Abstract B05: Assessment of TP53 mutation status in primary high-grade serous ovarian cancer and cell line models: Comparison between immunohistochemistry and next-generation sequencing.
Authors: Cole Alexander J. , Dwight Trisha , Zhu Ying , Gill Anthony J. , Dickson Kristie-Ann , Clarkson Adele , Gard Gregory B. , Maidens Jayne , Valmadre Susan , Clifton-Bligh Roderick J. , Marsh Deborah J. 
Published: May 2016

Mutations in TP53 have been shown to occur in around 96% of high-grade serous ovarian cancer (HGSOC). Different TP53 mutations can lead to accumulation of mutant p53 in the cell that support gain of function effects, or loss or abrogation of both wild-type and mutant p53. Success of new therapeutic strategies for HGSOC that target mutant p53 will likely depend on detailed knowledge of the type of TP53 mutation present and its influence on mutant p53 levels in the cell. The aim of this study was to identify the spectrum of TP53 mutations in a cohort of primary HGSOCs and compare this with p53 immunostaining patterns. In addition, we sought to identify TP53 mutations in the previously uncharacterised HGSOC cell line models OV167 and OV202, as well as the clear cell adenocarcinoma line OV207.

DNA from fresh frozen tumors and cell line samples were processed for next generation sequencing using The Fluidigm Access TP53 Array System run on the Fluidigm Biomark HD™ Real-Time PCR fluidics system (Fluidigm Corporation). Amplicon libraries were pooled and analyses performed in a single massively parallel sequencing run using the MiSeq Sequencing System (Illumina Inc.). Unaligned BAM files were analyzed within the Broad Institute's Genome Analysis Toolkit (GATK) best practice pipeline. The ANNOVAR software tool was used to generate an annotated variants list. Variants were further filtered based on their frequency in the 1000 Genome Database and predicted SIFT scores. Mutations were visualized using the Broad Institute's Integrative Genomics Viewer. All samples in which a mutation was identified underwent Sanger sequencing using primers recommended in the International Agency for Research on Cancer TP53 database. Immunohistochemistry for p53 was performed on formalin fixed paraffin embedded tissue sections using a commercially available mouse monoclonal anti-human antibody (Protein Clone DO-7, cat. #M7001, Dako) on an automated staining platform (Leica BOND-III™ autostainer). The percentage of cells showing positive nuclear staining for p53 was reported.

A mutation in TP53 was identified in 94% (68 of 72) of HGSOC. The majority of mutations identified (62%, 42 of 68) were missense, with all except one of these mutations located in the p53 DNA binding domain. Overall, 82% (56 of 68) of mutations occurred within the DNA binding domain. Frameshift, stop or splice mutations (38%, 26 of 68) were identified in exons or flanking intronic sequence between exons 4 – 10. The presence or location of a TP53 mutation did not influence overall survival. Sanger sequencing was unable to reliably detect variants at an allele frequency less than 25%. TP53 mutations were identified in all cell lines at a mutant allele frequency ≥99%.

Based on percent of nuclei positive for p53, tumors were immunohistochemically graded as High, Intermediate or Low for p53. All missense mutations scored High for expression of the p53 protein. Considerable variability was observed in p53 staining levels in samples containing stop, frameshift or splice mutations, with samples in all of High, Intermediate and Low categories. Furthermore, a single sample shown to be wild-type for TP53 was graded as High for p53, raising the possibility that p53 had been activated in this tumor via an alternative mechanism. The level of p53 did not affect overall survival.

Taken together, these results suggest that caution needs to be exercised when using p53 immunohistochemistry as a surrogate marker for either presence or type of TP53 mutation. A combination of next generation sequencing and p53 immunohistochemistry is required to robustly define both mutation type and effect on mutant p53 levels in the cell.

Citation Format: Alexander J. Cole, Trisha Dwight, Ying Zhu, Anthony J. Gill, Kristie-Ann Dickson, Adele Clarkson, Gregory B. Gard, Jayne Maidens, Susan Valmadre, Roderick J. Clifton-Bligh, Deborah J. Marsh. Assessment of TP53 mutation status in primary high-grade serous ovarian cancer and cell line models: Comparison between immunohistochemistry and next-generation sequencing. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; Oct 17-20, 2015; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(2 Suppl):Abstract nr B05.