scholarly journals Mass spectrometry imaging for identification of differentially expressed proteins between colorectal adenocarcinoma and colon adenoma

2013 ◽  
Vol 21 (34) ◽  
pp. 3806
Author(s):  
Tao He ◽  
Yun Guo ◽  
Xuan He ◽  
Xiao Hu ◽  
Ting-Ting Yu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Mass Spectrometry Imaging ◽  
Colorectal Adenocarcinoma ◽  
Differentially Expressed ◽  
Differentially Expressed Proteins ◽  
Colon Adenoma

scholarly journals Discovery and Verification of Gelsolin as a Potential Biomarker of Colorectal Adenocarcinoma in a Chinese Population: Examining Differential Protein Expression using an Itraq Labelling-Based Proteomics Approach

2012 ◽  
Vol 26 (1) ◽  
pp. 41-47 ◽  
Author(s):  
Nai-Jun Fan ◽  
Chun-Fang Gao ◽  
Chang-Song Wang ◽  
Jing-Jing Lv ◽  
Guang Zhao ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Liquid Chromatography ◽  
Protein Identification ◽  
Colorectal Adenocarcinoma ◽  
Biomarker Discovery ◽  
Differentially Expressed ◽  
Screening Tests ◽  
Differentially Expressed Proteins ◽  
Potential Biomarker ◽  
Wide Range

Despite the wide range of available colorectal cancer (CRC) screening tests, less than 50% of cases are detected at early stages. However, the identification of differentially expressed proteins or novel protein biomarkers in CRC may have some utility and, ultimately, improve patient care and survival. Proteomics combined with mass spectroscopy and liquid chromatography are emerging as powerful tools that have led to the discovery of potential markers in cancer biomarker discovery in several types of cancers. This article describes a novel technology that uses isotopic reagents to tag selected proteins that show a consistent pattern of differential expression in CRC.OBJECTIVE: To identify and validate potential biomarkers of colorectal adenocarcinoma using a proteomic approach.METHODS: Multidimensional liquid chromatography/mass spectrometry was used to analyze biological samples labelled with isobaric mass tags for relative and absolute quantitation to identify differentially expressed proteins in human colorectal adenocarcinoma and paired normal mucosa for the discovery of cancerous biomarkers. Cancerous and noncancerous samples were compared using online and offline separation. Protein identification was performed using mass spectrometry. The downregulation of gelsolin protein in colorectal adenocarcinoma samples was confirmed by Western blot analysis and validated using immunohistochemistry.RESULTS: A total of 802 nonredundant proteins were identified in colorectal adenocarcinoma samples, 82 of which fell outside the expression range of 0.8 to 1.2, and were considered to be potential cancer-specific proteins. Immunohistochemistry revealed a complete absence of gelsolin expression in 86.89% of samples and a reduction of expression in 13.11% of samples, yielding a sensitivity of 86.89% and a specificity of 100% for distinguishing colorectal adenocarcinoma from normal tissue.CONCLUSIONS: These findings suggest that decreased expression of gelsolin is a potential biomarker of colorectal adenocarcinoma.

Identification of differentially expressed proteins in retinoblastoma tumors using mass spectrometry-based comparative proteomic approach

2017 ◽  
Vol 159 ◽  
pp. 77-91 ◽  
Author(s):  
Jasmine Naru ◽  
Ritu Aggarwal ◽  
Ashok Kumar Mohanty ◽  
Usha Singh ◽  
Deepak Bansal ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Differentially Expressed ◽  
Differentially Expressed Proteins ◽  
Proteomic Approach

scholarly journals Bayesian identification of protein differential expression in multi-group isobaric labelled mass spectrometry data

2014 ◽  
Vol 13 (5) ◽  
Author(s):  
Howsun Jow ◽  
Richard J. Boys ◽  
Darren J. Wilkinson
Keyword(s):  
Mass Spectrometry ◽  
Simulated Data ◽  
Differentially Expressed ◽  
Mass Spectrometry Data ◽  
Control Group ◽  
Differentially Expressed Proteins ◽  
Statistical Methodology ◽  
Proteomic Data ◽  
Bayesian Identification ◽  
Multiple Groups

AbstractIn this paper we develop a Bayesian statistical inference approach to the unified analysis of isobaric labelled MS/MS proteomic data across multiple experiments. An explicit probabilistic model of the log-intensity of the isobaric labels’ reporter ions across multiple pre-defined groups and experiments is developed. This is then used to develop a full Bayesian statistical methodology for the identification of differentially expressed proteins, with respect to a control group, across multiple groups and experiments. This methodology is implemented and then evaluated on simulated data and on two model experimental datasets (for which the differentially expressed proteins are known) that use a TMT labelling protocol.

Identification of Differentially Expressed Proteins in Triple-Negative Breast Carcinomas Using DIGE and Mass Spectrometry

2009 ◽  
Vol 8 (7) ◽  
pp. 3430-3438 ◽  
Author(s):  
Daniela M. Schulz ◽  
Claudia Böllner ◽  
Gerry Thomas ◽  
Mike Atkinson ◽  
Irene Esposito ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Triple Negative ◽  
Differentially Expressed ◽  
Differentially Expressed Proteins ◽  
Breast Carcinomas

scholarly journals Differential Proteomics Based on TMT and PRM Reveal the Resistance Response of Bambusa pervariabilis × Dendrocalamopisis grandis Induced by AP-Toxin

Metabolites ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 166 ◽  
Author(s):  
Qianqian He ◽  
Xinmei Fang ◽  
Tianhui Zhu ◽  
Shan Han ◽  
Hanmingyue Zhu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Liquid Chromatography ◽  
Metabolic Pathways ◽  
Differentially Expressed ◽  
Tandem Mass ◽  
Differentially Expressed Proteins ◽  
Liquid Chromatography Mass Spectrometry ◽  
Chromatography Mass Spectrometry ◽  
Tandem Mass Tag ◽  
Mass Tag

Bambusa pervariabilis McClure × Dendrocalamopsis grandis (Q.H.Dai & X.l.Tao ex Keng f.) Ohrnb. blight is a widespread and dangerous forest fungus disease, and has been listed as a supplementary object of forest phytosanitary measures. In order to study the control of B. pervariabilis × D. grandis blight, this experiment was carried out. In this work, a toxin purified from the pathogen Arthrinium phaeospermum (Corda) Elli, which causes blight in B. pervariabilis × D. grandis, with homologous heterogeneity, was used as an inducer to increase resistance to B. pervariabilis × D. grandis. A functional analysis of the differentially expressed proteins after induction using a tandem mass tag labeling technique was combined with mass spectrometry and liquid chromatography mass spectrometry in order to effectively screen for the proteins related to the resistance of B. pervariabilis × D. grandis to blight. After peptide labeling, a total of 3320 unique peptides and 1791 quantitative proteins were obtained by liquid chromatography mass spectrometry analysis. Annotation and enrichment analysis of these peptides and proteins using the Gene ontology and Kyoto Encyclopedia of Genes and Genomes databases with bioinformatics software show that the differentially expressed protein functional annotation items are mainly concentrated on biological processes and cell components. Several pathways that are prominent in the Kyoto Encyclopedia of Genes and Genomes annotation and enrichment include metabolic pathways, the citrate cycle, and phenylpropanoid biosynthesis. In the Protein-protein interaction networks four differentially expressed proteins-sucrose synthase, adenosine triphosphate-citrate synthase beta chain protein 1, peroxidase, and phenylalanine ammonia-lyase significantly interact with multiple proteins and significantly enrich metabolic pathways. To verify the results of tandem mass tag, the candidate proteins were further verified by parallel reaction monitoring, and the results were consistent with the tandem mass tag data analysis results. It is confirmed that the data obtained by tandem mass tag technology are reliable. Therefore, the differentially expressed proteins and signaling pathways discovered here is the primary concern for subsequent disease resistance studies.

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