Cluster and Principal Component Analysis of Human Glioblastoma Multiforme (GBM) Tumor Proteome

authors:

avatar Mehdi Pooladi 1 , * , avatar Mostafa Rezaei-Tavirani 2 , avatar Mehrdad Hashemi 3 , avatar Saeed Hesami-Tackallou 4 , avatar Solmaz Khaghani-Razi-Abad 1 , avatar Afshin Moradi 5 , avatar Ali Reza Zali 6 , avatar Masoumeh Mousavi 2 , avatar Leila Firozi Dalvand 7 , avatar Azadeh Rakhshan 5 , avatar Mona Zamanian Azodi 2

Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Dept. of Biology, School of Basic Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran
Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Dept. Of Molecular Genetics, Tehran Medical Branch, Islamic Azad University Tehran, Iran
Dept. of Biology, Garmsar Branch, Islamic Azad University, Garmsar, Iran
Dept. Of Pathology, Shohada Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Dept. of Neurosurgery, Shohada Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Dept. of Biology, School of Basic Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran
International Journal of Cancer Management: Vol.7, issue 2; e80525
published online: June 30, 2014
article type: Research Article
received: January 27, 2014
accepted: April 26, 2014

how to cite: Pooladi M , Rezaei-Tavirani M, Hashemi M, Hesami-Tackallou S, Khaghani-Razi-Abad S, et al. Cluster and Principal Component Analysis of Human Glioblastoma Multiforme (GBM) Tumor Proteome. Int J Cancer Manag. 2014;7(2):e80525. 

Abstract

Background: Glioblastoma Multiforme (GBM) or grade IV astrocytoma is the most common and lethal adult malignant brain tumor. Several of the molecular alterations detected in gliomas may have diagnostic and/or prognostic implications. Proteomics has been widely applied in various areas of science, ranging from the deciphering of molecular pathogen nests of discuses.
Methods: In this study proteins were extracted from the tumor and normal brain tissues and then the protein purity was evaluated by Bradford test and spectrophotometry. In this study, proteins were separated by 2-Dimensional Gel (2DG) electrophoresis method and the spots were then analyzed and compared using statistical data and specific software. Protein clustering analysis was performed on the list of proteins deemed significantly altered in glioblastoma tumors (t-test and one-way ANOVA; P< 0.05).
Results: The 2D gel showed totally 876 spots. We reported, 172 spots were exhibited differently in expression level (fold > 2) for glioblastoma. On each analytical 2D gel, an average of 876 spots was observed. In this study, 188 spots exhibited up regulation of expression level, whereas the remaining 232 spots were decreased in glioblastoma tumor relative to normal tissue. Results demonstrate that functional clustering (up and down regulated) and Principal Component Analysis (PCA) has considerable merits in aiding the interpretation of proteomic data.
Conclusion: 2D gel electrophoresis is the core of proteomics which permitted the separation of thousands of proteins. High resolution 2DE can resolve up to 5,000 proteins simultaneously. Using cluster analysis, we can also form groups of related variables, similar to what is practiced in factor analysis.

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