title: Quantitative analysis of p53 expression in human normal and cancer tissue microarray with global normalization method.
abstract: Tissue microarray based immunohistochemical staining and proteomics are important tools to create and validate clinically relevant cancer biomarkers. Immunohistochemical stains using formalin-fixed tissue microarray sections for protein expression are scored manually and semi-quantitatively. Digital image analysis methods remove some of the drawbacks of manual scoring but may need other methods such as normalization to provide across the board utility. In the present study, quantitative proteomics-based global normalization method was used to evaluate its utility in the analysis of p53 protein expression in mixed human normal and cancer tissue microarray. Global normalization used the mean or median of β-actin to calculate ratios of individual core stain intensities, then log transformed the ratios, calculate a mean or median and subtracted the value from the log of ratios. In the absence of global normalization of p53 protein expression, 44% (42 of 95) of tissue cores were positive using the median of intensity values and 40% (38 of 95) using the mean of intensities as cut-off points. With global normalization, p53 positive cores changed to 20% (19 of 95) when using median of intensities and 15.8%(15 of 95) when the mean of intensities were used. In conclusion, the global normalization method helped to define positive p53 staining in the tissue microarray set used. The method used helped to define clear cut-off points and confirmed all negatively stained tissue cores. Such normalization methods should help to better define clinically useful biomarkers.
authors: Department of Pathology and Laboratory Medicine, University of Alberta Edmonton, ALBERTA T6G 2B7, Canada. hidikio@ualberta.ca
authors: Halliday A
authors: HA
authors: Idikio
mesh_terms: D000199:Actins / Q000032:analysis* / Q000378:metabolism; D000818:Animals; D000911:Antibodies, Monoclonal; D014408:Biomarkers, Tumor / Q000032:analysis* / Q000378:metabolism; D003627:Data Interpretation, Statistical; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007150:Immunohistochemistry; D009369:Neoplasms / Q000378:metabolism / Q000473:pathology*; D040901:Proteomics; D011817:Rabbits; D012680:Sensitivity and Specificity; D046888:Tissue Array Analysis / Q000379:methods*; D016159:Tumor Suppressor Protein p53 / Q000032:analysis* / Q000378:metabolism
chemical_list: D000199:Actins; D000911:Antibodies, Monoclonal; D014408:Biomarkers, Tumor; D016159:Tumor Suppressor Protein p53