Dataset Information

Development of glycoprotein capture-based label-free method for the high-throughput screening of differential glycoproteins in hepatocellular carcinoma.

ABSTRACT: A robust, reproducible, and high throughput method was developed for the relative quantitative analysis of glycoprotein abundances in human serum. Instead of quantifying glycoproteins by glycopeptides in conventional quantitative glycoproteomics, glycoproteins were quantified by nonglycosylated peptides derived from the glycoprotein digest, which consists of the capture of glycoproteins in serum samples and the release of nonglycopeptides by trypsin digestion of captured glycoproteins followed by two-dimensional liquid chromatography-tandem MS analysis of released peptides. Protein quantification was achieved by comparing the spectrum counts of identified nonglycosylated peptides of glycoproteins between different samples. This method was demonstrated to have almost the same specificity and sensitivity in glycoproteins quantification as capture at glycopeptides level. The differential abundance of proteins present at as low as nanogram per milliliter levels was quantified with high confidence. The established method was applied to the analysis of human serum samples from healthy people and patients with hepatocellular carcinoma (HCC) to screen differential glycoproteins in HCC. Thirty eight glycoproteins were found with substantial concentration changes between normal and HCC serum samples, including ?-fetoprotein, the only clinically used marker for HCC diagnosis. The abundance changes of three glycoproteins, i.e. galectin-3 binding protein, insulin-like growth factor binding protein 3, and thrombospondin 1, which were associated with the development of HCC, were further confirmed by enzyme-linked immunosorbent assay. In conclusion, the developed method was an effective approach to quantitatively analyze glycoproteins in human serum and could be further applied in the biomarker discovery for HCC and other cancers.

SUBMITTER: Chen R

PROVIDER: S-EPMC3134069 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

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Development of glycoprotein capture-based label-free method for the high-throughput screening of differential glycoproteins in hepatocellular carcinoma.

Chen Rui R Tan Yexiong Y Wang Min M Wang Fangjun F Yao Zhenzhen Z Dong Liwei L Ye Mingliang M Wang Hongyang H Zou Hanfa H

Molecular & cellular proteomics : MCP 20110407 7

A robust, reproducible, and high throughput method was developed for the relative quantitative analysis of glycoprotein abundances in human serum. Instead of quantifying glycoproteins by glycopeptides in conventional quantitative glycoproteomics, glycoproteins were quantified by nonglycosylated peptides derived from the glycoprotein digest, which consists of the capture of glycoproteins in serum samples and the release of nonglycopeptides by trypsin digestion of captured glycoproteins followed b ...[more]

PMID: 21474793

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Project description:Cancer cells metastasize through the bloodstream either as single migratory circulating tumor cells (CTCs) or as multicellular groupings (CTC-clusters). Existing technologies for CTC enrichment are designed primarily to isolate single CTCs, and while CTC-clusters are detectable in some cases, their true prevalence and significance remain to be determined. Here, we developed a microchip technology (Cluster-Chip) specifically designed to capture CTC-clusters independent of tumor-specific markers from unprocessed blood. CTC-clusters are isolated through specialized bifurcating traps under low shear-stress conditions that preserve their integrity and even two-cell clusters are captured efficiently. Highly parallel architecture of the chip allows deterministic screening of clinically relevant volumes of blood samples at slow, and hence, non-damaging flow rates. Using the Cluster-Chip, we identify CTC-clusters in 30-40% of patients with metastatic cancers of the breast, prostate and melanoma. RNA sequencing of CTC-clusters confirms their tumor origin and identifies leukocytes within the clusters as being tissue-derived macrophages. Together, the development of a device for efficient capture of CTC-clusters will enable detailed characterization of their biological properties and role in cancer metastasis. We used the Cluster-Chip to capture CTC-clusters from the blood of a breast cancer patient with high CTC counts, released CTC-clusters in solution, stained them with TexasRed-conjugated antibodies against the leukocyte cell surface markers CD45, CD14 and CD16, and then isolated intact CTC-clusters individually using a micromanipulator. From a single time point, we retrieved 15 CTC-clusters, and each of those clusters was individually subjected to RNA-sequencing analysis using a next generation platform (SOLiD 5500). In addition, two leukocytes were isolated from the blood of a healthy donor were individually subjected to RNA-sequencing analysis using the same platform.

Dataset Information

Development of glycoprotein capture-based label-free method for the high-throughput screening of differential glycoproteins in hepatocellular carcinoma.

Publications

Development of glycoprotein capture-based label-free method for the high-throughput screening of differential glycoproteins in hepatocellular carcinoma.

Similar Datasets

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