title: Optimized p53 immunohistochemistry is an accurate predictor ofTP53mutation in ovarian carcinoma.
abstract: TP53mutations are ubiquitous in high-grade serous ovarian carcinomas (HGSOC), and the presence ofTP53mutation discriminates between high and low-grade serous carcinomas and is now an important biomarker for clinical trials targeting mutant p53. p53 immunohistochemistry (IHC) is widely used as a surrogate forTP53mutation but its accuracy has not been established. The objective of this study was to test whether improved methods for p53 IHC could reliably predictTP53mutations independently identified by next generation sequencing (NGS). Four clinical p53 IHC assays and tagged-amplicon NGS forTP53were performed on 171 HGSOC and 80 endometrioid carcinomas (EC). p53 expression was scored as overexpression (OE), complete absence (CA), cytoplasmic (CY) or wild type (WT). p53 IHC was evaluated as a binary classifier where any abnormal staining predicted deleteriousTP53mutation and as a ternary classifier where OE, CA or WT staining predicted gain-of-function (GOF or nonsynonymous), loss-of-function (LOF including stopgain, indel, splicing) or no detectableTP53mutations (NDM), respectively. DeleteriousTP53mutations were detected in 169/171 (99%) HGSOC and 7/80 (8.8%) EC. The overall accuracy for the best performing IHC assay for binary and ternary prediction was 0.94 and 0.91 respectively, which improved to 0.97 (sensitivity 0.96, specificity 1.00) and 0.95 after secondary analysis of discordant cases. The sensitivity for predicting LOF mutations was lower at 0.76 because p53 IHC detected mutant p53 protein in 13 HGSOC with LOF mutations. CY staining associated with LOF was seen in 4 (2.3%) of HGSOC. Optimized p53 IHC can approach 100% specificity for the presence ofTP53mutation and its high negative predictive value is clinically useful as it can exclude the possibility of a low-grade serous tumour. 4.1% of HGSOC cases have detectable WT staining while harboring aTP53LOF mutation, which limits sensitivity for binary prediction of mutation to 96%.
authors.affiliation: Department of Pathology and Laboratory Medicine University of Calgary Calgary AB Canada.
authors.forename: Martin
authors.initials: M
authors.lastname: Köbel
authors.affiliation: Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre Cambridge CB2 0RE UK.
authors.forename: Anna M
authors.initials: AM
authors.lastname: Piskorz
authors.affiliation: Department of Pathology and Laboratory Medicine University of Calgary Calgary AB Canada.
authors.forename: Sandra
authors.initials: S
authors.lastname: Lee
authors.affiliation: Department of Pathology and Laboratory Medicine University of Calgary Calgary AB Canada.
authors.forename: Shuhong
authors.initials: S
authors.lastname: Lui
authors.affiliation: Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM)MontrealQCCanada; Institut du cancer de Montréal, MontrealQCCanada.
authors.forename: Cecile
authors.initials: C
authors.lastname: LePage
authors.affiliation: Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre Cambridge CB2 0RE UK.
authors.forename: Francesco
authors.initials: F
authors.lastname: Marass
authors.affiliation: Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre Cambridge CB2 0RE UK.
authors.forename: Nitzan
authors.initials: N
authors.lastname: Rosenfeld
authors.affiliation: Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM)MontrealQCCanada; Institut du cancer de Montréal, MontrealQCCanada.
authors.forename: Anne-Marie
authors.initials: AM
authors.lastname: Mes Masson
authors.affiliation: Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre Cambridge CB2 0RE UK.
authors.forename: James D
authors.initials: JD
authors.lastname: Brenton
keywords: TP53; biomarker; endometrioid ovarian carcinoma; high grade serous ovarian carcinoma; immunohistochemistry; next‐generation‐sequencing; p53; prediction