­­Differences in somatic TP53 Mutation Type in Breast Tumors by Race and Receptor Status

Abstract Background: Somatic driver mutations in TP53 are associated with triple negative breast cancer (TNBC) and poorer outcomes. Breast cancers arising in women of African ancestry (AA) are more likely to be TNBC and have somatic TP53 mutations than non-Hispanic White (NHW) women. Missense driver mutations in TP53 are known to have different functional effects including loss-of function (LOF) or gain-of-function (GOF) activity. A subset of variants exhibit dominant negative (DNE) activity over wildtype TP53 or other TP53 family members. Methods: To determine if there were differences in TP53 mutation type by race or TNBC status we identified published and unpublished datasets with somatic mutation data, race, age, and hormone receptor status. Mutations were classified as LOF, GOF or CpG Island hotspot by published literature or type of mutation (e.g. frameshift and nonsense mutations were considered to be LOF). We used Fisher’s Exact test to assess for significant differences. Results: We identified 96 independent breast cancer studies with race and somatic TP53 mutation status available. The study comprised data from a total of 2964 women with somatic TP53 mutations: 715 (24.1%) Asian, 258 (8.7%) AA, 1931 (65.2%) NHW, and 60 (2%) Latina. Of the total TP53 mutations, 939 (31.7%) were GOF, 1739 (58.7%) were LOF, and the remaining 286 (9.6%) were not able to be classified. With respect to DNE activity, 1246 (42%) showed activity, 1190 (40.1%) showed no activity, and 528 (17.8%) were unknown status. The distribution of TP53 mutation type was similar by race and ethnicity. However, 35.8% of tumors from NHW individuals had GOF mutations compared to 29% in AA individuals (p=0.04). Mutations lacking DNE activity were positively associated with TNBC (OR=1.37, p=0.03) and estrogen receptor (ER) negative status (OR=1.38; p=0.005). Conclusions: In summary, ER negative and TNBC breast tumors are less likely to have DNE+ TP53 mutations which could reflect biological processes. Larger cohorts are needed to further elucidate some of these findings.