Jintang He

CD90 is Identified as a Candidate Marker for Cancer Stem Cells in Primary High-Grade Gliomas Using Tissue Microarrays

Although CD90 has been identified as a marker for various kinds of stem cells including liver cancer stem cells (CSCs) that are responsible for tumorigenesis, the potential role of CD90 as a marker for CSCs in gliomas has not been characterized. To address the issue, we investigated the expression of CD90 in tissue microarrays containing 15 glioblastoma multiformes (GBMs), 19 WHO grade III astrocytomas, 13 WHO grade II astrocytomas, 3 WHO grade I astrocytomas and 8 normal brain tissues. Immunohistochemical analysis showed that CD90 was expressed at a medium to high level in all tested high-grade gliomas (grade III and GBM) whereas it was barely detectable in low-grade gliomas (grade I and grade II) and normal brains. Double immunofluorescence staining for CD90 and CD133 in GBM tissues revealed that CD133+ CSCs are a subpopulation of CD90+ cells in GBMs in vivo. Flow cytometry analysis of the expression of CD90 and CD133 in GBM-derived stem-like neurospheres further confirmed the conclusion in vitro. The expression levels of both CD90 and CD133 were reduced along with the loss of stem cells after differentiation. Furthermore, the limiting dilution assay demonstrated that the sphere formation ability was comparable between the CD90+/CD133+ and the CD90+/CD133− populations of GBM neurospheres, which is much higher than that of the CD90−/CD133− population. We also performed double staining for CD90 and a vascular endothelial cell marker CD31 in tissue microarrays which revealed that the CD90+ cells were clustered around the tumor vasculatures in high-grade glioma tissues. These findings suggest that CD90 is not only a potential prognostic marker for high-grade gliomas but also a marker for CSCs within gliomas, and it resides within endothelial niche and may also play a critical role in the generation of tumor vasculatures via differentiation into endothelial cells.

Identification and confirmation of differentially expressed fucosylated glycoproteins in the serum of ovarian cancer patients using a lectin array and LC-MS/MS

In order to discover potential glycoprotein biomarkers in ovarian cancer, we applied a lectin array and Exactag labeling based quantitative glycoproteomics approach. A lectin array strategy was used to detect overall lectin-specific glycosylation changes in serum proteins from patients with ovarian cancer and those with benign conditions. Lectins, which showed significant differential response for fucosylation, were used to extract glycoproteins that had been labeled using isobaric chemical tags. The glycoproteins were then identified and quantified by LC-MS/MS, and five glycoproteins were found to be differentially expressed in the serum of ovarian cancer patients compared to benign diseases. The differentially expressed glycoproteins were further confirmed by lectin-ELISA and ELISA assay. Corticosteroid-binding globulin (CBG), serum amyloid p component (SAP), complement factor B (CFAB), and histidine-rich glycoprotein (HRG) were identified as potential markers for differentiating ovarian cancer from benign diseases or healthy controls. A combination of CBG and HRG (AUC = 0.825) showed comparable performance to CA125 (AUC = 0.829) in differentiating early stage ovarian cancer from healthy controls. The combination of CBG, SAP, and CA125 showed improved performance for distinguishing stage III ovarian cancer from benign diseases compared to CA125 alone. The ability of CBG, SAP, HRG, and CFAB to differentiate the serum of ovarian cancer patients from that of controls was tested using an independent set of samples. Our findings suggest that glycoprotein modifications may be a means to identify novel diagnostic markers for detection of ovarian cancer.

Identification of cell surface glycoprotein markers for glioblastoma-derived stem-like cells using a lectin microarray and LC-MS/MS approach.

Despite progress in the treatment of glioblastoma, more than 95% of patients suffering from this disease still die within 2 years. Recent findings support the belief that cancer stem-like cells are responsible for tumor formation and ongoing growth. Here a method combining lectin microarray and LC-MS/MS was used to discover the cell surface glycoprotein markers of a glioblastoma-derived stem-like cell line. Lectin microarray analysis of cell surface glycans showed that two galactose-specific lectins Trichosanthes kirilowii agglutinin (TKA) and Peanut agglutinin (PNA) could distinguish the stem-like glioblastoma neurosphere culture from a traditional adherent glioblastoma cell line. Agarose-bound TKA and PNA were used to capture the glycoproteins from the two cell cultures, which were analyzed by LC-MS/MS. The glycoproteins were quantified by spectral counting, resulting in the identification of 12 and 11 potential glycoprotein markers from the TKA and PNA captured fractions respectively. Almost all of these proteins were membrane proteins. Differential expression was verified by Western blotting analysis of 6 interesting proteins, including the up-regulated Receptor-type tyrosine-protein phosphatase zeta, Tenascin-C, Chondroitin sulfate proteoglycan NG2, Podocalyxin-like protein 1 and CD90, and the down-regulated CD44. An improved understanding of these proteins may be important for earlier diagnosis and better therapeutic targeting of glioblastoma.

Identification and confirmation of biomarkers using an integrated platform for quantitative analysis of glycoproteins and their glycosylations.

Hepatocellular carcinoma (HCC) is the most common primary malignant tumor of the liver. However, accurate diagnosis can be difficult as most of the patients who develop this tumor have symptoms similar to those caused by longstanding liver disease. Herein we developed an integrated platform to discover the glycoprotein biomarkers in early HCC. At first, lectin arrays were applied to investigate the differences in glycan structures on serum glycoproteins from HCC and cirrhosis patients. The intensity for AAL and LCA was significantly higher in HCC, indicating an elevation of fucosylation level. Then serum from 10 HCC samples and 10 cirrhosis samples were used to screen the altered fucosylated proteins by a combination of Exactag labeling, lectin extraction and LC-MS/MS. Finally, 27 HCC and 27 cirrhosis serum samples were used for lectin-antibody arrays to confirm the change of these fucosylated proteins. C3, CE, HRG, CD14 and HGF were found to be biomarker candidates for distinguishing early HCC from cirrhosis, with a sensitivity of 72% and specificity of 79%. Our work gives insight to the detection of early HCC, and the application of this comprehensive strategy has the potential to facilitate biomarker discovery on a large scale.

Identification of Glycoprotein Markers for Pancreatic Cancer CD24+CD44+ Stem-like Cells Using Nano-LC–MS/MS and Tissue Microarray

Pancreatic adenocarcinoma is characterized by late diagnosis due to lack of early symptoms, extensive metastasis, and high resistance to chemo/radiation therapy. Recently, a subpopulation of cells within pancreatic cancers, termed cancer stem cells (CSCs), has been characterized and postulated to be the drivers for pancreatic cancer and responsible for metastatic spread. Further studies on pancreatic CSCs are therefore of particular importance to identify novel diagnosis markers and therapeutic targets for this dismal disease. Herein, the malignant phenotype of pancreatic cancer stem-like CD24+CD44+ cells was isolated from a human pancreatic carcinoma cell line (PANC-1) and demonstrated 4-fold increased invasion ability compared to CD24-CD44+ cells. Using lectin microarray and nano LC-MS/MS, we identified a differentially expressed set of glycoproteins between these two subpopulations. Lectin microarray analysis revealed that fucose- and galactose-specific lectins, UEA-1 and DBA, respectively, exhibit distinctly strong binding to CD24+CD44+ cells. The glycoproteins extracted by multilectin affinity chromatography were consequently analyzed by LC-MS/MS. Seventeen differentially expressed glycoproteins were identified, including up-regulated Cytokeratin 8/CK8, Integrin β1/CD29, ICAM1/CD54, and Ribophorin 2/RPN2 and down-regulated Aminopeptidase N/CD13. Immunohistochemical analysis of tissue microarrays showed that CD24 was significantly associated with late-stage pancreatic adenocarcinomas, and RPN2 was exclusively coexpressed with CD24 in a small population of CD24-positive cells. However, CD13 expression was dramatically decreased along with tumor progression, preferentially present on the apical membrane of ductal cells and vessels in early stage tumors. Our findings suggest that these glycoproteins may provide potential therapeutic targets and promising prognostic markers for pancreatic cancer.

Targeting glioblastoma stem cells: Cell surface markers

Glioblastoma multiforme (GBM) is the most common primary brain tumor and among the most lethal cancers. There is increasing evidence that cancer stem cells within GBMs, which are often referred to as glioblastoma stem cells (GSCs), play a critical role in tumor initiation and maintenance. Identification of novel markers for GSCs will lead to better targeting of GSCs which could have tremendous impact on treatment of GBMs. Cell surface markers are particularly suitable as therapeutic targets. Although several promising cell surface markers have successfully been used for enrichment of GSCs, their functional roles in maintenance of GSC properties as well as in GBM formation and development remain to be characterized. In this review, we primarily summarize recent advances in identification of GSC markers, with a particular focus on cell surface markers.

Glycoproteomic Analysis of Glioblastoma Stem Cell Differentiation

Cancer stem cells are responsible for tumor formation through self-renewal and differentiation into multiple cell types and thus represent a new therapeutic target for tumors. Glycoproteins play a critical role in determining the fates of stem cells such as self-renewal, proliferation, and differentiation. Here we applied a multilectin affinity chromatography and quantitative glycoproteomics approach to analyze alterations of glycoproteins relevant to the differentiation of a glioblastoma-derived stem cell line HSR-GBM1. Three lectins including concanavalin A (Con A), wheat germ agglutinin (WGA), and peanut agglutinin (PNA) were used to capture glycoproteins, followed by LC-MS/MS analysis. A total of 73 and 79 high-confidence (FDR < 0.01) glycoproteins were identified from the undifferentiated and differentiated cells, respectively. Label-free quantitation resulted in the discovery of 18 differentially expressed glycoproteins, wherein 9 proteins are localized in the lysosome. All of these lysosomal glycoproteins were up-regulated after differentiation, where their principal function was hydrolysis of glycosyl residues. Protein-protein interaction and functional analyses revealed the active involvement of lysosomes during the process of glioblastoma stem cell differentiation. This work provides glycoprotein markers to characterize differentiation status of glioblastoma stem cells that may be useful in stem-cell therapy of glioblastoma.

Serum autoantibody profiling using a natural glycoprotein microarray for the prognosis of early melanoma.

The poor prognosis of melanoma and the high cost of lymph node biopsy for melanoma patients have led to an urgent need for the discovery of convenient and accurate prognostic indicators. Here, we have developed a natural glycoprotein microarray to discover serum autoantibodies to distinguish between patients with node negative melanoma and node positive melanoma. Dual-lectin affinity chromatography was used to extract glycoproteins from a melanoma cell line. Liquid-based reverse phase separation and microarray platforms were then applied to separate and spot these natural proteins on nitrocellulose slides. The serum autoantibodies were investigated by exposing these proteins to sera from 43 patients that have already been diagnosed to have different stages of early melanoma. The combination of 9 fractions provides a 55% sensitivity with 100% specificity for the detection of node positive against node negative and a 62% sensitivity with 100% specificity for the detection of node negative against node positive. Recombinant proteins were used to confirm the results using a sample set with 79 patients with diagnosed melanoma. The response of sera against recombinant 94 kD glucose-regulated protein (GRP94), acid ceramidase (ASAH1), cathepsin D (CTSD), and lactate dehydrogenase B (LDHB) shared a similar pattern to the fractions where they were identified. The glycoarray platform provides a convenient and highly reproducible method to profile autoantibodies that could be used as serum biomarkers for prognosis of melanoma.

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.

Dose-dependent proteomic analysis of glioblastoma cancer stem cells upon treatment with γ-secretase inhibitor.

Notch signaling has been demonstrated to have a central role in glioblastoma (GBM) cancer stem cells (CSCs) and we have demonstrated recently that Notch pathway blockade by γ‐secretase inhibitor (GSI) depletes GBM CSCs and prevents tumor propagation both in vitro and in vivo. In order to understand the proteome alterations involved in this transformation, a dose‐dependent quantitative mass spectrometry (MS)‐based proteomic study has been performed based on the global proteome profiling and a target verification phase where both Immunoassay and a multiple reaction monitoring (MRM) assay are employed. The selection of putative protein candidates for confirmation poses a challenge due to the large number of identifications from the discovery phase. A multilevel filtering strategy together with literature mining is adopted to transmit the most confident candidates along the pipeline. Our results indicate that treating GBM CSCs with GSI induces a phenotype transformation towards non‐tumorigenic cells with decreased proliferation and increased differentiation, as well as elevated apoptosis. Suppressed glucose metabolism and attenuated NFR2‐mediated oxidative stress response are also suggested from our data, possibly due to their crosstalk with Notch Signaling. Overall, this quantitative proteomic‐based dose‐dependent work complements our current understanding of the altered signaling events occurring upon the treatment of GSI in GBM CSCs.