further investigated using immunohistochemistry in a large collection of human glioma samples of different grades. The results showed that sparc-like protein 1 expression correlates with glioma grade, suggesting the possible role for this protein in the progression of this malignancy.

Profiling of antibody production against xenograft-released proteins by protein microarrays discovers prostate cancer markers

This study describes a novel xenograft-based biomarker discovery platform and proves its usefulness in the discovery of serum markers for prostate cancer. By immunizing immuno-competent mice with serum from nude mice bearing prostate cancer xenografts, an antibody response against xenograft-derived antigens was elicited. By probing protein microarrays with serum from immunized mice, several prostate cancer-derived antigens were identified, of which a subset was successfully retrieved in serum from mice bearing prostate cancer xenografts and prevalidated in human serum samples of prostate cancer patients. Among the discovered and validated proteins were the members of the TAM receptor family (TYRO3, AXL, and MERTK), ACY1, and PSMA1. In conclusion, this novel method allows for the identification of low abundant cancer-derived serum proteins, circumventing dynamic range and host-response issues in standard patient cohort proteomics comparisons.

A xenograft mouse model coupled with in-depth plasma proteome analysis facilitates identification of novel serum biomarkers for human ovarian cancer

Proteomics discovery of novel cancer serum biomarkers is hindered by the great complexity of serum, patient-to-patient variability, and triggering by the tumor of an acute-phase inflammatory reaction. This host response alters many serum protein levels in cancer patients, but these changes have low specificity as they can be triggered by diverse causes. We addressed these hurdles by utilizing a xenograft mouse model coupled with an in-depth 4-D protein profiling method to identify human proteins in the mouse serum. This strategy ensures that identified putative biomarkers are shed by the tumor, and detection of low-abundance proteins shed by the tumor is enhanced because the mouse blood volume is more than a thousand times smaller than that of a human. Using TOV-112D ovarian tumors, more than 200 human proteins were identified in the mouse serum, including novel candidate biomarkers and proteins previously reported to be elevated in either ovarian tumors or the blood of ovarian cancer patients. Subsequent quantitation of selected putative biomarkers in human sera using label-free multiple reaction monitoring (MRM) mass spectrometry (MS) showed that chloride intracellular channel 1, the mature form of cathepsin D, and peroxiredoxin 6 were elevated significantly in sera from ovarian carcinoma patients.

Identification of transaldolase as a novel serum biomarker for hepatocellular carcinoma metastasis using xenografted mouse model and clinic samples

Hepatocellular carcinoma (HCC) is one of serious disorders with the highest morbidities and mortalities worldwide. Metastasis is the major concern that causes death in HCC. The goal of this study was to screen and identify potential serum proteins indicating HCC metastasis. Serum samples collected from control and HCCLM3-R metastatic HCC tumor model at specific stages of metastasis (1 wk, 3 wks and 6 wks) were subjected to iTRAQ labeling followed by 2DLC-ESI-MS/MS analysis. A total of 554 proteins were identified and 80 proteins were differential expressed at least between one adjacent time points. Among them, expression level of transaldolase (TALDO) was validated in mouse and human serum. The level of TALDO protein was found to be higher in metastatic mice serum compared to that of non-metastatic mice. Human specific TALDO was then identified in mouse serum through human specific peptides. Immunohistochemical and western blot analysis showed that the expression of TALDO in human HCC tissues and HCC cell lines was associated with its metastatic behavior. Subsequent screening of TALDO expression in 72 clinical serum samples (comprising 36 non-metastatic HCC and 36 metastatic HCC samples) revealed higher TALDO level in the serum of metastatic HCC patients. A receiver operating characteristic (ROC) curve estimated a maximal sensitivity of 77.8% and 86.1% specificity for TALDO in detection of HCC metastasis. The present results demonstrated that the nude mouse xenograft model is an efficient system for performing metastasis-related biomarker discovery. TALDO may be useful biomarkers for the detection of HCC metastasis.

Glycoproteomics-based identification of cancer biomarkers

Protein glycosylation is one of the most common posttranslational modifications in mammalian cells. It is involved in many biological pathways and molecular functions and is well suited for proteomics-based disease investigations. Aberrant protein glycosylation may be associated with disease processes. Specific glycoforms of glycoproteins may serve as potential biomarkers for the early detection of disease or as biomarkers for the evaluation of therapeutic efficacy for treatment of cancer, diabetes, and other diseases. Recent technological developments, including lectin affinity chromatography and mass spectrometry, have provided researchers the ability to obtain detailed information concerning protein glycosylation. These in-depth investigations, including profiling and quantifying glycoprotein expression, as well as comprehensive glycan structural analyses may provide important information leading to the development of disease-related biomarkers. This paper describes methodologies for the detection of cancer-related glycoprotein and glycan structural alterations and briefly summarizes several current cancer-related findings.

Differential profiling studies of N-linked glycoproteins in glioblastoma cancer stem cells upon treatment with γ-secretase inhibitor

We have recently demonstrated that Notch pathway blockade by γ-secretase inhibitor (GSI) depletes cancer stem cells (CSCs) in Glioblastoma Multiforme (GBM) through reduced proliferation and induced apoptosis. However, the detailed mechanism by which the manipulation of Notch signal induces alterations on post-translational modifications such as glycosylation has not been investigated. Herein, we present a differential profiling work to detect the change of glycosylation pattern upon drug treatment in GBM CSCs. Rapid screening of differential cell surface glycan structures has been performed by lectin microarray on live cells followed by the detection of N-linked glycoproteins from cell lysates using multi-lectin chromatography and label-free quantitative mass spectrometry analysis. A total of 51 and 52 glycoproteins were identified in the CSC- and GSI-treated groups, respectively, filtered by a combination of decoy database searching and Trans-Proteomic Pipeline (TPP) processing. Although no significant changes were detected from the lectin microarray experiment, 7 differentially expressed glycoproteins with high confidence were captured after the multi-lectin column including key enzymes involved in glycan processing. Functional annotations of the altered glycoproteins suggest a phenotype transformation of CSCs toward a less tumorigenic form upon GSI treatment.

Glycoproteomic analysis of embryonic stem cells: identification of potential glycobiomarkers using lectin affinity chromatography of glycopeptides

Numerous studies have recently focused on the identification of specific glycan biomarkers, given the important roles that protein linked glycans play, for example, during development and disease progression. The identification of protein glycobiomarkers, which are part of a very complex proteome, has involved the use of fractionation techniques such as lectin affinity chromatography. In this study, the glycoproteomic characterization of pluripotent murine embryonic stem cells (ES) and from ES cells that were differentiated into embroid bodies (EB) was performed using immobilized Concanavalin A (ConA). This procedure allowed the isolation of glycopeptides that express biantennary and hybrid N-linked structures (ConA2 fraction) as well as high mannose glycans (ConA3 fraction) that were abundant in both ES and EB stages. A total of 293 unique N-linked glycopeptide sequences (from 180 glycoproteins) were identified in the combined data sets from ES and EB cells. Of these glycopeptides, a total of 119 sequences were identified exclusively in only one of the lectin-bound fractions (24 in the ES-ConA2, 15 in the ES-ConA3, 16 in the EB-ConA2, and 64 in the EB-ConA3). Results from this study allowed the identification of individual N-glycosylation sites of proteins that express specific glycan types. The absence of some of these lectin-bound glycopeptides in a cell stage suggested that they were derived from proteins that were either expressed exclusively on a defined developmental stage or were expressed in both cell stages but carried the lectin-bound oligosaccharides in only one of them. Therefore, these lectin-bound glycopeptides can be considered as stage-specific glycobiomarkers.

CLUE-TIPS, clustering methods for pattern analysis of LC-MS data

Liquid Chromatography Mass Spectrometry (LC-MS) based proteomics is an important tool in detecting changes in peptide/protein abundances in samples potentially leading to the discovery of disease biomarker candidates. We present CLUE-TIPS (Clustering Using Euclidean distance in Tanimoto Inter-Point Space), an approach that compares complex proteomic samples for similarity/dissimilarity analysis. In CLUE-TIPS, an intersample distance feature map is generated from filtered, aligned and binarized raw LC-MS data by applying the Tanimoto distance metric to obtain normalized similarity scores between all sample pairs for each m/z value. We developed clustering and visualization methods for the intersample distance map to analyze various samples for differences at the sample level as well as the individual m/z level. An approach to query for specific m/z values that are associated with similarity/dissimilarity patterns in a set of samples was also briefly described. CLUE-TIPS can also be used as a tool in assessing the quality of LC-MS runs. The presented approach does not rely on tandem mass-spectrometry (MS/MS), isotopic labels or gels and also does not rely on feature extraction methods. CLUE-TIPS suite was applied to LC-MS data obtained from plasma samples collected at various time points and treatment conditions from immunosuppressed mice implanted with MCF-7 human breast cancer cells. The generated raw LC-MS data was used for pattern analysis and similarity/dissimilarity detection. CLUE-TIPS successfully detected the differences/similarities in samples at various time points taken during the progression of tumor, and also recognized differences/similarities in samples representing various treatment conditions.

Reevaluating cathepsin D as a biomarker for breast cancer: serum activity levels versus histopathology

Cathepsin D is a lysosomal hydrolase involved in intra- and extracellular proteolysis. This enzyme is aberrantly produced and processed in malignancy, and most notably is over-secreted into the tumor cell microenvironment. This hyper-secretion may lead to excessive degradation of the extracellular matrix, and contribute to tumor progression and metastases. These phenomena have been established in vitro, and there is evidence that Cathepsin D is similarly dysregulated in human breast cancer patients. Because breast cancer lacks an effective screening or surveillance biomarker, here we address the hypothesis that serum Cathepsin D activity may be useful to assess the presence or progression of breast cancer in females. While representative histologic sections from various disease-specific cohorts confirm previous findings that increased Cathepsin D production and secretion correlate with tumor progression, we report no difference in serum Cathepsin D activity between patients who are disease free, patients with pre-invasive or limited invasive disease, and patients with metastatic disease. Furthermore, in patients with known metastatic disease, there were no clinical variables associated with significantly different serum Cathepsin D activity. However, the immunohistochemical localization of Cathepsin D expression in histopathologic sections from breast cancer patients correlates with disease progression. Based on the serum results, and in contradistinction to Cathepsin D localization in breast cancer tissues, our findings support using Cathepsin D as a reliable histopathology biomarker for disease progression, but not for serum screening.

Proteomics-determined differences in the concanavalin-A-fractionated proteome of hippocampus and inferior parietal lobule in subjects with Alzheimer's disease and mild cognitive impairment: implications for progression of AD

Alzheimer's disease (AD) is the most common type of dementia, comprising 60-80% of all reported cases, and currently affects 5.2 million Americans. AD is characterized pathologically by the accumulation of senile plaques (SPs), neurofibrillary tangles (NFTs), and synapse loss. The early stages of memory loss associated with AD have been studied in a condition known as amnestic mild cognitive impairment (MCI), arguably the earliest form of AD. In spite of extensive research across a variety of disciplines, the cause of AD remains elusive. Proteomics techniques have helped to advance knowledge about AD by identifying irregularities in protein expression and post-translational modifications (PTMs) in AD brain. Glycosylation is a less studied PTM with regards to AD and MCI. This PTM is important to study because glycosylation is involved in proper protein folding, protein anchoring to cell membranes, and the delivery of proteins to organelles, and these processes are impaired in AD. Concanavalin-A (Con-A) binds to N-linked glycoproteins, but hydrophobic sites on nonglycoproteins are also known to bind Con-A. To our knowledge, the present study is the first to examine Con-A-associated brain proteins in MCI and AD with focus on the hippocampus and inferior parietal lobule (IPL) brain regions. Proteins found in AD hippocampus with altered levels are glutamate dehydrogenase (GDH), glial fibrillary acidic protein (GFAP), tropomyosin 3 (TPM3), Rab GDP-dissociation inhibitor XAP-4 (XAP4), and heat shock protein 90 (HSP90). Proteins found with altered levels in AD IPL are alpha-enolase, gamma-enolase, and XAP-4. MCI hippocampal proteins with altered levels are dihydropyrimidase-2 (DRP2), glucose-regulated protein 78 (GRP-78), protein phosphatase related protein Sds-22 (Sds22), and GFAP and the only protein found with altered levels in MCI IPL was beta-synuclein. These results are discussed with reference to biochemical and pathological alterations in and progression of AD.