Comprehensive glycomic and proteomic analysis of mouse striatum and lateral hypothalamus following repeated exposures to cocaine or methamphetamine.

Substance use disorder is a major concern, with few therapeutic options. Heparan sulfate (HS) and chondroitin sulfate (CS) interact with a plethora of growth factors and their receptors and have profound effects on cellular signaling. Thus, targeting these dynamic interactions might represent a potential novel therapeutic modality. In the present study, we performed mass spectrometry-based glycomic and proteomic analysis to understand the effects of cocaine and methamphetamine (METH) on HS, CS, and the proteome of two brain regions critically involved in drug addiction: the lateral hypothalamus (LH) and the striatum (ST). We observed that cocaine and METH significantly alter HS and CS abundances as well as sulfate contents and composition. In particular, repeated METH or cocaine treatments reduced CS 4-O-sulfation and increased CS 6-O-sulfation. Since C4S and C6S exercise differential effects on axon growth, regeneration and plasticity, these changes likely contribute to drug-induced neural plasticity in these brain regions. Notably, we observed that restoring these alterations by increasing CS 4-0 levels in the LH by adeno-associated virus (AAV) delivery of an shRNA to Arylsulfatase B (N-acetylgalactosamine-4-sulfatase, ARSB) ameliorated anxiety and prevented the expression of preference for cocaine in a novelty induced conditioned place preference test during cocaine withdrawal. Finally, proteomics analyses revealed a number of aberrant proteins in METH- and cocaine-treated vs. saline-treated mice, including MYPR, KCC2A, SYN2, TENR, CALX, ANXA7, HDGF, NCAN, and CSPG5, and oxidative phosphorylation among the top perturbed pathway. Taken together, these data support the role of HS, CS, and associated proteins in stimulants abuse and suggest that manipulation of HSPGs can represent a novel therapeutic strategy.

In-Depth Matrisome and Glycoproteomic Analysis of Human Brain Glioblastoma Versus Control Tissue.

Glioblastoma (GBM) is the most common and malignant primary brain tumor. The extracellular matrix, also known as the matrisome, helps determine glioma invasion, adhesion, and growth. Little attention, however, has been paid to glycosylation of the extracellular matrix components that constitute the majority of glycosylated protein mass and presumed biological properties. To acquire a comprehensive understanding of the biological functions of the matrisome and its components, including proteoglycans (PGs) and glycosaminoglycans (GAGs), in GBM tumorigenesis, and to identify potential biomarker candidates, we studied the alterations of GAGs, including heparan sulfate (HS) and chondroitin sulfate (CS), the core proteins of PGs, and other glycosylated matrisomal proteins in GBM subtypes versus control human brain tissue samples. We scrutinized the proteomics data to acquire in-depth site-specific glycoproteomic profiles of the GBM subtypes that will assist in identifying specific glycosylation changes in GBM. We observed an increase in CS 6-O sulfation and a decrease in HS 6-O sulfation, accompanied by an increase in unsulfated CS and HS disaccharides in GBM versus control samples. Several core matrisome proteins, including PGs (decorin, biglycan, agrin, prolargin, glypican-1, and chondroitin sulfate proteoglycan 4), tenascin, fibronectin, hyaluronan link protein 1 and 2, laminins, and collagens, were differentially regulated in GBM versus controls. Interestingly, a higher degree of collagen hydroxyprolination was also observed for GBM versus controls. Further, two PGs, chondroitin sulfate proteoglycan 4 and agrin, were significantly lower, about 6-fold for isocitrate dehydrogenase-mutant, compared to the WT GBM samples. Differential regulation of O-glycopeptides for PGs, including brevican, neurocan, and versican, was observed for GBM subtypes versus controls. Moreover, an increase in levels of glycosyltransferase and glycosidase enzymes was observed for GBM when compared to control samples. We also report distinct protein, peptide, and glycopeptide features for GBM subtypes comparisons. Taken together, our study informs understanding of the alterations to key matrisomal molecules that occur during GBM development. (Data are available via ProteomeXchange with identifier PXD028931, and the peaks project file is available at Zenodo with DOI 10.5281/zenodo.5911810).

Protein Paucimannosylation Is an Enriched N-Glycosylation Signature of Human Cancers.

While aberrant protein glycosylation is a recognized characteristic of human cancers, advances in glycoanalytics continue to discover new associations between glycoproteins and tumorigenesis. This glycomics-centric study investigates a possible link between protein paucimannosylation, an under-studied class of human N-glycosylation [Man1-3 GlcNAc2 Fuc0-1 ], and cancer. The paucimannosidic glycans (PMGs) of 34 cancer cell lines and 133 tissue samples spanning 11 cancer types and matching non-cancerous specimens are profiled from 467 published and unpublished PGC-LC-MS/MS N-glycome datasets collected over a decade. PMGs, particularly Man2-3 GlcNAc2 Fuc1 , are prominent features of 29 cancer cell lines, but the PMG level varies dramatically across and within the cancer types (1.0-50.2%). Analyses of paired (tumor/non-tumor) and stage-stratified tissues demonstrate that PMGs are significantly enriched in tumor tissues from several cancer types including liver cancer (p = 0.0033) and colorectal cancer (p = 0.0017) and is elevated as a result of prostate cancer and chronic lymphocytic leukaemia progression (p < 0.05). Surface expression of paucimannosidic epitopes is demonstrated on human glioblastoma cells using immunofluorescence while biosynthetic involvement of N-acetyl-ß-hexosaminidase is indicated by quantitative proteomics. This intriguing association between protein paucimannosylation and human cancers warrants further exploration to detail the biosynthesis, cellular location(s), protein carriers, and functions of paucimannosylation in tumorigenesis and metastasis.

Integrated Proteomic and Transcriptomic-Based Approaches to Identifying Signature Biomarkers and Pathways for Elucidation of Daoy and UW228 Subtypes.

Medulloblastoma (MB) is the most common malignant pediatric brain tumor. Patient survival has remained largely the same for the past 20 years, with therapies causing significant health, cognitive, behavioral and developmental complications for those who survive the tumor. In this study, we profiled the total transcriptome and proteome of two established MB cell lines, Daoy and UW228, using high-throughput RNA sequencing (RNA-Seq) and label-free nano-LC-MS/MS-based quantitative proteomics, coupled with advanced pathway analysis. While Daoy has been suggested to belong to the sonic hedgehog (SHH) subtype, the exact UW228 subtype is not yet clearly established. Thus, a goal of this study was to identify protein markers and pathways that would help elucidate their subtype classification. A number of differentially expressed genes and proteins, including a number of adhesion, cytoskeletal and signaling molecules, were observed between the two cell lines. While several cancer-associated genes/proteins exhibited similar expression across the two cell lines, upregulation of a number of signature proteins and enrichment of key components of SHH and WNT signaling pathways were uniquely observed in Daoy and UW228, respectively. The novel information on differentially expressed genes/proteins and enriched pathways provide insights into the biology of MB, which could help elucidate their subtype classification.

Identifying N-Glycan Biomarkers in Colorectal Cancer by Mass Spectrometry.

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide. Delineating biological markers (biomarkers) for early detection, when treatment is most effective, is key to prevention and long-term survival of patients. Development of reliable biomarkers requires an increased understanding of the CRC biology and the underlying molecular and cellular mechanisms of the disease. With recent advances in new technologies and approaches, tremendous efforts have been put in proteomics and genomics fields to deliver detailed analysis of the two major biomolecules, genes and proteins, to gain a more complete understanding of cellular systems at both genomic and proteomic levels, allowing a mechanistic understanding of the human diseases, including cancer, and opening avenues for identification of novel gene and protein based prognostic and therapeutic markers. Although the importance of glycosylation in modulating protein function has long been appreciated, glycan analysis has been complicated by the diversity of the glycan structures and the large number of potential glycosylation combinations. Driven by recent technological advances, LC-MS/MS based glycomics is gaining momentum in cancer research and holds considerable potential to deliver new glycan-based markers. In our laboratory, we investigated alterations in N-glycosylation associated with CRC malignancy in a panel of CRC cell lines and CRC patient tissues. In an initial study, LC-MS/MS-based N-glycomics were utilized to map the N-glycome landscape associated with a panel of CRC cell lines (LIM1215, LIM1899, and LIM2405). These studies were subsequently extended to paired tumor and nontumorigenic CRC tissues to validate the findings in the cell line. Our studies in both CRC cell lines and tissues identified a strong representation of high mannose and α2,6-linked sialylated complex N-glycans, which corroborate findings from previous studies in CRC and other cancers. In addition, certain unique glycan determinants such as bisecting ß1,4-GlcNAcylation and α2,3-sialylation, identified in the metastatic (LIM1215) and aggressive (LIM2405) CRC cell lines, respectively, were shown to be associated with epidermal growth factor receptor (EGFR) expression status. In this Account, we will describe the mass spectrometry based N-glycomics approach utilized in our laboratory to accurately profile the cell- and tissue-specific N-glycomes associated with CRC. We will highlight altered N-glycosylation observed by our studies, consistent with findings from other cancer studies, and discuss how the observed alterations can provide insights into CRC pathogenesis, opening new avenues to identify novel disease-associated glycan markers.

Mass Spectrometry-Based N-Glycomics of Colorectal Cancer.

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide. An increased molecular understanding of the CRC pathology is warranted to gain insights into the underlying molecular and cellular mechanisms of the disease. Altered protein glycosylation patterns are associated with most diseases including malignant transformation. Recent advances in mass spectrometry and bioinformatics have accelerated glycomics research and present a new paradigm for cancer biomarker discovery. Mass spectrometry (MS)-based glycoproteomics and glycomics, therefore, hold considerable promise to improve the discovery of novel biomarkers with utility in disease diagnosis and therapy. This review focuses on the emerging field of glycomics to present a comprehensive review of advances in technologies and their application in studies aimed at discovering novel glycan-based biomarkers. We will also discuss some of the challenges associated with using glycans as biomarkers.

Integrated Proteomic and Genomic Analysis of Gastric Cancer Patient Tissues.

V-erb-b2 erythroblastic leukemia viral oncogene homologue 2, known as ERBB2, is an important oncogene in the development of certain cancers. It can form a heterodimer with other epidermal growth factor receptor family members and activate kinase-mediated downstream signaling pathways. ERBB2 gene is located on chromosome 17 and is amplified in a subset of cancers, such as breast, gastric, and colon cancer. Of particular interest to the Chromosome-Centric Human Proteome Project (C-HPP) initiative is the amplification mechanism that typically results in overexpression of a set of genes adjacent to ERBB2, which provides evidence of a linkage between gene location and expression. In this report we studied patient samples from ERBB2-positive together with adjacent control nontumor tissues. In addition, non-ERBB2-expressing patient samples were selected as comparison to study the effect of expression of this oncogene. We detected 196 proteins in ERBB2-positive patient tumor samples that had minimal overlap (29 proteins) with the non-ERBB2 tumor samples. Interaction and pathway analysis identified extracellular signal regulated kinase (ERK) cascade and actin polymerization and actinmyosin assembly contraction as pathways of importance in ERBB2+ and ERBB2- gastric cancer samples, respectively. The raw data files are deposited at ProteomeXchange (identifier: PXD002674) as well as GPMDB.

Using Single Lectins to Enrich Glycoproteins in Conditioned Media.

Lectins are sugar-binding proteins that can recognize and bind to carbohydrates conjugated to proteins and lipids. Coupled with mass spectrometry technologies, lectin affinity chromatography is becoming a popular approach for identification and quantification of glycoproteins in complex samples such as blood, tumor tissues, and cell lines. Given the commercial availability of a large number of lectins that recognize diverse sugar structures, it is now possible to isolate and study glycoproteins for biological and medical research. This unit provides a general guide to single-lectin-based enrichment of glycoproteins from serum-free conditioned media. Due to the unique carbohydrate specificity of most lectins and the complexity of the samples, optimization steps may be required to evaluate different elution buffers and methods as well as binding conditions, for each lectin, for optimal recovery of bound glycoproteins.

In-depth N-glycome profiling of paired colorectal cancer and non-tumorigenic tissues reveals cancer-, stage- and EGFR-specific protein N-glycosylation.

Glycomics may assist in uncovering the structure-function relationships of protein glycosylation and identify glycoprotein markers in colorectal cancer (CRC) research. Herein, we performed label-free quantitative glycomics on a carbon-liquid chromatography-tandem mass spectrometry-based analytical platform to accurately profile the N-glycosylation changes associated with CRC malignancy. N-Glycome profiling was performed on isolated membrane proteomes of paired tumorigenic and adjacent non-tumorigenic colon tissues from a cohort of five males (62.6 ± 13.1 y.o.) suffering from colorectal adenocarcinoma. The CRC tissues were typed according to their epidermal growth factor receptor (EGFR) status by western blotting and immunohistochemistry. Detailed N-glycan characterization and relative quantitation identified an extensive structural heterogeneity with a total of 91 N-glycans. CRC-specific N-glycosylation phenotypes were observed including an overrepresentation of high mannose, hybrid and paucimannosidic type N-glycans and an under-representation of complex N-glycans (P < 0.05). Sialylation, in particular α2,6-sialylation, was significantly higher in CRC tumors relative to non-tumorigenic tissues, whereas α2,3-sialylation was down-regulated (P < 0.05). CRC stage-specific N-glycosylation was detected by high α2,3-sialylation and low bisecting ß1,4-GlcNAcylation and Lewis-type fucosylation in mid-late relative to early stage CRC. Interestingly, a novel link between the EGFR status and the N-glycosylation was identified using hierarchical clustering of the N-glycome profiles. EGFR-specific N-glycan signatures included high bisecting ß1,4-GlcNAcylation and low α2,3-sialylation (both P < 0.05) relative to EGFR-negative CRC tissues. This is the first study to correlate CRC stage and EGFR status with specific N-glycan features, thus advancing our understanding of the mechanisms causing the biomolecular deregulation associated with CRC.

Quantitative proteomic analysis of paired colorectal cancer and non-tumorigenic tissues reveals signature proteins and perturbed pathways involved in CRC progression and metastasis.

Modern proteomics has proven instrumental in our understanding of the molecular deregulations associated with the development and progression of cancer. Herein, we profile membrane-enriched proteome of tumor and adjacent normal tissues from eight CRC patients using label-free nanoLC-MS/MS-based quantitative proteomics and advanced pathway analysis. Of the 948 identified proteins, 184 proteins were differentially expressed (P<0.05, fold change>1.5) between the tumor and non-tumor tissue (69 up-regulated and 115 down-regulated in tumor tissues). The CRC tumor and non-tumor tissues clustered tightly in separate groups using hierarchical cluster analysis of the differentially expressed proteins, indicating a strong CRC-association of this proteome subset. Specifically, cancer associated proteins such as FN1, TNC, DEFA1, ITGB2, MLEC, CDH17, EZR and pathways including actin cytoskeleton and RhoGDI signaling were deregulated. Stage-specific proteome signatures were identified including up-regulated ribosomal proteins and down-regulated annexin proteins in early stage CRC. Finally, EGFR(+) CRC tissues showed an EGFR-dependent down-regulation of cell adhesion molecules, relative to EGFR(-) tissues. Taken together, this study provides a detailed map of the altered proteome and associated protein pathways in CRC, which enhances our mechanistic understanding of CRC biology and opens avenues for a knowledge-driven search for candidate CRC protein markers.

Comparative N-glycan profiling of colorectal cancer cell lines reveals unique bisecting GlcNAc and α-2,3-linked sialic acid determinants are associated with membrane proteins of the more metastatic/aggressive cell lines.

Advances in colorectal cancer (CRC) diagnosis will be enhanced by development of more sensitive and reliable methods for early detection of the disease when treatment is more effective. Because many known disease biomarkers are membrane-bound glycoproteins with important biological functions, we chose to compare N-glycan profiles of membrane proteins from three phenotypically different CRC cell lines, LIM1215, LIM1899, and LIM2405, representing moderately differentiated metastatic, moderately differentiated primary, and poorly differentiated (aggressive) primary CRC cell lines, respectively. The N-glycan structures and their relative abundances were determined as their underivatized reduced forms, using porous graphitized carbon LC-ESI-MS/MS. A key observation was the similar N-glycan landscape in these cells with the dominance of high mannose type glycan structures (70-90%) in all three cell lines, suggesting an incomplete glycan processing. Importantly, unique glycan determinants such as bisecting N-acetylglucosamine were observed at a high level in the metastatic LIM1215 cells, with some expressed in the moderately differentiated LIM1899, while none were detected in the poorly differentiated LIM2405 cells. Conversely, α-2,3-sialylation was completely absent in LIM1215 and LIM1899 and present only in LIM2405. RNA-Seq and lectin immunofluorescence data correlated well with these data, showing the highest upregulation of Mgat3 and binding with PHA-E in LIM1215. Downregulation of Man1α1 and Mgat1 in LIM1215 also coincided with the higher degree of incomplete N-glycan processing and accumulation of high mannose type structures as well as bisecting N-glycans when compared to the other two cell lines. This study provides a comprehensive analysis of the membrane N-glycome in three CRC cell lines and identifies N-glycosylation differences that correlate with the histological and pathological features of the cell lines. The unique glycosylation phenotypes may therefore serve as a molecular feature to differentiate CRC disease stages.

Chromosome 7-centric analysis of proteomics data from a panel of human colon carcinoma cell lines.

In this manuscript, we describe a shotgun proteomics approach for a comprehensive proteomic analysis of samples including total lysates, membrane, secretome, and exosome fractions from a panel of colorectal cancer cell lines. We will present an analysis of our proteomics data in two alternative formats. First we will discuss a traditional analysis of our data, in which we identify a number of cancer-associated proteins using various proteomic data analysis tools. In a second approach, we use a chromosome format to organize the proteomic data on chromosome 7, allowing the identification of clusters of cancer-associated genes with boundaries defined by physical proximity on different chromosomes.