JCO Precis Oncol. 2018;2018. doi: 10.1200/PO.17.00245. Epub 2018 Apr 25.
Survival Outcomes by TP53 Mutation Status in Metastatic Breast Cancer.
Meric-Bernstam F1,2,3, Zheng X4, Shariati M2, Damodaran S2,5, Wathoo C1, Brusco L1,2, Demirhan ME2, Tapia C2,6, Eterovic AK7, Basho RK8,9, Ueno NT5, Janku F2, Sahin A10, Rodon J1,2, Broaddus R10, Kim TB4, Mendelsohn J1,11, Mills Shaw KR1, Tripathy D5, Mills GB1,7, Chen K4.
Abstract
PURPOSE:
We sought to determine the significant genomic alterations in patients with metastatic breast cancer (MBC), and survival outcomes in common genotypes.
PATIENTS AND METHODS:
High-depth next generation sequencing was performed for 202 genes in tumor and normal DNA from 257 patients with MBC, including 165 patients with ER/PR+ HER2- (hormone receptor positive, HR+ positive), 32 patients with HER2+ and 60 patients with triple negative (ER/PR/HER2-) cancer. Kaplan Meier survival analysis was performed in our discovery set, in breast cancer patients analyzed in The Cancer Genome Atlas, and in a separate cohort of 98 patients with MBC who underwent clinical genomic testing.
RESULTS:
Significantly mutated genes (SMGs) varied by histology and tumor subtype, but TP53 was a SMG in all three subtypes. The most SMGs in HR+ patients included PIK3CA (32%), TP53 (29%), GATA3 (15%), CDH1 (8%), MAP3K1 (8%), PTEN (5%), TGFBR2 (4%), AKT1(4%), and MAP2K4 (4%). TP53 mutations were associated with shorter recurrence-free survival (P=0.004), progression-free survival (P=0.00057) and overall survival (P=0.003). Further, TP53 status was prognostic among HR+ patients with PIK3CA mutations. TP53mutations were also associated with poorer overall survival in the 442 HR+ breast cancer patients in the TCGA (P=0.042) and in an independent set of 96 HR+ MBC who underwent clinical sequencing (P=0.0004).
CONCLUSIONS:
SMGs differ by tumor subtype but TP53 is significantly mutated in all three breast cancer subtypes. TP53 mutations are associated with poor prognosis in HR+ breast cancer. TP53 mutations should be considered in the design and interpretation of precision oncology trials.
- PMID:
- 30035249
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