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Dive into the research topics where Yashu Liu is active.

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Featured researches published by Yashu Liu.


Clinical Cancer Research | 2011

Urinary Glycoprotein Biomarker Discovery for Bladder Cancer Detection Using LC/MS-MS and Label-Free Quantification

Na Yang; Shun Feng; Kerby Shedden; Xiaolei Xie; Yashu Liu; Charles J. Rosser; David M. Lubman; Steven Goodison

Background: Cancers of the urinary bladder are the fifth most commonly diagnosed malignancy in the United States. Early clinical diagnosis of bladder cancer remains a major challenge, and the development of noninvasive methods for detection and surveillance is desirable for both patients and health care providers. Approach: To identify urinary proteins with potential clinical utility, we enriched and profiled the glycoprotein component of urine samples by using a dual-lectin affinity chromatography and liquid chromatography/tandem mass spectrometry platform. Results: From a primary sample set obtained from 54 cancer patients and 46 controls, a total of 265 distinct glycoproteins were identified with high confidence, and changes in glycoprotein abundance between groups were quantified by a label-free spectral counting method. Validation of candidate biomarker alpha-1-antitrypsin (A1AT) for disease association was done on an independent set of 70 samples (35 cancer cases) by using an ELISA. Increased levels of urinary A1AT glycoprotein were indicative of the presence of bladder cancer (P < 0.0001) and augmented voided urine cytology results. A1AT detection classified bladder cancer patients with a sensitivity of 74% and specificity of 80%. Summary: The described strategy can enable higher resolution profiling of the proteome in biological fluids by reducing complexity. Application of glycoprotein enrichment provided novel candidates for further investigation as biomarkers for the noninvasive detection of bladder cancer. Clin Cancer Res; 17(10); 3349–59. ©2011 AACR.


Molecular & Cellular Proteomics | 2012

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

Jintang He; Yashu Liu; Thant S. Zhu; Jianhui Zhu; Francesco DiMeco; Angelo L. Vescovi; Jason A. Heth; Karin M. Muraszko; Xing Fan; David M. Lubman

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.


Journal of Proteome Research | 2012

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

Jing Wu; Xiaolei Xie; Yashu Liu; Jintang He; Ricardo Benitez; Ronald J. Buckanovich; David M. Lubman

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.


Journal of Proteome Research | 2010

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

Jintang He; Yashu Liu; Xiaolei Xie; Thant S. Zhu; Mary E. Soules; Francesco DiMeco; Angelo L. Vescovi; Xing Fan; David M. Lubman

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.


Journal of Proteome Research | 2010

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

Yashu Liu; Jintang He; Chen Li; Ricardo Benitez; Sherry Fu; Jorge A. Marrero; David M. Lubman

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.


Journal of Proteome Research | 2012

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

Jianhui Zhu; Jintang He; Yashu Liu; Diane M. Simeone; David M. Lubman

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.


Journal of Proteome Research | 2011

Glycoproteomic Analysis of Glioblastoma Stem Cell Differentiation

Jintang He; Yashu Liu; Thant S. Zhu; Xiaolei Xie; Mark A. Costello; Caroline E. Talsma; Callie G. Flack; Jessica G. Crowley; Francesco DiMeco; Angelo L. Vescovi; Xing Fan; David M. Lubman

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.


International Journal of Proteomics | 2011

Proteomics in Melanoma Biomarker Discovery: Great Potential, Many Obstacles

Michael S. Sabel; Yashu Liu; David M. Lubman

The present clinical staging of melanoma stratifies patients into heterogeneous groups, resulting in the application of aggressive therapies to large populations, diluting impact and increasing toxicity. To move to a new era of therapeutic decisions based on highly specific tumor profiling, the discovery and validation of new prognostic and predictive biomarkers in melanoma is critical. Genomic profiling, which is showing promise in other solid tumors, requires fresh tissue from a large number of primary tumors, and thus faces a unique challenge in melanoma. For this and other reasons, proteomics appears to be an ideal choice for the discovery of new melanoma biomarkers. Several approaches to proteomics have been utilized in the search for clinically relevant biomarkers, but to date the results have been relatively limited. This article will review the present work using both tissue and serum proteomics in the search for melanoma biomarkers, highlighting both the relative advantages and disadvantages of each approach. In addition, we review several of the major obstacles that need to be overcome in order to advance the field.


Journal of Proteome Research | 2010

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

Yashu Liu; Jintang He; Xaiolei Xie; Gang Su; Seagal Teitz-Tennenbaum; Michael S. Sabel; David M. Lubman

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.


Electrophoresis | 2010

A comparative phosphoproteomic analysis of a human tumor metastasis model using a label-free quantitative approach

Xiaolei Xie; Shun Feng; Huy Vuong; Yashu Liu; Steve Goodison; David M. Lubman

Alterations in cellular phosphorylation patterns have been implicated in a number of diseases, including cancer, through multiple mechanisms. Herein we present a survey of the phosphorylation profiles of an isogenic pair of human cancer cell lines with opposite metastatic phenotype. Phosphopeptides were enriched from tumor cell lysates with titanium dioxide and zirconium dioxide, and identified with nano‐LC‐MS/MS using an automatic cross‐validation of MS/MS and MS/MS/MS (MS2+MS3) data‐dependent neutral loss method. A spectral counting quantitative strategy was applied to the two cell line samples on the MS2‐only scan, which was implemented successively after each MS2+MS3 scan in the same sample. For all regulated phosphopeptides reported by spectral counting analysis, sequence and phosphorylation site assignments were validated by a MS2+MS3 data‐dependent neutral loss method. With this approach, we identified over 70 phosphorylated sites on 27 phosphoproteins as being differentially expressed with respect to tumor cell phenotype. The altered expression levels of proteins identified by LC‐MS/MS were validated using Western blotting. Using network pathway analysis, we observed that the majority of the differentially expressed proteins were highly interconnected and belong to two major intracellular signaling pathways. Our findings suggest that the phosphorylation of isoform A of lamin A/C and GTPase activating protein binding protein 1 is associated with metastatic propensity. The study demonstrates a quantitative and comparative proteomics strategy to identify differential phosphorylation patterns in complex biological samples.

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Jintang He

University of Michigan

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Xiaolei Xie

University of Michigan

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Xing Fan

University of Michigan

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Jianhui Zhu

University of Michigan

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Angelo L. Vescovi

Casa Sollievo della Sofferenza

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