Supplemental Digital Content is available in the text. TP53 gene mutations are known to manifest in distinct p53 immunohistochemical staining patterns; overexpression, wild-type, and null. These stratified staining patterns are… Click to show full abstract
Supplemental Digital Content is available in the text. TP53 gene mutations are known to manifest in distinct p53 immunohistochemical staining patterns; overexpression, wild-type, and null. These stratified staining patterns are routinely utilized in subtyping ovarian cancer subtypes. Three ovarian cancer cell lines were used in the construction of an immunohistochemical p53 expression pattern control panel that highlight respective TP53 mutation status. The cell line control panel sections demonstrated consistent clean and easily interpretable p53 immunohistochemical staining. Procured resection, biopsy, and cytologic specimens were submitted along with either standard control tissue or a p53 cell line control panel to pathologists of varying experience for interrater reliability analysis. Individual interrater reliability was near-perfect and was improved with the p53 cell line control panel when compared with the tissue control. The cell line control panel demonstrated decreased misinterpretation of null expression pattern as wild-type. Next-generation sequencing analysis was performed on the cell lines and select cases, in which there was discordance in p53 expression pattern interpretation. Next-generation sequencing analysis demonstrated low-frequency variant mutations in some cases in which there was reviewer discordance. This study suggests the addition of a p53 cell line expression pattern control panel could potentially increase p53 interpretation accuracy for ovarian cancer subtypes. We developed a cell line–based p53 control panel that has the potential to increase individual interrater reliability for p53 immunohistochemical expression pattern determination, support immunohistochemical optimization, and direct submission of difficult to interpret p53 staining cases to next-generation sequencing.
               
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