Correlating p53 immunostaining patterns with somatic TP53 mutation and functional properties of mutant p53 in triple-negative breast cancer

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Abstract

Aims: Immunohistochemical (IHC) staining of p53 is a potential marker for TP53 mutations in various cancers. However, criteria for predicting TP53 mutations in triple-negative breast cancer (TNBC) using p53 IHC staining are not yet established. We aim to correlate p53 IHC expression patterns with TP53 mutation status in TNBC. Methods and Results: A total of 113 TNBC cases were analysed for p53 IHC staining pattern and somatic TP53 mutation using whole-exome sequencing. Functional properties of TP53 mutations were determined using the National Cancer Institute (NCI) TP53 database. P53 IHC patterns were categorized as nuclear overexpression (n = 58), null pattern (n = 40), wildtype (n = 15), cytoplasmic (n = 5), and subclonal (n = 5). The cutoff for predictive p53 nuclear overexpression was determined to be 80%, which strongly correlated with TP53 mutations. Notably, p53 overexpression had a positive predictive value (PPV) of 83% for missense or in-frame mutations, while the null pattern showed a PPV of 85% for detecting nonsense, frameshift, or splicing mutations. P53 overexpression was significantly linked to missense mutations within the DNA-binding domain (DBD) exhibiting gain-of-function (GOF) or dominant-negative effect (DNE). Cases exhibiting cytoplasmic expression correlated with nonsense or frameshift mutations in the DBD, nuclear localization signal (NLS), or splice sites. Cases with subclonal p53 staining patterns were associated with TP53 mutations. Conclusion: Our study proposes newly defined criteria for interpreting p53 immunostaining patterns in TNBC, potentially allowing for the prediction of TP53 mutation types and their functional implications.

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Kim, M., Lee, M., Lee, A., Choi, B. O., Park, W. C., Kim, S. H., … Kang, J. (2025). Correlating p53 immunostaining patterns with somatic TP53 mutation and functional properties of mutant p53 in triple-negative breast cancer. Histopathology, 87(2), 299–309. https://doi.org/10.1111/his.15453

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