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

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. We extracted proteins of tumor and normal brain tissues and then evaluated the protein purity by Bradford test and spectrophotometery method. In this study, we separated proteins by two-dimensional (2DG) gel electrophoresis method and the spots were then analyzed and compared using statistical data and specific software. Proteins clustering analyses were performed on the list of proteins deemed significantly altered in glioblastoma tumors (t-test and one-way ANOVA; P < 0.05). The 2D gel showed totally 876 spots. We reported, 172 spots exhibited different 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 decreased in glioblastoma tumor relative to normal tissue. Results demonstrate that functional clustering (up and down regulated) and principal component analysis has considerable merits in aiding the interpretation of proteomic data. At the core of proteomics was 2D gel electrophoresis witch permitted the separation of thousands of protein, High resolution 2DE can resolve up to 5,000 proteins simultaneously. Using cluster analysis, we can also from groups of related variables, similar to what you do in factor analysis.