title: Patterns of p73 N-terminal isoform expression and p53 status have prognostic value in gynecological cancers.
abstract: The goal of this study was to determine whether patterns of expression profiles of p73 isoforms and of p53 mutational status are useful combinatorial biomarkers for predicting outcome in a gynecological cancer cohort. This is the first such study using matched tumor/normal tissue pairs from each patient. The median follow-up was over two years. The expression of all 5 N-terminal isoforms (TAp73, DeltaNp73, DeltaN'p73, Ex2p73 and Ex2/3p73) was measured by real-time RT-PCR and p53 status was analyzed by immunohistochemistry. TAp73, DeltaNp73 and DeltaN'p73 were significantly upregulated in tumors. Surprisingly, their range of overexpression was age-dependent, with the highest differences delta (tumor-normal) in the youngest age group. Correction of this age effect was important in further survival correlations. We used all 6 variables (five p73 isoform levels plus p53 status) as input into a principal component analysis with Varimax rotation (VrPCA) to filter out noise from non-disease related individual variability of p73 levels. Rationally selected and individually weighted principal components from each patient were then used to train a support vector machine (SVM) algorithm to predict clinical outcome. This SVM algorithm was able to predict correct outcome in 30 of the 35 patients. We use here a mathematical tool for pattern recognition that has been commonly used in e.g. microarray data mining and apply it for the first time in a prognostic model. We find that PCA/SVM is able to test a clinical hypothesis with robust statistics and show that p73 expression profiles and p53 status are useful prognostic biomarkers that differentiate patients with good vs. poor prognosis with gynecological cancers.
authors.affiliation: Department of Pathology, State University of New York at Stony Brook, Stony Brook, NY, USA.
authors.forename: Kerstin
authors.initials: K
authors.lastname: Becker
authors.forename: Petr
authors.initials: P
authors.lastname: Pancoska
authors.forename: Nicole
authors.initials: N
authors.lastname: Concin
authors.forename: Kelly
authors.initials: K
authors.lastname: Vanden Heuvel
authors.forename: Neda
authors.initials: N
authors.lastname: Slade
authors.forename: Margaret
authors.initials: M
authors.lastname: Fischer
authors.forename: Eva
authors.initials: E
authors.lastname: Chalas
authors.forename: Ute M
authors.initials: UM
authors.lastname: Moll
mesh_terms: D000367:Age Factors; D004268:DNA-Binding Proteins / Q000235:genetics / Q000378:metabolism*; D016889:Endometrial Neoplasms / Q000175:diagnosis* / Q000378:metabolism / Q000473:pathology; D005260:Female; D006801:Humans; D047908:Intracellular Signaling Peptides and Proteins; D009687:Nuclear Proteins / Q000235:genetics / Q000378:metabolism*; D010051:Ovarian Neoplasms / Q000175:diagnosis* / Q000378:metabolism / Q000473:pathology; D011379:Prognosis; D020033:Protein Isoforms / Q000032:analysis / Q000235:genetics / Q000378:metabolism; D011506:Proteins / Q000032:analysis / Q000378:metabolism; D012333:RNA, Messenger / Q000032:analysis / Q000378:metabolism; D000072160:Tumor Protein p73; D016159:Tumor Suppressor Protein p53 / Q000032:analysis*; D025521:Tumor Suppressor Proteins / Q000235:genetics / Q000378:metabolism*; D015854:Up-Regulation
chemical_list: D004268:DNA-Binding Proteins; D047908:Intracellular Signaling Peptides and Proteins; C549756:NBR1 protein, human; D009687:Nuclear Proteins; D020033:Protein Isoforms; D011506:Proteins; D012333:RNA, Messenger; C000606460:TP73 protein, human; D000072160:Tumor Protein p73; D016159:Tumor Suppressor Protein p53; D025521:Tumor Suppressor Proteins; C000606369:delta Np73 protein, human