Analysis of p53 protein expression levels on ovarian cancer tissue microarray using automated quantitative analysis elucidates prognostic patient subsets.
BACKGROUND
p53 protein is regarded as a valuable prognostic marker in cancer with a potential use as a molecular target. Here, we sought to determine the prognostic value of p53 in ovarian cancer using a novel method of compartmentalized in situ protein analysis.


METHODS
A tissue array composed of 141 advanced stage ovarian cancers uniformly treated was constructed. For evaluation of p53 protein expression, we used an immunofluorescence-based method of automated in situ quantitative measurement of protein analysis (AQUA).


RESULTS
High nuclear p53 expression levels were associated with better outcome for overall survival (OS) (P = 0.0023) and disease-free survival (P = 0.0338) at 5-years. High cytoplasmic p53 expression levels were associated with better outcome for OS (P = 0.0002). In multivariable analysis, high nuclear and high cytoplasmic p53 level with International Federation of Gynecology and Obstetrics (FIGO) stage were the most significant predictor variables for OS and high nuclear p53 level with FIGO stage were the significant predictor variables for disease-free survival.


CONCLUSIONS
Assessment of the prognostic value of p53 protein levels using conventional immunohistochemistry is limited by the nonquantitative nature of the method. AQUA provides precise estimation of p53 protein levels and was able to elucidate the association of p53 protein levels and ovarian cancer prognosis.
Psyrri
A
A
Department of Medical Oncology, Yale Cancer Center, New Haven, CT 06520, USA. diamando.psyrri@ yale.edu
Kountourakis
P
P
Yu
Z
Z
Papadimitriou
C
C
Markakis
S
S
Camp
R L
RL
Economopoulos
T
T
Dimopoulos
M A
MA
D000328:Adult; D000368:Aged; D005260:Female; D016158:Genes, p53; D006801:Humans; D008875:Middle Aged; D009154:Mutation; D010051:Ovarian Neoplasms / Q000737:chemistry* / Q000401:mortality / Q000473:pathology; D011379:Prognosis; D046888:Tissue Array Analysis / Q000379:methods*; D016159:Tumor Suppressor Protein p53 / Q000032:analysis*
D016159:Tumor Suppressor Protein p53