Dataset Information

Plasma glycoprotein profiling for colorectal cancer biomarker identification by lectin glycoarray and lectin blot.

ABSTRACT: Colorectal cancer (CRC) remains a major worldwide cause of cancer-related morbidity and mortality largely due to the insidious onset of the disease. The current clinical procedures utilized for disease diagnosis are invasive, unpleasant, and inconvenient; hence, the need for simple blood tests that could be used for the early detection of CRC. In this work, we have developed methods for glycoproteomics analysis to identify plasma markers with utility to assist in the detection of colorectal cancer (CRC). Following immunodepletion of the most abundant plasma proteins, the plasma N -linked glycoproteins were enriched using lectin affinity chromatography and subsequently further separated by nonporous silica reversed-phase (NPS-RP)-HPLC. Individual RP-HPLC fractions were printed on nitrocellulose coated slides which were then probed with lectins to determine glycan patterns in plasma samples from 9 normal, 5 adenoma, and 6 colorectal cancer patients. Statistical tools, including principal component analysis, hierarchical clustering, and Z-statistics analysis, were employed to identify distinctive glycosylation patterns. Patients diagnosed with colorectal cancer or adenomas were shown to have dramatically higher levels of sialylation and fucosylation as compared to normal controls. Plasma glycoproteins with aberrant glycosylation were identified by nano-LC-MS/MS, while a lectin blotting methodology was used to validate proteins with significantly altered glycosylation as a function of cancer progression. The potential markers identified in this study for diagnosis to distinguish colorectal cancer from adenoma and normal include elevated sialylation and fucosylation in complement C3, histidine-rich glycoprotein, and kininogen-1. These potential markers of colorectal cancer were subsequently validated by lectin blotting in an independent set of plasma samples obtained from 10 CRC patients, 10 patients with adenomas, and 10 normal subjects. These results demonstrate the utility of this strategy for the identification of N -linked glycan patterns as potential markers of CRC in human plasma, and may have the utility to distinguish different disease states.

SUBMITTER: Qiu Y

PROVIDER: S-EPMC2751808 | biostudies-literature | 2008 Apr

REPOSITORIES: biostudies-literature

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Plasma glycoprotein profiling for colorectal cancer biomarker identification by lectin glycoarray and lectin blot.

Qiu Yinghua Y Patwa Tasneem H TH Xu Li L Shedden Kerby K Misek David E DE Tuck Missy M Jin Gracie G Ruffin Mack T MT Turgeon Danielle K DK Synal Sapna S Bresalier Robert R Marcon Norman N Brenner Dean E DE Lubman David M DM

Journal of proteome research 20080227 4

Colorectal cancer (CRC) remains a major worldwide cause of cancer-related morbidity and mortality largely due to the insidious onset of the disease. The current clinical procedures utilized for disease diagnosis are invasive, unpleasant, and inconvenient; hence, the need for simple blood tests that could be used for the early detection of CRC. In this work, we have developed methods for glycoproteomics analysis to identify plasma markers with utility to assist in the detection of colorectal canc ...[more]

PMID: 18311904

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Project description:BackgroundEpigenetic alternation is a common contributing factor to neoplastic transformation. Although previous studies have reported a cluster of aberrant promoter methylation changes associated with silencing of tumor suppressor genes, little is known concerning their sequential DNA methylation changes during the carcinogenetic process. The aim of the present study was to address a genome-wide search for identifying potentially important methylated changes and investigate the onset and pattern of methylation changes during the progression of colorectal neoplasia.MethodsA three-phase design was employed in this study. In the screening phase, DNA methylation profile of 12 pairs of colorectal cancer (CRC) and adjacent normal tissues was analyzed by using the Illumina MethylationEPIC BeadChip. Significant CpG sites were selected based on a cross-validation analysis from The Cancer Genome Atlas (TCGA) database. Methylation levels of candidate CpGs were assessed using pyrosequencing in the training dataset (tumor lesions and adjacent normal tissues from 46 CRCs) and the validation dataset (tumor lesions and paired normal tissues from 13 hyperplastic polyps, 129 adenomas, and 256 CRCs). A linear mixed-effects model was used to examine the incremental changes of DNA methylation during the progression of colorectal neoplasia.ResultsThe comparisons between normal and tumor samples in the screening phase revealed an extensive CRC-specific methylomic pattern with 174,006 (21%) methylated CpG sites, of which 22,232 (13%) were hyermethylated and 151,774 (87%) were hypomethylated. Hypermethylation mostly occurred in CpG islands with an overlap of gene promoters, while hypomethylation tended to be mapped far away from functional regions. Further cross validation analysis from TCGA dataset confirmed 265 hypermethylated promoters coupling with downregulated gene expression. Among which, hypermethylated changes in MEEPD2 promoter was successfully replicated in both training and validation phase. Significant hypermethylation appeared since precursor lesions with an extensive modification in CRCs. The linear mixed-effects modeling analysis found that a cumulative pattern of MPPED2 methylation changes from normal mucosa to hyperplastic polyp to adenoma, and to carcinoma (P < 0.001).ConclusionsOur findings indicate that epigenetic alterations of MPPED2 promoter region appear sequentially during the colorectal neoplastic progression. It might be able to serve as a promising biomarker for early diagnosis and stage surveillance of colorectal tumorigenesis.

Dataset Information

Plasma glycoprotein profiling for colorectal cancer biomarker identification by lectin glycoarray and lectin blot.

Publications

Plasma glycoprotein profiling for colorectal cancer biomarker identification by lectin glycoarray and lectin blot.

Similar Datasets

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